Rapid automated quantification of cerebral small-vessel ...



Rapid automated quantification of cerebral leukoaraiosis on CT Liang Chen1,2, Anoma Lalani Carlton Jones2, Grant Mair3, Rajiv Patel4, Anastasia Gontsarova2, Jeban Ganesalingam2, Nikhil Math2, Angela Dawson2, Aweid Basaam2, David Cohen4,, Amrish Mehta2, Joanna Wardlaw3, Daniel Rueckert1, Paul Bentley2IST-3 Collaborative Group 1 Biomedical Imaging Analysis Group, Computer Science, Imperial College London2 Division of Brain Sciences, Imperial College London, UK3 Centre for Clinical Brain Sciences, University of Edinburgh, UK4 Northwick Park Hospital, London North West Healthcare NHS Trust, UKCorresponding Author: Paul Bentley, p.bentley@ic.ac.ukAddress: 11L15, Charing Cross Hospital, Fulham Palace Road, W6 8RFFax: 0203 3117284Tel: 0203 3117284Short title: Automated quantification of SVD Abstract Word Count: 249Body Word Count: 2868Tables: 3 Figures: 3 Key words: small-vessel disease, leukoaraiosis, white-matter lesions, cerebrovascular disease, stroke, vascular dementia, imaging, machine-learningAbstractObjective: Assessment of cerebral ischemic white matter lesions (WML; or leukoaraiosis) using computerised tomography (CT) is important for the practical management of acute stroke, traumatic head injury and cognitive impairment, but limited by visual-rating systems prone to imprecision and interrater variability. We validated a fully-automated, image machine-learning method (Auto) that delineates and quantifies cerebral WML. Methods: Comparisons were made between Auto versus expert WML drawings on CT, and on co-registered FLAIR-MRIs (n=120); and between Auto versus expert ratings using two conventional scores (n=687 + 200, hospital and multicentre trial-populations respectively; all acute ischemic strokes). Results: Auto-estimated WML volumes correlated strongly with expert-drawing WML volumes on MRI and on CT (r2=0.85, 0.71 respectively; p<0.001); and showed a similar spatial-similarity measure with MRI-WML to that achieved by expert CT drawings. Expert WML drawing volumes on CT correlated strongly with each other (r2=0.85), but varied widely between experts (range: 91% of mean expert estimate). Agreements between Auto and consensus-expert ratings were superior or similar, depending upon scoring system, to agreements between pairs of experts (kappa: 0.60 vs. 0.51; 0.64 vs. 0.67 for the two score types; p<0.01 for first comparison only). Image preprocessing failure rate was 4%; Auto ratings errors (scores >1 point from expert consensus) occurred in a further 4%. Processing time averaged 109s per scan using Auto (including image preprocessing). Conclusions: We validate a rapid, fully-automated method for quantifying leukoaraiosis on CT in a large real-world case mix of samples. IntroductionCerebral small-vessel disease (SVD) - a major cause of age-related physical and cognitive morbidity - is most sensitively detected by FLAIR-MRIPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XYXJkbGF3PC9BdXRob3I+PFllYXI+MjAxMzwvWWVhcj48

SURUZXh0Pk5ldXJvaW1hZ2luZyBzdGFuZGFyZHMgZm9yIHJlc2VhcmNoIGludG8gc21hbGwgdmVz

c2VsIGRpc2Vhc2UgYW5kIGl0cyBjb250cmlidXRpb24gdG8gYWdlaW5nIGFuZCBuZXVyb2RlZ2Vu

ZXJhdGlvbjwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5bGUgZmFjZT0ic3VwZXJzY3JpcHQiPjE8

L3N0eWxlPjwvRGlzcGxheVRleHQ+PHJlY29yZD48ZGF0ZXM+PHB1Yi1kYXRlcz48ZGF0ZT5BdWc8

L2RhdGU+PC9wdWItZGF0ZXM+PHllYXI+MjAxMzwveWVhcj48L2RhdGVzPjxrZXl3b3Jkcz48a2V5

d29yZD5BZ2luZzwva2V5d29yZD48a2V5d29yZD5DZXJlYnJhbCBTbWFsbCBWZXNzZWwgRGlzZWFz

ZXM8L2tleXdvcmQ+PGtleXdvcmQ+RmVtYWxlPC9rZXl3b3JkPjxrZXl3b3JkPkd1aWRlbGluZXMg

YXMgVG9waWM8L2tleXdvcmQ+PGtleXdvcmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPkltYWdl

IFByb2Nlc3NpbmcsIENvbXB1dGVyLUFzc2lzdGVkPC9rZXl3b3JkPjxrZXl3b3JkPkludGVybmF0

aW9uYWwgQ29vcGVyYXRpb248L2tleXdvcmQ+PGtleXdvcmQ+TWFsZTwva2V5d29yZD48a2V5d29y

ZD5OZXVyb2RlZ2VuZXJhdGl2ZSBEaXNlYXNlczwva2V5d29yZD48a2V5d29yZD5OZXVyb2ltYWdp

bmc8L2tleXdvcmQ+PGtleXdvcmQ+VGVybWlub2xvZ3kgYXMgVG9waWM8L2tleXdvcmQ+PC9rZXl3

b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cHM6Ly93d3cubmNiaS5ubG0ubmloLmdv

di9wdWJtZWQvMjM4NjcyMDA8L3VybD48L3JlbGF0ZWQtdXJscz48L3VybHM+PGlzYm4+MTQ3NC00

NDY1PC9pc2JuPjxjdXN0b20yPlBNQzM3MTQ0Mzc8L2N1c3RvbTI+PHRpdGxlcz48dGl0bGU+TmV1

cm9pbWFnaW5nIHN0YW5kYXJkcyBmb3IgcmVzZWFyY2ggaW50byBzbWFsbCB2ZXNzZWwgZGlzZWFz

ZSBhbmQgaXRzIGNvbnRyaWJ1dGlvbiB0byBhZ2VpbmcgYW5kIG5ldXJvZGVnZW5lcmF0aW9uPC90

aXRsZT48c2Vjb25kYXJ5LXRpdGxlPkxhbmNldCBOZXVyb2w8L3NlY29uZGFyeS10aXRsZT48L3Rp

dGxlcz48cGFnZXM+ODIyLTM4PC9wYWdlcz48bnVtYmVyPjg8L251bWJlcj48Y29udHJpYnV0b3Jz

PjxhdXRob3JzPjxhdXRob3I+V2FyZGxhdywgSi4gTS48L2F1dGhvcj48YXV0aG9yPlNtaXRoLCBF

LiBFLjwvYXV0aG9yPjxhdXRob3I+Qmllc3NlbHMsIEcuIEouPC9hdXRob3I+PGF1dGhvcj5Db3Jk

b25uaWVyLCBDLjwvYXV0aG9yPjxhdXRob3I+RmF6ZWthcywgRi48L2F1dGhvcj48YXV0aG9yPkZy

YXluZSwgUi48L2F1dGhvcj48YXV0aG9yPkxpbmRsZXksIFIuIEkuPC9hdXRob3I+PGF1dGhvcj5P

JmFwb3M7QnJpZW4sIEouIFQuPC9hdXRob3I+PGF1dGhvcj5CYXJraG9mLCBGLjwvYXV0aG9yPjxh

dXRob3I+QmVuYXZlbnRlLCBPLiBSLjwvYXV0aG9yPjxhdXRob3I+QmxhY2ssIFMuIEUuPC9hdXRo

b3I+PGF1dGhvcj5CcmF5bmUsIEMuPC9hdXRob3I+PGF1dGhvcj5CcmV0ZWxlciwgTS48L2F1dGhv

cj48YXV0aG9yPkNoYWJyaWF0LCBILjwvYXV0aG9yPjxhdXRob3I+RGVjYXJsaSwgQy48L2F1dGhv

cj48YXV0aG9yPmRlIExlZXV3LCBGLiBFLjwvYXV0aG9yPjxhdXRob3I+RG91YmFsLCBGLjwvYXV0

aG9yPjxhdXRob3I+RHVlcmluZywgTS48L2F1dGhvcj48YXV0aG9yPkZveCwgTi4gQy48L2F1dGhv

cj48YXV0aG9yPkdyZWVuYmVyZywgUy48L2F1dGhvcj48YXV0aG9yPkhhY2hpbnNraSwgVi48L2F1

dGhvcj48YXV0aG9yPktpbGltYW5uLCBJLjwvYXV0aG9yPjxhdXRob3I+TW9rLCBWLjwvYXV0aG9y

PjxhdXRob3I+T29zdGVuYnJ1Z2dlLCBSLjwvYXV0aG9yPjxhdXRob3I+UGFudG9uaSwgTC48L2F1

dGhvcj48YXV0aG9yPlNwZWNrLCBPLjwvYXV0aG9yPjxhdXRob3I+U3RlcGhhbiwgQi4gQy48L2F1

dGhvcj48YXV0aG9yPlRlaXBlbCwgUy48L2F1dGhvcj48YXV0aG9yPlZpc3dhbmF0aGFuLCBBLjwv

YXV0aG9yPjxhdXRob3I+V2VycmluZywgRC48L2F1dGhvcj48YXV0aG9yPkNoZW4sIEMuPC9hdXRo

b3I+PGF1dGhvcj5TbWl0aCwgQy48L2F1dGhvcj48YXV0aG9yPnZhbiBCdWNoZW0sIE0uPC9hdXRo

b3I+PGF1dGhvcj5Ob3JydmluZywgQi48L2F1dGhvcj48YXV0aG9yPkdvcmVsaWNrLCBQLiBCLjwv

YXV0aG9yPjxhdXRob3I+RGljaGdhbnMsIE0uPC9hdXRob3I+PGF1dGhvcj5TVGFuZGFyZHMgZm9y

IFJlcG9ydEluZyBWYXNjdWxhciBjaGFuZ2VzIG9uIG5FdXJvaW1hZ2luZyAoU1RSSVZFIHYxKTwv

YXV0aG9yPjwvYXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3VhZ2U+RU5HPC9sYW5ndWFnZT48

YWRkZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3ODE3NDU3MzwvYWRkZWQtZGF0ZT48cmVmLXR5cGUg

bmFtZT0iSm91cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PHJlYy1udW1iZXI+NTI0PC9yZWMt

bnVtYmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3ODE3NDU3MzwvbGFzdC11

cGRhdGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MjM4NjcyMDA8L2FjY2Vzc2lvbi1udW0+PGVsZWN0

cm9uaWMtcmVzb3VyY2UtbnVtPjEwLjEwMTYvUzE0NzQtNDQyMigxMyk3MDEyNC04PC9lbGVjdHJv

bmljLXJlc291cmNlLW51bT48dm9sdW1lPjEyPC92b2x1bWU+PC9yZWNvcmQ+PC9DaXRlPjwvRW5k

Tm90ZT4AAAAA

ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XYXJkbGF3PC9BdXRob3I+PFllYXI+MjAxMzwvWWVhcj48

SURUZXh0Pk5ldXJvaW1hZ2luZyBzdGFuZGFyZHMgZm9yIHJlc2VhcmNoIGludG8gc21hbGwgdmVz

c2VsIGRpc2Vhc2UgYW5kIGl0cyBjb250cmlidXRpb24gdG8gYWdlaW5nIGFuZCBuZXVyb2RlZ2Vu

ZXJhdGlvbjwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5bGUgZmFjZT0ic3VwZXJzY3JpcHQiPjE8

L3N0eWxlPjwvRGlzcGxheVRleHQ+PHJlY29yZD48ZGF0ZXM+PHB1Yi1kYXRlcz48ZGF0ZT5BdWc8

L2RhdGU+PC9wdWItZGF0ZXM+PHllYXI+MjAxMzwveWVhcj48L2RhdGVzPjxrZXl3b3Jkcz48a2V5

d29yZD5BZ2luZzwva2V5d29yZD48a2V5d29yZD5DZXJlYnJhbCBTbWFsbCBWZXNzZWwgRGlzZWFz

ZXM8L2tleXdvcmQ+PGtleXdvcmQ+RmVtYWxlPC9rZXl3b3JkPjxrZXl3b3JkPkd1aWRlbGluZXMg

YXMgVG9waWM8L2tleXdvcmQ+PGtleXdvcmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPkltYWdl

IFByb2Nlc3NpbmcsIENvbXB1dGVyLUFzc2lzdGVkPC9rZXl3b3JkPjxrZXl3b3JkPkludGVybmF0

aW9uYWwgQ29vcGVyYXRpb248L2tleXdvcmQ+PGtleXdvcmQ+TWFsZTwva2V5d29yZD48a2V5d29y

ZD5OZXVyb2RlZ2VuZXJhdGl2ZSBEaXNlYXNlczwva2V5d29yZD48a2V5d29yZD5OZXVyb2ltYWdp

bmc8L2tleXdvcmQ+PGtleXdvcmQ+VGVybWlub2xvZ3kgYXMgVG9waWM8L2tleXdvcmQ+PC9rZXl3

b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cHM6Ly93d3cubmNiaS5ubG0ubmloLmdv

di9wdWJtZWQvMjM4NjcyMDA8L3VybD48L3JlbGF0ZWQtdXJscz48L3VybHM+PGlzYm4+MTQ3NC00

NDY1PC9pc2JuPjxjdXN0b20yPlBNQzM3MTQ0Mzc8L2N1c3RvbTI+PHRpdGxlcz48dGl0bGU+TmV1

cm9pbWFnaW5nIHN0YW5kYXJkcyBmb3IgcmVzZWFyY2ggaW50byBzbWFsbCB2ZXNzZWwgZGlzZWFz

ZSBhbmQgaXRzIGNvbnRyaWJ1dGlvbiB0byBhZ2VpbmcgYW5kIG5ldXJvZGVnZW5lcmF0aW9uPC90

aXRsZT48c2Vjb25kYXJ5LXRpdGxlPkxhbmNldCBOZXVyb2w8L3NlY29uZGFyeS10aXRsZT48L3Rp

dGxlcz48cGFnZXM+ODIyLTM4PC9wYWdlcz48bnVtYmVyPjg8L251bWJlcj48Y29udHJpYnV0b3Jz

PjxhdXRob3JzPjxhdXRob3I+V2FyZGxhdywgSi4gTS48L2F1dGhvcj48YXV0aG9yPlNtaXRoLCBF

LiBFLjwvYXV0aG9yPjxhdXRob3I+Qmllc3NlbHMsIEcuIEouPC9hdXRob3I+PGF1dGhvcj5Db3Jk

b25uaWVyLCBDLjwvYXV0aG9yPjxhdXRob3I+RmF6ZWthcywgRi48L2F1dGhvcj48YXV0aG9yPkZy

YXluZSwgUi48L2F1dGhvcj48YXV0aG9yPkxpbmRsZXksIFIuIEkuPC9hdXRob3I+PGF1dGhvcj5P

JmFwb3M7QnJpZW4sIEouIFQuPC9hdXRob3I+PGF1dGhvcj5CYXJraG9mLCBGLjwvYXV0aG9yPjxh

dXRob3I+QmVuYXZlbnRlLCBPLiBSLjwvYXV0aG9yPjxhdXRob3I+QmxhY2ssIFMuIEUuPC9hdXRo

b3I+PGF1dGhvcj5CcmF5bmUsIEMuPC9hdXRob3I+PGF1dGhvcj5CcmV0ZWxlciwgTS48L2F1dGhv

cj48YXV0aG9yPkNoYWJyaWF0LCBILjwvYXV0aG9yPjxhdXRob3I+RGVjYXJsaSwgQy48L2F1dGhv

cj48YXV0aG9yPmRlIExlZXV3LCBGLiBFLjwvYXV0aG9yPjxhdXRob3I+RG91YmFsLCBGLjwvYXV0

aG9yPjxhdXRob3I+RHVlcmluZywgTS48L2F1dGhvcj48YXV0aG9yPkZveCwgTi4gQy48L2F1dGhv

cj48YXV0aG9yPkdyZWVuYmVyZywgUy48L2F1dGhvcj48YXV0aG9yPkhhY2hpbnNraSwgVi48L2F1

dGhvcj48YXV0aG9yPktpbGltYW5uLCBJLjwvYXV0aG9yPjxhdXRob3I+TW9rLCBWLjwvYXV0aG9y

PjxhdXRob3I+T29zdGVuYnJ1Z2dlLCBSLjwvYXV0aG9yPjxhdXRob3I+UGFudG9uaSwgTC48L2F1

dGhvcj48YXV0aG9yPlNwZWNrLCBPLjwvYXV0aG9yPjxhdXRob3I+U3RlcGhhbiwgQi4gQy48L2F1

dGhvcj48YXV0aG9yPlRlaXBlbCwgUy48L2F1dGhvcj48YXV0aG9yPlZpc3dhbmF0aGFuLCBBLjwv

YXV0aG9yPjxhdXRob3I+V2VycmluZywgRC48L2F1dGhvcj48YXV0aG9yPkNoZW4sIEMuPC9hdXRo

b3I+PGF1dGhvcj5TbWl0aCwgQy48L2F1dGhvcj48YXV0aG9yPnZhbiBCdWNoZW0sIE0uPC9hdXRo

b3I+PGF1dGhvcj5Ob3JydmluZywgQi48L2F1dGhvcj48YXV0aG9yPkdvcmVsaWNrLCBQLiBCLjwv

YXV0aG9yPjxhdXRob3I+RGljaGdhbnMsIE0uPC9hdXRob3I+PGF1dGhvcj5TVGFuZGFyZHMgZm9y

IFJlcG9ydEluZyBWYXNjdWxhciBjaGFuZ2VzIG9uIG5FdXJvaW1hZ2luZyAoU1RSSVZFIHYxKTwv

YXV0aG9yPjwvYXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3VhZ2U+RU5HPC9sYW5ndWFnZT48

YWRkZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3ODE3NDU3MzwvYWRkZWQtZGF0ZT48cmVmLXR5cGUg

bmFtZT0iSm91cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PHJlYy1udW1iZXI+NTI0PC9yZWMt

bnVtYmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3ODE3NDU3MzwvbGFzdC11

cGRhdGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MjM4NjcyMDA8L2FjY2Vzc2lvbi1udW0+PGVsZWN0

cm9uaWMtcmVzb3VyY2UtbnVtPjEwLjEwMTYvUzE0NzQtNDQyMigxMyk3MDEyNC04PC9lbGVjdHJv

bmljLXJlc291cmNlLW51bT48dm9sdW1lPjEyPC92b2x1bWU+PC9yZWNvcmQ+PC9DaXRlPjwvRW5k

Tm90ZT4AAAAA

ADDIN EN.CITE.DATA 1, typically as leukoaraiosis, i.e. white matter lesions, WML, and lacunar infarcts. In practice, WML are most commonly observed on CT ADDIN EN.CITE <EndNote><Cite><Author>Rossi</Author><Year>2005</Year><IDText>Pathological validation of a CT-based scale for subcortical vascular disease. The OPTIMA Study</IDText><DisplayText><style face="superscript">2</style></DisplayText><record><keywords><keyword>Aged</keyword><keyword>Aged, 80 and over</keyword><keyword>Brain</keyword><keyword>Cerebral Angiography</keyword><keyword>Cerebral Arteries</keyword><keyword>Dementia, Multi-Infarct</keyword><keyword>Dementia, Vascular</keyword><keyword>Female</keyword><keyword>Humans</keyword><keyword>Leukoaraiosis</keyword><keyword>Longitudinal Studies</keyword><keyword>Male</keyword><keyword>Microcirculation</keyword><keyword>Middle Aged</keyword><keyword>Prospective Studies</keyword><keyword>Reproducibility of Results</keyword><keyword>Sensitivity and Specificity</keyword><keyword>Statistics as Topic</keyword><keyword>Tomography, X-Ray Computed</keyword></keywords><urls><related-urls><url> validation of a CT-based scale for subcortical vascular disease. The OPTIMA Study</title><secondary-title>Dement Geriatr Cogn Disord</secondary-title></titles><pages>61-6</pages><number>2-3</number><contributors><authors><author>Rossi, R.</author><author>Joachim, C.</author><author>Geroldi, C.</author><author>Esiri, M. M.</author><author>Smith, A. D.</author><author>Frisoni, G. B.</author></authors></contributors><language>ENG</language><added-date format="utc">1478697809</added-date><ref-type name="Journal Article">17</ref-type><dates><year>2005</year></dates><rec-number>543</rec-number><last-updated-date format="utc">1478697809</last-updated-date><accession-num>15572873</accession-num><electronic-resource-num>10.1159/000082350</electronic-resource-num><volume>19</volume></record></Cite></EndNote>2, rather than MRI, because of scanner-type availability and accessibility considerations in target populations. In acute stroke and traumatic head injury, CT is the first-line imaging modality of choice ADDIN EN.CITE <EndNote><Cite><Author>Sanossian</Author><Year>2016</Year><IDText>Utilization of Emergent Neuroimaging for Thrombolysis-Eligible Stroke Patients</IDText><DisplayText><style face="superscript">3</style></DisplayText><record><dates><pub-dates><date>Jun</date></pub-dates><year>2016</year></dates><urls><related-urls><url> of Emergent Neuroimaging for Thrombolysis-Eligible Stroke Patients</title><secondary-title>J Neuroimaging</secondary-title></titles><contributors><authors><author>Sanossian, N.</author><author>Fu, K. A.</author><author>Liebeskind, D. S.</author><author>Starkman, S.</author><author>Hamilton, S.</author><author>Villablanca, J. P.</author><author>Burgos, A. M.</author><author>Conwit, R.</author><author>Saver, J. L.</author></authors></contributors><language>ENG</language><added-date format="utc">1478706286</added-date><ref-type name="Journal Article">17</ref-type><rec-number>552</rec-number><last-updated-date format="utc">1478706286</last-updated-date><accession-num>27300498</accession-num><electronic-resource-num>10.1111/jon.12369</electronic-resource-num></record></Cite></EndNote>3; yet WML burden is an important variable, being a prognostic marker of functional outcomePEVuZE5vdGU+PENpdGU+PEF1dGhvcj5JU1QtMzwvQXV0aG9yPjxZZWFyPjIwMTU8L1llYXI+PElE

VGV4dD5Bc3NvY2lhdGlvbiBiZXR3ZWVuIGJyYWluIGltYWdpbmcgc2lnbnMsIGVhcmx5IGFuZCBs

YXRlIG91dGNvbWVzLCBhbmQgcmVzcG9uc2UgdG8gaW50cmF2ZW5vdXMgYWx0ZXBsYXNlIGFmdGVy

IGFjdXRlIGlzY2hhZW1pYyBzdHJva2UgaW4gdGhlIHRoaXJkIEludGVybmF0aW9uYWwgU3Ryb2tl

IFRyaWFsIChJU1QtMyk6IHNlY29uZGFyeSBhbmFseXNpcyBvZiBhIHJhbmRvbWlzZWQgY29udHJv

bGxlZCB0cmlhbDwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5bGUgZmFjZT0ic3VwZXJzY3JpcHQi

PjQtNjwvc3R5bGU+PC9EaXNwbGF5VGV4dD48cmVjb3JkPjxkYXRlcz48cHViLWRhdGVzPjxkYXRl

Pk1heTwvZGF0ZT48L3B1Yi1kYXRlcz48eWVhcj4yMDE1PC95ZWFyPjwvZGF0ZXM+PGtleXdvcmRz

PjxrZXl3b3JkPkFkdWx0PC9rZXl3b3JkPjxrZXl3b3JkPkFnZWQ8L2tleXdvcmQ+PGtleXdvcmQ+

QWdlZCwgODAgYW5kIG92ZXI8L2tleXdvcmQ+PGtleXdvcmQ+QnJhaW4gSXNjaGVtaWE8L2tleXdv

cmQ+PGtleXdvcmQ+RGF0YSBJbnRlcnByZXRhdGlvbiwgU3RhdGlzdGljYWw8L2tleXdvcmQ+PGtl

eXdvcmQ+RmVtYWxlPC9rZXl3b3JkPjxrZXl3b3JkPkZpYnJpbm9seXRpYyBBZ2VudHM8L2tleXdv

cmQ+PGtleXdvcmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPk1hZ25ldGljIFJlc29uYW5jZSBJ

bWFnaW5nLCBDaW5lPC9rZXl3b3JkPjxrZXl3b3JkPk1hbGU8L2tleXdvcmQ+PGtleXdvcmQ+TWlk

ZGxlIEFnZWQ8L2tleXdvcmQ+PGtleXdvcmQ+T3V0Y29tZSBBc3Nlc3NtZW50IChIZWFsdGggQ2Fy

ZSk8L2tleXdvcmQ+PGtleXdvcmQ+U2luZ2xlLUJsaW5kIE1ldGhvZDwva2V5d29yZD48a2V5d29y

ZD5TdHJva2U8L2tleXdvcmQ+PGtleXdvcmQ+VGhyb21ib2x5dGljIFRoZXJhcHk8L2tleXdvcmQ+

PGtleXdvcmQ+VGlzc3VlIFBsYXNtaW5vZ2VuIEFjdGl2YXRvcjwva2V5d29yZD48L2tleXdvcmRz

Pjx1cmxzPjxyZWxhdGVkLXVybHM+PHVybD5odHRwczovL3d3dy5uY2JpLm5sbS5uaWguZ292L3B1

Ym1lZC8yNTgxOTQ4NDwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJscz48aXNibj4xNDc0LTQ0NjU8

L2lzYm4+PGN1c3RvbTI+UE1DNDUxMzE5MDwvY3VzdG9tMj48dGl0bGVzPjx0aXRsZT5Bc3NvY2lh

dGlvbiBiZXR3ZWVuIGJyYWluIGltYWdpbmcgc2lnbnMsIGVhcmx5IGFuZCBsYXRlIG91dGNvbWVz

LCBhbmQgcmVzcG9uc2UgdG8gaW50cmF2ZW5vdXMgYWx0ZXBsYXNlIGFmdGVyIGFjdXRlIGlzY2hh

ZW1pYyBzdHJva2UgaW4gdGhlIHRoaXJkIEludGVybmF0aW9uYWwgU3Ryb2tlIFRyaWFsIChJU1Qt

Myk6IHNlY29uZGFyeSBhbmFseXNpcyBvZiBhIHJhbmRvbWlzZWQgY29udHJvbGxlZCB0cmlhbDwv

dGl0bGU+PHNlY29uZGFyeS10aXRsZT5MYW5jZXQgTmV1cm9sPC9zZWNvbmRhcnktdGl0bGU+PC90

aXRsZXM+PHBhZ2VzPjQ4NS05NjwvcGFnZXM+PG51bWJlcj41PC9udW1iZXI+PGNvbnRyaWJ1dG9y

cz48YXV0aG9ycz48YXV0aG9yPklTVC0zIGNvbGxhYm9yYXRpdmUgZ3JvdXA8L2F1dGhvcj48L2F1

dGhvcnM+PC9jb250cmlidXRvcnM+PGxhbmd1YWdlPkVORzwvbGFuZ3VhZ2U+PGFkZGVkLWRhdGUg

Zm9ybWF0PSJ1dGMiPjE0NzgxNzg4Njc8L2FkZGVkLWRhdGU+PHJlZi10eXBlIG5hbWU9IkpvdXJu

YWwgQXJ0aWNsZSI+MTc8L3JlZi10eXBlPjxyZWMtbnVtYmVyPjUzMzwvcmVjLW51bWJlcj48bGFz

dC11cGRhdGVkLWRhdGUgZm9ybWF0PSJ1dGMiPjE0NzgxNzg4Njc8L2xhc3QtdXBkYXRlZC1kYXRl

PjxhY2Nlc3Npb24tbnVtPjI1ODE5NDg0PC9hY2Nlc3Npb24tbnVtPjxlbGVjdHJvbmljLXJlc291

cmNlLW51bT4xMC4xMDE2L1MxNDc0LTQ0MjIoMTUpMDAwMTItNTwvZWxlY3Ryb25pYy1yZXNvdXJj

ZS1udW0+PHZvbHVtZT4xNDwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48Q2l0ZT48QXV0aG9yPklT

VC0zPC9BdXRob3I+PFllYXI+MjAxNTwvWWVhcj48SURUZXh0PkFzc29jaWF0aW9uIGJldHdlZW4g

YnJhaW4gaW1hZ2luZyBzaWducywgZWFybHkgYW5kIGxhdGUgb3V0Y29tZXMsIGFuZCByZXNwb25z

ZSB0byBpbnRyYXZlbm91cyBhbHRlcGxhc2UgYWZ0ZXIgYWN1dGUgaXNjaGFlbWljIHN0cm9rZSBp

biB0aGUgdGhpcmQgSW50ZXJuYXRpb25hbCBTdHJva2UgVHJpYWwgKElTVC0zKTogc2Vjb25kYXJ5

IGFuYWx5c2lzIG9mIGEgcmFuZG9taXNlZCBjb250cm9sbGVkIHRyaWFsPC9JRFRleHQ+PHJlY29y

ZD48ZGF0ZXM+PHB1Yi1kYXRlcz48ZGF0ZT5NYXk8L2RhdGU+PC9wdWItZGF0ZXM+PHllYXI+MjAx

NTwveWVhcj48L2RhdGVzPjxrZXl3b3Jkcz48a2V5d29yZD5BZHVsdDwva2V5d29yZD48a2V5d29y

ZD5BZ2VkPC9rZXl3b3JkPjxrZXl3b3JkPkFnZWQsIDgwIGFuZCBvdmVyPC9rZXl3b3JkPjxrZXl3

b3JkPkJyYWluIElzY2hlbWlhPC9rZXl3b3JkPjxrZXl3b3JkPkRhdGEgSW50ZXJwcmV0YXRpb24s

IFN0YXRpc3RpY2FsPC9rZXl3b3JkPjxrZXl3b3JkPkZlbWFsZTwva2V5d29yZD48a2V5d29yZD5G

aWJyaW5vbHl0aWMgQWdlbnRzPC9rZXl3b3JkPjxrZXl3b3JkPkh1bWFuczwva2V5d29yZD48a2V5

d29yZD5NYWduZXRpYyBSZXNvbmFuY2UgSW1hZ2luZywgQ2luZTwva2V5d29yZD48a2V5d29yZD5N

YWxlPC9rZXl3b3JkPjxrZXl3b3JkPk1pZGRsZSBBZ2VkPC9rZXl3b3JkPjxrZXl3b3JkPk91dGNv

bWUgQXNzZXNzbWVudCAoSGVhbHRoIENhcmUpPC9rZXl3b3JkPjxrZXl3b3JkPlNpbmdsZS1CbGlu

ZCBNZXRob2Q8L2tleXdvcmQ+PGtleXdvcmQ+U3Ryb2tlPC9rZXl3b3JkPjxrZXl3b3JkPlRocm9t

Ym9seXRpYyBUaGVyYXB5PC9rZXl3b3JkPjxrZXl3b3JkPlRpc3N1ZSBQbGFzbWlub2dlbiBBY3Rp

dmF0b3I8L2tleXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cHM6

Ly93d3cubmNiaS5ubG0ubmloLmdvdi9wdWJtZWQvMjU4MTk0ODQ8L3VybD48L3JlbGF0ZWQtdXJs

cz48L3VybHM+PGlzYm4+MTQ3NC00NDY1PC9pc2JuPjxjdXN0b20yPlBNQzQ1MTMxOTA8L2N1c3Rv

bTI+PHRpdGxlcz48dGl0bGU+QXNzb2NpYXRpb24gYmV0d2VlbiBicmFpbiBpbWFnaW5nIHNpZ25z

LCBlYXJseSBhbmQgbGF0ZSBvdXRjb21lcywgYW5kIHJlc3BvbnNlIHRvIGludHJhdmVub3VzIGFs

dGVwbGFzZSBhZnRlciBhY3V0ZSBpc2NoYWVtaWMgc3Ryb2tlIGluIHRoZSB0aGlyZCBJbnRlcm5h

dGlvbmFsIFN0cm9rZSBUcmlhbCAoSVNULTMpOiBzZWNvbmRhcnkgYW5hbHlzaXMgb2YgYSByYW5k

b21pc2VkIGNvbnRyb2xsZWQgdHJpYWw8L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+TGFuY2V0IE5l

dXJvbDwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0bGVzPjxwYWdlcz40ODUtOTY8L3BhZ2VzPjxudW1i

ZXI+NTwvbnVtYmVyPjxjb250cmlidXRvcnM+PGF1dGhvcnM+PGF1dGhvcj5JU1QtMyBjb2xsYWJv

cmF0aXZlIGdyb3VwPC9hdXRob3I+PC9hdXRob3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5F

Tkc8L2xhbmd1YWdlPjxhZGRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc4MTc4ODY3PC9hZGRlZC1k

YXRlPjxyZWYtdHlwZSBuYW1lPSJKb3VybmFsIEFydGljbGUiPjE3PC9yZWYtdHlwZT48cmVjLW51

bWJlcj41MzM8L3JlYy1udW1iZXI+PGxhc3QtdXBkYXRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc4

MTc4ODY3PC9sYXN0LXVwZGF0ZWQtZGF0ZT48YWNjZXNzaW9uLW51bT4yNTgxOTQ4NDwvYWNjZXNz

aW9uLW51bT48ZWxlY3Ryb25pYy1yZXNvdXJjZS1udW0+MTAuMTAxNi9TMTQ3NC00NDIyKDE1KTAw

MDEyLTU8L2VsZWN0cm9uaWMtcmVzb3VyY2UtbnVtPjx2b2x1bWU+MTQ8L3ZvbHVtZT48L3JlY29y

ZD48L0NpdGU+PENpdGU+PEF1dGhvcj5SeXU8L0F1dGhvcj48WWVhcj4yMDE3PC9ZZWFyPjxJRFRl

eHQ+U3Ryb2tlIG91dGNvbWVzIGFyZSB3b3JzZSB3aXRoIGxhcmdlciBsZXVrb2FyYWlvc2lzIHZv

bHVtZXM8L0lEVGV4dD48cmVjb3JkPjxkYXRlcz48cHViLWRhdGVzPjxkYXRlPkphbjwvZGF0ZT48

L3B1Yi1kYXRlcz48eWVhcj4yMDE3PC95ZWFyPjwvZGF0ZXM+PHVybHM+PHJlbGF0ZWQtdXJscz48

dXJsPmh0dHBzOi8vd3d3Lm5jYmkubmxtLm5paC5nb3YvcHVibWVkLzI4MDA4MDAwPC91cmw+PC9y

ZWxhdGVkLXVybHM+PC91cmxzPjxpc2JuPjE0NjAtMjE1NjwvaXNibj48dGl0bGVzPjx0aXRsZT5T

dHJva2Ugb3V0Y29tZXMgYXJlIHdvcnNlIHdpdGggbGFyZ2VyIGxldWtvYXJhaW9zaXMgdm9sdW1l

czwvdGl0bGU+PHNlY29uZGFyeS10aXRsZT5CcmFpbjwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0bGVz

PjxwYWdlcz4xNTgtMTcwPC9wYWdlcz48bnVtYmVyPlB0IDE8L251bWJlcj48Y29udHJpYnV0b3Jz

PjxhdXRob3JzPjxhdXRob3I+Unl1LCBXLiBTLjwvYXV0aG9yPjxhdXRob3I+V29vLCBTLiBILjwv

YXV0aG9yPjxhdXRob3I+U2NoZWxsaW5nZXJob3V0LCBELjwvYXV0aG9yPjxhdXRob3I+SmFuZywg

TS4gVS48L2F1dGhvcj48YXV0aG9yPlBhcmssIEsuIEouPC9hdXRob3I+PGF1dGhvcj5Ib25nLCBL

LiBTLjwvYXV0aG9yPjxhdXRob3I+SmVvbmcsIFMuIFcuPC9hdXRob3I+PGF1dGhvcj5OYSwgSi4g

WS48L2F1dGhvcj48YXV0aG9yPkNobywgSy4gSC48L2F1dGhvcj48YXV0aG9yPktpbSwgSi4gVC48

L2F1dGhvcj48YXV0aG9yPktpbSwgQi4gSi48L2F1dGhvcj48YXV0aG9yPkhhbiwgTS4gSy48L2F1

dGhvcj48YXV0aG9yPkxlZSwgSi48L2F1dGhvcj48YXV0aG9yPkNoYSwgSi4gSy48L2F1dGhvcj48

YXV0aG9yPktpbSwgRC4gSC48L2F1dGhvcj48YXV0aG9yPkxlZSwgUy4gSi48L2F1dGhvcj48YXV0

aG9yPktvLCBZLjwvYXV0aG9yPjxhdXRob3I+Q2hvLCBZLiBKLjwvYXV0aG9yPjxhdXRob3I+TGVl

LCBCLiBDLjwvYXV0aG9yPjxhdXRob3I+WXUsIEsuIEguPC9hdXRob3I+PGF1dGhvcj5PaCwgTS4g

Uy48L2F1dGhvcj48YXV0aG9yPlBhcmssIEouIE0uPC9hdXRob3I+PGF1dGhvcj5LYW5nLCBLLjwv

YXV0aG9yPjxhdXRob3I+TGVlLCBLLiBCLjwvYXV0aG9yPjxhdXRob3I+UGFyaywgVC4gSC48L2F1

dGhvcj48YXV0aG9yPkNob2ksIEguIEsuPC9hdXRob3I+PGF1dGhvcj5MZWUsIEsuPC9hdXRob3I+

PGF1dGhvcj5CYWUsIEguIEouPC9hdXRob3I+PGF1dGhvcj5LaW0sIEQuIEUuPC9hdXRob3I+PC9h

dXRob3JzPjwvY29udHJpYnV0b3JzPjxlZGl0aW9uPjIwMTYvMTIvMjI8L2VkaXRpb24+PGxhbmd1

YWdlPmVuZzwvbGFuZ3VhZ2U+PGFkZGVkLWRhdGUgZm9ybWF0PSJ1dGMiPjE0ODU0MzEzMzg8L2Fk

ZGVkLWRhdGU+PHJlZi10eXBlIG5hbWU9IkpvdXJuYWwgQXJ0aWNsZSI+MTc8L3JlZi10eXBlPjxy

ZWMtbnVtYmVyPjU2ODwvcmVjLW51bWJlcj48bGFzdC11cGRhdGVkLWRhdGUgZm9ybWF0PSJ1dGMi

PjE0ODU0MzEzMzg8L2xhc3QtdXBkYXRlZC1kYXRlPjxhY2Nlc3Npb24tbnVtPjI4MDA4MDAwPC9h

Y2Nlc3Npb24tbnVtPjxlbGVjdHJvbmljLXJlc291cmNlLW51bT4xMC4xMDkzL2JyYWluL2F3dzI1

OTwvZWxlY3Ryb25pYy1yZXNvdXJjZS1udW0+PHZvbHVtZT4xNDA8L3ZvbHVtZT48L3JlY29yZD48

L0NpdGU+PENpdGU+PEF1dGhvcj5IZW5uaW5nZXI8L0F1dGhvcj48WWVhcj4yMDE0PC9ZZWFyPjxJ

RFRleHQ+U2V2ZXJlIGxldWtvYXJhaW9zaXMgcG9ydGVuZHMgYSBwb29yIG91dGNvbWUgYWZ0ZXIg

dHJhdW1hdGljIGJyYWluIGluanVyeTwvSURUZXh0PjxyZWNvcmQ+PGRhdGVzPjxwdWItZGF0ZXM+

PGRhdGU+RGVjPC9kYXRlPjwvcHViLWRhdGVzPjx5ZWFyPjIwMTQ8L3llYXI+PC9kYXRlcz48a2V5

d29yZHM+PGtleXdvcmQ+QWdlIEZhY3RvcnM8L2tleXdvcmQ+PGtleXdvcmQ+QWdlZDwva2V5d29y

ZD48a2V5d29yZD5BZ2VkLCA4MCBhbmQgb3Zlcjwva2V5d29yZD48a2V5d29yZD5CcmFpbiBJbmp1

cmllczwva2V5d29yZD48a2V5d29yZD5Db2hvcnQgU3R1ZGllczwva2V5d29yZD48a2V5d29yZD5G

ZW1hbGU8L2tleXdvcmQ+PGtleXdvcmQ+R2xhc2dvdyBDb21hIFNjYWxlPC9rZXl3b3JkPjxrZXl3

b3JkPkdsYXNnb3cgT3V0Y29tZSBTY2FsZTwva2V5d29yZD48a2V5d29yZD5IdW1hbnM8L2tleXdv

cmQ+PGtleXdvcmQ+TGV1a29hcmFpb3Npczwva2V5d29yZD48a2V5d29yZD5NYWxlPC9rZXl3b3Jk

PjxrZXl3b3JkPk1pZGRsZSBBZ2VkPC9rZXl3b3JkPjxrZXl3b3JkPlByb2dub3Npczwva2V5d29y

ZD48a2V5d29yZD5SZXRyb3NwZWN0aXZlIFN0dWRpZXM8L2tleXdvcmQ+PGtleXdvcmQ+U2V2ZXJp

dHkgb2YgSWxsbmVzcyBJbmRleDwva2V5d29yZD48a2V5d29yZD5Ub21vZ3JhcGh5LCBYLVJheSBD

b21wdXRlZDwva2V5d29yZD48a2V5d29yZD5XaGl0ZSBNYXR0ZXI8L2tleXdvcmQ+PC9rZXl3b3Jk

cz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cHM6Ly93d3cubmNiaS5ubG0ubmloLmdvdi9w

dWJtZWQvMjQ3NTI0NTk8L3VybD48L3JlbGF0ZWQtdXJscz48L3VybHM+PGlzYm4+MTU1Ni0wOTYx

PC9pc2JuPjx0aXRsZXM+PHRpdGxlPlNldmVyZSBsZXVrb2FyYWlvc2lzIHBvcnRlbmRzIGEgcG9v

ciBvdXRjb21lIGFmdGVyIHRyYXVtYXRpYyBicmFpbiBpbmp1cnk8L3RpdGxlPjxzZWNvbmRhcnkt

dGl0bGU+TmV1cm9jcml0IENhcmU8L3NlY29uZGFyeS10aXRsZT48L3RpdGxlcz48cGFnZXM+NDgz

LTk1PC9wYWdlcz48bnVtYmVyPjM8L251bWJlcj48Y29udHJpYnV0b3JzPjxhdXRob3JzPjxhdXRo

b3I+SGVubmluZ2VyLCBOLjwvYXV0aG9yPjxhdXRob3I+SXp6eSwgUy48L2F1dGhvcj48YXV0aG9y

PkNhcmFuZGFuZywgUi48L2F1dGhvcj48YXV0aG9yPkhhbGwsIFcuPC9hdXRob3I+PGF1dGhvcj5N

dWVobHNjaGxlZ2VsLCBTLjwvYXV0aG9yPjwvYXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3Vh

Z2U+ZW5nPC9sYW5ndWFnZT48YWRkZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ4NjA2MDI4ODwvYWRk

ZWQtZGF0ZT48cmVmLXR5cGUgbmFtZT0iSm91cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PHJl

Yy1udW1iZXI+NTY5PC9yZWMtbnVtYmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+

MTQ4NjA2MDI4ODwvbGFzdC11cGRhdGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MjQ3NTI0NTk8L2Fj

Y2Vzc2lvbi1udW0+PGVsZWN0cm9uaWMtcmVzb3VyY2UtbnVtPjEwLjEwMDcvczEyMDI4LTAxNC05

OTgwLTA8L2VsZWN0cm9uaWMtcmVzb3VyY2UtbnVtPjx2b2x1bWU+MjE8L3ZvbHVtZT48L3JlY29y

ZD48L0NpdGU+PC9FbmROb3RlPgAA

ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5JU1QtMzwvQXV0aG9yPjxZZWFyPjIwMTU8L1llYXI+PElE

VGV4dD5Bc3NvY2lhdGlvbiBiZXR3ZWVuIGJyYWluIGltYWdpbmcgc2lnbnMsIGVhcmx5IGFuZCBs

YXRlIG91dGNvbWVzLCBhbmQgcmVzcG9uc2UgdG8gaW50cmF2ZW5vdXMgYWx0ZXBsYXNlIGFmdGVy

IGFjdXRlIGlzY2hhZW1pYyBzdHJva2UgaW4gdGhlIHRoaXJkIEludGVybmF0aW9uYWwgU3Ryb2tl

IFRyaWFsIChJU1QtMyk6IHNlY29uZGFyeSBhbmFseXNpcyBvZiBhIHJhbmRvbWlzZWQgY29udHJv

bGxlZCB0cmlhbDwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5bGUgZmFjZT0ic3VwZXJzY3JpcHQi

PjQtNjwvc3R5bGU+PC9EaXNwbGF5VGV4dD48cmVjb3JkPjxkYXRlcz48cHViLWRhdGVzPjxkYXRl

Pk1heTwvZGF0ZT48L3B1Yi1kYXRlcz48eWVhcj4yMDE1PC95ZWFyPjwvZGF0ZXM+PGtleXdvcmRz

PjxrZXl3b3JkPkFkdWx0PC9rZXl3b3JkPjxrZXl3b3JkPkFnZWQ8L2tleXdvcmQ+PGtleXdvcmQ+

QWdlZCwgODAgYW5kIG92ZXI8L2tleXdvcmQ+PGtleXdvcmQ+QnJhaW4gSXNjaGVtaWE8L2tleXdv

cmQ+PGtleXdvcmQ+RGF0YSBJbnRlcnByZXRhdGlvbiwgU3RhdGlzdGljYWw8L2tleXdvcmQ+PGtl

eXdvcmQ+RmVtYWxlPC9rZXl3b3JkPjxrZXl3b3JkPkZpYnJpbm9seXRpYyBBZ2VudHM8L2tleXdv

cmQ+PGtleXdvcmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPk1hZ25ldGljIFJlc29uYW5jZSBJ

bWFnaW5nLCBDaW5lPC9rZXl3b3JkPjxrZXl3b3JkPk1hbGU8L2tleXdvcmQ+PGtleXdvcmQ+TWlk

ZGxlIEFnZWQ8L2tleXdvcmQ+PGtleXdvcmQ+T3V0Y29tZSBBc3Nlc3NtZW50IChIZWFsdGggQ2Fy

ZSk8L2tleXdvcmQ+PGtleXdvcmQ+U2luZ2xlLUJsaW5kIE1ldGhvZDwva2V5d29yZD48a2V5d29y

ZD5TdHJva2U8L2tleXdvcmQ+PGtleXdvcmQ+VGhyb21ib2x5dGljIFRoZXJhcHk8L2tleXdvcmQ+

PGtleXdvcmQ+VGlzc3VlIFBsYXNtaW5vZ2VuIEFjdGl2YXRvcjwva2V5d29yZD48L2tleXdvcmRz

Pjx1cmxzPjxyZWxhdGVkLXVybHM+PHVybD5odHRwczovL3d3dy5uY2JpLm5sbS5uaWguZ292L3B1

Ym1lZC8yNTgxOTQ4NDwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJscz48aXNibj4xNDc0LTQ0NjU8

L2lzYm4+PGN1c3RvbTI+UE1DNDUxMzE5MDwvY3VzdG9tMj48dGl0bGVzPjx0aXRsZT5Bc3NvY2lh

dGlvbiBiZXR3ZWVuIGJyYWluIGltYWdpbmcgc2lnbnMsIGVhcmx5IGFuZCBsYXRlIG91dGNvbWVz

LCBhbmQgcmVzcG9uc2UgdG8gaW50cmF2ZW5vdXMgYWx0ZXBsYXNlIGFmdGVyIGFjdXRlIGlzY2hh

ZW1pYyBzdHJva2UgaW4gdGhlIHRoaXJkIEludGVybmF0aW9uYWwgU3Ryb2tlIFRyaWFsIChJU1Qt

Myk6IHNlY29uZGFyeSBhbmFseXNpcyBvZiBhIHJhbmRvbWlzZWQgY29udHJvbGxlZCB0cmlhbDwv

dGl0bGU+PHNlY29uZGFyeS10aXRsZT5MYW5jZXQgTmV1cm9sPC9zZWNvbmRhcnktdGl0bGU+PC90

aXRsZXM+PHBhZ2VzPjQ4NS05NjwvcGFnZXM+PG51bWJlcj41PC9udW1iZXI+PGNvbnRyaWJ1dG9y

cz48YXV0aG9ycz48YXV0aG9yPklTVC0zIGNvbGxhYm9yYXRpdmUgZ3JvdXA8L2F1dGhvcj48L2F1

dGhvcnM+PC9jb250cmlidXRvcnM+PGxhbmd1YWdlPkVORzwvbGFuZ3VhZ2U+PGFkZGVkLWRhdGUg

Zm9ybWF0PSJ1dGMiPjE0NzgxNzg4Njc8L2FkZGVkLWRhdGU+PHJlZi10eXBlIG5hbWU9IkpvdXJu

YWwgQXJ0aWNsZSI+MTc8L3JlZi10eXBlPjxyZWMtbnVtYmVyPjUzMzwvcmVjLW51bWJlcj48bGFz

dC11cGRhdGVkLWRhdGUgZm9ybWF0PSJ1dGMiPjE0NzgxNzg4Njc8L2xhc3QtdXBkYXRlZC1kYXRl

PjxhY2Nlc3Npb24tbnVtPjI1ODE5NDg0PC9hY2Nlc3Npb24tbnVtPjxlbGVjdHJvbmljLXJlc291

cmNlLW51bT4xMC4xMDE2L1MxNDc0LTQ0MjIoMTUpMDAwMTItNTwvZWxlY3Ryb25pYy1yZXNvdXJj

ZS1udW0+PHZvbHVtZT4xNDwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48Q2l0ZT48QXV0aG9yPklT

VC0zPC9BdXRob3I+PFllYXI+MjAxNTwvWWVhcj48SURUZXh0PkFzc29jaWF0aW9uIGJldHdlZW4g

YnJhaW4gaW1hZ2luZyBzaWducywgZWFybHkgYW5kIGxhdGUgb3V0Y29tZXMsIGFuZCByZXNwb25z

ZSB0byBpbnRyYXZlbm91cyBhbHRlcGxhc2UgYWZ0ZXIgYWN1dGUgaXNjaGFlbWljIHN0cm9rZSBp

biB0aGUgdGhpcmQgSW50ZXJuYXRpb25hbCBTdHJva2UgVHJpYWwgKElTVC0zKTogc2Vjb25kYXJ5

IGFuYWx5c2lzIG9mIGEgcmFuZG9taXNlZCBjb250cm9sbGVkIHRyaWFsPC9JRFRleHQ+PHJlY29y

ZD48ZGF0ZXM+PHB1Yi1kYXRlcz48ZGF0ZT5NYXk8L2RhdGU+PC9wdWItZGF0ZXM+PHllYXI+MjAx

NTwveWVhcj48L2RhdGVzPjxrZXl3b3Jkcz48a2V5d29yZD5BZHVsdDwva2V5d29yZD48a2V5d29y

ZD5BZ2VkPC9rZXl3b3JkPjxrZXl3b3JkPkFnZWQsIDgwIGFuZCBvdmVyPC9rZXl3b3JkPjxrZXl3

b3JkPkJyYWluIElzY2hlbWlhPC9rZXl3b3JkPjxrZXl3b3JkPkRhdGEgSW50ZXJwcmV0YXRpb24s

IFN0YXRpc3RpY2FsPC9rZXl3b3JkPjxrZXl3b3JkPkZlbWFsZTwva2V5d29yZD48a2V5d29yZD5G

aWJyaW5vbHl0aWMgQWdlbnRzPC9rZXl3b3JkPjxrZXl3b3JkPkh1bWFuczwva2V5d29yZD48a2V5

d29yZD5NYWduZXRpYyBSZXNvbmFuY2UgSW1hZ2luZywgQ2luZTwva2V5d29yZD48a2V5d29yZD5N

YWxlPC9rZXl3b3JkPjxrZXl3b3JkPk1pZGRsZSBBZ2VkPC9rZXl3b3JkPjxrZXl3b3JkPk91dGNv

bWUgQXNzZXNzbWVudCAoSGVhbHRoIENhcmUpPC9rZXl3b3JkPjxrZXl3b3JkPlNpbmdsZS1CbGlu

ZCBNZXRob2Q8L2tleXdvcmQ+PGtleXdvcmQ+U3Ryb2tlPC9rZXl3b3JkPjxrZXl3b3JkPlRocm9t

Ym9seXRpYyBUaGVyYXB5PC9rZXl3b3JkPjxrZXl3b3JkPlRpc3N1ZSBQbGFzbWlub2dlbiBBY3Rp

dmF0b3I8L2tleXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cHM6

Ly93d3cubmNiaS5ubG0ubmloLmdvdi9wdWJtZWQvMjU4MTk0ODQ8L3VybD48L3JlbGF0ZWQtdXJs

cz48L3VybHM+PGlzYm4+MTQ3NC00NDY1PC9pc2JuPjxjdXN0b20yPlBNQzQ1MTMxOTA8L2N1c3Rv

bTI+PHRpdGxlcz48dGl0bGU+QXNzb2NpYXRpb24gYmV0d2VlbiBicmFpbiBpbWFnaW5nIHNpZ25z

LCBlYXJseSBhbmQgbGF0ZSBvdXRjb21lcywgYW5kIHJlc3BvbnNlIHRvIGludHJhdmVub3VzIGFs

dGVwbGFzZSBhZnRlciBhY3V0ZSBpc2NoYWVtaWMgc3Ryb2tlIGluIHRoZSB0aGlyZCBJbnRlcm5h

dGlvbmFsIFN0cm9rZSBUcmlhbCAoSVNULTMpOiBzZWNvbmRhcnkgYW5hbHlzaXMgb2YgYSByYW5k

b21pc2VkIGNvbnRyb2xsZWQgdHJpYWw8L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+TGFuY2V0IE5l

dXJvbDwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0bGVzPjxwYWdlcz40ODUtOTY8L3BhZ2VzPjxudW1i

ZXI+NTwvbnVtYmVyPjxjb250cmlidXRvcnM+PGF1dGhvcnM+PGF1dGhvcj5JU1QtMyBjb2xsYWJv

cmF0aXZlIGdyb3VwPC9hdXRob3I+PC9hdXRob3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5F

Tkc8L2xhbmd1YWdlPjxhZGRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc4MTc4ODY3PC9hZGRlZC1k

YXRlPjxyZWYtdHlwZSBuYW1lPSJKb3VybmFsIEFydGljbGUiPjE3PC9yZWYtdHlwZT48cmVjLW51

bWJlcj41MzM8L3JlYy1udW1iZXI+PGxhc3QtdXBkYXRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc4

MTc4ODY3PC9sYXN0LXVwZGF0ZWQtZGF0ZT48YWNjZXNzaW9uLW51bT4yNTgxOTQ4NDwvYWNjZXNz

aW9uLW51bT48ZWxlY3Ryb25pYy1yZXNvdXJjZS1udW0+MTAuMTAxNi9TMTQ3NC00NDIyKDE1KTAw

MDEyLTU8L2VsZWN0cm9uaWMtcmVzb3VyY2UtbnVtPjx2b2x1bWU+MTQ8L3ZvbHVtZT48L3JlY29y

ZD48L0NpdGU+PENpdGU+PEF1dGhvcj5SeXU8L0F1dGhvcj48WWVhcj4yMDE3PC9ZZWFyPjxJRFRl

eHQ+U3Ryb2tlIG91dGNvbWVzIGFyZSB3b3JzZSB3aXRoIGxhcmdlciBsZXVrb2FyYWlvc2lzIHZv

bHVtZXM8L0lEVGV4dD48cmVjb3JkPjxkYXRlcz48cHViLWRhdGVzPjxkYXRlPkphbjwvZGF0ZT48

L3B1Yi1kYXRlcz48eWVhcj4yMDE3PC95ZWFyPjwvZGF0ZXM+PHVybHM+PHJlbGF0ZWQtdXJscz48

dXJsPmh0dHBzOi8vd3d3Lm5jYmkubmxtLm5paC5nb3YvcHVibWVkLzI4MDA4MDAwPC91cmw+PC9y

ZWxhdGVkLXVybHM+PC91cmxzPjxpc2JuPjE0NjAtMjE1NjwvaXNibj48dGl0bGVzPjx0aXRsZT5T

dHJva2Ugb3V0Y29tZXMgYXJlIHdvcnNlIHdpdGggbGFyZ2VyIGxldWtvYXJhaW9zaXMgdm9sdW1l

czwvdGl0bGU+PHNlY29uZGFyeS10aXRsZT5CcmFpbjwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0bGVz

PjxwYWdlcz4xNTgtMTcwPC9wYWdlcz48bnVtYmVyPlB0IDE8L251bWJlcj48Y29udHJpYnV0b3Jz

PjxhdXRob3JzPjxhdXRob3I+Unl1LCBXLiBTLjwvYXV0aG9yPjxhdXRob3I+V29vLCBTLiBILjwv

YXV0aG9yPjxhdXRob3I+U2NoZWxsaW5nZXJob3V0LCBELjwvYXV0aG9yPjxhdXRob3I+SmFuZywg

TS4gVS48L2F1dGhvcj48YXV0aG9yPlBhcmssIEsuIEouPC9hdXRob3I+PGF1dGhvcj5Ib25nLCBL

LiBTLjwvYXV0aG9yPjxhdXRob3I+SmVvbmcsIFMuIFcuPC9hdXRob3I+PGF1dGhvcj5OYSwgSi4g

WS48L2F1dGhvcj48YXV0aG9yPkNobywgSy4gSC48L2F1dGhvcj48YXV0aG9yPktpbSwgSi4gVC48

L2F1dGhvcj48YXV0aG9yPktpbSwgQi4gSi48L2F1dGhvcj48YXV0aG9yPkhhbiwgTS4gSy48L2F1

dGhvcj48YXV0aG9yPkxlZSwgSi48L2F1dGhvcj48YXV0aG9yPkNoYSwgSi4gSy48L2F1dGhvcj48

YXV0aG9yPktpbSwgRC4gSC48L2F1dGhvcj48YXV0aG9yPkxlZSwgUy4gSi48L2F1dGhvcj48YXV0

aG9yPktvLCBZLjwvYXV0aG9yPjxhdXRob3I+Q2hvLCBZLiBKLjwvYXV0aG9yPjxhdXRob3I+TGVl

LCBCLiBDLjwvYXV0aG9yPjxhdXRob3I+WXUsIEsuIEguPC9hdXRob3I+PGF1dGhvcj5PaCwgTS4g

Uy48L2F1dGhvcj48YXV0aG9yPlBhcmssIEouIE0uPC9hdXRob3I+PGF1dGhvcj5LYW5nLCBLLjwv

YXV0aG9yPjxhdXRob3I+TGVlLCBLLiBCLjwvYXV0aG9yPjxhdXRob3I+UGFyaywgVC4gSC48L2F1

dGhvcj48YXV0aG9yPkNob2ksIEguIEsuPC9hdXRob3I+PGF1dGhvcj5MZWUsIEsuPC9hdXRob3I+

PGF1dGhvcj5CYWUsIEguIEouPC9hdXRob3I+PGF1dGhvcj5LaW0sIEQuIEUuPC9hdXRob3I+PC9h

dXRob3JzPjwvY29udHJpYnV0b3JzPjxlZGl0aW9uPjIwMTYvMTIvMjI8L2VkaXRpb24+PGxhbmd1

YWdlPmVuZzwvbGFuZ3VhZ2U+PGFkZGVkLWRhdGUgZm9ybWF0PSJ1dGMiPjE0ODU0MzEzMzg8L2Fk

ZGVkLWRhdGU+PHJlZi10eXBlIG5hbWU9IkpvdXJuYWwgQXJ0aWNsZSI+MTc8L3JlZi10eXBlPjxy

ZWMtbnVtYmVyPjU2ODwvcmVjLW51bWJlcj48bGFzdC11cGRhdGVkLWRhdGUgZm9ybWF0PSJ1dGMi

PjE0ODU0MzEzMzg8L2xhc3QtdXBkYXRlZC1kYXRlPjxhY2Nlc3Npb24tbnVtPjI4MDA4MDAwPC9h

Y2Nlc3Npb24tbnVtPjxlbGVjdHJvbmljLXJlc291cmNlLW51bT4xMC4xMDkzL2JyYWluL2F3dzI1

OTwvZWxlY3Ryb25pYy1yZXNvdXJjZS1udW0+PHZvbHVtZT4xNDA8L3ZvbHVtZT48L3JlY29yZD48

L0NpdGU+PENpdGU+PEF1dGhvcj5IZW5uaW5nZXI8L0F1dGhvcj48WWVhcj4yMDE0PC9ZZWFyPjxJ

RFRleHQ+U2V2ZXJlIGxldWtvYXJhaW9zaXMgcG9ydGVuZHMgYSBwb29yIG91dGNvbWUgYWZ0ZXIg

dHJhdW1hdGljIGJyYWluIGluanVyeTwvSURUZXh0PjxyZWNvcmQ+PGRhdGVzPjxwdWItZGF0ZXM+

PGRhdGU+RGVjPC9kYXRlPjwvcHViLWRhdGVzPjx5ZWFyPjIwMTQ8L3llYXI+PC9kYXRlcz48a2V5

d29yZHM+PGtleXdvcmQ+QWdlIEZhY3RvcnM8L2tleXdvcmQ+PGtleXdvcmQ+QWdlZDwva2V5d29y

ZD48a2V5d29yZD5BZ2VkLCA4MCBhbmQgb3Zlcjwva2V5d29yZD48a2V5d29yZD5CcmFpbiBJbmp1

cmllczwva2V5d29yZD48a2V5d29yZD5Db2hvcnQgU3R1ZGllczwva2V5d29yZD48a2V5d29yZD5G

ZW1hbGU8L2tleXdvcmQ+PGtleXdvcmQ+R2xhc2dvdyBDb21hIFNjYWxlPC9rZXl3b3JkPjxrZXl3

b3JkPkdsYXNnb3cgT3V0Y29tZSBTY2FsZTwva2V5d29yZD48a2V5d29yZD5IdW1hbnM8L2tleXdv

cmQ+PGtleXdvcmQ+TGV1a29hcmFpb3Npczwva2V5d29yZD48a2V5d29yZD5NYWxlPC9rZXl3b3Jk

PjxrZXl3b3JkPk1pZGRsZSBBZ2VkPC9rZXl3b3JkPjxrZXl3b3JkPlByb2dub3Npczwva2V5d29y

ZD48a2V5d29yZD5SZXRyb3NwZWN0aXZlIFN0dWRpZXM8L2tleXdvcmQ+PGtleXdvcmQ+U2V2ZXJp

dHkgb2YgSWxsbmVzcyBJbmRleDwva2V5d29yZD48a2V5d29yZD5Ub21vZ3JhcGh5LCBYLVJheSBD

b21wdXRlZDwva2V5d29yZD48a2V5d29yZD5XaGl0ZSBNYXR0ZXI8L2tleXdvcmQ+PC9rZXl3b3Jk

cz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cHM6Ly93d3cubmNiaS5ubG0ubmloLmdvdi9w

dWJtZWQvMjQ3NTI0NTk8L3VybD48L3JlbGF0ZWQtdXJscz48L3VybHM+PGlzYm4+MTU1Ni0wOTYx

PC9pc2JuPjx0aXRsZXM+PHRpdGxlPlNldmVyZSBsZXVrb2FyYWlvc2lzIHBvcnRlbmRzIGEgcG9v

ciBvdXRjb21lIGFmdGVyIHRyYXVtYXRpYyBicmFpbiBpbmp1cnk8L3RpdGxlPjxzZWNvbmRhcnkt

dGl0bGU+TmV1cm9jcml0IENhcmU8L3NlY29uZGFyeS10aXRsZT48L3RpdGxlcz48cGFnZXM+NDgz

LTk1PC9wYWdlcz48bnVtYmVyPjM8L251bWJlcj48Y29udHJpYnV0b3JzPjxhdXRob3JzPjxhdXRo

b3I+SGVubmluZ2VyLCBOLjwvYXV0aG9yPjxhdXRob3I+SXp6eSwgUy48L2F1dGhvcj48YXV0aG9y

PkNhcmFuZGFuZywgUi48L2F1dGhvcj48YXV0aG9yPkhhbGwsIFcuPC9hdXRob3I+PGF1dGhvcj5N

dWVobHNjaGxlZ2VsLCBTLjwvYXV0aG9yPjwvYXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3Vh

Z2U+ZW5nPC9sYW5ndWFnZT48YWRkZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ4NjA2MDI4ODwvYWRk

ZWQtZGF0ZT48cmVmLXR5cGUgbmFtZT0iSm91cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PHJl

Yy1udW1iZXI+NTY5PC9yZWMtbnVtYmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+

MTQ4NjA2MDI4ODwvbGFzdC11cGRhdGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MjQ3NTI0NTk8L2Fj

Y2Vzc2lvbi1udW0+PGVsZWN0cm9uaWMtcmVzb3VyY2UtbnVtPjEwLjEwMDcvczEyMDI4LTAxNC05

OTgwLTA8L2VsZWN0cm9uaWMtcmVzb3VyY2UtbnVtPjx2b2x1bWU+MjE8L3ZvbHVtZT48L3JlY29y

ZD48L0NpdGU+PC9FbmROb3RlPgAA

ADDIN EN.CITE.DATA 4-6 and hemorrhagic transformation of ischemiaPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5DaGFyaWRpbW91PC9BdXRob3I+PFllYXI+MjAxNjwvWWVh

cj48SURUZXh0PkxldWtvYXJhaW9zaXMsIENlcmVicmFsIEhlbW9ycmhhZ2UsIGFuZCBPdXRjb21l

IEFmdGVyIEludHJhdmVub3VzIFRocm9tYm9seXNpcyBmb3IgQWN1dGUgSXNjaGVtaWMgU3Ryb2tl

OiBBIE1ldGEtQW5hbHlzaXMgKHYxKTwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5bGUgZmFjZT0i

c3VwZXJzY3JpcHQiPjQsIDcsIDg8L3N0eWxlPjwvRGlzcGxheVRleHQ+PHJlY29yZD48ZGF0ZXM+

PHB1Yi1kYXRlcz48ZGF0ZT5TZXA8L2RhdGU+PC9wdWItZGF0ZXM+PHllYXI+MjAxNjwveWVhcj48

L2RhdGVzPjx1cmxzPjxyZWxhdGVkLXVybHM+PHVybD5odHRwczovL3d3dy5uY2JpLm5sbS5uaWgu

Z292L3B1Ym1lZC8yNzQ5MTczODwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJscz48aXNibj4xNTI0

LTQ2Mjg8L2lzYm4+PGN1c3RvbTI+UE1DNDk5NTExOTwvY3VzdG9tMj48dGl0bGVzPjx0aXRsZT5M

ZXVrb2FyYWlvc2lzLCBDZXJlYnJhbCBIZW1vcnJoYWdlLCBhbmQgT3V0Y29tZSBBZnRlciBJbnRy

YXZlbm91cyBUaHJvbWJvbHlzaXMgZm9yIEFjdXRlIElzY2hlbWljIFN0cm9rZTogQSBNZXRhLUFu

YWx5c2lzICh2MSk8L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+U3Ryb2tlPC9zZWNvbmRhcnktdGl0

bGU+PC90aXRsZXM+PHBhZ2VzPjIzNjQtNzI8L3BhZ2VzPjxudW1iZXI+OTwvbnVtYmVyPjxjb250

cmlidXRvcnM+PGF1dGhvcnM+PGF1dGhvcj5DaGFyaWRpbW91LCBBLjwvYXV0aG9yPjxhdXRob3I+

UGFzaSwgTS48L2F1dGhvcj48YXV0aG9yPkZpb3JlbGxpLCBNLjwvYXV0aG9yPjxhdXRob3I+U2hh

bXMsIFMuPC9hdXRob3I+PGF1dGhvcj52b24gS3VtbWVyLCBSLjwvYXV0aG9yPjxhdXRob3I+UGFu

dG9uaSwgTC48L2F1dGhvcj48YXV0aG9yPlJvc3QsIE4uPC9hdXRob3I+PC9hdXRob3JzPjwvY29u

dHJpYnV0b3JzPjxsYW5ndWFnZT5FTkc8L2xhbmd1YWdlPjxhZGRlZC1kYXRlIGZvcm1hdD0idXRj

Ij4xNDc4MTc0ODA4PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1lPSJKb3VybmFsIEFydGljbGUi

PjE3PC9yZWYtdHlwZT48cmVjLW51bWJlcj41MjY8L3JlYy1udW1iZXI+PGxhc3QtdXBkYXRlZC1k

YXRlIGZvcm1hdD0idXRjIj4xNDc4MTc0ODA4PC9sYXN0LXVwZGF0ZWQtZGF0ZT48YWNjZXNzaW9u

LW51bT4yNzQ5MTczODwvYWNjZXNzaW9uLW51bT48ZWxlY3Ryb25pYy1yZXNvdXJjZS1udW0+MTAu

MTE2MS9TVFJPS0VBSEEuMTE2LjAxNDA5NjwvZWxlY3Ryb25pYy1yZXNvdXJjZS1udW0+PHZvbHVt

ZT40Nzwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48Q2l0ZT48QXV0aG9yPldpbGxlcjwvQXV0aG9y

PjxZZWFyPjIwMTU8L1llYXI+PElEVGV4dD5Db21wdXRlZCBUb21vZ3JhcGh5LS1WZXJpZmllZCBM

ZXVrb2FyYWlvc2lzIElzIGEgUmlzayBGYWN0b3IgZm9yIFBvc3QtdGhyb21ib2x5dGljIEhlbW9y

cmhhZ2U8L0lEVGV4dD48cmVjb3JkPjxkYXRlcz48cHViLWRhdGVzPjxkYXRlPkp1bjwvZGF0ZT48

L3B1Yi1kYXRlcz48eWVhcj4yMDE1PC95ZWFyPjwvZGF0ZXM+PGtleXdvcmRzPjxrZXl3b3JkPkFn

ZWQ8L2tleXdvcmQ+PGtleXdvcmQ+QnJhaW4gSXNjaGVtaWE8L2tleXdvcmQ+PGtleXdvcmQ+RmVt

YWxlPC9rZXl3b3JkPjxrZXl3b3JkPkZpYnJpbm9seXRpYyBBZ2VudHM8L2tleXdvcmQ+PGtleXdv

cmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPkludHJhY3JhbmlhbCBIZW1vcnJoYWdlczwva2V5

d29yZD48a2V5d29yZD5MZXVrb2FyYWlvc2lzPC9rZXl3b3JkPjxrZXl3b3JkPk1hbGU8L2tleXdv

cmQ+PGtleXdvcmQ+TWlkZGxlIEFnZWQ8L2tleXdvcmQ+PGtleXdvcmQ+UmV0cm9zcGVjdGl2ZSBT

dHVkaWVzPC9rZXl3b3JkPjxrZXl3b3JkPlJpc2sgRmFjdG9yczwva2V5d29yZD48a2V5d29yZD5T

dHJva2U8L2tleXdvcmQ+PGtleXdvcmQ+VGhyb21ib2x5dGljIFRoZXJhcHk8L2tleXdvcmQ+PGtl

eXdvcmQ+VGlzc3VlIFBsYXNtaW5vZ2VuIEFjdGl2YXRvcjwva2V5d29yZD48L2tleXdvcmRzPjx1

cmxzPjxyZWxhdGVkLXVybHM+PHVybD5odHRwczovL3d3dy5uY2JpLm5sbS5uaWguZ292L3B1Ym1l

ZC8yNTkyMDc1NjwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJscz48aXNibj4xNTMyLTg1MTE8L2lz

Ym4+PHRpdGxlcz48dGl0bGU+Q29tcHV0ZWQgVG9tb2dyYXBoeS0tVmVyaWZpZWQgTGV1a29hcmFp

b3NpcyBJcyBhIFJpc2sgRmFjdG9yIGZvciBQb3N0LXRocm9tYm9seXRpYyBIZW1vcnJoYWdlPC90

aXRsZT48c2Vjb25kYXJ5LXRpdGxlPkogU3Ryb2tlIENlcmVicm92YXNjIERpczwvc2Vjb25kYXJ5

LXRpdGxlPjwvdGl0bGVzPjxwYWdlcz4xMTI2LTMwPC9wYWdlcz48bnVtYmVyPjY8L251bWJlcj48

Y29udHJpYnV0b3JzPjxhdXRob3JzPjxhdXRob3I+V2lsbGVyLCBMLjwvYXV0aG9yPjxhdXRob3I+

SGF2c3RlZW4sIEkuPC9hdXRob3I+PGF1dGhvcj5PdmVzZW4sIEMuPC9hdXRob3I+PGF1dGhvcj5D

aHJpc3RlbnNlbiwgQS4gRi48L2F1dGhvcj48YXV0aG9yPkNocmlzdGVuc2VuLCBILjwvYXV0aG9y

PjwvYXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3VhZ2U+RU5HPC9sYW5ndWFnZT48YWRkZWQt

ZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3ODcxMTUyNjwvYWRkZWQtZGF0ZT48cmVmLXR5cGUgbmFtZT0i

Sm91cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PHJlYy1udW1iZXI+NTUzPC9yZWMtbnVtYmVy

PjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3ODcxMTUyNjwvbGFzdC11cGRhdGVk

LWRhdGU+PGFjY2Vzc2lvbi1udW0+MjU5MjA3NTY8L2FjY2Vzc2lvbi1udW0+PGVsZWN0cm9uaWMt

cmVzb3VyY2UtbnVtPjEwLjEwMTYvai5qc3Ryb2tlY2VyZWJyb3Zhc2Rpcy4yMDE0LjEyLjAxODwv

ZWxlY3Ryb25pYy1yZXNvdXJjZS1udW0+PHZvbHVtZT4yNDwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0

ZT48Q2l0ZT48QXV0aG9yPklTVC0zPC9BdXRob3I+PFllYXI+MjAxNTwvWWVhcj48SURUZXh0PkFz

c29jaWF0aW9uIGJldHdlZW4gYnJhaW4gaW1hZ2luZyBzaWducywgZWFybHkgYW5kIGxhdGUgb3V0

Y29tZXMsIGFuZCByZXNwb25zZSB0byBpbnRyYXZlbm91cyBhbHRlcGxhc2UgYWZ0ZXIgYWN1dGUg

aXNjaGFlbWljIHN0cm9rZSBpbiB0aGUgdGhpcmQgSW50ZXJuYXRpb25hbCBTdHJva2UgVHJpYWwg

KElTVC0zKTogc2Vjb25kYXJ5IGFuYWx5c2lzIG9mIGEgcmFuZG9taXNlZCBjb250cm9sbGVkIHRy

aWFsPC9JRFRleHQ+PHJlY29yZD48ZGF0ZXM+PHB1Yi1kYXRlcz48ZGF0ZT5NYXk8L2RhdGU+PC9w

dWItZGF0ZXM+PHllYXI+MjAxNTwveWVhcj48L2RhdGVzPjxrZXl3b3Jkcz48a2V5d29yZD5BZHVs

dDwva2V5d29yZD48a2V5d29yZD5BZ2VkPC9rZXl3b3JkPjxrZXl3b3JkPkFnZWQsIDgwIGFuZCBv

dmVyPC9rZXl3b3JkPjxrZXl3b3JkPkJyYWluIElzY2hlbWlhPC9rZXl3b3JkPjxrZXl3b3JkPkRh

dGEgSW50ZXJwcmV0YXRpb24sIFN0YXRpc3RpY2FsPC9rZXl3b3JkPjxrZXl3b3JkPkZlbWFsZTwv

a2V5d29yZD48a2V5d29yZD5GaWJyaW5vbHl0aWMgQWdlbnRzPC9rZXl3b3JkPjxrZXl3b3JkPkh1

bWFuczwva2V5d29yZD48a2V5d29yZD5NYWduZXRpYyBSZXNvbmFuY2UgSW1hZ2luZywgQ2luZTwv

a2V5d29yZD48a2V5d29yZD5NYWxlPC9rZXl3b3JkPjxrZXl3b3JkPk1pZGRsZSBBZ2VkPC9rZXl3

b3JkPjxrZXl3b3JkPk91dGNvbWUgQXNzZXNzbWVudCAoSGVhbHRoIENhcmUpPC9rZXl3b3JkPjxr

ZXl3b3JkPlNpbmdsZS1CbGluZCBNZXRob2Q8L2tleXdvcmQ+PGtleXdvcmQ+U3Ryb2tlPC9rZXl3

b3JkPjxrZXl3b3JkPlRocm9tYm9seXRpYyBUaGVyYXB5PC9rZXl3b3JkPjxrZXl3b3JkPlRpc3N1

ZSBQbGFzbWlub2dlbiBBY3RpdmF0b3I8L2tleXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVsYXRl

ZC11cmxzPjx1cmw+aHR0cHM6Ly93d3cubmNiaS5ubG0ubmloLmdvdi9wdWJtZWQvMjU4MTk0ODQ8

L3VybD48L3JlbGF0ZWQtdXJscz48L3VybHM+PGlzYm4+MTQ3NC00NDY1PC9pc2JuPjxjdXN0b20y

PlBNQzQ1MTMxOTA8L2N1c3RvbTI+PHRpdGxlcz48dGl0bGU+QXNzb2NpYXRpb24gYmV0d2VlbiBi

cmFpbiBpbWFnaW5nIHNpZ25zLCBlYXJseSBhbmQgbGF0ZSBvdXRjb21lcywgYW5kIHJlc3BvbnNl

IHRvIGludHJhdmVub3VzIGFsdGVwbGFzZSBhZnRlciBhY3V0ZSBpc2NoYWVtaWMgc3Ryb2tlIGlu

IHRoZSB0aGlyZCBJbnRlcm5hdGlvbmFsIFN0cm9rZSBUcmlhbCAoSVNULTMpOiBzZWNvbmRhcnkg

YW5hbHlzaXMgb2YgYSByYW5kb21pc2VkIGNvbnRyb2xsZWQgdHJpYWw8L3RpdGxlPjxzZWNvbmRh

cnktdGl0bGU+TGFuY2V0IE5ldXJvbDwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0bGVzPjxwYWdlcz40

ODUtOTY8L3BhZ2VzPjxudW1iZXI+NTwvbnVtYmVyPjxjb250cmlidXRvcnM+PGF1dGhvcnM+PGF1

dGhvcj5JU1QtMyBjb2xsYWJvcmF0aXZlIGdyb3VwPC9hdXRob3I+PC9hdXRob3JzPjwvY29udHJp

YnV0b3JzPjxsYW5ndWFnZT5FTkc8L2xhbmd1YWdlPjxhZGRlZC1kYXRlIGZvcm1hdD0idXRjIj4x

NDc4MTc4ODY3PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1lPSJKb3VybmFsIEFydGljbGUiPjE3

PC9yZWYtdHlwZT48cmVjLW51bWJlcj41MzM8L3JlYy1udW1iZXI+PGxhc3QtdXBkYXRlZC1kYXRl

IGZvcm1hdD0idXRjIj4xNDc4MTc4ODY3PC9sYXN0LXVwZGF0ZWQtZGF0ZT48YWNjZXNzaW9uLW51

bT4yNTgxOTQ4NDwvYWNjZXNzaW9uLW51bT48ZWxlY3Ryb25pYy1yZXNvdXJjZS1udW0+MTAuMTAx

Ni9TMTQ3NC00NDIyKDE1KTAwMDEyLTU8L2VsZWN0cm9uaWMtcmVzb3VyY2UtbnVtPjx2b2x1bWU+

MTQ8L3ZvbHVtZT48L3JlY29yZD48L0NpdGU+PC9FbmROb3RlPgAA

ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5DaGFyaWRpbW91PC9BdXRob3I+PFllYXI+MjAxNjwvWWVh

cj48SURUZXh0PkxldWtvYXJhaW9zaXMsIENlcmVicmFsIEhlbW9ycmhhZ2UsIGFuZCBPdXRjb21l

IEFmdGVyIEludHJhdmVub3VzIFRocm9tYm9seXNpcyBmb3IgQWN1dGUgSXNjaGVtaWMgU3Ryb2tl

OiBBIE1ldGEtQW5hbHlzaXMgKHYxKTwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5bGUgZmFjZT0i

c3VwZXJzY3JpcHQiPjQsIDcsIDg8L3N0eWxlPjwvRGlzcGxheVRleHQ+PHJlY29yZD48ZGF0ZXM+

PHB1Yi1kYXRlcz48ZGF0ZT5TZXA8L2RhdGU+PC9wdWItZGF0ZXM+PHllYXI+MjAxNjwveWVhcj48

L2RhdGVzPjx1cmxzPjxyZWxhdGVkLXVybHM+PHVybD5odHRwczovL3d3dy5uY2JpLm5sbS5uaWgu

Z292L3B1Ym1lZC8yNzQ5MTczODwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJscz48aXNibj4xNTI0

LTQ2Mjg8L2lzYm4+PGN1c3RvbTI+UE1DNDk5NTExOTwvY3VzdG9tMj48dGl0bGVzPjx0aXRsZT5M

ZXVrb2FyYWlvc2lzLCBDZXJlYnJhbCBIZW1vcnJoYWdlLCBhbmQgT3V0Y29tZSBBZnRlciBJbnRy

YXZlbm91cyBUaHJvbWJvbHlzaXMgZm9yIEFjdXRlIElzY2hlbWljIFN0cm9rZTogQSBNZXRhLUFu

YWx5c2lzICh2MSk8L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+U3Ryb2tlPC9zZWNvbmRhcnktdGl0

bGU+PC90aXRsZXM+PHBhZ2VzPjIzNjQtNzI8L3BhZ2VzPjxudW1iZXI+OTwvbnVtYmVyPjxjb250

cmlidXRvcnM+PGF1dGhvcnM+PGF1dGhvcj5DaGFyaWRpbW91LCBBLjwvYXV0aG9yPjxhdXRob3I+

UGFzaSwgTS48L2F1dGhvcj48YXV0aG9yPkZpb3JlbGxpLCBNLjwvYXV0aG9yPjxhdXRob3I+U2hh

bXMsIFMuPC9hdXRob3I+PGF1dGhvcj52b24gS3VtbWVyLCBSLjwvYXV0aG9yPjxhdXRob3I+UGFu

dG9uaSwgTC48L2F1dGhvcj48YXV0aG9yPlJvc3QsIE4uPC9hdXRob3I+PC9hdXRob3JzPjwvY29u

dHJpYnV0b3JzPjxsYW5ndWFnZT5FTkc8L2xhbmd1YWdlPjxhZGRlZC1kYXRlIGZvcm1hdD0idXRj

Ij4xNDc4MTc0ODA4PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1lPSJKb3VybmFsIEFydGljbGUi

PjE3PC9yZWYtdHlwZT48cmVjLW51bWJlcj41MjY8L3JlYy1udW1iZXI+PGxhc3QtdXBkYXRlZC1k

YXRlIGZvcm1hdD0idXRjIj4xNDc4MTc0ODA4PC9sYXN0LXVwZGF0ZWQtZGF0ZT48YWNjZXNzaW9u

LW51bT4yNzQ5MTczODwvYWNjZXNzaW9uLW51bT48ZWxlY3Ryb25pYy1yZXNvdXJjZS1udW0+MTAu

MTE2MS9TVFJPS0VBSEEuMTE2LjAxNDA5NjwvZWxlY3Ryb25pYy1yZXNvdXJjZS1udW0+PHZvbHVt

ZT40Nzwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48Q2l0ZT48QXV0aG9yPldpbGxlcjwvQXV0aG9y

PjxZZWFyPjIwMTU8L1llYXI+PElEVGV4dD5Db21wdXRlZCBUb21vZ3JhcGh5LS1WZXJpZmllZCBM

ZXVrb2FyYWlvc2lzIElzIGEgUmlzayBGYWN0b3IgZm9yIFBvc3QtdGhyb21ib2x5dGljIEhlbW9y

cmhhZ2U8L0lEVGV4dD48cmVjb3JkPjxkYXRlcz48cHViLWRhdGVzPjxkYXRlPkp1bjwvZGF0ZT48

L3B1Yi1kYXRlcz48eWVhcj4yMDE1PC95ZWFyPjwvZGF0ZXM+PGtleXdvcmRzPjxrZXl3b3JkPkFn

ZWQ8L2tleXdvcmQ+PGtleXdvcmQ+QnJhaW4gSXNjaGVtaWE8L2tleXdvcmQ+PGtleXdvcmQ+RmVt

YWxlPC9rZXl3b3JkPjxrZXl3b3JkPkZpYnJpbm9seXRpYyBBZ2VudHM8L2tleXdvcmQ+PGtleXdv

cmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPkludHJhY3JhbmlhbCBIZW1vcnJoYWdlczwva2V5

d29yZD48a2V5d29yZD5MZXVrb2FyYWlvc2lzPC9rZXl3b3JkPjxrZXl3b3JkPk1hbGU8L2tleXdv

cmQ+PGtleXdvcmQ+TWlkZGxlIEFnZWQ8L2tleXdvcmQ+PGtleXdvcmQ+UmV0cm9zcGVjdGl2ZSBT

dHVkaWVzPC9rZXl3b3JkPjxrZXl3b3JkPlJpc2sgRmFjdG9yczwva2V5d29yZD48a2V5d29yZD5T

dHJva2U8L2tleXdvcmQ+PGtleXdvcmQ+VGhyb21ib2x5dGljIFRoZXJhcHk8L2tleXdvcmQ+PGtl

eXdvcmQ+VGlzc3VlIFBsYXNtaW5vZ2VuIEFjdGl2YXRvcjwva2V5d29yZD48L2tleXdvcmRzPjx1

cmxzPjxyZWxhdGVkLXVybHM+PHVybD5odHRwczovL3d3dy5uY2JpLm5sbS5uaWguZ292L3B1Ym1l

ZC8yNTkyMDc1NjwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJscz48aXNibj4xNTMyLTg1MTE8L2lz

Ym4+PHRpdGxlcz48dGl0bGU+Q29tcHV0ZWQgVG9tb2dyYXBoeS0tVmVyaWZpZWQgTGV1a29hcmFp

b3NpcyBJcyBhIFJpc2sgRmFjdG9yIGZvciBQb3N0LXRocm9tYm9seXRpYyBIZW1vcnJoYWdlPC90

aXRsZT48c2Vjb25kYXJ5LXRpdGxlPkogU3Ryb2tlIENlcmVicm92YXNjIERpczwvc2Vjb25kYXJ5

LXRpdGxlPjwvdGl0bGVzPjxwYWdlcz4xMTI2LTMwPC9wYWdlcz48bnVtYmVyPjY8L251bWJlcj48

Y29udHJpYnV0b3JzPjxhdXRob3JzPjxhdXRob3I+V2lsbGVyLCBMLjwvYXV0aG9yPjxhdXRob3I+

SGF2c3RlZW4sIEkuPC9hdXRob3I+PGF1dGhvcj5PdmVzZW4sIEMuPC9hdXRob3I+PGF1dGhvcj5D

aHJpc3RlbnNlbiwgQS4gRi48L2F1dGhvcj48YXV0aG9yPkNocmlzdGVuc2VuLCBILjwvYXV0aG9y

PjwvYXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3VhZ2U+RU5HPC9sYW5ndWFnZT48YWRkZWQt

ZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3ODcxMTUyNjwvYWRkZWQtZGF0ZT48cmVmLXR5cGUgbmFtZT0i

Sm91cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PHJlYy1udW1iZXI+NTUzPC9yZWMtbnVtYmVy

PjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3ODcxMTUyNjwvbGFzdC11cGRhdGVk

LWRhdGU+PGFjY2Vzc2lvbi1udW0+MjU5MjA3NTY8L2FjY2Vzc2lvbi1udW0+PGVsZWN0cm9uaWMt

cmVzb3VyY2UtbnVtPjEwLjEwMTYvai5qc3Ryb2tlY2VyZWJyb3Zhc2Rpcy4yMDE0LjEyLjAxODwv

ZWxlY3Ryb25pYy1yZXNvdXJjZS1udW0+PHZvbHVtZT4yNDwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0

ZT48Q2l0ZT48QXV0aG9yPklTVC0zPC9BdXRob3I+PFllYXI+MjAxNTwvWWVhcj48SURUZXh0PkFz

c29jaWF0aW9uIGJldHdlZW4gYnJhaW4gaW1hZ2luZyBzaWducywgZWFybHkgYW5kIGxhdGUgb3V0

Y29tZXMsIGFuZCByZXNwb25zZSB0byBpbnRyYXZlbm91cyBhbHRlcGxhc2UgYWZ0ZXIgYWN1dGUg

aXNjaGFlbWljIHN0cm9rZSBpbiB0aGUgdGhpcmQgSW50ZXJuYXRpb25hbCBTdHJva2UgVHJpYWwg

KElTVC0zKTogc2Vjb25kYXJ5IGFuYWx5c2lzIG9mIGEgcmFuZG9taXNlZCBjb250cm9sbGVkIHRy

aWFsPC9JRFRleHQ+PHJlY29yZD48ZGF0ZXM+PHB1Yi1kYXRlcz48ZGF0ZT5NYXk8L2RhdGU+PC9w

dWItZGF0ZXM+PHllYXI+MjAxNTwveWVhcj48L2RhdGVzPjxrZXl3b3Jkcz48a2V5d29yZD5BZHVs

dDwva2V5d29yZD48a2V5d29yZD5BZ2VkPC9rZXl3b3JkPjxrZXl3b3JkPkFnZWQsIDgwIGFuZCBv

dmVyPC9rZXl3b3JkPjxrZXl3b3JkPkJyYWluIElzY2hlbWlhPC9rZXl3b3JkPjxrZXl3b3JkPkRh

dGEgSW50ZXJwcmV0YXRpb24sIFN0YXRpc3RpY2FsPC9rZXl3b3JkPjxrZXl3b3JkPkZlbWFsZTwv

a2V5d29yZD48a2V5d29yZD5GaWJyaW5vbHl0aWMgQWdlbnRzPC9rZXl3b3JkPjxrZXl3b3JkPkh1

bWFuczwva2V5d29yZD48a2V5d29yZD5NYWduZXRpYyBSZXNvbmFuY2UgSW1hZ2luZywgQ2luZTwv

a2V5d29yZD48a2V5d29yZD5NYWxlPC9rZXl3b3JkPjxrZXl3b3JkPk1pZGRsZSBBZ2VkPC9rZXl3

b3JkPjxrZXl3b3JkPk91dGNvbWUgQXNzZXNzbWVudCAoSGVhbHRoIENhcmUpPC9rZXl3b3JkPjxr

ZXl3b3JkPlNpbmdsZS1CbGluZCBNZXRob2Q8L2tleXdvcmQ+PGtleXdvcmQ+U3Ryb2tlPC9rZXl3

b3JkPjxrZXl3b3JkPlRocm9tYm9seXRpYyBUaGVyYXB5PC9rZXl3b3JkPjxrZXl3b3JkPlRpc3N1

ZSBQbGFzbWlub2dlbiBBY3RpdmF0b3I8L2tleXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVsYXRl

ZC11cmxzPjx1cmw+aHR0cHM6Ly93d3cubmNiaS5ubG0ubmloLmdvdi9wdWJtZWQvMjU4MTk0ODQ8

L3VybD48L3JlbGF0ZWQtdXJscz48L3VybHM+PGlzYm4+MTQ3NC00NDY1PC9pc2JuPjxjdXN0b20y

PlBNQzQ1MTMxOTA8L2N1c3RvbTI+PHRpdGxlcz48dGl0bGU+QXNzb2NpYXRpb24gYmV0d2VlbiBi

cmFpbiBpbWFnaW5nIHNpZ25zLCBlYXJseSBhbmQgbGF0ZSBvdXRjb21lcywgYW5kIHJlc3BvbnNl

IHRvIGludHJhdmVub3VzIGFsdGVwbGFzZSBhZnRlciBhY3V0ZSBpc2NoYWVtaWMgc3Ryb2tlIGlu

IHRoZSB0aGlyZCBJbnRlcm5hdGlvbmFsIFN0cm9rZSBUcmlhbCAoSVNULTMpOiBzZWNvbmRhcnkg

YW5hbHlzaXMgb2YgYSByYW5kb21pc2VkIGNvbnRyb2xsZWQgdHJpYWw8L3RpdGxlPjxzZWNvbmRh

cnktdGl0bGU+TGFuY2V0IE5ldXJvbDwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0bGVzPjxwYWdlcz40

ODUtOTY8L3BhZ2VzPjxudW1iZXI+NTwvbnVtYmVyPjxjb250cmlidXRvcnM+PGF1dGhvcnM+PGF1

dGhvcj5JU1QtMyBjb2xsYWJvcmF0aXZlIGdyb3VwPC9hdXRob3I+PC9hdXRob3JzPjwvY29udHJp

YnV0b3JzPjxsYW5ndWFnZT5FTkc8L2xhbmd1YWdlPjxhZGRlZC1kYXRlIGZvcm1hdD0idXRjIj4x

NDc4MTc4ODY3PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1lPSJKb3VybmFsIEFydGljbGUiPjE3

PC9yZWYtdHlwZT48cmVjLW51bWJlcj41MzM8L3JlYy1udW1iZXI+PGxhc3QtdXBkYXRlZC1kYXRl

IGZvcm1hdD0idXRjIj4xNDc4MTc4ODY3PC9sYXN0LXVwZGF0ZWQtZGF0ZT48YWNjZXNzaW9uLW51

bT4yNTgxOTQ4NDwvYWNjZXNzaW9uLW51bT48ZWxlY3Ryb25pYy1yZXNvdXJjZS1udW0+MTAuMTAx

Ni9TMTQ3NC00NDIyKDE1KTAwMDEyLTU8L2VsZWN0cm9uaWMtcmVzb3VyY2UtbnVtPjx2b2x1bWU+

MTQ8L3ZvbHVtZT48L3JlY29yZD48L0NpdGU+PC9FbmROb3RlPgAA

ADDIN EN.CITE.DATA 4, 7, 8. For dementia, even though MRI is well-recognised to be superior in contributing towards diagnosis, hospital audits suggest that CT is used exclusively in the majority of casesPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5BbGFjaGthcjwvQXV0aG9yPjxZZWFyPjIwMTQ8L1llYXI+

PElEVGV4dD5OZXVyb2ltYWdpbmcgaW4gZGVtZW50aWE6IGhvdyBiZXN0IHRvIHVzZSB0aGUgZ3Vp

ZGVsaW5lcz88L0lEVGV4dD48RGlzcGxheVRleHQ+PHN0eWxlIGZhY2U9InN1cGVyc2NyaXB0Ij45

LTExPC9zdHlsZT48L0Rpc3BsYXlUZXh0PjxyZWNvcmQ+PGRhdGVzPjxwdWItZGF0ZXM+PGRhdGU+

SnVuPC9kYXRlPjwvcHViLWRhdGVzPjx5ZWFyPjIwMTQ8L3llYXI+PC9kYXRlcz48dXJscz48cmVs

YXRlZC11cmxzPjx1cmw+aHR0cHM6Ly93d3cubmNiaS5ubG0ubmloLmdvdi9wdWJtZWQvMjUyMzc1

MjU8L3VybD48L3JlbGF0ZWQtdXJscz48L3VybHM+PGlzYm4+MjA1My00ODY4PC9pc2JuPjxjdXN0

b20yPlBNQzQxMTUzODQ8L2N1c3RvbTI+PHRpdGxlcz48dGl0bGU+TmV1cm9pbWFnaW5nIGluIGRl

bWVudGlhOiBob3cgYmVzdCB0byB1c2UgdGhlIGd1aWRlbGluZXM/PC90aXRsZT48c2Vjb25kYXJ5

LXRpdGxlPlBzeWNoaWF0ciBCdWxsICgyMDE0KTwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0bGVzPjxw

YWdlcz4xMzctODwvcGFnZXM+PG51bWJlcj4zPC9udW1iZXI+PGNvbnRyaWJ1dG9ycz48YXV0aG9y

cz48YXV0aG9yPkFsYWNoa2FyLCBNLjwvYXV0aG9yPjwvYXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48

bGFuZ3VhZ2U+RU5HPC9sYW5ndWFnZT48YWRkZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3ODE3NTQz

MjwvYWRkZWQtZGF0ZT48cmVmLXR5cGUgbmFtZT0iSm91cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5

cGU+PHJlYy1udW1iZXI+NTI4PC9yZWMtbnVtYmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9

InV0YyI+MTQ3ODE3NTQzMjwvbGFzdC11cGRhdGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MjUyMzc1

MjU8L2FjY2Vzc2lvbi1udW0+PGVsZWN0cm9uaWMtcmVzb3VyY2UtbnVtPjEwLjExOTIvcGIuMzgu

My4xMzdhPC9lbGVjdHJvbmljLXJlc291cmNlLW51bT48dm9sdW1lPjM4PC92b2x1bWU+PC9yZWNv

cmQ+PC9DaXRlPjxDaXRlPjxBdXRob3I+S3VydXZpbGxhPC9BdXRob3I+PFllYXI+MjAxNDwvWWVh

cj48SURUZXh0Pk5ldXJvaW1hZ2luZyBpbiBhIG1lbW9yeSBhc3Nlc3NtZW50IHNlcnZpY2U6IGEg

Y29tcGxldGVkIGF1ZGl0IGN5Y2xlPC9JRFRleHQ+PHJlY29yZD48ZGF0ZXM+PHB1Yi1kYXRlcz48

ZGF0ZT5GZWI8L2RhdGU+PC9wdWItZGF0ZXM+PHllYXI+MjAxNDwveWVhcj48L2RhdGVzPjx1cmxz

PjxyZWxhdGVkLXVybHM+PHVybD5odHRwczovL3d3dy5uY2JpLm5sbS5uaWguZ292L3B1Ym1lZC8y

NTIzNzQ4NjwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJscz48aXNibj4yMDUzLTQ4Njg8L2lzYm4+

PGN1c3RvbTI+UE1DNDA2Nzg0NDwvY3VzdG9tMj48dGl0bGVzPjx0aXRsZT5OZXVyb2ltYWdpbmcg

aW4gYSBtZW1vcnkgYXNzZXNzbWVudCBzZXJ2aWNlOiBhIGNvbXBsZXRlZCBhdWRpdCBjeWNsZTwv

dGl0bGU+PHNlY29uZGFyeS10aXRsZT5Qc3ljaGlhdHIgQnVsbCAoMjAxNCk8L3NlY29uZGFyeS10

aXRsZT48L3RpdGxlcz48cGFnZXM+MjQtODwvcGFnZXM+PG51bWJlcj4xPC9udW1iZXI+PGNvbnRy

aWJ1dG9ycz48YXV0aG9ycz48YXV0aG9yPkt1cnV2aWxsYSwgVC48L2F1dGhvcj48YXV0aG9yPlpo

ZW5nLCBSLjwvYXV0aG9yPjxhdXRob3I+U29kZW4sIEIuPC9hdXRob3I+PGF1dGhvcj5HcmVlZiwg

Uy48L2F1dGhvcj48YXV0aG9yPkx5YnVybiwgSS48L2F1dGhvcj48L2F1dGhvcnM+PC9jb250cmli

dXRvcnM+PGxhbmd1YWdlPkVORzwvbGFuZ3VhZ2U+PGFkZGVkLWRhdGUgZm9ybWF0PSJ1dGMiPjE0

NzgxNzUzMzE8L2FkZGVkLWRhdGU+PHJlZi10eXBlIG5hbWU9IkpvdXJuYWwgQXJ0aWNsZSI+MTc8

L3JlZi10eXBlPjxyZWMtbnVtYmVyPjUyNzwvcmVjLW51bWJlcj48bGFzdC11cGRhdGVkLWRhdGUg

Zm9ybWF0PSJ1dGMiPjE0NzgxNzUzMzE8L2xhc3QtdXBkYXRlZC1kYXRlPjxhY2Nlc3Npb24tbnVt

PjI1MjM3NDg2PC9hY2Nlc3Npb24tbnVtPjxlbGVjdHJvbmljLXJlc291cmNlLW51bT4xMC4xMTky

L3BiLmJwLjExMy4wNDMzOTg8L2VsZWN0cm9uaWMtcmVzb3VyY2UtbnVtPjx2b2x1bWU+Mzg8L3Zv

bHVtZT48L3JlY29yZD48L0NpdGU+PENpdGU+PEF1dGhvcj5SaWVsbG88L0F1dGhvcj48WWVhcj4y

MDAzPC9ZZWFyPjxJRFRleHQ+UHJlc2NyaXB0aW9uIHByYWN0aWNlcyBvZiBkaWFnbm9zdGljIGlt

YWdpbmcgaW4gZGVtZW50aWE6IGEgc3VydmV5IG9mIDQ3IEFsemhlaW1lciZhcG9zO3MgQ2VudHJl

cyBpbiBOb3J0aGVybiBJdGFseTwvSURUZXh0PjxyZWNvcmQ+PGRhdGVzPjxwdWItZGF0ZXM+PGRh

dGU+SnVsPC9kYXRlPjwvcHViLWRhdGVzPjx5ZWFyPjIwMDM8L3llYXI+PC9kYXRlcz48a2V5d29y

ZHM+PGtleXdvcmQ+RGVtZW50aWE8L2tleXdvcmQ+PGtleXdvcmQ+RGlhZ25vc3RpYyBJbWFnaW5n

PC9rZXl3b3JkPjxrZXl3b3JkPkh1bWFuczwva2V5d29yZD48a2V5d29yZD5JdGFseTwva2V5d29y

ZD48a2V5d29yZD5NYWduZXRpYyBSZXNvbmFuY2UgSW1hZ2luZzwva2V5d29yZD48a2V5d29yZD5T

dXJ2ZXlzIGFuZCBRdWVzdGlvbm5haXJlczwva2V5d29yZD48a2V5d29yZD5Ub21vZ3JhcGh5LCBF

bWlzc2lvbi1Db21wdXRlZCwgU2luZ2xlLVBob3Rvbjwva2V5d29yZD48a2V5d29yZD5Ub21vZ3Jh

cGh5LCBYLVJheSBDb21wdXRlZDwva2V5d29yZD48L2tleXdvcmRzPjx1cmxzPjxyZWxhdGVkLXVy

bHM+PHVybD5odHRwczovL3d3dy5uY2JpLm5sbS5uaWguZ292L3B1Ym1lZC8xMjgzMzMwMTwvdXJs

PjwvcmVsYXRlZC11cmxzPjwvdXJscz48aXNibj4wODg1LTYyMzA8L2lzYm4+PHRpdGxlcz48dGl0

bGU+UHJlc2NyaXB0aW9uIHByYWN0aWNlcyBvZiBkaWFnbm9zdGljIGltYWdpbmcgaW4gZGVtZW50

aWE6IGEgc3VydmV5IG9mIDQ3IEFsemhlaW1lciZhcG9zO3MgQ2VudHJlcyBpbiBOb3J0aGVybiBJ

dGFseTwvdGl0bGU+PHNlY29uZGFyeS10aXRsZT5JbnQgSiBHZXJpYXRyIFBzeWNoaWF0cnk8L3Nl

Y29uZGFyeS10aXRsZT48L3RpdGxlcz48cGFnZXM+NTc3LTg1PC9wYWdlcz48bnVtYmVyPjc8L251

bWJlcj48Y29udHJpYnV0b3JzPjxhdXRob3JzPjxhdXRob3I+UmllbGxvLCBSLjwvYXV0aG9yPjxh

dXRob3I+QWxiaW5pLCBDLjwvYXV0aG9yPjxhdXRob3I+R2FsbHV6emksIFMuPC9hdXRob3I+PGF1

dGhvcj5QYXNxdWFsZXR0aSwgUC48L2F1dGhvcj48YXV0aG9yPkZyaXNvbmksIEcuIEIuPC9hdXRo

b3I+PC9hdXRob3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5FTkc8L2xhbmd1YWdlPjxhZGRl

ZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc4Njk3OTQ3PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1l

PSJKb3VybmFsIEFydGljbGUiPjE3PC9yZWYtdHlwZT48cmVjLW51bWJlcj41NDU8L3JlYy1udW1i

ZXI+PGxhc3QtdXBkYXRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc4Njk3OTQ3PC9sYXN0LXVwZGF0

ZWQtZGF0ZT48YWNjZXNzaW9uLW51bT4xMjgzMzMwMTwvYWNjZXNzaW9uLW51bT48ZWxlY3Ryb25p

Yy1yZXNvdXJjZS1udW0+MTAuMTAwMi9ncHMuODkzPC9lbGVjdHJvbmljLXJlc291cmNlLW51bT48

dm9sdW1lPjE4PC92b2x1bWU+PC9yZWNvcmQ+PC9DaXRlPjwvRW5kTm90ZT4AAAA=

ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5BbGFjaGthcjwvQXV0aG9yPjxZZWFyPjIwMTQ8L1llYXI+

PElEVGV4dD5OZXVyb2ltYWdpbmcgaW4gZGVtZW50aWE6IGhvdyBiZXN0IHRvIHVzZSB0aGUgZ3Vp

ZGVsaW5lcz88L0lEVGV4dD48RGlzcGxheVRleHQ+PHN0eWxlIGZhY2U9InN1cGVyc2NyaXB0Ij45

LTExPC9zdHlsZT48L0Rpc3BsYXlUZXh0PjxyZWNvcmQ+PGRhdGVzPjxwdWItZGF0ZXM+PGRhdGU+

SnVuPC9kYXRlPjwvcHViLWRhdGVzPjx5ZWFyPjIwMTQ8L3llYXI+PC9kYXRlcz48dXJscz48cmVs

YXRlZC11cmxzPjx1cmw+aHR0cHM6Ly93d3cubmNiaS5ubG0ubmloLmdvdi9wdWJtZWQvMjUyMzc1

MjU8L3VybD48L3JlbGF0ZWQtdXJscz48L3VybHM+PGlzYm4+MjA1My00ODY4PC9pc2JuPjxjdXN0

b20yPlBNQzQxMTUzODQ8L2N1c3RvbTI+PHRpdGxlcz48dGl0bGU+TmV1cm9pbWFnaW5nIGluIGRl

bWVudGlhOiBob3cgYmVzdCB0byB1c2UgdGhlIGd1aWRlbGluZXM/PC90aXRsZT48c2Vjb25kYXJ5

LXRpdGxlPlBzeWNoaWF0ciBCdWxsICgyMDE0KTwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0bGVzPjxw

YWdlcz4xMzctODwvcGFnZXM+PG51bWJlcj4zPC9udW1iZXI+PGNvbnRyaWJ1dG9ycz48YXV0aG9y

cz48YXV0aG9yPkFsYWNoa2FyLCBNLjwvYXV0aG9yPjwvYXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48

bGFuZ3VhZ2U+RU5HPC9sYW5ndWFnZT48YWRkZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3ODE3NTQz

MjwvYWRkZWQtZGF0ZT48cmVmLXR5cGUgbmFtZT0iSm91cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5

cGU+PHJlYy1udW1iZXI+NTI4PC9yZWMtbnVtYmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9

InV0YyI+MTQ3ODE3NTQzMjwvbGFzdC11cGRhdGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MjUyMzc1

MjU8L2FjY2Vzc2lvbi1udW0+PGVsZWN0cm9uaWMtcmVzb3VyY2UtbnVtPjEwLjExOTIvcGIuMzgu

My4xMzdhPC9lbGVjdHJvbmljLXJlc291cmNlLW51bT48dm9sdW1lPjM4PC92b2x1bWU+PC9yZWNv

cmQ+PC9DaXRlPjxDaXRlPjxBdXRob3I+S3VydXZpbGxhPC9BdXRob3I+PFllYXI+MjAxNDwvWWVh

cj48SURUZXh0Pk5ldXJvaW1hZ2luZyBpbiBhIG1lbW9yeSBhc3Nlc3NtZW50IHNlcnZpY2U6IGEg

Y29tcGxldGVkIGF1ZGl0IGN5Y2xlPC9JRFRleHQ+PHJlY29yZD48ZGF0ZXM+PHB1Yi1kYXRlcz48

ZGF0ZT5GZWI8L2RhdGU+PC9wdWItZGF0ZXM+PHllYXI+MjAxNDwveWVhcj48L2RhdGVzPjx1cmxz

PjxyZWxhdGVkLXVybHM+PHVybD5odHRwczovL3d3dy5uY2JpLm5sbS5uaWguZ292L3B1Ym1lZC8y

NTIzNzQ4NjwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJscz48aXNibj4yMDUzLTQ4Njg8L2lzYm4+

PGN1c3RvbTI+UE1DNDA2Nzg0NDwvY3VzdG9tMj48dGl0bGVzPjx0aXRsZT5OZXVyb2ltYWdpbmcg

aW4gYSBtZW1vcnkgYXNzZXNzbWVudCBzZXJ2aWNlOiBhIGNvbXBsZXRlZCBhdWRpdCBjeWNsZTwv

dGl0bGU+PHNlY29uZGFyeS10aXRsZT5Qc3ljaGlhdHIgQnVsbCAoMjAxNCk8L3NlY29uZGFyeS10

aXRsZT48L3RpdGxlcz48cGFnZXM+MjQtODwvcGFnZXM+PG51bWJlcj4xPC9udW1iZXI+PGNvbnRy

aWJ1dG9ycz48YXV0aG9ycz48YXV0aG9yPkt1cnV2aWxsYSwgVC48L2F1dGhvcj48YXV0aG9yPlpo

ZW5nLCBSLjwvYXV0aG9yPjxhdXRob3I+U29kZW4sIEIuPC9hdXRob3I+PGF1dGhvcj5HcmVlZiwg

Uy48L2F1dGhvcj48YXV0aG9yPkx5YnVybiwgSS48L2F1dGhvcj48L2F1dGhvcnM+PC9jb250cmli

dXRvcnM+PGxhbmd1YWdlPkVORzwvbGFuZ3VhZ2U+PGFkZGVkLWRhdGUgZm9ybWF0PSJ1dGMiPjE0

NzgxNzUzMzE8L2FkZGVkLWRhdGU+PHJlZi10eXBlIG5hbWU9IkpvdXJuYWwgQXJ0aWNsZSI+MTc8

L3JlZi10eXBlPjxyZWMtbnVtYmVyPjUyNzwvcmVjLW51bWJlcj48bGFzdC11cGRhdGVkLWRhdGUg

Zm9ybWF0PSJ1dGMiPjE0NzgxNzUzMzE8L2xhc3QtdXBkYXRlZC1kYXRlPjxhY2Nlc3Npb24tbnVt

PjI1MjM3NDg2PC9hY2Nlc3Npb24tbnVtPjxlbGVjdHJvbmljLXJlc291cmNlLW51bT4xMC4xMTky

L3BiLmJwLjExMy4wNDMzOTg8L2VsZWN0cm9uaWMtcmVzb3VyY2UtbnVtPjx2b2x1bWU+Mzg8L3Zv

bHVtZT48L3JlY29yZD48L0NpdGU+PENpdGU+PEF1dGhvcj5SaWVsbG88L0F1dGhvcj48WWVhcj4y

MDAzPC9ZZWFyPjxJRFRleHQ+UHJlc2NyaXB0aW9uIHByYWN0aWNlcyBvZiBkaWFnbm9zdGljIGlt

YWdpbmcgaW4gZGVtZW50aWE6IGEgc3VydmV5IG9mIDQ3IEFsemhlaW1lciZhcG9zO3MgQ2VudHJl

cyBpbiBOb3J0aGVybiBJdGFseTwvSURUZXh0PjxyZWNvcmQ+PGRhdGVzPjxwdWItZGF0ZXM+PGRh

dGU+SnVsPC9kYXRlPjwvcHViLWRhdGVzPjx5ZWFyPjIwMDM8L3llYXI+PC9kYXRlcz48a2V5d29y

ZHM+PGtleXdvcmQ+RGVtZW50aWE8L2tleXdvcmQ+PGtleXdvcmQ+RGlhZ25vc3RpYyBJbWFnaW5n

PC9rZXl3b3JkPjxrZXl3b3JkPkh1bWFuczwva2V5d29yZD48a2V5d29yZD5JdGFseTwva2V5d29y

ZD48a2V5d29yZD5NYWduZXRpYyBSZXNvbmFuY2UgSW1hZ2luZzwva2V5d29yZD48a2V5d29yZD5T

dXJ2ZXlzIGFuZCBRdWVzdGlvbm5haXJlczwva2V5d29yZD48a2V5d29yZD5Ub21vZ3JhcGh5LCBF

bWlzc2lvbi1Db21wdXRlZCwgU2luZ2xlLVBob3Rvbjwva2V5d29yZD48a2V5d29yZD5Ub21vZ3Jh

cGh5LCBYLVJheSBDb21wdXRlZDwva2V5d29yZD48L2tleXdvcmRzPjx1cmxzPjxyZWxhdGVkLXVy

bHM+PHVybD5odHRwczovL3d3dy5uY2JpLm5sbS5uaWguZ292L3B1Ym1lZC8xMjgzMzMwMTwvdXJs

PjwvcmVsYXRlZC11cmxzPjwvdXJscz48aXNibj4wODg1LTYyMzA8L2lzYm4+PHRpdGxlcz48dGl0

bGU+UHJlc2NyaXB0aW9uIHByYWN0aWNlcyBvZiBkaWFnbm9zdGljIGltYWdpbmcgaW4gZGVtZW50

aWE6IGEgc3VydmV5IG9mIDQ3IEFsemhlaW1lciZhcG9zO3MgQ2VudHJlcyBpbiBOb3J0aGVybiBJ

dGFseTwvdGl0bGU+PHNlY29uZGFyeS10aXRsZT5JbnQgSiBHZXJpYXRyIFBzeWNoaWF0cnk8L3Nl

Y29uZGFyeS10aXRsZT48L3RpdGxlcz48cGFnZXM+NTc3LTg1PC9wYWdlcz48bnVtYmVyPjc8L251

bWJlcj48Y29udHJpYnV0b3JzPjxhdXRob3JzPjxhdXRob3I+UmllbGxvLCBSLjwvYXV0aG9yPjxh

dXRob3I+QWxiaW5pLCBDLjwvYXV0aG9yPjxhdXRob3I+R2FsbHV6emksIFMuPC9hdXRob3I+PGF1

dGhvcj5QYXNxdWFsZXR0aSwgUC48L2F1dGhvcj48YXV0aG9yPkZyaXNvbmksIEcuIEIuPC9hdXRo

b3I+PC9hdXRob3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5FTkc8L2xhbmd1YWdlPjxhZGRl

ZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc4Njk3OTQ3PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1l

PSJKb3VybmFsIEFydGljbGUiPjE3PC9yZWYtdHlwZT48cmVjLW51bWJlcj41NDU8L3JlYy1udW1i

ZXI+PGxhc3QtdXBkYXRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc4Njk3OTQ3PC9sYXN0LXVwZGF0

ZWQtZGF0ZT48YWNjZXNzaW9uLW51bT4xMjgzMzMwMTwvYWNjZXNzaW9uLW51bT48ZWxlY3Ryb25p

Yy1yZXNvdXJjZS1udW0+MTAuMTAwMi9ncHMuODkzPC9lbGVjdHJvbmljLXJlc291cmNlLW51bT48

dm9sdW1lPjE4PC92b2x1bWU+PC9yZWNvcmQ+PC9DaXRlPjwvRW5kTm90ZT4AAAA=

ADDIN EN.CITE.DATA 9-11.Assessment of cerebral WML on CT, is more challenging than using MRI, because signal characteristics of WML (hypoattenuation) are less distinctive relative to background white matter on CTPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XYWhsdW5kPC9BdXRob3I+PFllYXI+MjAwMTwvWWVhcj48

SURUZXh0PkEgbmV3IHJhdGluZyBzY2FsZSBmb3IgYWdlLXJlbGF0ZWQgd2hpdGUgbWF0dGVyIGNo

YW5nZXMgYXBwbGljYWJsZSB0byBNUkkgYW5kIENULjwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5

bGUgZmFjZT0ic3VwZXJzY3JpcHQiPjEyPC9zdHlsZT48L0Rpc3BsYXlUZXh0PjxyZWNvcmQ+PGRh

dGVzPjxwdWItZGF0ZXM+PGRhdGU+SnVuPC9kYXRlPjwvcHViLWRhdGVzPjx5ZWFyPjIwMDE8L3ll

YXI+PC9kYXRlcz48a2V5d29yZHM+PGtleXdvcmQ+QWdpbmc8L2tleXdvcmQ+PGtleXdvcmQ+QnJh

aW48L2tleXdvcmQ+PGtleXdvcmQ+QnJhaW4gRGlzZWFzZXM8L2tleXdvcmQ+PGtleXdvcmQ+Q29n

bml0aW9uIERpc29yZGVyczwva2V5d29yZD48a2V5d29yZD5FdXJvcGU8L2tleXdvcmQ+PGtleXdv

cmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPk1hZ25ldGljIFJlc29uYW5jZSBJbWFnaW5nPC9r

ZXl3b3JkPjxrZXl3b3JkPk1lbW9yeSBEaXNvcmRlcnM8L2tleXdvcmQ+PGtleXdvcmQ+TXllbGlu

IFNoZWF0aDwva2V5d29yZD48a2V5d29yZD5PYnNlcnZlciBWYXJpYXRpb248L2tleXdvcmQ+PGtl

eXdvcmQ+UHJlZGljdGl2ZSBWYWx1ZSBvZiBUZXN0czwva2V5d29yZD48a2V5d29yZD5SZXByb2R1

Y2liaWxpdHkgb2YgUmVzdWx0czwva2V5d29yZD48a2V5d29yZD5TZW5zaXRpdml0eSBhbmQgU3Bl

Y2lmaWNpdHk8L2tleXdvcmQ+PGtleXdvcmQ+VG9tb2dyYXBoeSwgWC1SYXkgQ29tcHV0ZWQ8L2tl

eXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cDovL3d3dy5uY2Jp

Lm5sbS5uaWguZ292L3B1Ym1lZC8xMTM4NzQ5MzwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJscz48

aXNibj4xNTI0LTQ2Mjg8L2lzYm4+PHRpdGxlcz48dGl0bGU+QSBuZXcgcmF0aW5nIHNjYWxlIGZv

ciBhZ2UtcmVsYXRlZCB3aGl0ZSBtYXR0ZXIgY2hhbmdlcyBhcHBsaWNhYmxlIHRvIE1SSSBhbmQg

Q1QuPC90aXRsZT48c2Vjb25kYXJ5LXRpdGxlPlN0cm9rZTwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0

bGVzPjxwYWdlcz4xMzE4LTIyPC9wYWdlcz48bnVtYmVyPjY8L251bWJlcj48Y29udHJpYnV0b3Jz

PjxhdXRob3JzPjxhdXRob3I+V2FobHVuZCwgTC4gTy48L2F1dGhvcj48YXV0aG9yPkJhcmtob2Ys

IEYuPC9hdXRob3I+PGF1dGhvcj5GYXpla2FzLCBGLjwvYXV0aG9yPjxhdXRob3I+QnJvbmdlLCBM

LjwvYXV0aG9yPjxhdXRob3I+QXVndXN0aW4sIE0uPC9hdXRob3I+PGF1dGhvcj5TasO2Z3Jlbiwg

TS48L2F1dGhvcj48YXV0aG9yPldhbGxpbiwgQS48L2F1dGhvcj48YXV0aG9yPkFkZXIsIEguPC9h

dXRob3I+PGF1dGhvcj5MZXlzLCBELjwvYXV0aG9yPjxhdXRob3I+UGFudG9uaSwgTC48L2F1dGhv

cj48YXV0aG9yPlBhc3F1aWVyLCBGLjwvYXV0aG9yPjxhdXRob3I+RXJraW5qdW50dGksIFQuPC9h

dXRob3I+PGF1dGhvcj5TY2hlbHRlbnMsIFAuPC9hdXRob3I+PGF1dGhvcj5FdXJvcGVhbiBUYXNr

IEZvcmNlIG9uIEFnZS1SZWxhdGVkIFdoaXRlIE1hdHRlciBDaGFuZ2VzPC9hdXRob3I+PC9hdXRo

b3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5lbmc8L2xhbmd1YWdlPjxhZGRlZC1kYXRlIGZv

cm1hdD0idXRjIj4xMzM0OTM3NjY2PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1lPSJKb3VybmFs

IEFydGljbGUiPjE3PC9yZWYtdHlwZT48YXV0aC1hZGRyZXNzPkRlcGFydG1lbnQgb2YgQ2xpbmlj

YWwgTmV1cm9zY2llbmNlLCBORVVST1RFQywgS2Fyb2xpbnNrYSBJbnN0aXR1dGV0IGF0IEh1ZGRp

bmdlIFVuaXZlcnNpdHkgSG9zcGl0YWwsIEh1ZGRpbmdlLCBTd2VkZW4uIGxhcnMtb2xvZi53YWhs

dW5kQG5ldXJvdGVjLmtpLnNlPC9hdXRoLWFkZHJlc3M+PHJlYy1udW1iZXI+MTMzPC9yZWMtbnVt

YmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTMzNDkzNzY2NjwvbGFzdC11cGRh

dGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MTEzODc0OTM8L2FjY2Vzc2lvbi1udW0+PHZvbHVtZT4z

Mjwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48L0VuZE5vdGU+AAA=

ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XYWhsdW5kPC9BdXRob3I+PFllYXI+MjAwMTwvWWVhcj48

SURUZXh0PkEgbmV3IHJhdGluZyBzY2FsZSBmb3IgYWdlLXJlbGF0ZWQgd2hpdGUgbWF0dGVyIGNo

YW5nZXMgYXBwbGljYWJsZSB0byBNUkkgYW5kIENULjwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5

bGUgZmFjZT0ic3VwZXJzY3JpcHQiPjEyPC9zdHlsZT48L0Rpc3BsYXlUZXh0PjxyZWNvcmQ+PGRh

dGVzPjxwdWItZGF0ZXM+PGRhdGU+SnVuPC9kYXRlPjwvcHViLWRhdGVzPjx5ZWFyPjIwMDE8L3ll

YXI+PC9kYXRlcz48a2V5d29yZHM+PGtleXdvcmQ+QWdpbmc8L2tleXdvcmQ+PGtleXdvcmQ+QnJh

aW48L2tleXdvcmQ+PGtleXdvcmQ+QnJhaW4gRGlzZWFzZXM8L2tleXdvcmQ+PGtleXdvcmQ+Q29n

bml0aW9uIERpc29yZGVyczwva2V5d29yZD48a2V5d29yZD5FdXJvcGU8L2tleXdvcmQ+PGtleXdv

cmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPk1hZ25ldGljIFJlc29uYW5jZSBJbWFnaW5nPC9r

ZXl3b3JkPjxrZXl3b3JkPk1lbW9yeSBEaXNvcmRlcnM8L2tleXdvcmQ+PGtleXdvcmQ+TXllbGlu

IFNoZWF0aDwva2V5d29yZD48a2V5d29yZD5PYnNlcnZlciBWYXJpYXRpb248L2tleXdvcmQ+PGtl

eXdvcmQ+UHJlZGljdGl2ZSBWYWx1ZSBvZiBUZXN0czwva2V5d29yZD48a2V5d29yZD5SZXByb2R1

Y2liaWxpdHkgb2YgUmVzdWx0czwva2V5d29yZD48a2V5d29yZD5TZW5zaXRpdml0eSBhbmQgU3Bl

Y2lmaWNpdHk8L2tleXdvcmQ+PGtleXdvcmQ+VG9tb2dyYXBoeSwgWC1SYXkgQ29tcHV0ZWQ8L2tl

eXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cDovL3d3dy5uY2Jp

Lm5sbS5uaWguZ292L3B1Ym1lZC8xMTM4NzQ5MzwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJscz48

aXNibj4xNTI0LTQ2Mjg8L2lzYm4+PHRpdGxlcz48dGl0bGU+QSBuZXcgcmF0aW5nIHNjYWxlIGZv

ciBhZ2UtcmVsYXRlZCB3aGl0ZSBtYXR0ZXIgY2hhbmdlcyBhcHBsaWNhYmxlIHRvIE1SSSBhbmQg

Q1QuPC90aXRsZT48c2Vjb25kYXJ5LXRpdGxlPlN0cm9rZTwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0

bGVzPjxwYWdlcz4xMzE4LTIyPC9wYWdlcz48bnVtYmVyPjY8L251bWJlcj48Y29udHJpYnV0b3Jz

PjxhdXRob3JzPjxhdXRob3I+V2FobHVuZCwgTC4gTy48L2F1dGhvcj48YXV0aG9yPkJhcmtob2Ys

IEYuPC9hdXRob3I+PGF1dGhvcj5GYXpla2FzLCBGLjwvYXV0aG9yPjxhdXRob3I+QnJvbmdlLCBM

LjwvYXV0aG9yPjxhdXRob3I+QXVndXN0aW4sIE0uPC9hdXRob3I+PGF1dGhvcj5TasO2Z3Jlbiwg

TS48L2F1dGhvcj48YXV0aG9yPldhbGxpbiwgQS48L2F1dGhvcj48YXV0aG9yPkFkZXIsIEguPC9h

dXRob3I+PGF1dGhvcj5MZXlzLCBELjwvYXV0aG9yPjxhdXRob3I+UGFudG9uaSwgTC48L2F1dGhv

cj48YXV0aG9yPlBhc3F1aWVyLCBGLjwvYXV0aG9yPjxhdXRob3I+RXJraW5qdW50dGksIFQuPC9h

dXRob3I+PGF1dGhvcj5TY2hlbHRlbnMsIFAuPC9hdXRob3I+PGF1dGhvcj5FdXJvcGVhbiBUYXNr

IEZvcmNlIG9uIEFnZS1SZWxhdGVkIFdoaXRlIE1hdHRlciBDaGFuZ2VzPC9hdXRob3I+PC9hdXRo

b3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5lbmc8L2xhbmd1YWdlPjxhZGRlZC1kYXRlIGZv

cm1hdD0idXRjIj4xMzM0OTM3NjY2PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1lPSJKb3VybmFs

IEFydGljbGUiPjE3PC9yZWYtdHlwZT48YXV0aC1hZGRyZXNzPkRlcGFydG1lbnQgb2YgQ2xpbmlj

YWwgTmV1cm9zY2llbmNlLCBORVVST1RFQywgS2Fyb2xpbnNrYSBJbnN0aXR1dGV0IGF0IEh1ZGRp

bmdlIFVuaXZlcnNpdHkgSG9zcGl0YWwsIEh1ZGRpbmdlLCBTd2VkZW4uIGxhcnMtb2xvZi53YWhs

dW5kQG5ldXJvdGVjLmtpLnNlPC9hdXRoLWFkZHJlc3M+PHJlYy1udW1iZXI+MTMzPC9yZWMtbnVt

YmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTMzNDkzNzY2NjwvbGFzdC11cGRh

dGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MTEzODc0OTM8L2FjY2Vzc2lvbi1udW0+PHZvbHVtZT4z

Mjwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48L0VuZE5vdGU+AAA=

ADDIN EN.CITE.DATA 12. Moreover, sensitivity of CT decreases with smaller WML volumesPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5TaW1vbmk8L0F1dGhvcj48WWVhcj4yMDEyPC9ZZWFyPjxJ

RFRleHQ+QWdlLSBhbmQgc2V4LXNwZWNpZmljIHJhdGVzIG9mIGxldWtvYXJhaW9zaXMgaW4gVElB

IGFuZCBzdHJva2UgcGF0aWVudHM6IHBvcHVsYXRpb24tYmFzZWQgc3R1ZHk8L0lEVGV4dD48RGlz

cGxheVRleHQ+PHN0eWxlIGZhY2U9InN1cGVyc2NyaXB0Ij4xMiwgMTM8L3N0eWxlPjwvRGlzcGxh

eVRleHQ+PHJlY29yZD48ZGF0ZXM+PHB1Yi1kYXRlcz48ZGF0ZT5TZXA8L2RhdGU+PC9wdWItZGF0

ZXM+PHllYXI+MjAxMjwveWVhcj48L2RhdGVzPjxrZXl3b3Jkcz48a2V5d29yZD5BZ2UgRmFjdG9y

czwva2V5d29yZD48a2V5d29yZD5BZ2VkPC9rZXl3b3JkPjxrZXl3b3JkPkFnZWQsIDgwIGFuZCBv

dmVyPC9rZXl3b3JkPjxrZXl3b3JkPkJyYWluPC9rZXl3b3JkPjxrZXl3b3JkPkZlbWFsZTwva2V5

d29yZD48a2V5d29yZD5IdW1hbnM8L2tleXdvcmQ+PGtleXdvcmQ+SW5jaWRlbmNlPC9rZXl3b3Jk

PjxrZXl3b3JkPklzY2hlbWljIEF0dGFjaywgVHJhbnNpZW50PC9rZXl3b3JkPjxrZXl3b3JkPkxl

dWtvYXJhaW9zaXM8L2tleXdvcmQ+PGtleXdvcmQ+TWFnbmV0aWMgUmVzb25hbmNlIEltYWdpbmc8

L2tleXdvcmQ+PGtleXdvcmQ+TWFsZTwva2V5d29yZD48a2V5d29yZD5NaWRkbGUgQWdlZDwva2V5

d29yZD48a2V5d29yZD5OZXJ2ZSBGaWJlcnMsIE15ZWxpbmF0ZWQ8L2tleXdvcmQ+PGtleXdvcmQ+

UHJldmFsZW5jZTwva2V5d29yZD48a2V5d29yZD5TZXggQ2hhcmFjdGVyaXN0aWNzPC9rZXl3b3Jk

PjxrZXl3b3JkPlN0cm9rZTwva2V5d29yZD48L2tleXdvcmRzPjx1cmxzPjxyZWxhdGVkLXVybHM+

PHVybD5odHRwczovL3d3dy5uY2JpLm5sbS5uaWguZ292L3B1Ym1lZC8yMjk1NTEzODwvdXJsPjwv

cmVsYXRlZC11cmxzPjwvdXJscz48aXNibj4xNTI2LTYzMlg8L2lzYm4+PGN1c3RvbTI+UE1DMzQ0

MDQ0NzwvY3VzdG9tMj48dGl0bGVzPjx0aXRsZT5BZ2UtIGFuZCBzZXgtc3BlY2lmaWMgcmF0ZXMg

b2YgbGV1a29hcmFpb3NpcyBpbiBUSUEgYW5kIHN0cm9rZSBwYXRpZW50czogcG9wdWxhdGlvbi1i

YXNlZCBzdHVkeTwvdGl0bGU+PHNlY29uZGFyeS10aXRsZT5OZXVyb2xvZ3k8L3NlY29uZGFyeS10

aXRsZT48L3RpdGxlcz48cGFnZXM+MTIxNS0yMjwvcGFnZXM+PG51bWJlcj4xMjwvbnVtYmVyPjxj

b250cmlidXRvcnM+PGF1dGhvcnM+PGF1dGhvcj5TaW1vbmksIE0uPC9hdXRob3I+PGF1dGhvcj5M

aSwgTC48L2F1dGhvcj48YXV0aG9yPlBhdWwsIE4uIEwuPC9hdXRob3I+PGF1dGhvcj5HcnV0ZXIs

IEIuIEUuPC9hdXRob3I+PGF1dGhvcj5TY2h1bHosIFUuIEcuPC9hdXRob3I+PGF1dGhvcj5Lw7xr

ZXIsIFcuPC9hdXRob3I+PGF1dGhvcj5Sb3Rod2VsbCwgUC4gTS48L2F1dGhvcj48L2F1dGhvcnM+

PC9jb250cmlidXRvcnM+PGVkaXRpb24+MjAxMi8wOS8wNTwvZWRpdGlvbj48bGFuZ3VhZ2U+ZW5n

PC9sYW5ndWFnZT48YWRkZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ4ODQ1NzEyODwvYWRkZWQtZGF0

ZT48cmVmLXR5cGUgbmFtZT0iSm91cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PHJlYy1udW1i

ZXI+NTcxPC9yZWMtbnVtYmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ4ODQ1

NzEyODwvbGFzdC11cGRhdGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MjI5NTUxMzg8L2FjY2Vzc2lv

bi1udW0+PGVsZWN0cm9uaWMtcmVzb3VyY2UtbnVtPjEwLjEyMTIvV05MLjBiMDEzZTMxODI2Yjk1

MWU8L2VsZWN0cm9uaWMtcmVzb3VyY2UtbnVtPjx2b2x1bWU+Nzk8L3ZvbHVtZT48L3JlY29yZD48

L0NpdGU+PENpdGU+PEF1dGhvcj5XYWhsdW5kPC9BdXRob3I+PFllYXI+MjAwMTwvWWVhcj48SURU

ZXh0PkEgbmV3IHJhdGluZyBzY2FsZSBmb3IgYWdlLXJlbGF0ZWQgd2hpdGUgbWF0dGVyIGNoYW5n

ZXMgYXBwbGljYWJsZSB0byBNUkkgYW5kIENULjwvSURUZXh0PjxyZWNvcmQ+PGRhdGVzPjxwdWIt

ZGF0ZXM+PGRhdGU+SnVuPC9kYXRlPjwvcHViLWRhdGVzPjx5ZWFyPjIwMDE8L3llYXI+PC9kYXRl

cz48a2V5d29yZHM+PGtleXdvcmQ+QWdpbmc8L2tleXdvcmQ+PGtleXdvcmQ+QnJhaW48L2tleXdv

cmQ+PGtleXdvcmQ+QnJhaW4gRGlzZWFzZXM8L2tleXdvcmQ+PGtleXdvcmQ+Q29nbml0aW9uIERp

c29yZGVyczwva2V5d29yZD48a2V5d29yZD5FdXJvcGU8L2tleXdvcmQ+PGtleXdvcmQ+SHVtYW5z

PC9rZXl3b3JkPjxrZXl3b3JkPk1hZ25ldGljIFJlc29uYW5jZSBJbWFnaW5nPC9rZXl3b3JkPjxr

ZXl3b3JkPk1lbW9yeSBEaXNvcmRlcnM8L2tleXdvcmQ+PGtleXdvcmQ+TXllbGluIFNoZWF0aDwv

a2V5d29yZD48a2V5d29yZD5PYnNlcnZlciBWYXJpYXRpb248L2tleXdvcmQ+PGtleXdvcmQ+UHJl

ZGljdGl2ZSBWYWx1ZSBvZiBUZXN0czwva2V5d29yZD48a2V5d29yZD5SZXByb2R1Y2liaWxpdHkg

b2YgUmVzdWx0czwva2V5d29yZD48a2V5d29yZD5TZW5zaXRpdml0eSBhbmQgU3BlY2lmaWNpdHk8

L2tleXdvcmQ+PGtleXdvcmQ+VG9tb2dyYXBoeSwgWC1SYXkgQ29tcHV0ZWQ8L2tleXdvcmQ+PC9r

ZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cDovL3d3dy5uY2JpLm5sbS5uaWgu

Z292L3B1Ym1lZC8xMTM4NzQ5MzwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJscz48aXNibj4xNTI0

LTQ2Mjg8L2lzYm4+PHRpdGxlcz48dGl0bGU+QSBuZXcgcmF0aW5nIHNjYWxlIGZvciBhZ2UtcmVs

YXRlZCB3aGl0ZSBtYXR0ZXIgY2hhbmdlcyBhcHBsaWNhYmxlIHRvIE1SSSBhbmQgQ1QuPC90aXRs

ZT48c2Vjb25kYXJ5LXRpdGxlPlN0cm9rZTwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0bGVzPjxwYWdl

cz4xMzE4LTIyPC9wYWdlcz48bnVtYmVyPjY8L251bWJlcj48Y29udHJpYnV0b3JzPjxhdXRob3Jz

PjxhdXRob3I+V2FobHVuZCwgTC4gTy48L2F1dGhvcj48YXV0aG9yPkJhcmtob2YsIEYuPC9hdXRo

b3I+PGF1dGhvcj5GYXpla2FzLCBGLjwvYXV0aG9yPjxhdXRob3I+QnJvbmdlLCBMLjwvYXV0aG9y

PjxhdXRob3I+QXVndXN0aW4sIE0uPC9hdXRob3I+PGF1dGhvcj5TasO2Z3JlbiwgTS48L2F1dGhv

cj48YXV0aG9yPldhbGxpbiwgQS48L2F1dGhvcj48YXV0aG9yPkFkZXIsIEguPC9hdXRob3I+PGF1

dGhvcj5MZXlzLCBELjwvYXV0aG9yPjxhdXRob3I+UGFudG9uaSwgTC48L2F1dGhvcj48YXV0aG9y

PlBhc3F1aWVyLCBGLjwvYXV0aG9yPjxhdXRob3I+RXJraW5qdW50dGksIFQuPC9hdXRob3I+PGF1

dGhvcj5TY2hlbHRlbnMsIFAuPC9hdXRob3I+PGF1dGhvcj5FdXJvcGVhbiBUYXNrIEZvcmNlIG9u

IEFnZS1SZWxhdGVkIFdoaXRlIE1hdHRlciBDaGFuZ2VzPC9hdXRob3I+PC9hdXRob3JzPjwvY29u

dHJpYnV0b3JzPjxsYW5ndWFnZT5lbmc8L2xhbmd1YWdlPjxhZGRlZC1kYXRlIGZvcm1hdD0idXRj

Ij4xMzM0OTM3NjY2PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1lPSJKb3VybmFsIEFydGljbGUi

PjE3PC9yZWYtdHlwZT48YXV0aC1hZGRyZXNzPkRlcGFydG1lbnQgb2YgQ2xpbmljYWwgTmV1cm9z

Y2llbmNlLCBORVVST1RFQywgS2Fyb2xpbnNrYSBJbnN0aXR1dGV0IGF0IEh1ZGRpbmdlIFVuaXZl

cnNpdHkgSG9zcGl0YWwsIEh1ZGRpbmdlLCBTd2VkZW4uIGxhcnMtb2xvZi53YWhsdW5kQG5ldXJv

dGVjLmtpLnNlPC9hdXRoLWFkZHJlc3M+PHJlYy1udW1iZXI+MTMzPC9yZWMtbnVtYmVyPjxsYXN0

LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTMzNDkzNzY2NjwvbGFzdC11cGRhdGVkLWRhdGU+

PGFjY2Vzc2lvbi1udW0+MTEzODc0OTM8L2FjY2Vzc2lvbi1udW0+PHZvbHVtZT4zMjwvdm9sdW1l

PjwvcmVjb3JkPjwvQ2l0ZT48L0VuZE5vdGU+AAA=

ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5TaW1vbmk8L0F1dGhvcj48WWVhcj4yMDEyPC9ZZWFyPjxJ

RFRleHQ+QWdlLSBhbmQgc2V4LXNwZWNpZmljIHJhdGVzIG9mIGxldWtvYXJhaW9zaXMgaW4gVElB

IGFuZCBzdHJva2UgcGF0aWVudHM6IHBvcHVsYXRpb24tYmFzZWQgc3R1ZHk8L0lEVGV4dD48RGlz

cGxheVRleHQ+PHN0eWxlIGZhY2U9InN1cGVyc2NyaXB0Ij4xMiwgMTM8L3N0eWxlPjwvRGlzcGxh

eVRleHQ+PHJlY29yZD48ZGF0ZXM+PHB1Yi1kYXRlcz48ZGF0ZT5TZXA8L2RhdGU+PC9wdWItZGF0

ZXM+PHllYXI+MjAxMjwveWVhcj48L2RhdGVzPjxrZXl3b3Jkcz48a2V5d29yZD5BZ2UgRmFjdG9y

czwva2V5d29yZD48a2V5d29yZD5BZ2VkPC9rZXl3b3JkPjxrZXl3b3JkPkFnZWQsIDgwIGFuZCBv

dmVyPC9rZXl3b3JkPjxrZXl3b3JkPkJyYWluPC9rZXl3b3JkPjxrZXl3b3JkPkZlbWFsZTwva2V5

d29yZD48a2V5d29yZD5IdW1hbnM8L2tleXdvcmQ+PGtleXdvcmQ+SW5jaWRlbmNlPC9rZXl3b3Jk

PjxrZXl3b3JkPklzY2hlbWljIEF0dGFjaywgVHJhbnNpZW50PC9rZXl3b3JkPjxrZXl3b3JkPkxl

dWtvYXJhaW9zaXM8L2tleXdvcmQ+PGtleXdvcmQ+TWFnbmV0aWMgUmVzb25hbmNlIEltYWdpbmc8

L2tleXdvcmQ+PGtleXdvcmQ+TWFsZTwva2V5d29yZD48a2V5d29yZD5NaWRkbGUgQWdlZDwva2V5

d29yZD48a2V5d29yZD5OZXJ2ZSBGaWJlcnMsIE15ZWxpbmF0ZWQ8L2tleXdvcmQ+PGtleXdvcmQ+

UHJldmFsZW5jZTwva2V5d29yZD48a2V5d29yZD5TZXggQ2hhcmFjdGVyaXN0aWNzPC9rZXl3b3Jk

PjxrZXl3b3JkPlN0cm9rZTwva2V5d29yZD48L2tleXdvcmRzPjx1cmxzPjxyZWxhdGVkLXVybHM+

PHVybD5odHRwczovL3d3dy5uY2JpLm5sbS5uaWguZ292L3B1Ym1lZC8yMjk1NTEzODwvdXJsPjwv

cmVsYXRlZC11cmxzPjwvdXJscz48aXNibj4xNTI2LTYzMlg8L2lzYm4+PGN1c3RvbTI+UE1DMzQ0

MDQ0NzwvY3VzdG9tMj48dGl0bGVzPjx0aXRsZT5BZ2UtIGFuZCBzZXgtc3BlY2lmaWMgcmF0ZXMg

b2YgbGV1a29hcmFpb3NpcyBpbiBUSUEgYW5kIHN0cm9rZSBwYXRpZW50czogcG9wdWxhdGlvbi1i

YXNlZCBzdHVkeTwvdGl0bGU+PHNlY29uZGFyeS10aXRsZT5OZXVyb2xvZ3k8L3NlY29uZGFyeS10

aXRsZT48L3RpdGxlcz48cGFnZXM+MTIxNS0yMjwvcGFnZXM+PG51bWJlcj4xMjwvbnVtYmVyPjxj

b250cmlidXRvcnM+PGF1dGhvcnM+PGF1dGhvcj5TaW1vbmksIE0uPC9hdXRob3I+PGF1dGhvcj5M

aSwgTC48L2F1dGhvcj48YXV0aG9yPlBhdWwsIE4uIEwuPC9hdXRob3I+PGF1dGhvcj5HcnV0ZXIs

IEIuIEUuPC9hdXRob3I+PGF1dGhvcj5TY2h1bHosIFUuIEcuPC9hdXRob3I+PGF1dGhvcj5Lw7xr

ZXIsIFcuPC9hdXRob3I+PGF1dGhvcj5Sb3Rod2VsbCwgUC4gTS48L2F1dGhvcj48L2F1dGhvcnM+

PC9jb250cmlidXRvcnM+PGVkaXRpb24+MjAxMi8wOS8wNTwvZWRpdGlvbj48bGFuZ3VhZ2U+ZW5n

PC9sYW5ndWFnZT48YWRkZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ4ODQ1NzEyODwvYWRkZWQtZGF0

ZT48cmVmLXR5cGUgbmFtZT0iSm91cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PHJlYy1udW1i

ZXI+NTcxPC9yZWMtbnVtYmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ4ODQ1

NzEyODwvbGFzdC11cGRhdGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MjI5NTUxMzg8L2FjY2Vzc2lv

bi1udW0+PGVsZWN0cm9uaWMtcmVzb3VyY2UtbnVtPjEwLjEyMTIvV05MLjBiMDEzZTMxODI2Yjk1

MWU8L2VsZWN0cm9uaWMtcmVzb3VyY2UtbnVtPjx2b2x1bWU+Nzk8L3ZvbHVtZT48L3JlY29yZD48

L0NpdGU+PENpdGU+PEF1dGhvcj5XYWhsdW5kPC9BdXRob3I+PFllYXI+MjAwMTwvWWVhcj48SURU

ZXh0PkEgbmV3IHJhdGluZyBzY2FsZSBmb3IgYWdlLXJlbGF0ZWQgd2hpdGUgbWF0dGVyIGNoYW5n

ZXMgYXBwbGljYWJsZSB0byBNUkkgYW5kIENULjwvSURUZXh0PjxyZWNvcmQ+PGRhdGVzPjxwdWIt

ZGF0ZXM+PGRhdGU+SnVuPC9kYXRlPjwvcHViLWRhdGVzPjx5ZWFyPjIwMDE8L3llYXI+PC9kYXRl

cz48a2V5d29yZHM+PGtleXdvcmQ+QWdpbmc8L2tleXdvcmQ+PGtleXdvcmQ+QnJhaW48L2tleXdv

cmQ+PGtleXdvcmQ+QnJhaW4gRGlzZWFzZXM8L2tleXdvcmQ+PGtleXdvcmQ+Q29nbml0aW9uIERp

c29yZGVyczwva2V5d29yZD48a2V5d29yZD5FdXJvcGU8L2tleXdvcmQ+PGtleXdvcmQ+SHVtYW5z

PC9rZXl3b3JkPjxrZXl3b3JkPk1hZ25ldGljIFJlc29uYW5jZSBJbWFnaW5nPC9rZXl3b3JkPjxr

ZXl3b3JkPk1lbW9yeSBEaXNvcmRlcnM8L2tleXdvcmQ+PGtleXdvcmQ+TXllbGluIFNoZWF0aDwv

a2V5d29yZD48a2V5d29yZD5PYnNlcnZlciBWYXJpYXRpb248L2tleXdvcmQ+PGtleXdvcmQ+UHJl

ZGljdGl2ZSBWYWx1ZSBvZiBUZXN0czwva2V5d29yZD48a2V5d29yZD5SZXByb2R1Y2liaWxpdHkg

b2YgUmVzdWx0czwva2V5d29yZD48a2V5d29yZD5TZW5zaXRpdml0eSBhbmQgU3BlY2lmaWNpdHk8

L2tleXdvcmQ+PGtleXdvcmQ+VG9tb2dyYXBoeSwgWC1SYXkgQ29tcHV0ZWQ8L2tleXdvcmQ+PC9r

ZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cDovL3d3dy5uY2JpLm5sbS5uaWgu

Z292L3B1Ym1lZC8xMTM4NzQ5MzwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJscz48aXNibj4xNTI0

LTQ2Mjg8L2lzYm4+PHRpdGxlcz48dGl0bGU+QSBuZXcgcmF0aW5nIHNjYWxlIGZvciBhZ2UtcmVs

YXRlZCB3aGl0ZSBtYXR0ZXIgY2hhbmdlcyBhcHBsaWNhYmxlIHRvIE1SSSBhbmQgQ1QuPC90aXRs

ZT48c2Vjb25kYXJ5LXRpdGxlPlN0cm9rZTwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0bGVzPjxwYWdl

cz4xMzE4LTIyPC9wYWdlcz48bnVtYmVyPjY8L251bWJlcj48Y29udHJpYnV0b3JzPjxhdXRob3Jz

PjxhdXRob3I+V2FobHVuZCwgTC4gTy48L2F1dGhvcj48YXV0aG9yPkJhcmtob2YsIEYuPC9hdXRo

b3I+PGF1dGhvcj5GYXpla2FzLCBGLjwvYXV0aG9yPjxhdXRob3I+QnJvbmdlLCBMLjwvYXV0aG9y

PjxhdXRob3I+QXVndXN0aW4sIE0uPC9hdXRob3I+PGF1dGhvcj5TasO2Z3JlbiwgTS48L2F1dGhv

cj48YXV0aG9yPldhbGxpbiwgQS48L2F1dGhvcj48YXV0aG9yPkFkZXIsIEguPC9hdXRob3I+PGF1

dGhvcj5MZXlzLCBELjwvYXV0aG9yPjxhdXRob3I+UGFudG9uaSwgTC48L2F1dGhvcj48YXV0aG9y

PlBhc3F1aWVyLCBGLjwvYXV0aG9yPjxhdXRob3I+RXJraW5qdW50dGksIFQuPC9hdXRob3I+PGF1

dGhvcj5TY2hlbHRlbnMsIFAuPC9hdXRob3I+PGF1dGhvcj5FdXJvcGVhbiBUYXNrIEZvcmNlIG9u

IEFnZS1SZWxhdGVkIFdoaXRlIE1hdHRlciBDaGFuZ2VzPC9hdXRob3I+PC9hdXRob3JzPjwvY29u

dHJpYnV0b3JzPjxsYW5ndWFnZT5lbmc8L2xhbmd1YWdlPjxhZGRlZC1kYXRlIGZvcm1hdD0idXRj

Ij4xMzM0OTM3NjY2PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1lPSJKb3VybmFsIEFydGljbGUi

PjE3PC9yZWYtdHlwZT48YXV0aC1hZGRyZXNzPkRlcGFydG1lbnQgb2YgQ2xpbmljYWwgTmV1cm9z

Y2llbmNlLCBORVVST1RFQywgS2Fyb2xpbnNrYSBJbnN0aXR1dGV0IGF0IEh1ZGRpbmdlIFVuaXZl

cnNpdHkgSG9zcGl0YWwsIEh1ZGRpbmdlLCBTd2VkZW4uIGxhcnMtb2xvZi53YWhsdW5kQG5ldXJv

dGVjLmtpLnNlPC9hdXRoLWFkZHJlc3M+PHJlYy1udW1iZXI+MTMzPC9yZWMtbnVtYmVyPjxsYXN0

LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTMzNDkzNzY2NjwvbGFzdC11cGRhdGVkLWRhdGU+

PGFjY2Vzc2lvbi1udW0+MTEzODc0OTM8L2FjY2Vzc2lvbi1udW0+PHZvbHVtZT4zMjwvdm9sdW1l

PjwvcmVjb3JkPjwvQ2l0ZT48L0VuZE5vdGU+AAA=

ADDIN EN.CITE.DATA 12, 13, and varies between brain regionsPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XYWhsdW5kPC9BdXRob3I+PFllYXI+MjAwMTwvWWVhcj48

SURUZXh0PkEgbmV3IHJhdGluZyBzY2FsZSBmb3IgYWdlLXJlbGF0ZWQgd2hpdGUgbWF0dGVyIGNo

YW5nZXMgYXBwbGljYWJsZSB0byBNUkkgYW5kIENULjwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5

bGUgZmFjZT0ic3VwZXJzY3JpcHQiPjEyPC9zdHlsZT48L0Rpc3BsYXlUZXh0PjxyZWNvcmQ+PGRh

dGVzPjxwdWItZGF0ZXM+PGRhdGU+SnVuPC9kYXRlPjwvcHViLWRhdGVzPjx5ZWFyPjIwMDE8L3ll

YXI+PC9kYXRlcz48a2V5d29yZHM+PGtleXdvcmQ+QWdpbmc8L2tleXdvcmQ+PGtleXdvcmQ+QnJh

aW48L2tleXdvcmQ+PGtleXdvcmQ+QnJhaW4gRGlzZWFzZXM8L2tleXdvcmQ+PGtleXdvcmQ+Q29n

bml0aW9uIERpc29yZGVyczwva2V5d29yZD48a2V5d29yZD5FdXJvcGU8L2tleXdvcmQ+PGtleXdv

cmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPk1hZ25ldGljIFJlc29uYW5jZSBJbWFnaW5nPC9r

ZXl3b3JkPjxrZXl3b3JkPk1lbW9yeSBEaXNvcmRlcnM8L2tleXdvcmQ+PGtleXdvcmQ+TXllbGlu

IFNoZWF0aDwva2V5d29yZD48a2V5d29yZD5PYnNlcnZlciBWYXJpYXRpb248L2tleXdvcmQ+PGtl

eXdvcmQ+UHJlZGljdGl2ZSBWYWx1ZSBvZiBUZXN0czwva2V5d29yZD48a2V5d29yZD5SZXByb2R1

Y2liaWxpdHkgb2YgUmVzdWx0czwva2V5d29yZD48a2V5d29yZD5TZW5zaXRpdml0eSBhbmQgU3Bl

Y2lmaWNpdHk8L2tleXdvcmQ+PGtleXdvcmQ+VG9tb2dyYXBoeSwgWC1SYXkgQ29tcHV0ZWQ8L2tl

eXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cDovL3d3dy5uY2Jp

Lm5sbS5uaWguZ292L3B1Ym1lZC8xMTM4NzQ5MzwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJscz48

aXNibj4xNTI0LTQ2Mjg8L2lzYm4+PHRpdGxlcz48dGl0bGU+QSBuZXcgcmF0aW5nIHNjYWxlIGZv

ciBhZ2UtcmVsYXRlZCB3aGl0ZSBtYXR0ZXIgY2hhbmdlcyBhcHBsaWNhYmxlIHRvIE1SSSBhbmQg

Q1QuPC90aXRsZT48c2Vjb25kYXJ5LXRpdGxlPlN0cm9rZTwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0

bGVzPjxwYWdlcz4xMzE4LTIyPC9wYWdlcz48bnVtYmVyPjY8L251bWJlcj48Y29udHJpYnV0b3Jz

PjxhdXRob3JzPjxhdXRob3I+V2FobHVuZCwgTC4gTy48L2F1dGhvcj48YXV0aG9yPkJhcmtob2Ys

IEYuPC9hdXRob3I+PGF1dGhvcj5GYXpla2FzLCBGLjwvYXV0aG9yPjxhdXRob3I+QnJvbmdlLCBM

LjwvYXV0aG9yPjxhdXRob3I+QXVndXN0aW4sIE0uPC9hdXRob3I+PGF1dGhvcj5TasO2Z3Jlbiwg

TS48L2F1dGhvcj48YXV0aG9yPldhbGxpbiwgQS48L2F1dGhvcj48YXV0aG9yPkFkZXIsIEguPC9h

dXRob3I+PGF1dGhvcj5MZXlzLCBELjwvYXV0aG9yPjxhdXRob3I+UGFudG9uaSwgTC48L2F1dGhv

cj48YXV0aG9yPlBhc3F1aWVyLCBGLjwvYXV0aG9yPjxhdXRob3I+RXJraW5qdW50dGksIFQuPC9h

dXRob3I+PGF1dGhvcj5TY2hlbHRlbnMsIFAuPC9hdXRob3I+PGF1dGhvcj5FdXJvcGVhbiBUYXNr

IEZvcmNlIG9uIEFnZS1SZWxhdGVkIFdoaXRlIE1hdHRlciBDaGFuZ2VzPC9hdXRob3I+PC9hdXRo

b3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5lbmc8L2xhbmd1YWdlPjxhZGRlZC1kYXRlIGZv

cm1hdD0idXRjIj4xMzM0OTM3NjY2PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1lPSJKb3VybmFs

IEFydGljbGUiPjE3PC9yZWYtdHlwZT48YXV0aC1hZGRyZXNzPkRlcGFydG1lbnQgb2YgQ2xpbmlj

YWwgTmV1cm9zY2llbmNlLCBORVVST1RFQywgS2Fyb2xpbnNrYSBJbnN0aXR1dGV0IGF0IEh1ZGRp

bmdlIFVuaXZlcnNpdHkgSG9zcGl0YWwsIEh1ZGRpbmdlLCBTd2VkZW4uIGxhcnMtb2xvZi53YWhs

dW5kQG5ldXJvdGVjLmtpLnNlPC9hdXRoLWFkZHJlc3M+PHJlYy1udW1iZXI+MTMzPC9yZWMtbnVt

YmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTMzNDkzNzY2NjwvbGFzdC11cGRh

dGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MTEzODc0OTM8L2FjY2Vzc2lvbi1udW0+PHZvbHVtZT4z

Mjwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48L0VuZE5vdGU+AAA=

ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XYWhsdW5kPC9BdXRob3I+PFllYXI+MjAwMTwvWWVhcj48

SURUZXh0PkEgbmV3IHJhdGluZyBzY2FsZSBmb3IgYWdlLXJlbGF0ZWQgd2hpdGUgbWF0dGVyIGNo

YW5nZXMgYXBwbGljYWJsZSB0byBNUkkgYW5kIENULjwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5

bGUgZmFjZT0ic3VwZXJzY3JpcHQiPjEyPC9zdHlsZT48L0Rpc3BsYXlUZXh0PjxyZWNvcmQ+PGRh

dGVzPjxwdWItZGF0ZXM+PGRhdGU+SnVuPC9kYXRlPjwvcHViLWRhdGVzPjx5ZWFyPjIwMDE8L3ll

YXI+PC9kYXRlcz48a2V5d29yZHM+PGtleXdvcmQ+QWdpbmc8L2tleXdvcmQ+PGtleXdvcmQ+QnJh

aW48L2tleXdvcmQ+PGtleXdvcmQ+QnJhaW4gRGlzZWFzZXM8L2tleXdvcmQ+PGtleXdvcmQ+Q29n

bml0aW9uIERpc29yZGVyczwva2V5d29yZD48a2V5d29yZD5FdXJvcGU8L2tleXdvcmQ+PGtleXdv

cmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPk1hZ25ldGljIFJlc29uYW5jZSBJbWFnaW5nPC9r

ZXl3b3JkPjxrZXl3b3JkPk1lbW9yeSBEaXNvcmRlcnM8L2tleXdvcmQ+PGtleXdvcmQ+TXllbGlu

IFNoZWF0aDwva2V5d29yZD48a2V5d29yZD5PYnNlcnZlciBWYXJpYXRpb248L2tleXdvcmQ+PGtl

eXdvcmQ+UHJlZGljdGl2ZSBWYWx1ZSBvZiBUZXN0czwva2V5d29yZD48a2V5d29yZD5SZXByb2R1

Y2liaWxpdHkgb2YgUmVzdWx0czwva2V5d29yZD48a2V5d29yZD5TZW5zaXRpdml0eSBhbmQgU3Bl

Y2lmaWNpdHk8L2tleXdvcmQ+PGtleXdvcmQ+VG9tb2dyYXBoeSwgWC1SYXkgQ29tcHV0ZWQ8L2tl

eXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cDovL3d3dy5uY2Jp

Lm5sbS5uaWguZ292L3B1Ym1lZC8xMTM4NzQ5MzwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJscz48

aXNibj4xNTI0LTQ2Mjg8L2lzYm4+PHRpdGxlcz48dGl0bGU+QSBuZXcgcmF0aW5nIHNjYWxlIGZv

ciBhZ2UtcmVsYXRlZCB3aGl0ZSBtYXR0ZXIgY2hhbmdlcyBhcHBsaWNhYmxlIHRvIE1SSSBhbmQg

Q1QuPC90aXRsZT48c2Vjb25kYXJ5LXRpdGxlPlN0cm9rZTwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0

bGVzPjxwYWdlcz4xMzE4LTIyPC9wYWdlcz48bnVtYmVyPjY8L251bWJlcj48Y29udHJpYnV0b3Jz

PjxhdXRob3JzPjxhdXRob3I+V2FobHVuZCwgTC4gTy48L2F1dGhvcj48YXV0aG9yPkJhcmtob2Ys

IEYuPC9hdXRob3I+PGF1dGhvcj5GYXpla2FzLCBGLjwvYXV0aG9yPjxhdXRob3I+QnJvbmdlLCBM

LjwvYXV0aG9yPjxhdXRob3I+QXVndXN0aW4sIE0uPC9hdXRob3I+PGF1dGhvcj5TasO2Z3Jlbiwg

TS48L2F1dGhvcj48YXV0aG9yPldhbGxpbiwgQS48L2F1dGhvcj48YXV0aG9yPkFkZXIsIEguPC9h

dXRob3I+PGF1dGhvcj5MZXlzLCBELjwvYXV0aG9yPjxhdXRob3I+UGFudG9uaSwgTC48L2F1dGhv

cj48YXV0aG9yPlBhc3F1aWVyLCBGLjwvYXV0aG9yPjxhdXRob3I+RXJraW5qdW50dGksIFQuPC9h

dXRob3I+PGF1dGhvcj5TY2hlbHRlbnMsIFAuPC9hdXRob3I+PGF1dGhvcj5FdXJvcGVhbiBUYXNr

IEZvcmNlIG9uIEFnZS1SZWxhdGVkIFdoaXRlIE1hdHRlciBDaGFuZ2VzPC9hdXRob3I+PC9hdXRo

b3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5lbmc8L2xhbmd1YWdlPjxhZGRlZC1kYXRlIGZv

cm1hdD0idXRjIj4xMzM0OTM3NjY2PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1lPSJKb3VybmFs

IEFydGljbGUiPjE3PC9yZWYtdHlwZT48YXV0aC1hZGRyZXNzPkRlcGFydG1lbnQgb2YgQ2xpbmlj

YWwgTmV1cm9zY2llbmNlLCBORVVST1RFQywgS2Fyb2xpbnNrYSBJbnN0aXR1dGV0IGF0IEh1ZGRp

bmdlIFVuaXZlcnNpdHkgSG9zcGl0YWwsIEh1ZGRpbmdlLCBTd2VkZW4uIGxhcnMtb2xvZi53YWhs

dW5kQG5ldXJvdGVjLmtpLnNlPC9hdXRoLWFkZHJlc3M+PHJlYy1udW1iZXI+MTMzPC9yZWMtbnVt

YmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTMzNDkzNzY2NjwvbGFzdC11cGRh

dGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MTEzODc0OTM8L2FjY2Vzc2lvbi1udW0+PHZvbHVtZT4z

Mjwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48L0VuZE5vdGU+AAA=

ADDIN EN.CITE.DATA 12. Studies measuring inter-rater reliability of expert-based WML ratings show poorer agreement using CT than MRIPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5TY2hlbHRlbnM8L0F1dGhvcj48WWVhcj4xOTk4PC9ZZWFy

PjxJRFRleHQ+V2hpdGUgbWF0dGVyIGNoYW5nZXMgb24gQ1QgYW5kIE1SSTogYW4gb3ZlcnZpZXcg

b2YgdmlzdWFsIHJhdGluZyBzY2FsZXMuIEV1cm9wZWFuIFRhc2sgRm9yY2Ugb24gQWdlLVJlbGF0

ZWQgV2hpdGUgTWF0dGVyIENoYW5nZXM8L0lEVGV4dD48RGlzcGxheVRleHQ+PHN0eWxlIGZhY2U9

InN1cGVyc2NyaXB0Ij4xMywgMTQ8L3N0eWxlPjwvRGlzcGxheVRleHQ+PHJlY29yZD48a2V5d29y

ZHM+PGtleXdvcmQ+QnJhaW4gSXNjaGVtaWE8L2tleXdvcmQ+PGtleXdvcmQ+RGVtZW50aWE8L2tl

eXdvcmQ+PGtleXdvcmQ+RGlzYWJpbGl0eSBFdmFsdWF0aW9uPC9rZXl3b3JkPjxrZXl3b3JkPkh1

bWFuczwva2V5d29yZD48a2V5d29yZD5NYWduZXRpYyBSZXNvbmFuY2UgSW1hZ2luZzwva2V5d29y

ZD48a2V5d29yZD5PYnNlcnZlciBWYXJpYXRpb248L2tleXdvcmQ+PGtleXdvcmQ+VG9tb2dyYXBo

eSwgWC1SYXkgQ29tcHV0ZWQ8L2tleXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxz

Pjx1cmw+aHR0cHM6Ly93d3cubmNiaS5ubG0ubmloLmdvdi9wdWJtZWQvOTUyMDA2ODwvdXJsPjwv

cmVsYXRlZC11cmxzPjwvdXJscz48aXNibj4wMDE0LTMwMjI8L2lzYm4+PHRpdGxlcz48dGl0bGU+

V2hpdGUgbWF0dGVyIGNoYW5nZXMgb24gQ1QgYW5kIE1SSTogYW4gb3ZlcnZpZXcgb2YgdmlzdWFs

IHJhdGluZyBzY2FsZXMuIEV1cm9wZWFuIFRhc2sgRm9yY2Ugb24gQWdlLVJlbGF0ZWQgV2hpdGUg

TWF0dGVyIENoYW5nZXM8L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+RXVyIE5ldXJvbDwvc2Vjb25k

YXJ5LXRpdGxlPjwvdGl0bGVzPjxwYWdlcz44MC05PC9wYWdlcz48bnVtYmVyPjI8L251bWJlcj48

Y29udHJpYnV0b3JzPjxhdXRob3JzPjxhdXRob3I+U2NoZWx0ZW5zLCBQLjwvYXV0aG9yPjxhdXRo

b3I+RXJraW5qdW50aSwgVC48L2F1dGhvcj48YXV0aG9yPkxleXMsIEQuPC9hdXRob3I+PGF1dGhv

cj5XYWhsdW5kLCBMLiBPLjwvYXV0aG9yPjxhdXRob3I+SW56aXRhcmksIEQuPC9hdXRob3I+PGF1

dGhvcj5kZWwgU2VyLCBULjwvYXV0aG9yPjxhdXRob3I+UGFzcXVpZXIsIEYuPC9hdXRob3I+PGF1

dGhvcj5CYXJraG9mLCBGLjwvYXV0aG9yPjxhdXRob3I+TcOkbnR5bMOkLCBSLjwvYXV0aG9yPjxh

dXRob3I+Qm93bGVyLCBKLjwvYXV0aG9yPjxhdXRob3I+V2FsbGluLCBBLjwvYXV0aG9yPjxhdXRo

b3I+R2hpa2EsIEouPC9hdXRob3I+PGF1dGhvcj5GYXpla2FzLCBGLjwvYXV0aG9yPjxhdXRob3I+

UGFudG9uaSwgTC48L2F1dGhvcj48L2F1dGhvcnM+PC9jb250cmlidXRvcnM+PGxhbmd1YWdlPkVO

RzwvbGFuZ3VhZ2U+PGFkZGVkLWRhdGUgZm9ybWF0PSJ1dGMiPjE0Nzg2OTkwNjQ8L2FkZGVkLWRh

dGU+PHJlZi10eXBlIG5hbWU9IkpvdXJuYWwgQXJ0aWNsZSI+MTc8L3JlZi10eXBlPjxkYXRlcz48

eWVhcj4xOTk4PC95ZWFyPjwvZGF0ZXM+PHJlYy1udW1iZXI+NTQ4PC9yZWMtbnVtYmVyPjxsYXN0

LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3ODY5OTA2NDwvbGFzdC11cGRhdGVkLWRhdGU+

PGFjY2Vzc2lvbi1udW0+OTUyMDA2ODwvYWNjZXNzaW9uLW51bT48dm9sdW1lPjM5PC92b2x1bWU+

PC9yZWNvcmQ+PC9DaXRlPjxDaXRlPjxBdXRob3I+U2ltb25pPC9BdXRob3I+PFllYXI+MjAxMjwv

WWVhcj48SURUZXh0PkFnZS0gYW5kIHNleC1zcGVjaWZpYyByYXRlcyBvZiBsZXVrb2FyYWlvc2lz

IGluIFRJQSBhbmQgc3Ryb2tlIHBhdGllbnRzOiBwb3B1bGF0aW9uLWJhc2VkIHN0dWR5PC9JRFRl

eHQ+PHJlY29yZD48ZGF0ZXM+PHB1Yi1kYXRlcz48ZGF0ZT5TZXA8L2RhdGU+PC9wdWItZGF0ZXM+

PHllYXI+MjAxMjwveWVhcj48L2RhdGVzPjxrZXl3b3Jkcz48a2V5d29yZD5BZ2UgRmFjdG9yczwv

a2V5d29yZD48a2V5d29yZD5BZ2VkPC9rZXl3b3JkPjxrZXl3b3JkPkFnZWQsIDgwIGFuZCBvdmVy

PC9rZXl3b3JkPjxrZXl3b3JkPkJyYWluPC9rZXl3b3JkPjxrZXl3b3JkPkZlbWFsZTwva2V5d29y

ZD48a2V5d29yZD5IdW1hbnM8L2tleXdvcmQ+PGtleXdvcmQ+SW5jaWRlbmNlPC9rZXl3b3JkPjxr

ZXl3b3JkPklzY2hlbWljIEF0dGFjaywgVHJhbnNpZW50PC9rZXl3b3JkPjxrZXl3b3JkPkxldWtv

YXJhaW9zaXM8L2tleXdvcmQ+PGtleXdvcmQ+TWFnbmV0aWMgUmVzb25hbmNlIEltYWdpbmc8L2tl

eXdvcmQ+PGtleXdvcmQ+TWFsZTwva2V5d29yZD48a2V5d29yZD5NaWRkbGUgQWdlZDwva2V5d29y

ZD48a2V5d29yZD5OZXJ2ZSBGaWJlcnMsIE15ZWxpbmF0ZWQ8L2tleXdvcmQ+PGtleXdvcmQ+UHJl

dmFsZW5jZTwva2V5d29yZD48a2V5d29yZD5TZXggQ2hhcmFjdGVyaXN0aWNzPC9rZXl3b3JkPjxr

ZXl3b3JkPlN0cm9rZTwva2V5d29yZD48L2tleXdvcmRzPjx1cmxzPjxyZWxhdGVkLXVybHM+PHVy

bD5odHRwczovL3d3dy5uY2JpLm5sbS5uaWguZ292L3B1Ym1lZC8yMjk1NTEzODwvdXJsPjwvcmVs

YXRlZC11cmxzPjwvdXJscz48aXNibj4xNTI2LTYzMlg8L2lzYm4+PGN1c3RvbTI+UE1DMzQ0MDQ0

NzwvY3VzdG9tMj48dGl0bGVzPjx0aXRsZT5BZ2UtIGFuZCBzZXgtc3BlY2lmaWMgcmF0ZXMgb2Yg

bGV1a29hcmFpb3NpcyBpbiBUSUEgYW5kIHN0cm9rZSBwYXRpZW50czogcG9wdWxhdGlvbi1iYXNl

ZCBzdHVkeTwvdGl0bGU+PHNlY29uZGFyeS10aXRsZT5OZXVyb2xvZ3k8L3NlY29uZGFyeS10aXRs

ZT48L3RpdGxlcz48cGFnZXM+MTIxNS0yMjwvcGFnZXM+PG51bWJlcj4xMjwvbnVtYmVyPjxjb250

cmlidXRvcnM+PGF1dGhvcnM+PGF1dGhvcj5TaW1vbmksIE0uPC9hdXRob3I+PGF1dGhvcj5MaSwg

TC48L2F1dGhvcj48YXV0aG9yPlBhdWwsIE4uIEwuPC9hdXRob3I+PGF1dGhvcj5HcnV0ZXIsIEIu

IEUuPC9hdXRob3I+PGF1dGhvcj5TY2h1bHosIFUuIEcuPC9hdXRob3I+PGF1dGhvcj5Lw7xrZXIs

IFcuPC9hdXRob3I+PGF1dGhvcj5Sb3Rod2VsbCwgUC4gTS48L2F1dGhvcj48L2F1dGhvcnM+PC9j

b250cmlidXRvcnM+PGVkaXRpb24+MjAxMi8wOS8wNTwvZWRpdGlvbj48bGFuZ3VhZ2U+ZW5nPC9s

YW5ndWFnZT48YWRkZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ4ODQ1NzEyODwvYWRkZWQtZGF0ZT48

cmVmLXR5cGUgbmFtZT0iSm91cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PHJlYy1udW1iZXI+

NTcxPC9yZWMtbnVtYmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ4ODQ1NzEy

ODwvbGFzdC11cGRhdGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MjI5NTUxMzg8L2FjY2Vzc2lvbi1u

dW0+PGVsZWN0cm9uaWMtcmVzb3VyY2UtbnVtPjEwLjEyMTIvV05MLjBiMDEzZTMxODI2Yjk1MWU8

L2VsZWN0cm9uaWMtcmVzb3VyY2UtbnVtPjx2b2x1bWU+Nzk8L3ZvbHVtZT48L3JlY29yZD48L0Np

dGU+PC9FbmROb3RlPgAAAA==

ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5TY2hlbHRlbnM8L0F1dGhvcj48WWVhcj4xOTk4PC9ZZWFy

PjxJRFRleHQ+V2hpdGUgbWF0dGVyIGNoYW5nZXMgb24gQ1QgYW5kIE1SSTogYW4gb3ZlcnZpZXcg

b2YgdmlzdWFsIHJhdGluZyBzY2FsZXMuIEV1cm9wZWFuIFRhc2sgRm9yY2Ugb24gQWdlLVJlbGF0

ZWQgV2hpdGUgTWF0dGVyIENoYW5nZXM8L0lEVGV4dD48RGlzcGxheVRleHQ+PHN0eWxlIGZhY2U9

InN1cGVyc2NyaXB0Ij4xMywgMTQ8L3N0eWxlPjwvRGlzcGxheVRleHQ+PHJlY29yZD48a2V5d29y

ZHM+PGtleXdvcmQ+QnJhaW4gSXNjaGVtaWE8L2tleXdvcmQ+PGtleXdvcmQ+RGVtZW50aWE8L2tl

eXdvcmQ+PGtleXdvcmQ+RGlzYWJpbGl0eSBFdmFsdWF0aW9uPC9rZXl3b3JkPjxrZXl3b3JkPkh1

bWFuczwva2V5d29yZD48a2V5d29yZD5NYWduZXRpYyBSZXNvbmFuY2UgSW1hZ2luZzwva2V5d29y

ZD48a2V5d29yZD5PYnNlcnZlciBWYXJpYXRpb248L2tleXdvcmQ+PGtleXdvcmQ+VG9tb2dyYXBo

eSwgWC1SYXkgQ29tcHV0ZWQ8L2tleXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxz

Pjx1cmw+aHR0cHM6Ly93d3cubmNiaS5ubG0ubmloLmdvdi9wdWJtZWQvOTUyMDA2ODwvdXJsPjwv

cmVsYXRlZC11cmxzPjwvdXJscz48aXNibj4wMDE0LTMwMjI8L2lzYm4+PHRpdGxlcz48dGl0bGU+

V2hpdGUgbWF0dGVyIGNoYW5nZXMgb24gQ1QgYW5kIE1SSTogYW4gb3ZlcnZpZXcgb2YgdmlzdWFs

IHJhdGluZyBzY2FsZXMuIEV1cm9wZWFuIFRhc2sgRm9yY2Ugb24gQWdlLVJlbGF0ZWQgV2hpdGUg

TWF0dGVyIENoYW5nZXM8L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+RXVyIE5ldXJvbDwvc2Vjb25k

YXJ5LXRpdGxlPjwvdGl0bGVzPjxwYWdlcz44MC05PC9wYWdlcz48bnVtYmVyPjI8L251bWJlcj48

Y29udHJpYnV0b3JzPjxhdXRob3JzPjxhdXRob3I+U2NoZWx0ZW5zLCBQLjwvYXV0aG9yPjxhdXRo

b3I+RXJraW5qdW50aSwgVC48L2F1dGhvcj48YXV0aG9yPkxleXMsIEQuPC9hdXRob3I+PGF1dGhv

cj5XYWhsdW5kLCBMLiBPLjwvYXV0aG9yPjxhdXRob3I+SW56aXRhcmksIEQuPC9hdXRob3I+PGF1

dGhvcj5kZWwgU2VyLCBULjwvYXV0aG9yPjxhdXRob3I+UGFzcXVpZXIsIEYuPC9hdXRob3I+PGF1

dGhvcj5CYXJraG9mLCBGLjwvYXV0aG9yPjxhdXRob3I+TcOkbnR5bMOkLCBSLjwvYXV0aG9yPjxh

dXRob3I+Qm93bGVyLCBKLjwvYXV0aG9yPjxhdXRob3I+V2FsbGluLCBBLjwvYXV0aG9yPjxhdXRo

b3I+R2hpa2EsIEouPC9hdXRob3I+PGF1dGhvcj5GYXpla2FzLCBGLjwvYXV0aG9yPjxhdXRob3I+

UGFudG9uaSwgTC48L2F1dGhvcj48L2F1dGhvcnM+PC9jb250cmlidXRvcnM+PGxhbmd1YWdlPkVO

RzwvbGFuZ3VhZ2U+PGFkZGVkLWRhdGUgZm9ybWF0PSJ1dGMiPjE0Nzg2OTkwNjQ8L2FkZGVkLWRh

dGU+PHJlZi10eXBlIG5hbWU9IkpvdXJuYWwgQXJ0aWNsZSI+MTc8L3JlZi10eXBlPjxkYXRlcz48

eWVhcj4xOTk4PC95ZWFyPjwvZGF0ZXM+PHJlYy1udW1iZXI+NTQ4PC9yZWMtbnVtYmVyPjxsYXN0

LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3ODY5OTA2NDwvbGFzdC11cGRhdGVkLWRhdGU+

PGFjY2Vzc2lvbi1udW0+OTUyMDA2ODwvYWNjZXNzaW9uLW51bT48dm9sdW1lPjM5PC92b2x1bWU+

PC9yZWNvcmQ+PC9DaXRlPjxDaXRlPjxBdXRob3I+U2ltb25pPC9BdXRob3I+PFllYXI+MjAxMjwv

WWVhcj48SURUZXh0PkFnZS0gYW5kIHNleC1zcGVjaWZpYyByYXRlcyBvZiBsZXVrb2FyYWlvc2lz

IGluIFRJQSBhbmQgc3Ryb2tlIHBhdGllbnRzOiBwb3B1bGF0aW9uLWJhc2VkIHN0dWR5PC9JRFRl

eHQ+PHJlY29yZD48ZGF0ZXM+PHB1Yi1kYXRlcz48ZGF0ZT5TZXA8L2RhdGU+PC9wdWItZGF0ZXM+

PHllYXI+MjAxMjwveWVhcj48L2RhdGVzPjxrZXl3b3Jkcz48a2V5d29yZD5BZ2UgRmFjdG9yczwv

a2V5d29yZD48a2V5d29yZD5BZ2VkPC9rZXl3b3JkPjxrZXl3b3JkPkFnZWQsIDgwIGFuZCBvdmVy

PC9rZXl3b3JkPjxrZXl3b3JkPkJyYWluPC9rZXl3b3JkPjxrZXl3b3JkPkZlbWFsZTwva2V5d29y

ZD48a2V5d29yZD5IdW1hbnM8L2tleXdvcmQ+PGtleXdvcmQ+SW5jaWRlbmNlPC9rZXl3b3JkPjxr

ZXl3b3JkPklzY2hlbWljIEF0dGFjaywgVHJhbnNpZW50PC9rZXl3b3JkPjxrZXl3b3JkPkxldWtv

YXJhaW9zaXM8L2tleXdvcmQ+PGtleXdvcmQ+TWFnbmV0aWMgUmVzb25hbmNlIEltYWdpbmc8L2tl

eXdvcmQ+PGtleXdvcmQ+TWFsZTwva2V5d29yZD48a2V5d29yZD5NaWRkbGUgQWdlZDwva2V5d29y

ZD48a2V5d29yZD5OZXJ2ZSBGaWJlcnMsIE15ZWxpbmF0ZWQ8L2tleXdvcmQ+PGtleXdvcmQ+UHJl

dmFsZW5jZTwva2V5d29yZD48a2V5d29yZD5TZXggQ2hhcmFjdGVyaXN0aWNzPC9rZXl3b3JkPjxr

ZXl3b3JkPlN0cm9rZTwva2V5d29yZD48L2tleXdvcmRzPjx1cmxzPjxyZWxhdGVkLXVybHM+PHVy

bD5odHRwczovL3d3dy5uY2JpLm5sbS5uaWguZ292L3B1Ym1lZC8yMjk1NTEzODwvdXJsPjwvcmVs

YXRlZC11cmxzPjwvdXJscz48aXNibj4xNTI2LTYzMlg8L2lzYm4+PGN1c3RvbTI+UE1DMzQ0MDQ0

NzwvY3VzdG9tMj48dGl0bGVzPjx0aXRsZT5BZ2UtIGFuZCBzZXgtc3BlY2lmaWMgcmF0ZXMgb2Yg

bGV1a29hcmFpb3NpcyBpbiBUSUEgYW5kIHN0cm9rZSBwYXRpZW50czogcG9wdWxhdGlvbi1iYXNl

ZCBzdHVkeTwvdGl0bGU+PHNlY29uZGFyeS10aXRsZT5OZXVyb2xvZ3k8L3NlY29uZGFyeS10aXRs

ZT48L3RpdGxlcz48cGFnZXM+MTIxNS0yMjwvcGFnZXM+PG51bWJlcj4xMjwvbnVtYmVyPjxjb250

cmlidXRvcnM+PGF1dGhvcnM+PGF1dGhvcj5TaW1vbmksIE0uPC9hdXRob3I+PGF1dGhvcj5MaSwg

TC48L2F1dGhvcj48YXV0aG9yPlBhdWwsIE4uIEwuPC9hdXRob3I+PGF1dGhvcj5HcnV0ZXIsIEIu

IEUuPC9hdXRob3I+PGF1dGhvcj5TY2h1bHosIFUuIEcuPC9hdXRob3I+PGF1dGhvcj5Lw7xrZXIs

IFcuPC9hdXRob3I+PGF1dGhvcj5Sb3Rod2VsbCwgUC4gTS48L2F1dGhvcj48L2F1dGhvcnM+PC9j

b250cmlidXRvcnM+PGVkaXRpb24+MjAxMi8wOS8wNTwvZWRpdGlvbj48bGFuZ3VhZ2U+ZW5nPC9s

YW5ndWFnZT48YWRkZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ4ODQ1NzEyODwvYWRkZWQtZGF0ZT48

cmVmLXR5cGUgbmFtZT0iSm91cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PHJlYy1udW1iZXI+

NTcxPC9yZWMtbnVtYmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ4ODQ1NzEy

ODwvbGFzdC11cGRhdGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MjI5NTUxMzg8L2FjY2Vzc2lvbi1u

dW0+PGVsZWN0cm9uaWMtcmVzb3VyY2UtbnVtPjEwLjEyMTIvV05MLjBiMDEzZTMxODI2Yjk1MWU8

L2VsZWN0cm9uaWMtcmVzb3VyY2UtbnVtPjx2b2x1bWU+Nzk8L3ZvbHVtZT48L3JlY29yZD48L0Np

dGU+PC9FbmROb3RlPgAAAA==

ADDIN EN.CITE.DATA 13, 14 (kappa values ~0.5–0.6 for CT, versus 0.7-0.8 for MRIPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XYWhsdW5kPC9BdXRob3I+PFllYXI+MjAwMTwvWWVhcj48

SURUZXh0PkEgbmV3IHJhdGluZyBzY2FsZSBmb3IgYWdlLXJlbGF0ZWQgd2hpdGUgbWF0dGVyIGNo

YW5nZXMgYXBwbGljYWJsZSB0byBNUkkgYW5kIENULjwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5

bGUgZmFjZT0ic3VwZXJzY3JpcHQiPjEyLCAxNTwvc3R5bGU+PC9EaXNwbGF5VGV4dD48cmVjb3Jk

PjxkYXRlcz48cHViLWRhdGVzPjxkYXRlPkp1bjwvZGF0ZT48L3B1Yi1kYXRlcz48eWVhcj4yMDAx

PC95ZWFyPjwvZGF0ZXM+PGtleXdvcmRzPjxrZXl3b3JkPkFnaW5nPC9rZXl3b3JkPjxrZXl3b3Jk

PkJyYWluPC9rZXl3b3JkPjxrZXl3b3JkPkJyYWluIERpc2Vhc2VzPC9rZXl3b3JkPjxrZXl3b3Jk

PkNvZ25pdGlvbiBEaXNvcmRlcnM8L2tleXdvcmQ+PGtleXdvcmQ+RXVyb3BlPC9rZXl3b3JkPjxr

ZXl3b3JkPkh1bWFuczwva2V5d29yZD48a2V5d29yZD5NYWduZXRpYyBSZXNvbmFuY2UgSW1hZ2lu

Zzwva2V5d29yZD48a2V5d29yZD5NZW1vcnkgRGlzb3JkZXJzPC9rZXl3b3JkPjxrZXl3b3JkPk15

ZWxpbiBTaGVhdGg8L2tleXdvcmQ+PGtleXdvcmQ+T2JzZXJ2ZXIgVmFyaWF0aW9uPC9rZXl3b3Jk

PjxrZXl3b3JkPlByZWRpY3RpdmUgVmFsdWUgb2YgVGVzdHM8L2tleXdvcmQ+PGtleXdvcmQ+UmVw

cm9kdWNpYmlsaXR5IG9mIFJlc3VsdHM8L2tleXdvcmQ+PGtleXdvcmQ+U2Vuc2l0aXZpdHkgYW5k

IFNwZWNpZmljaXR5PC9rZXl3b3JkPjxrZXl3b3JkPlRvbW9ncmFwaHksIFgtUmF5IENvbXB1dGVk

PC9rZXl3b3JkPjwva2V5d29yZHM+PHVybHM+PHJlbGF0ZWQtdXJscz48dXJsPmh0dHA6Ly93d3cu

bmNiaS5ubG0ubmloLmdvdi9wdWJtZWQvMTEzODc0OTM8L3VybD48L3JlbGF0ZWQtdXJscz48L3Vy

bHM+PGlzYm4+MTUyNC00NjI4PC9pc2JuPjx0aXRsZXM+PHRpdGxlPkEgbmV3IHJhdGluZyBzY2Fs

ZSBmb3IgYWdlLXJlbGF0ZWQgd2hpdGUgbWF0dGVyIGNoYW5nZXMgYXBwbGljYWJsZSB0byBNUkkg

YW5kIENULjwvdGl0bGU+PHNlY29uZGFyeS10aXRsZT5TdHJva2U8L3NlY29uZGFyeS10aXRsZT48

L3RpdGxlcz48cGFnZXM+MTMxOC0yMjwvcGFnZXM+PG51bWJlcj42PC9udW1iZXI+PGNvbnRyaWJ1

dG9ycz48YXV0aG9ycz48YXV0aG9yPldhaGx1bmQsIEwuIE8uPC9hdXRob3I+PGF1dGhvcj5CYXJr

aG9mLCBGLjwvYXV0aG9yPjxhdXRob3I+RmF6ZWthcywgRi48L2F1dGhvcj48YXV0aG9yPkJyb25n

ZSwgTC48L2F1dGhvcj48YXV0aG9yPkF1Z3VzdGluLCBNLjwvYXV0aG9yPjxhdXRob3I+U2rDtmdy

ZW4sIE0uPC9hdXRob3I+PGF1dGhvcj5XYWxsaW4sIEEuPC9hdXRob3I+PGF1dGhvcj5BZGVyLCBI

LjwvYXV0aG9yPjxhdXRob3I+TGV5cywgRC48L2F1dGhvcj48YXV0aG9yPlBhbnRvbmksIEwuPC9h

dXRob3I+PGF1dGhvcj5QYXNxdWllciwgRi48L2F1dGhvcj48YXV0aG9yPkVya2luanVudHRpLCBU

LjwvYXV0aG9yPjxhdXRob3I+U2NoZWx0ZW5zLCBQLjwvYXV0aG9yPjxhdXRob3I+RXVyb3BlYW4g

VGFzayBGb3JjZSBvbiBBZ2UtUmVsYXRlZCBXaGl0ZSBNYXR0ZXIgQ2hhbmdlczwvYXV0aG9yPjwv

YXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3VhZ2U+ZW5nPC9sYW5ndWFnZT48YWRkZWQtZGF0

ZSBmb3JtYXQ9InV0YyI+MTMzNDkzNzY2NjwvYWRkZWQtZGF0ZT48cmVmLXR5cGUgbmFtZT0iSm91

cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PGF1dGgtYWRkcmVzcz5EZXBhcnRtZW50IG9mIENs

aW5pY2FsIE5ldXJvc2NpZW5jZSwgTkVVUk9URUMsIEthcm9saW5za2EgSW5zdGl0dXRldCBhdCBI

dWRkaW5nZSBVbml2ZXJzaXR5IEhvc3BpdGFsLCBIdWRkaW5nZSwgU3dlZGVuLiBsYXJzLW9sb2Yu

d2FobHVuZEBuZXVyb3RlYy5raS5zZTwvYXV0aC1hZGRyZXNzPjxyZWMtbnVtYmVyPjEzMzwvcmVj

LW51bWJlcj48bGFzdC11cGRhdGVkLWRhdGUgZm9ybWF0PSJ1dGMiPjEzMzQ5Mzc2NjY8L2xhc3Qt

dXBkYXRlZC1kYXRlPjxhY2Nlc3Npb24tbnVtPjExMzg3NDkzPC9hY2Nlc3Npb24tbnVtPjx2b2x1

bWU+MzI8L3ZvbHVtZT48L3JlY29yZD48L0NpdGU+PENpdGU+PEF1dGhvcj52YW4gU3dpZXRlbjwv

QXV0aG9yPjxZZWFyPjE5OTA8L1llYXI+PElEVGV4dD5HcmFkaW5nIHdoaXRlIG1hdHRlciBsZXNp

b25zIG9uIENUIGFuZCBNUkk6IGEgc2ltcGxlIHNjYWxlPC9JRFRleHQ+PHJlY29yZD48ZGF0ZXM+

PHB1Yi1kYXRlcz48ZGF0ZT5EZWM8L2RhdGU+PC9wdWItZGF0ZXM+PHllYXI+MTk5MDwveWVhcj48

L2RhdGVzPjxrZXl3b3Jkcz48a2V5d29yZD5CcmFpbjwva2V5d29yZD48a2V5d29yZD5CcmFpbiBE

aXNlYXNlczwva2V5d29yZD48a2V5d29yZD5Dcm9zcy1TZWN0aW9uYWwgU3R1ZGllczwva2V5d29y

ZD48a2V5d29yZD5EYXRhIEludGVycHJldGF0aW9uLCBTdGF0aXN0aWNhbDwva2V5d29yZD48a2V5

d29yZD5IdW1hbnM8L2tleXdvcmQ+PGtleXdvcmQ+SXNjaGVtaWMgQXR0YWNrLCBUcmFuc2llbnQ8

L2tleXdvcmQ+PGtleXdvcmQ+TG9uZ2l0dWRpbmFsIFN0dWRpZXM8L2tleXdvcmQ+PGtleXdvcmQ+

TWFnbmV0aWMgUmVzb25hbmNlIEltYWdpbmc8L2tleXdvcmQ+PGtleXdvcmQ+VG9tb2dyYXBoeSwg

WC1SYXkgQ29tcHV0ZWQ8L2tleXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1

cmw+aHR0cHM6Ly93d3cubmNiaS5ubG0ubmloLmdvdi9wdWJtZWQvMjI5MjcwMzwvdXJsPjwvcmVs

YXRlZC11cmxzPjwvdXJscz48aXNibj4wMDIyLTMwNTA8L2lzYm4+PGN1c3RvbTI+UE1DNDg4MzIw

PC9jdXN0b20yPjx0aXRsZXM+PHRpdGxlPkdyYWRpbmcgd2hpdGUgbWF0dGVyIGxlc2lvbnMgb24g

Q1QgYW5kIE1SSTogYSBzaW1wbGUgc2NhbGU8L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+SiBOZXVy

b2wgTmV1cm9zdXJnIFBzeWNoaWF0cnk8L3NlY29uZGFyeS10aXRsZT48L3RpdGxlcz48cGFnZXM+

MTA4MC0zPC9wYWdlcz48bnVtYmVyPjEyPC9udW1iZXI+PGNvbnRyaWJ1dG9ycz48YXV0aG9ycz48

YXV0aG9yPnZhbiBTd2lldGVuLCBKLiBDLjwvYXV0aG9yPjxhdXRob3I+SGlqZHJhLCBBLjwvYXV0

aG9yPjxhdXRob3I+S291ZHN0YWFsLCBQLiBKLjwvYXV0aG9yPjxhdXRob3I+dmFuIEdpam4sIEou

PC9hdXRob3I+PC9hdXRob3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5FTkc8L2xhbmd1YWdl

PjxhZGRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc4MTc3NjAwPC9hZGRlZC1kYXRlPjxyZWYtdHlw

ZSBuYW1lPSJKb3VybmFsIEFydGljbGUiPjE3PC9yZWYtdHlwZT48cmVjLW51bWJlcj41MzE8L3Jl

Yy1udW1iZXI+PGxhc3QtdXBkYXRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc4MTc3NjAwPC9sYXN0

LXVwZGF0ZWQtZGF0ZT48YWNjZXNzaW9uLW51bT4yMjkyNzAzPC9hY2Nlc3Npb24tbnVtPjx2b2x1

bWU+NTM8L3ZvbHVtZT48L3JlY29yZD48L0NpdGU+PC9FbmROb3RlPgAA

ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XYWhsdW5kPC9BdXRob3I+PFllYXI+MjAwMTwvWWVhcj48

SURUZXh0PkEgbmV3IHJhdGluZyBzY2FsZSBmb3IgYWdlLXJlbGF0ZWQgd2hpdGUgbWF0dGVyIGNo

YW5nZXMgYXBwbGljYWJsZSB0byBNUkkgYW5kIENULjwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5

bGUgZmFjZT0ic3VwZXJzY3JpcHQiPjEyLCAxNTwvc3R5bGU+PC9EaXNwbGF5VGV4dD48cmVjb3Jk

PjxkYXRlcz48cHViLWRhdGVzPjxkYXRlPkp1bjwvZGF0ZT48L3B1Yi1kYXRlcz48eWVhcj4yMDAx

PC95ZWFyPjwvZGF0ZXM+PGtleXdvcmRzPjxrZXl3b3JkPkFnaW5nPC9rZXl3b3JkPjxrZXl3b3Jk

PkJyYWluPC9rZXl3b3JkPjxrZXl3b3JkPkJyYWluIERpc2Vhc2VzPC9rZXl3b3JkPjxrZXl3b3Jk

PkNvZ25pdGlvbiBEaXNvcmRlcnM8L2tleXdvcmQ+PGtleXdvcmQ+RXVyb3BlPC9rZXl3b3JkPjxr

ZXl3b3JkPkh1bWFuczwva2V5d29yZD48a2V5d29yZD5NYWduZXRpYyBSZXNvbmFuY2UgSW1hZ2lu

Zzwva2V5d29yZD48a2V5d29yZD5NZW1vcnkgRGlzb3JkZXJzPC9rZXl3b3JkPjxrZXl3b3JkPk15

ZWxpbiBTaGVhdGg8L2tleXdvcmQ+PGtleXdvcmQ+T2JzZXJ2ZXIgVmFyaWF0aW9uPC9rZXl3b3Jk

PjxrZXl3b3JkPlByZWRpY3RpdmUgVmFsdWUgb2YgVGVzdHM8L2tleXdvcmQ+PGtleXdvcmQ+UmVw

cm9kdWNpYmlsaXR5IG9mIFJlc3VsdHM8L2tleXdvcmQ+PGtleXdvcmQ+U2Vuc2l0aXZpdHkgYW5k

IFNwZWNpZmljaXR5PC9rZXl3b3JkPjxrZXl3b3JkPlRvbW9ncmFwaHksIFgtUmF5IENvbXB1dGVk

PC9rZXl3b3JkPjwva2V5d29yZHM+PHVybHM+PHJlbGF0ZWQtdXJscz48dXJsPmh0dHA6Ly93d3cu

bmNiaS5ubG0ubmloLmdvdi9wdWJtZWQvMTEzODc0OTM8L3VybD48L3JlbGF0ZWQtdXJscz48L3Vy

bHM+PGlzYm4+MTUyNC00NjI4PC9pc2JuPjx0aXRsZXM+PHRpdGxlPkEgbmV3IHJhdGluZyBzY2Fs

ZSBmb3IgYWdlLXJlbGF0ZWQgd2hpdGUgbWF0dGVyIGNoYW5nZXMgYXBwbGljYWJsZSB0byBNUkkg

YW5kIENULjwvdGl0bGU+PHNlY29uZGFyeS10aXRsZT5TdHJva2U8L3NlY29uZGFyeS10aXRsZT48

L3RpdGxlcz48cGFnZXM+MTMxOC0yMjwvcGFnZXM+PG51bWJlcj42PC9udW1iZXI+PGNvbnRyaWJ1

dG9ycz48YXV0aG9ycz48YXV0aG9yPldhaGx1bmQsIEwuIE8uPC9hdXRob3I+PGF1dGhvcj5CYXJr

aG9mLCBGLjwvYXV0aG9yPjxhdXRob3I+RmF6ZWthcywgRi48L2F1dGhvcj48YXV0aG9yPkJyb25n

ZSwgTC48L2F1dGhvcj48YXV0aG9yPkF1Z3VzdGluLCBNLjwvYXV0aG9yPjxhdXRob3I+U2rDtmdy

ZW4sIE0uPC9hdXRob3I+PGF1dGhvcj5XYWxsaW4sIEEuPC9hdXRob3I+PGF1dGhvcj5BZGVyLCBI

LjwvYXV0aG9yPjxhdXRob3I+TGV5cywgRC48L2F1dGhvcj48YXV0aG9yPlBhbnRvbmksIEwuPC9h

dXRob3I+PGF1dGhvcj5QYXNxdWllciwgRi48L2F1dGhvcj48YXV0aG9yPkVya2luanVudHRpLCBU

LjwvYXV0aG9yPjxhdXRob3I+U2NoZWx0ZW5zLCBQLjwvYXV0aG9yPjxhdXRob3I+RXVyb3BlYW4g

VGFzayBGb3JjZSBvbiBBZ2UtUmVsYXRlZCBXaGl0ZSBNYXR0ZXIgQ2hhbmdlczwvYXV0aG9yPjwv

YXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3VhZ2U+ZW5nPC9sYW5ndWFnZT48YWRkZWQtZGF0

ZSBmb3JtYXQ9InV0YyI+MTMzNDkzNzY2NjwvYWRkZWQtZGF0ZT48cmVmLXR5cGUgbmFtZT0iSm91

cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PGF1dGgtYWRkcmVzcz5EZXBhcnRtZW50IG9mIENs

aW5pY2FsIE5ldXJvc2NpZW5jZSwgTkVVUk9URUMsIEthcm9saW5za2EgSW5zdGl0dXRldCBhdCBI

dWRkaW5nZSBVbml2ZXJzaXR5IEhvc3BpdGFsLCBIdWRkaW5nZSwgU3dlZGVuLiBsYXJzLW9sb2Yu

d2FobHVuZEBuZXVyb3RlYy5raS5zZTwvYXV0aC1hZGRyZXNzPjxyZWMtbnVtYmVyPjEzMzwvcmVj

LW51bWJlcj48bGFzdC11cGRhdGVkLWRhdGUgZm9ybWF0PSJ1dGMiPjEzMzQ5Mzc2NjY8L2xhc3Qt

dXBkYXRlZC1kYXRlPjxhY2Nlc3Npb24tbnVtPjExMzg3NDkzPC9hY2Nlc3Npb24tbnVtPjx2b2x1

bWU+MzI8L3ZvbHVtZT48L3JlY29yZD48L0NpdGU+PENpdGU+PEF1dGhvcj52YW4gU3dpZXRlbjwv

QXV0aG9yPjxZZWFyPjE5OTA8L1llYXI+PElEVGV4dD5HcmFkaW5nIHdoaXRlIG1hdHRlciBsZXNp

b25zIG9uIENUIGFuZCBNUkk6IGEgc2ltcGxlIHNjYWxlPC9JRFRleHQ+PHJlY29yZD48ZGF0ZXM+

PHB1Yi1kYXRlcz48ZGF0ZT5EZWM8L2RhdGU+PC9wdWItZGF0ZXM+PHllYXI+MTk5MDwveWVhcj48

L2RhdGVzPjxrZXl3b3Jkcz48a2V5d29yZD5CcmFpbjwva2V5d29yZD48a2V5d29yZD5CcmFpbiBE

aXNlYXNlczwva2V5d29yZD48a2V5d29yZD5Dcm9zcy1TZWN0aW9uYWwgU3R1ZGllczwva2V5d29y

ZD48a2V5d29yZD5EYXRhIEludGVycHJldGF0aW9uLCBTdGF0aXN0aWNhbDwva2V5d29yZD48a2V5

d29yZD5IdW1hbnM8L2tleXdvcmQ+PGtleXdvcmQ+SXNjaGVtaWMgQXR0YWNrLCBUcmFuc2llbnQ8

L2tleXdvcmQ+PGtleXdvcmQ+TG9uZ2l0dWRpbmFsIFN0dWRpZXM8L2tleXdvcmQ+PGtleXdvcmQ+

TWFnbmV0aWMgUmVzb25hbmNlIEltYWdpbmc8L2tleXdvcmQ+PGtleXdvcmQ+VG9tb2dyYXBoeSwg

WC1SYXkgQ29tcHV0ZWQ8L2tleXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1

cmw+aHR0cHM6Ly93d3cubmNiaS5ubG0ubmloLmdvdi9wdWJtZWQvMjI5MjcwMzwvdXJsPjwvcmVs

YXRlZC11cmxzPjwvdXJscz48aXNibj4wMDIyLTMwNTA8L2lzYm4+PGN1c3RvbTI+UE1DNDg4MzIw

PC9jdXN0b20yPjx0aXRsZXM+PHRpdGxlPkdyYWRpbmcgd2hpdGUgbWF0dGVyIGxlc2lvbnMgb24g

Q1QgYW5kIE1SSTogYSBzaW1wbGUgc2NhbGU8L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+SiBOZXVy

b2wgTmV1cm9zdXJnIFBzeWNoaWF0cnk8L3NlY29uZGFyeS10aXRsZT48L3RpdGxlcz48cGFnZXM+

MTA4MC0zPC9wYWdlcz48bnVtYmVyPjEyPC9udW1iZXI+PGNvbnRyaWJ1dG9ycz48YXV0aG9ycz48

YXV0aG9yPnZhbiBTd2lldGVuLCBKLiBDLjwvYXV0aG9yPjxhdXRob3I+SGlqZHJhLCBBLjwvYXV0

aG9yPjxhdXRob3I+S291ZHN0YWFsLCBQLiBKLjwvYXV0aG9yPjxhdXRob3I+dmFuIEdpam4sIEou

PC9hdXRob3I+PC9hdXRob3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5FTkc8L2xhbmd1YWdl

PjxhZGRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc4MTc3NjAwPC9hZGRlZC1kYXRlPjxyZWYtdHlw

ZSBuYW1lPSJKb3VybmFsIEFydGljbGUiPjE3PC9yZWYtdHlwZT48cmVjLW51bWJlcj41MzE8L3Jl

Yy1udW1iZXI+PGxhc3QtdXBkYXRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc4MTc3NjAwPC9sYXN0

LXVwZGF0ZWQtZGF0ZT48YWNjZXNzaW9uLW51bT4yMjkyNzAzPC9hY2Nlc3Npb24tbnVtPjx2b2x1

bWU+NTM8L3ZvbHVtZT48L3JlY29yZD48L0NpdGU+PC9FbmROb3RlPgAA

ADDIN EN.CITE.DATA 12, 15). Furthermore, WML scoring systems typically allow for only a small number of ordinal ratings (4-6 ADDIN EN.CITE <EndNote><Cite><Author>Pantoni</Author><Year>2002</Year><IDText>Visual rating scales for age-related white matter changes (leukoaraiosis): can the heterogeneity be reduced?</IDText><DisplayText><style face="superscript">16</style></DisplayText><record><dates><pub-dates><date>Dec</date></pub-dates><year>2002</year></dates><keywords><keyword>Aging</keyword><keyword>Brain</keyword><keyword>Brain Diseases</keyword><keyword>Cognition Disorders</keyword><keyword>Feasibility Studies</keyword><keyword>Gait Disorders, Neurologic</keyword><keyword>Humans</keyword><keyword>Hypertension</keyword><keyword>Linear Models</keyword><keyword>Magnetic Resonance Imaging</keyword><keyword>Middle Aged</keyword><keyword>Predictive Value of Tests</keyword><keyword>Risk Factors</keyword><keyword>Sensitivity and Specificity</keyword><keyword>Statistics, Nonparametric</keyword><keyword>Tomography, X-Ray Computed</keyword></keywords><urls><related-urls><url> rating scales for age-related white matter changes (leukoaraiosis): can the heterogeneity be reduced?</title><secondary-title>Stroke</secondary-title></titles><pages>2827-33</pages><number>12</number><contributors><authors><author>Pantoni, L.</author><author>Simoni, M.</author><author>Pracucci, G.</author><author>Schmidt, R.</author><author>Barkhof, F.</author><author>Inzitari, D.</author></authors></contributors><language>ENG</language><added-date format="utc">1478699064</added-date><ref-type name="Journal Article">17</ref-type><rec-number>546</rec-number><last-updated-date format="utc">1478699064</last-updated-date><accession-num>12468777</accession-num><volume>33</volume></record></Cite></EndNote>16), and use visual criteria (e.g. restricted to periventricular regions versus extending to cortex) that are imprecise, and do not convert directly to an estimate of total WML load ADDIN EN.CITE <EndNote><Cite><Author>Scheltens</Author><Year>1998</Year><IDText>White matter changes on CT and MRI: an overview of visual rating scales. European Task Force on Age-Related White Matter Changes</IDText><DisplayText><style face="superscript">14</style></DisplayText><record><keywords><keyword>Brain Ischemia</keyword><keyword>Dementia</keyword><keyword>Disability Evaluation</keyword><keyword>Humans</keyword><keyword>Magnetic Resonance Imaging</keyword><keyword>Observer Variation</keyword><keyword>Tomography, X-Ray Computed</keyword></keywords><urls><related-urls><url> matter changes on CT and MRI: an overview of visual rating scales. European Task Force on Age-Related White Matter Changes</title><secondary-title>Eur Neurol</secondary-title></titles><pages>80-9</pages><number>2</number><contributors><authors><author>Scheltens, P.</author><author>Erkinjunti, T.</author><author>Leys, D.</author><author>Wahlund, L. O.</author><author>Inzitari, D.</author><author>del Ser, T.</author><author>Pasquier, F.</author><author>Barkhof, F.</author><author>M?ntyl?, R.</author><author>Bowler, J.</author><author>Wallin, A.</author><author>Ghika, J.</author><author>Fazekas, F.</author><author>Pantoni, L.</author></authors></contributors><language>ENG</language><added-date format="utc">1478699064</added-date><ref-type name="Journal Article">17</ref-type><dates><year>1998</year></dates><rec-number>548</rec-number><last-updated-date format="utc">1478699064</last-updated-date><accession-num>9520068</accession-num><volume>39</volume></record></Cite></EndNote>14. As such, visual estimates of WML severity, although providing valuable prognostic information ADDIN EN.CITE <EndNote><Cite><Author>IST-3</Author><Year>2015</Year><IDText>Association between brain imaging signs, early and late outcomes, and response to intravenous alteplase after acute ischaemic stroke in the third International Stroke Trial (IST-3): secondary analysis of a randomised controlled trial</IDText><DisplayText><style face="superscript">4</style></DisplayText><record><dates><pub-dates><date>May</date></pub-dates><year>2015</year></dates><keywords><keyword>Adult</keyword><keyword>Aged</keyword><keyword>Aged, 80 and over</keyword><keyword>Brain Ischemia</keyword><keyword>Data Interpretation, Statistical</keyword><keyword>Female</keyword><keyword>Fibrinolytic Agents</keyword><keyword>Humans</keyword><keyword>Magnetic Resonance Imaging, Cine</keyword><keyword>Male</keyword><keyword>Middle Aged</keyword><keyword>Outcome Assessment (Health Care)</keyword><keyword>Radiography</keyword><keyword>Single-Blind Method</keyword><keyword>Stroke</keyword><keyword>Thrombolytic Therapy</keyword><keyword>Tissue Plasminogen Activator</keyword></keywords><urls><related-urls><url> between brain imaging signs, early and late outcomes, and response to intravenous alteplase after acute ischaemic stroke in the third International Stroke Trial (IST-3): secondary analysis of a randomised controlled trial</title><secondary-title>Lancet Neurol</secondary-title></titles><pages>485-96</pages><number>5</number><contributors><authors><author>IST-3 collaborative group</author></authors></contributors><edition>2015/03/27</edition><language>eng</language><added-date format="utc">1488458505</added-date><ref-type name="Journal Article">17</ref-type><rec-number>573</rec-number><last-updated-date format="utc">1488458505</last-updated-date><accession-num>25819484</accession-num><electronic-resource-num>10.1016/S1474-4422(15)00012-5</electronic-resource-num><volume>14</volume></record></Cite></EndNote>4, have limited sensitivity as diagnostic markers, for monitoring disease progression, or in research. Our group have previously described a machine-learning method for automatically delineating WML on standard unenhanced CT, that performed favourably on a limited test against expert WML ratingsPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5DaGVuPC9BdXRob3I+PFllYXI+MjAxNTwvWWVhcj48SURU

ZXh0PklkZW50aWZpY2F0aW9uIG9mIENlcmVicmFsIFNtYWxsIFZlc3NlbCBEaXNlYXNlIFVzaW5n

IE11bHRpcGxlIEluc3RhbmNlIExlYXJuaW5nPC9JRFRleHQ+PERpc3BsYXlUZXh0PjxzdHlsZSBm

YWNlPSJzdXBlcnNjcmlwdCI+MTcsIDE4PC9zdHlsZT48L0Rpc3BsYXlUZXh0PjxyZWNvcmQ+PGlz

Ym4+MDMwMi05NzQzPC9pc2JuPjx0aXRsZXM+PHRpdGxlPklkZW50aWZpY2F0aW9uIG9mIENlcmVi

cmFsIFNtYWxsIFZlc3NlbCBEaXNlYXNlIFVzaW5nIE11bHRpcGxlIEluc3RhbmNlIExlYXJuaW5n

PC90aXRsZT48c2Vjb25kYXJ5LXRpdGxlPk1lZGljYWwgSW1hZ2UgQ29tcHV0aW5nIGFuZCBDb21w

dXRlci1Bc3Npc3RlZCBJbnRlcnZlbnRpb24gKE1JQ0NBSSAyMDE1KTwvc2Vjb25kYXJ5LXRpdGxl

PjwvdGl0bGVzPjxwYWdlcz41MjMtNTMwPC9wYWdlcz48Y29udHJpYnV0b3JzPjxhdXRob3JzPjxh

dXRob3I+Q2hlbiwgTGlhbmc8L2F1dGhvcj48YXV0aG9yPlRvbmcsIFRvbmc8L2F1dGhvcj48YXV0

aG9yPlBhbmcgSG8sIENoaW48L2F1dGhvcj48YXV0aG9yPlBhdGVsLCBSYWppdjwvYXV0aG9yPjxh

dXRob3I+Q29oZW4sIERhdmlkPC9hdXRob3I+PGF1dGhvcj5EYXdzb24sIEFuZ2VsYSBDPC9hdXRo

b3I+PGF1dGhvcj5IYWxzZSwgT21pZDwvYXV0aG9yPjxhdXRob3I+R2VyYWdodHksIE9saXZpYTwv

YXV0aG9yPjxhdXRob3I+UmlubmUsIFBhdWw8L2F1dGhvcj48YXV0aG9yPldoaXRlLCBDaHJpc3Rv

cGhlcjwvYXV0aG9yPjxhdXRob3I+TmFrb3JuY2hhaSwgVGFnb3JlPC9hdXRob3I+PGF1dGhvcj5C

ZW50bGV5LCBQYXVsPC9hdXRob3I+PGF1dGhvcj5SdWVja2VydCwgRGFuaWVsPC9hdXRob3I+PC9h

dXRob3JzPjwvY29udHJpYnV0b3JzPjxlZGl0aW9uPjE4IE5vdiAyMDE1PC9lZGl0aW9uPjxhZGRl

ZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc4MTgxNzkyPC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1l

PSJKb3VybmFsIEFydGljbGUiPjE3PC9yZWYtdHlwZT48ZGF0ZXM+PHllYXI+MjAxNTwveWVhcj48

L2RhdGVzPjxyZWMtbnVtYmVyPjUzNDwvcmVjLW51bWJlcj48bGFzdC11cGRhdGVkLWRhdGUgZm9y

bWF0PSJ1dGMiPjE0NzgxODIyMzE8L2xhc3QtdXBkYXRlZC1kYXRlPjxlbGVjdHJvbmljLXJlc291

cmNlLW51bT4xMC4xMDA3Lzk3OC0zLTMxOS0yNDU1My05XzY0PC9lbGVjdHJvbmljLXJlc291cmNl

LW51bT48dm9sdW1lPjkzNDk8L3ZvbHVtZT48L3JlY29yZD48L0NpdGU+PENpdGU+PEF1dGhvcj5N

YWllcjwvQXV0aG9yPjxZZWFyPjIwMTc8L1llYXI+PElEVGV4dD5JU0xFUyAyMDE1IC0gQSBwdWJs

aWMgZXZhbHVhdGlvbiBiZW5jaG1hcmsgZm9yIGlzY2hlbWljIHN0cm9rZSBsZXNpb24gc2VnbWVu

dGF0aW9uIGZyb20gbXVsdGlzcGVjdHJhbCBNUkk8L0lEVGV4dD48cmVjb3JkPjxkYXRlcz48cHVi

LWRhdGVzPjxkYXRlPkphbjwvZGF0ZT48L3B1Yi1kYXRlcz48eWVhcj4yMDE3PC95ZWFyPjwvZGF0

ZXM+PHVybHM+PHJlbGF0ZWQtdXJscz48dXJsPmh0dHBzOi8vd3d3Lm5jYmkubmxtLm5paC5nb3Yv

cHVibWVkLzI3NDc1OTExPC91cmw+PC9yZWxhdGVkLXVybHM+PC91cmxzPjxpc2JuPjEzNjEtODQx

NTwvaXNibj48Y3VzdG9tMj5QTUM1MDk5MTE4PC9jdXN0b20yPjx0aXRsZXM+PHRpdGxlPklTTEVT

IDIwMTUgLSBBIHB1YmxpYyBldmFsdWF0aW9uIGJlbmNobWFyayBmb3IgaXNjaGVtaWMgc3Ryb2tl

IGxlc2lvbiBzZWdtZW50YXRpb24gZnJvbSBtdWx0aXNwZWN0cmFsIE1SSTwvdGl0bGU+PHNlY29u

ZGFyeS10aXRsZT5NZWQgSW1hZ2UgQW5hbDwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0bGVzPjxwYWdl

cz4yNTAtMjY5PC9wYWdlcz48Y29udHJpYnV0b3JzPjxhdXRob3JzPjxhdXRob3I+TWFpZXIsIE8u

PC9hdXRob3I+PGF1dGhvcj5NZW56ZSwgQi4gSC48L2F1dGhvcj48YXV0aG9yPnZvbiBkZXIgR2Fi

bGVudHosIEouPC9hdXRob3I+PGF1dGhvcj5Iw6RuaSwgTC48L2F1dGhvcj48YXV0aG9yPkhlaW5y

aWNoLCBNLiBQLjwvYXV0aG9yPjxhdXRob3I+TGllYnJhbmQsIE0uPC9hdXRob3I+PGF1dGhvcj5X

aW56ZWNrLCBTLjwvYXV0aG9yPjxhdXRob3I+QmFzaXQsIEEuPC9hdXRob3I+PGF1dGhvcj5CZW50

bGV5LCBQLjwvYXV0aG9yPjxhdXRob3I+Q2hlbiwgTC48L2F1dGhvcj48YXV0aG9yPkNocmlzdGlh

ZW5zLCBELjwvYXV0aG9yPjxhdXRob3I+RHV0aWwsIEYuPC9hdXRob3I+PGF1dGhvcj5FZ2dlciwg

Sy48L2F1dGhvcj48YXV0aG9yPkZlbmcsIEMuPC9hdXRob3I+PGF1dGhvcj5HbG9ja2VyLCBCLjwv

YXV0aG9yPjxhdXRob3I+R8O2dHosIE0uPC9hdXRob3I+PGF1dGhvcj5IYWVjaywgVC48L2F1dGhv

cj48YXV0aG9yPkhhbG1lLCBILiBMLjwvYXV0aG9yPjxhdXRob3I+SGF2YWVpLCBNLjwvYXV0aG9y

PjxhdXRob3I+SWZ0ZWtoYXJ1ZGRpbiwgSy4gTS48L2F1dGhvcj48YXV0aG9yPkpvZG9pbiwgUC4g

TS48L2F1dGhvcj48YXV0aG9yPkthbW5pdHNhcywgSy48L2F1dGhvcj48YXV0aG9yPktlbGxuZXIs

IEUuPC9hdXRob3I+PGF1dGhvcj5Lb3J2ZW5vamEsIEEuPC9hdXRob3I+PGF1dGhvcj5MYXJvY2hl

bGxlLCBILjwvYXV0aG9yPjxhdXRob3I+TGVkaWcsIEMuPC9hdXRob3I+PGF1dGhvcj5MZWUsIEou

IEguPC9hdXRob3I+PGF1dGhvcj5NYWVzLCBGLjwvYXV0aG9yPjxhdXRob3I+TWFobW9vZCwgUS48

L2F1dGhvcj48YXV0aG9yPk1haWVyLUhlaW4sIEsuIEguPC9hdXRob3I+PGF1dGhvcj5NY0tpbmxl

eSwgUi48L2F1dGhvcj48YXV0aG9yPk11c2NoZWxsaSwgSi48L2F1dGhvcj48YXV0aG9yPlBhbCwg

Qy48L2F1dGhvcj48YXV0aG9yPlBlaSwgTC48L2F1dGhvcj48YXV0aG9yPlJhbmdhcmFqYW4sIEou

IFIuPC9hdXRob3I+PGF1dGhvcj5SZXphLCBTLiBNLjwvYXV0aG9yPjxhdXRob3I+Um9iYmVuLCBE

LjwvYXV0aG9yPjxhdXRob3I+UnVlY2tlcnQsIEQuPC9hdXRob3I+PGF1dGhvcj5TYWxsaSwgRS48

L2F1dGhvcj48YXV0aG9yPlN1ZXRlbnMsIFAuPC9hdXRob3I+PGF1dGhvcj5XYW5nLCBDLiBXLjwv

YXV0aG9yPjxhdXRob3I+V2lsbXMsIE0uPC9hdXRob3I+PGF1dGhvcj5LaXJzY2hrZSwgSi4gUy48

L2F1dGhvcj48YXV0aG9yPktyw6RtZXIsIFUuIE0uPC9hdXRob3I+PGF1dGhvcj5Nw7xudGUsIFQu

IEYuPC9hdXRob3I+PGF1dGhvcj5TY2hyYW1tLCBQLjwvYXV0aG9yPjxhdXRob3I+V2llc3QsIFIu

PC9hdXRob3I+PGF1dGhvcj5IYW5kZWxzLCBILjwvYXV0aG9yPjxhdXRob3I+UmV5ZXMsIE0uPC9h

dXRob3I+PC9hdXRob3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5FTkc8L2xhbmd1YWdlPjxh

ZGRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc5MjkzMjE4PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBu

YW1lPSJKb3VybmFsIEFydGljbGUiPjE3PC9yZWYtdHlwZT48cmVjLW51bWJlcj41NTU8L3JlYy1u

dW1iZXI+PGxhc3QtdXBkYXRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc5MjkzMjE4PC9sYXN0LXVw

ZGF0ZWQtZGF0ZT48YWNjZXNzaW9uLW51bT4yNzQ3NTkxMTwvYWNjZXNzaW9uLW51bT48ZWxlY3Ry

b25pYy1yZXNvdXJjZS1udW0+MTAuMTAxNi9qLm1lZGlhLjIwMTYuMDcuMDA5PC9lbGVjdHJvbmlj

LXJlc291cmNlLW51bT48dm9sdW1lPjM1PC92b2x1bWU+PC9yZWNvcmQ+PC9DaXRlPjwvRW5kTm90

ZT4AAAA=

ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5DaGVuPC9BdXRob3I+PFllYXI+MjAxNTwvWWVhcj48SURU

ZXh0PklkZW50aWZpY2F0aW9uIG9mIENlcmVicmFsIFNtYWxsIFZlc3NlbCBEaXNlYXNlIFVzaW5n

IE11bHRpcGxlIEluc3RhbmNlIExlYXJuaW5nPC9JRFRleHQ+PERpc3BsYXlUZXh0PjxzdHlsZSBm

YWNlPSJzdXBlcnNjcmlwdCI+MTcsIDE4PC9zdHlsZT48L0Rpc3BsYXlUZXh0PjxyZWNvcmQ+PGlz

Ym4+MDMwMi05NzQzPC9pc2JuPjx0aXRsZXM+PHRpdGxlPklkZW50aWZpY2F0aW9uIG9mIENlcmVi

cmFsIFNtYWxsIFZlc3NlbCBEaXNlYXNlIFVzaW5nIE11bHRpcGxlIEluc3RhbmNlIExlYXJuaW5n

PC90aXRsZT48c2Vjb25kYXJ5LXRpdGxlPk1lZGljYWwgSW1hZ2UgQ29tcHV0aW5nIGFuZCBDb21w

dXRlci1Bc3Npc3RlZCBJbnRlcnZlbnRpb24gKE1JQ0NBSSAyMDE1KTwvc2Vjb25kYXJ5LXRpdGxl

PjwvdGl0bGVzPjxwYWdlcz41MjMtNTMwPC9wYWdlcz48Y29udHJpYnV0b3JzPjxhdXRob3JzPjxh

dXRob3I+Q2hlbiwgTGlhbmc8L2F1dGhvcj48YXV0aG9yPlRvbmcsIFRvbmc8L2F1dGhvcj48YXV0

aG9yPlBhbmcgSG8sIENoaW48L2F1dGhvcj48YXV0aG9yPlBhdGVsLCBSYWppdjwvYXV0aG9yPjxh

dXRob3I+Q29oZW4sIERhdmlkPC9hdXRob3I+PGF1dGhvcj5EYXdzb24sIEFuZ2VsYSBDPC9hdXRo

b3I+PGF1dGhvcj5IYWxzZSwgT21pZDwvYXV0aG9yPjxhdXRob3I+R2VyYWdodHksIE9saXZpYTwv

YXV0aG9yPjxhdXRob3I+UmlubmUsIFBhdWw8L2F1dGhvcj48YXV0aG9yPldoaXRlLCBDaHJpc3Rv

cGhlcjwvYXV0aG9yPjxhdXRob3I+TmFrb3JuY2hhaSwgVGFnb3JlPC9hdXRob3I+PGF1dGhvcj5C

ZW50bGV5LCBQYXVsPC9hdXRob3I+PGF1dGhvcj5SdWVja2VydCwgRGFuaWVsPC9hdXRob3I+PC9h

dXRob3JzPjwvY29udHJpYnV0b3JzPjxlZGl0aW9uPjE4IE5vdiAyMDE1PC9lZGl0aW9uPjxhZGRl

ZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc4MTgxNzkyPC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1l

PSJKb3VybmFsIEFydGljbGUiPjE3PC9yZWYtdHlwZT48ZGF0ZXM+PHllYXI+MjAxNTwveWVhcj48

L2RhdGVzPjxyZWMtbnVtYmVyPjUzNDwvcmVjLW51bWJlcj48bGFzdC11cGRhdGVkLWRhdGUgZm9y

bWF0PSJ1dGMiPjE0NzgxODIyMzE8L2xhc3QtdXBkYXRlZC1kYXRlPjxlbGVjdHJvbmljLXJlc291

cmNlLW51bT4xMC4xMDA3Lzk3OC0zLTMxOS0yNDU1My05XzY0PC9lbGVjdHJvbmljLXJlc291cmNl

LW51bT48dm9sdW1lPjkzNDk8L3ZvbHVtZT48L3JlY29yZD48L0NpdGU+PENpdGU+PEF1dGhvcj5N

YWllcjwvQXV0aG9yPjxZZWFyPjIwMTc8L1llYXI+PElEVGV4dD5JU0xFUyAyMDE1IC0gQSBwdWJs

aWMgZXZhbHVhdGlvbiBiZW5jaG1hcmsgZm9yIGlzY2hlbWljIHN0cm9rZSBsZXNpb24gc2VnbWVu

dGF0aW9uIGZyb20gbXVsdGlzcGVjdHJhbCBNUkk8L0lEVGV4dD48cmVjb3JkPjxkYXRlcz48cHVi

LWRhdGVzPjxkYXRlPkphbjwvZGF0ZT48L3B1Yi1kYXRlcz48eWVhcj4yMDE3PC95ZWFyPjwvZGF0

ZXM+PHVybHM+PHJlbGF0ZWQtdXJscz48dXJsPmh0dHBzOi8vd3d3Lm5jYmkubmxtLm5paC5nb3Yv

cHVibWVkLzI3NDc1OTExPC91cmw+PC9yZWxhdGVkLXVybHM+PC91cmxzPjxpc2JuPjEzNjEtODQx

NTwvaXNibj48Y3VzdG9tMj5QTUM1MDk5MTE4PC9jdXN0b20yPjx0aXRsZXM+PHRpdGxlPklTTEVT

IDIwMTUgLSBBIHB1YmxpYyBldmFsdWF0aW9uIGJlbmNobWFyayBmb3IgaXNjaGVtaWMgc3Ryb2tl

IGxlc2lvbiBzZWdtZW50YXRpb24gZnJvbSBtdWx0aXNwZWN0cmFsIE1SSTwvdGl0bGU+PHNlY29u

ZGFyeS10aXRsZT5NZWQgSW1hZ2UgQW5hbDwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0bGVzPjxwYWdl

cz4yNTAtMjY5PC9wYWdlcz48Y29udHJpYnV0b3JzPjxhdXRob3JzPjxhdXRob3I+TWFpZXIsIE8u

PC9hdXRob3I+PGF1dGhvcj5NZW56ZSwgQi4gSC48L2F1dGhvcj48YXV0aG9yPnZvbiBkZXIgR2Fi

bGVudHosIEouPC9hdXRob3I+PGF1dGhvcj5Iw6RuaSwgTC48L2F1dGhvcj48YXV0aG9yPkhlaW5y

aWNoLCBNLiBQLjwvYXV0aG9yPjxhdXRob3I+TGllYnJhbmQsIE0uPC9hdXRob3I+PGF1dGhvcj5X

aW56ZWNrLCBTLjwvYXV0aG9yPjxhdXRob3I+QmFzaXQsIEEuPC9hdXRob3I+PGF1dGhvcj5CZW50

bGV5LCBQLjwvYXV0aG9yPjxhdXRob3I+Q2hlbiwgTC48L2F1dGhvcj48YXV0aG9yPkNocmlzdGlh

ZW5zLCBELjwvYXV0aG9yPjxhdXRob3I+RHV0aWwsIEYuPC9hdXRob3I+PGF1dGhvcj5FZ2dlciwg

Sy48L2F1dGhvcj48YXV0aG9yPkZlbmcsIEMuPC9hdXRob3I+PGF1dGhvcj5HbG9ja2VyLCBCLjwv

YXV0aG9yPjxhdXRob3I+R8O2dHosIE0uPC9hdXRob3I+PGF1dGhvcj5IYWVjaywgVC48L2F1dGhv

cj48YXV0aG9yPkhhbG1lLCBILiBMLjwvYXV0aG9yPjxhdXRob3I+SGF2YWVpLCBNLjwvYXV0aG9y

PjxhdXRob3I+SWZ0ZWtoYXJ1ZGRpbiwgSy4gTS48L2F1dGhvcj48YXV0aG9yPkpvZG9pbiwgUC4g

TS48L2F1dGhvcj48YXV0aG9yPkthbW5pdHNhcywgSy48L2F1dGhvcj48YXV0aG9yPktlbGxuZXIs

IEUuPC9hdXRob3I+PGF1dGhvcj5Lb3J2ZW5vamEsIEEuPC9hdXRob3I+PGF1dGhvcj5MYXJvY2hl

bGxlLCBILjwvYXV0aG9yPjxhdXRob3I+TGVkaWcsIEMuPC9hdXRob3I+PGF1dGhvcj5MZWUsIEou

IEguPC9hdXRob3I+PGF1dGhvcj5NYWVzLCBGLjwvYXV0aG9yPjxhdXRob3I+TWFobW9vZCwgUS48

L2F1dGhvcj48YXV0aG9yPk1haWVyLUhlaW4sIEsuIEguPC9hdXRob3I+PGF1dGhvcj5NY0tpbmxl

eSwgUi48L2F1dGhvcj48YXV0aG9yPk11c2NoZWxsaSwgSi48L2F1dGhvcj48YXV0aG9yPlBhbCwg

Qy48L2F1dGhvcj48YXV0aG9yPlBlaSwgTC48L2F1dGhvcj48YXV0aG9yPlJhbmdhcmFqYW4sIEou

IFIuPC9hdXRob3I+PGF1dGhvcj5SZXphLCBTLiBNLjwvYXV0aG9yPjxhdXRob3I+Um9iYmVuLCBE

LjwvYXV0aG9yPjxhdXRob3I+UnVlY2tlcnQsIEQuPC9hdXRob3I+PGF1dGhvcj5TYWxsaSwgRS48

L2F1dGhvcj48YXV0aG9yPlN1ZXRlbnMsIFAuPC9hdXRob3I+PGF1dGhvcj5XYW5nLCBDLiBXLjwv

YXV0aG9yPjxhdXRob3I+V2lsbXMsIE0uPC9hdXRob3I+PGF1dGhvcj5LaXJzY2hrZSwgSi4gUy48

L2F1dGhvcj48YXV0aG9yPktyw6RtZXIsIFUuIE0uPC9hdXRob3I+PGF1dGhvcj5Nw7xudGUsIFQu

IEYuPC9hdXRob3I+PGF1dGhvcj5TY2hyYW1tLCBQLjwvYXV0aG9yPjxhdXRob3I+V2llc3QsIFIu

PC9hdXRob3I+PGF1dGhvcj5IYW5kZWxzLCBILjwvYXV0aG9yPjxhdXRob3I+UmV5ZXMsIE0uPC9h

dXRob3I+PC9hdXRob3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5FTkc8L2xhbmd1YWdlPjxh

ZGRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc5MjkzMjE4PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBu

YW1lPSJKb3VybmFsIEFydGljbGUiPjE3PC9yZWYtdHlwZT48cmVjLW51bWJlcj41NTU8L3JlYy1u

dW1iZXI+PGxhc3QtdXBkYXRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc5MjkzMjE4PC9sYXN0LXVw

ZGF0ZWQtZGF0ZT48YWNjZXNzaW9uLW51bT4yNzQ3NTkxMTwvYWNjZXNzaW9uLW51bT48ZWxlY3Ry

b25pYy1yZXNvdXJjZS1udW0+MTAuMTAxNi9qLm1lZGlhLjIwMTYuMDcuMDA5PC9lbGVjdHJvbmlj

LXJlc291cmNlLW51bT48dm9sdW1lPjM1PC92b2x1bWU+PC9yZWNvcmQ+PC9DaXRlPjwvRW5kTm90

ZT4AAAA=

ADDIN EN.CITE.DATA 17, 18. In the current study, we validate the method more comprehensively, comparing the automated output with expert delineations on CT and MRI (i.e. gold-standard), and ratings in ~1000 stroke patients, using images originating from a wide range of scanner types, thus reflecting typical populations that the technique is likely to be used in. MethodsStudy populationsSince one of the primary potential applications for automated WML estimation is prognostication of acute ischemic stroke, the study focused on this patient population. The test cohorts comprised (Fig. 1A): 1) all acute ischemic stroke patients presenting to Imperial College (IC) Hyperacute Stroke Unit between 2010-14 who subsequently received thrombolysis treatment (IC-thrombolysed, cohort; n=627); 2) all acute ischemic stroke patients from IC from the same time-period who underwent both CT and MRI within 1 week of each other (IC CT-MRI cohort; n=255; mean scan interval: 2 days; excludes IC-thrombolysed subjects); 3) a random sample of patients recruited to the Third International Stroke TrialPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5TYW5kZXJjb2NrPC9BdXRob3I+PFllYXI+MjAxMjwvWWVh

cj48SURUZXh0PlRoZSBiZW5lZml0cyBhbmQgaGFybXMgb2YgaW50cmF2ZW5vdXMgdGhyb21ib2x5

c2lzIHdpdGggcmVjb21iaW5hbnQgdGlzc3VlIHBsYXNtaW5vZ2VuIGFjdGl2YXRvciB3aXRoaW4g

NiBoIG9mIGFjdXRlIGlzY2hhZW1pYyBzdHJva2UgKHRoZSB0aGlyZCBpbnRlcm5hdGlvbmFsIHN0

cm9rZSB0cmlhbCBbSVNULTNdKTogYSByYW5kb21pc2VkIGNvbnRyb2xsZWQgdHJpYWw8L0lEVGV4

dD48RGlzcGxheVRleHQ+PHN0eWxlIGZhY2U9InN1cGVyc2NyaXB0Ij4xOTwvc3R5bGU+PC9EaXNw

bGF5VGV4dD48cmVjb3JkPjxkYXRlcz48cHViLWRhdGVzPjxkYXRlPkp1bjwvZGF0ZT48L3B1Yi1k

YXRlcz48eWVhcj4yMDEyPC95ZWFyPjwvZGF0ZXM+PGtleXdvcmRzPjxrZXl3b3JkPkFkb2xlc2Nl

bnQ8L2tleXdvcmQ+PGtleXdvcmQ+QWR1bHQ8L2tleXdvcmQ+PGtleXdvcmQ+QWdlIERpc3RyaWJ1

dGlvbjwva2V5d29yZD48a2V5d29yZD5BZ2VkPC9rZXl3b3JkPjxrZXl3b3JkPkFnZWQsIDgwIGFu

ZCBvdmVyPC9rZXl3b3JkPjxrZXl3b3JkPkJyYWluIElzY2hlbWlhPC9rZXl3b3JkPjxrZXl3b3Jk

PkRvdWJsZS1CbGluZCBNZXRob2Q8L2tleXdvcmQ+PGtleXdvcmQ+RHJ1ZyBBZG1pbmlzdHJhdGlv

biBTY2hlZHVsZTwva2V5d29yZD48a2V5d29yZD5GZW1hbGU8L2tleXdvcmQ+PGtleXdvcmQ+Rmli

cmlub2x5dGljIEFnZW50czwva2V5d29yZD48a2V5d29yZD5IdW1hbnM8L2tleXdvcmQ+PGtleXdv

cmQ+SW5mdXNpb25zLCBJbnRyYXZlbm91czwva2V5d29yZD48a2V5d29yZD5NYWxlPC9rZXl3b3Jk

PjxrZXl3b3JkPk1pZGRsZSBBZ2VkPC9rZXl3b3JkPjxrZXl3b3JkPlJlY29tYmluYW50IFByb3Rl

aW5zPC9rZXl3b3JkPjxrZXl3b3JkPlJlY3VycmVuY2U8L2tleXdvcmQ+PGtleXdvcmQ+U2V2ZXJp

dHkgb2YgSWxsbmVzcyBJbmRleDwva2V5d29yZD48a2V5d29yZD5TdHJva2U8L2tleXdvcmQ+PGtl

eXdvcmQ+VGhyb21ib2x5dGljIFRoZXJhcHk8L2tleXdvcmQ+PGtleXdvcmQ+VGlzc3VlIFBsYXNt

aW5vZ2VuIEFjdGl2YXRvcjwva2V5d29yZD48a2V5d29yZD5UcmVhdG1lbnQgT3V0Y29tZTwva2V5

d29yZD48a2V5d29yZD5Zb3VuZyBBZHVsdDwva2V5d29yZD48L2tleXdvcmRzPjx1cmxzPjxyZWxh

dGVkLXVybHM+PHVybD5odHRwOi8vd3d3Lm5jYmkubmxtLm5paC5nb3YvcHVibWVkLzIyNjMyOTA4

PC91cmw+PC9yZWxhdGVkLXVybHM+PC91cmxzPjxpc2JuPjE0NzQtNTQ3WDwvaXNibj48Y3VzdG9t

Mj5QTUMzMzg2NDk1PC9jdXN0b20yPjx0aXRsZXM+PHRpdGxlPlRoZSBiZW5lZml0cyBhbmQgaGFy

bXMgb2YgaW50cmF2ZW5vdXMgdGhyb21ib2x5c2lzIHdpdGggcmVjb21iaW5hbnQgdGlzc3VlIHBs

YXNtaW5vZ2VuIGFjdGl2YXRvciB3aXRoaW4gNiBoIG9mIGFjdXRlIGlzY2hhZW1pYyBzdHJva2Ug

KHRoZSB0aGlyZCBpbnRlcm5hdGlvbmFsIHN0cm9rZSB0cmlhbCBbSVNULTNdKTogYSByYW5kb21p

c2VkIGNvbnRyb2xsZWQgdHJpYWw8L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+TGFuY2V0PC9zZWNv

bmRhcnktdGl0bGU+PC90aXRsZXM+PHBhZ2VzPjIzNTItNjM8L3BhZ2VzPjxudW1iZXI+OTgzNDwv

bnVtYmVyPjxjb250cmlidXRvcnM+PGF1dGhvcnM+PGF1dGhvcj5TYW5kZXJjb2NrLCBQLjwvYXV0

aG9yPjxhdXRob3I+V2FyZGxhdywgSi4gTS48L2F1dGhvcj48YXV0aG9yPkxpbmRsZXksIFIuIEku

PC9hdXRob3I+PGF1dGhvcj5EZW5uaXMsIE0uPC9hdXRob3I+PGF1dGhvcj5Db2hlbiwgRy48L2F1

dGhvcj48YXV0aG9yPk11cnJheSwgRy48L2F1dGhvcj48YXV0aG9yPklubmVzLCBLLjwvYXV0aG9y

PjxhdXRob3I+VmVuYWJsZXMsIEcuPC9hdXRob3I+PGF1dGhvcj5Demxvbmtvd3NrYSwgQS48L2F1

dGhvcj48YXV0aG9yPktvYmF5YXNoaSwgQS48L2F1dGhvcj48YXV0aG9yPlJpY2NpLCBTLjwvYXV0

aG9yPjxhdXRob3I+TXVycmF5LCBWLjwvYXV0aG9yPjxhdXRob3I+QmVyZ2UsIEUuPC9hdXRob3I+

PGF1dGhvcj5TbG90LCBLLiBCLjwvYXV0aG9yPjxhdXRob3I+SGFua2V5LCBHLiBKLjwvYXV0aG9y

PjxhdXRob3I+Q29ycmVpYSwgTS48L2F1dGhvcj48YXV0aG9yPlBlZXRlcnMsIEEuPC9hdXRob3I+

PGF1dGhvcj5NYXR6LCBLLjwvYXV0aG9yPjxhdXRob3I+THlyZXIsIFAuPC9hdXRob3I+PGF1dGhv

cj5HdWJpdHosIEcuPC9hdXRob3I+PGF1dGhvcj5QaGlsbGlwcywgUy4gSi48L2F1dGhvcj48YXV0

aG9yPkFyYXV6LCBBLjwvYXV0aG9yPjxhdXRob3I+SVNULTMgY29sbGFib3JhdGl2ZSBncm91cDwv

YXV0aG9yPjwvYXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3VhZ2U+ZW5nPC9sYW5ndWFnZT48

YWRkZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTM4NzU0NzU0MjwvYWRkZWQtZGF0ZT48cmVmLXR5cGUg

bmFtZT0iSm91cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PHJlYy1udW1iZXI+MzQ5PC9yZWMt

bnVtYmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTM4NzU0NzU0MjwvbGFzdC11

cGRhdGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MjI2MzI5MDg8L2FjY2Vzc2lvbi1udW0+PGVsZWN0

cm9uaWMtcmVzb3VyY2UtbnVtPjEwLjEwMTYvUzAxNDAtNjczNigxMik2MDc2OC01PC9lbGVjdHJv

bmljLXJlc291cmNlLW51bT48dm9sdW1lPjM3OTwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48L0Vu

ZE5vdGU+AAA=

ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5TYW5kZXJjb2NrPC9BdXRob3I+PFllYXI+MjAxMjwvWWVh

cj48SURUZXh0PlRoZSBiZW5lZml0cyBhbmQgaGFybXMgb2YgaW50cmF2ZW5vdXMgdGhyb21ib2x5

c2lzIHdpdGggcmVjb21iaW5hbnQgdGlzc3VlIHBsYXNtaW5vZ2VuIGFjdGl2YXRvciB3aXRoaW4g

NiBoIG9mIGFjdXRlIGlzY2hhZW1pYyBzdHJva2UgKHRoZSB0aGlyZCBpbnRlcm5hdGlvbmFsIHN0

cm9rZSB0cmlhbCBbSVNULTNdKTogYSByYW5kb21pc2VkIGNvbnRyb2xsZWQgdHJpYWw8L0lEVGV4

dD48RGlzcGxheVRleHQ+PHN0eWxlIGZhY2U9InN1cGVyc2NyaXB0Ij4xOTwvc3R5bGU+PC9EaXNw

bGF5VGV4dD48cmVjb3JkPjxkYXRlcz48cHViLWRhdGVzPjxkYXRlPkp1bjwvZGF0ZT48L3B1Yi1k

YXRlcz48eWVhcj4yMDEyPC95ZWFyPjwvZGF0ZXM+PGtleXdvcmRzPjxrZXl3b3JkPkFkb2xlc2Nl

bnQ8L2tleXdvcmQ+PGtleXdvcmQ+QWR1bHQ8L2tleXdvcmQ+PGtleXdvcmQ+QWdlIERpc3RyaWJ1

dGlvbjwva2V5d29yZD48a2V5d29yZD5BZ2VkPC9rZXl3b3JkPjxrZXl3b3JkPkFnZWQsIDgwIGFu

ZCBvdmVyPC9rZXl3b3JkPjxrZXl3b3JkPkJyYWluIElzY2hlbWlhPC9rZXl3b3JkPjxrZXl3b3Jk

PkRvdWJsZS1CbGluZCBNZXRob2Q8L2tleXdvcmQ+PGtleXdvcmQ+RHJ1ZyBBZG1pbmlzdHJhdGlv

biBTY2hlZHVsZTwva2V5d29yZD48a2V5d29yZD5GZW1hbGU8L2tleXdvcmQ+PGtleXdvcmQ+Rmli

cmlub2x5dGljIEFnZW50czwva2V5d29yZD48a2V5d29yZD5IdW1hbnM8L2tleXdvcmQ+PGtleXdv

cmQ+SW5mdXNpb25zLCBJbnRyYXZlbm91czwva2V5d29yZD48a2V5d29yZD5NYWxlPC9rZXl3b3Jk

PjxrZXl3b3JkPk1pZGRsZSBBZ2VkPC9rZXl3b3JkPjxrZXl3b3JkPlJlY29tYmluYW50IFByb3Rl

aW5zPC9rZXl3b3JkPjxrZXl3b3JkPlJlY3VycmVuY2U8L2tleXdvcmQ+PGtleXdvcmQ+U2V2ZXJp

dHkgb2YgSWxsbmVzcyBJbmRleDwva2V5d29yZD48a2V5d29yZD5TdHJva2U8L2tleXdvcmQ+PGtl

eXdvcmQ+VGhyb21ib2x5dGljIFRoZXJhcHk8L2tleXdvcmQ+PGtleXdvcmQ+VGlzc3VlIFBsYXNt

aW5vZ2VuIEFjdGl2YXRvcjwva2V5d29yZD48a2V5d29yZD5UcmVhdG1lbnQgT3V0Y29tZTwva2V5

d29yZD48a2V5d29yZD5Zb3VuZyBBZHVsdDwva2V5d29yZD48L2tleXdvcmRzPjx1cmxzPjxyZWxh

dGVkLXVybHM+PHVybD5odHRwOi8vd3d3Lm5jYmkubmxtLm5paC5nb3YvcHVibWVkLzIyNjMyOTA4

PC91cmw+PC9yZWxhdGVkLXVybHM+PC91cmxzPjxpc2JuPjE0NzQtNTQ3WDwvaXNibj48Y3VzdG9t

Mj5QTUMzMzg2NDk1PC9jdXN0b20yPjx0aXRsZXM+PHRpdGxlPlRoZSBiZW5lZml0cyBhbmQgaGFy

bXMgb2YgaW50cmF2ZW5vdXMgdGhyb21ib2x5c2lzIHdpdGggcmVjb21iaW5hbnQgdGlzc3VlIHBs

YXNtaW5vZ2VuIGFjdGl2YXRvciB3aXRoaW4gNiBoIG9mIGFjdXRlIGlzY2hhZW1pYyBzdHJva2Ug

KHRoZSB0aGlyZCBpbnRlcm5hdGlvbmFsIHN0cm9rZSB0cmlhbCBbSVNULTNdKTogYSByYW5kb21p

c2VkIGNvbnRyb2xsZWQgdHJpYWw8L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+TGFuY2V0PC9zZWNv

bmRhcnktdGl0bGU+PC90aXRsZXM+PHBhZ2VzPjIzNTItNjM8L3BhZ2VzPjxudW1iZXI+OTgzNDwv

bnVtYmVyPjxjb250cmlidXRvcnM+PGF1dGhvcnM+PGF1dGhvcj5TYW5kZXJjb2NrLCBQLjwvYXV0

aG9yPjxhdXRob3I+V2FyZGxhdywgSi4gTS48L2F1dGhvcj48YXV0aG9yPkxpbmRsZXksIFIuIEku

PC9hdXRob3I+PGF1dGhvcj5EZW5uaXMsIE0uPC9hdXRob3I+PGF1dGhvcj5Db2hlbiwgRy48L2F1

dGhvcj48YXV0aG9yPk11cnJheSwgRy48L2F1dGhvcj48YXV0aG9yPklubmVzLCBLLjwvYXV0aG9y

PjxhdXRob3I+VmVuYWJsZXMsIEcuPC9hdXRob3I+PGF1dGhvcj5Demxvbmtvd3NrYSwgQS48L2F1

dGhvcj48YXV0aG9yPktvYmF5YXNoaSwgQS48L2F1dGhvcj48YXV0aG9yPlJpY2NpLCBTLjwvYXV0

aG9yPjxhdXRob3I+TXVycmF5LCBWLjwvYXV0aG9yPjxhdXRob3I+QmVyZ2UsIEUuPC9hdXRob3I+

PGF1dGhvcj5TbG90LCBLLiBCLjwvYXV0aG9yPjxhdXRob3I+SGFua2V5LCBHLiBKLjwvYXV0aG9y

PjxhdXRob3I+Q29ycmVpYSwgTS48L2F1dGhvcj48YXV0aG9yPlBlZXRlcnMsIEEuPC9hdXRob3I+

PGF1dGhvcj5NYXR6LCBLLjwvYXV0aG9yPjxhdXRob3I+THlyZXIsIFAuPC9hdXRob3I+PGF1dGhv

cj5HdWJpdHosIEcuPC9hdXRob3I+PGF1dGhvcj5QaGlsbGlwcywgUy4gSi48L2F1dGhvcj48YXV0

aG9yPkFyYXV6LCBBLjwvYXV0aG9yPjxhdXRob3I+SVNULTMgY29sbGFib3JhdGl2ZSBncm91cDwv

YXV0aG9yPjwvYXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3VhZ2U+ZW5nPC9sYW5ndWFnZT48

YWRkZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTM4NzU0NzU0MjwvYWRkZWQtZGF0ZT48cmVmLXR5cGUg

bmFtZT0iSm91cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PHJlYy1udW1iZXI+MzQ5PC9yZWMt

bnVtYmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTM4NzU0NzU0MjwvbGFzdC11

cGRhdGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MjI2MzI5MDg8L2FjY2Vzc2lvbi1udW0+PGVsZWN0

cm9uaWMtcmVzb3VyY2UtbnVtPjEwLjEwMTYvUzAxNDAtNjczNigxMik2MDc2OC01PC9lbGVjdHJv

bmljLXJlc291cmNlLW51bT48dm9sdW1lPjM3OTwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48L0Vu

ZE5vdGU+AAA=

ADDIN EN.CITE.DATA 19 (IST-3 cohort n=200; median age: 82), from which patients with obvious extensive acute ischemic changes were first excluded (this subset therefore being more typical of patients who might also present to a cognitive impairment clinic). Validation of the automated WML quantification method was assessed by comparison with experts’: 1) drawings of WML outlines on CTs and co-registered FLAIR-MRIs (the latter considered to be a ground-truth), and 2) ratings using two conventional ordinal qualitative WML scoring systemsPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XYWhsdW5kPC9BdXRob3I+PFllYXI+MjAwMTwvWWVhcj48

SURUZXh0PkEgbmV3IHJhdGluZyBzY2FsZSBmb3IgYWdlLXJlbGF0ZWQgd2hpdGUgbWF0dGVyIGNo

YW5nZXMgYXBwbGljYWJsZSB0byBNUkkgYW5kIENULjwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5

bGUgZmFjZT0ic3VwZXJzY3JpcHQiPjEyLCAxNTwvc3R5bGU+PC9EaXNwbGF5VGV4dD48cmVjb3Jk

PjxkYXRlcz48cHViLWRhdGVzPjxkYXRlPkp1bjwvZGF0ZT48L3B1Yi1kYXRlcz48eWVhcj4yMDAx

PC95ZWFyPjwvZGF0ZXM+PGtleXdvcmRzPjxrZXl3b3JkPkFnaW5nPC9rZXl3b3JkPjxrZXl3b3Jk

PkJyYWluPC9rZXl3b3JkPjxrZXl3b3JkPkJyYWluIERpc2Vhc2VzPC9rZXl3b3JkPjxrZXl3b3Jk

PkNvZ25pdGlvbiBEaXNvcmRlcnM8L2tleXdvcmQ+PGtleXdvcmQ+RXVyb3BlPC9rZXl3b3JkPjxr

ZXl3b3JkPkh1bWFuczwva2V5d29yZD48a2V5d29yZD5NYWduZXRpYyBSZXNvbmFuY2UgSW1hZ2lu

Zzwva2V5d29yZD48a2V5d29yZD5NZW1vcnkgRGlzb3JkZXJzPC9rZXl3b3JkPjxrZXl3b3JkPk15

ZWxpbiBTaGVhdGg8L2tleXdvcmQ+PGtleXdvcmQ+T2JzZXJ2ZXIgVmFyaWF0aW9uPC9rZXl3b3Jk

PjxrZXl3b3JkPlByZWRpY3RpdmUgVmFsdWUgb2YgVGVzdHM8L2tleXdvcmQ+PGtleXdvcmQ+UmVw

cm9kdWNpYmlsaXR5IG9mIFJlc3VsdHM8L2tleXdvcmQ+PGtleXdvcmQ+U2Vuc2l0aXZpdHkgYW5k

IFNwZWNpZmljaXR5PC9rZXl3b3JkPjxrZXl3b3JkPlRvbW9ncmFwaHksIFgtUmF5IENvbXB1dGVk

PC9rZXl3b3JkPjwva2V5d29yZHM+PHVybHM+PHJlbGF0ZWQtdXJscz48dXJsPmh0dHA6Ly93d3cu

bmNiaS5ubG0ubmloLmdvdi9wdWJtZWQvMTEzODc0OTM8L3VybD48L3JlbGF0ZWQtdXJscz48L3Vy

bHM+PGlzYm4+MTUyNC00NjI4PC9pc2JuPjx0aXRsZXM+PHRpdGxlPkEgbmV3IHJhdGluZyBzY2Fs

ZSBmb3IgYWdlLXJlbGF0ZWQgd2hpdGUgbWF0dGVyIGNoYW5nZXMgYXBwbGljYWJsZSB0byBNUkkg

YW5kIENULjwvdGl0bGU+PHNlY29uZGFyeS10aXRsZT5TdHJva2U8L3NlY29uZGFyeS10aXRsZT48

L3RpdGxlcz48cGFnZXM+MTMxOC0yMjwvcGFnZXM+PG51bWJlcj42PC9udW1iZXI+PGNvbnRyaWJ1

dG9ycz48YXV0aG9ycz48YXV0aG9yPldhaGx1bmQsIEwuIE8uPC9hdXRob3I+PGF1dGhvcj5CYXJr

aG9mLCBGLjwvYXV0aG9yPjxhdXRob3I+RmF6ZWthcywgRi48L2F1dGhvcj48YXV0aG9yPkJyb25n

ZSwgTC48L2F1dGhvcj48YXV0aG9yPkF1Z3VzdGluLCBNLjwvYXV0aG9yPjxhdXRob3I+U2rDtmdy

ZW4sIE0uPC9hdXRob3I+PGF1dGhvcj5XYWxsaW4sIEEuPC9hdXRob3I+PGF1dGhvcj5BZGVyLCBI

LjwvYXV0aG9yPjxhdXRob3I+TGV5cywgRC48L2F1dGhvcj48YXV0aG9yPlBhbnRvbmksIEwuPC9h

dXRob3I+PGF1dGhvcj5QYXNxdWllciwgRi48L2F1dGhvcj48YXV0aG9yPkVya2luanVudHRpLCBU

LjwvYXV0aG9yPjxhdXRob3I+U2NoZWx0ZW5zLCBQLjwvYXV0aG9yPjxhdXRob3I+RXVyb3BlYW4g

VGFzayBGb3JjZSBvbiBBZ2UtUmVsYXRlZCBXaGl0ZSBNYXR0ZXIgQ2hhbmdlczwvYXV0aG9yPjwv

YXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3VhZ2U+ZW5nPC9sYW5ndWFnZT48YWRkZWQtZGF0

ZSBmb3JtYXQ9InV0YyI+MTMzNDkzNzY2NjwvYWRkZWQtZGF0ZT48cmVmLXR5cGUgbmFtZT0iSm91

cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PGF1dGgtYWRkcmVzcz5EZXBhcnRtZW50IG9mIENs

aW5pY2FsIE5ldXJvc2NpZW5jZSwgTkVVUk9URUMsIEthcm9saW5za2EgSW5zdGl0dXRldCBhdCBI

dWRkaW5nZSBVbml2ZXJzaXR5IEhvc3BpdGFsLCBIdWRkaW5nZSwgU3dlZGVuLiBsYXJzLW9sb2Yu

d2FobHVuZEBuZXVyb3RlYy5raS5zZTwvYXV0aC1hZGRyZXNzPjxyZWMtbnVtYmVyPjEzMzwvcmVj

LW51bWJlcj48bGFzdC11cGRhdGVkLWRhdGUgZm9ybWF0PSJ1dGMiPjEzMzQ5Mzc2NjY8L2xhc3Qt

dXBkYXRlZC1kYXRlPjxhY2Nlc3Npb24tbnVtPjExMzg3NDkzPC9hY2Nlc3Npb24tbnVtPjx2b2x1

bWU+MzI8L3ZvbHVtZT48L3JlY29yZD48L0NpdGU+PENpdGU+PEF1dGhvcj52YW4gU3dpZXRlbjwv

QXV0aG9yPjxZZWFyPjE5OTA8L1llYXI+PElEVGV4dD5HcmFkaW5nIHdoaXRlIG1hdHRlciBsZXNp

b25zIG9uIENUIGFuZCBNUkk6IGEgc2ltcGxlIHNjYWxlPC9JRFRleHQ+PHJlY29yZD48ZGF0ZXM+

PHB1Yi1kYXRlcz48ZGF0ZT5EZWM8L2RhdGU+PC9wdWItZGF0ZXM+PHllYXI+MTk5MDwveWVhcj48

L2RhdGVzPjxrZXl3b3Jkcz48a2V5d29yZD5CcmFpbjwva2V5d29yZD48a2V5d29yZD5CcmFpbiBE

aXNlYXNlczwva2V5d29yZD48a2V5d29yZD5Dcm9zcy1TZWN0aW9uYWwgU3R1ZGllczwva2V5d29y

ZD48a2V5d29yZD5EYXRhIEludGVycHJldGF0aW9uLCBTdGF0aXN0aWNhbDwva2V5d29yZD48a2V5

d29yZD5IdW1hbnM8L2tleXdvcmQ+PGtleXdvcmQ+SXNjaGVtaWMgQXR0YWNrLCBUcmFuc2llbnQ8

L2tleXdvcmQ+PGtleXdvcmQ+TG9uZ2l0dWRpbmFsIFN0dWRpZXM8L2tleXdvcmQ+PGtleXdvcmQ+

TWFnbmV0aWMgUmVzb25hbmNlIEltYWdpbmc8L2tleXdvcmQ+PGtleXdvcmQ+VG9tb2dyYXBoeSwg

WC1SYXkgQ29tcHV0ZWQ8L2tleXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1

cmw+aHR0cHM6Ly93d3cubmNiaS5ubG0ubmloLmdvdi9wdWJtZWQvMjI5MjcwMzwvdXJsPjwvcmVs

YXRlZC11cmxzPjwvdXJscz48aXNibj4wMDIyLTMwNTA8L2lzYm4+PGN1c3RvbTI+UE1DNDg4MzIw

PC9jdXN0b20yPjx0aXRsZXM+PHRpdGxlPkdyYWRpbmcgd2hpdGUgbWF0dGVyIGxlc2lvbnMgb24g

Q1QgYW5kIE1SSTogYSBzaW1wbGUgc2NhbGU8L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+SiBOZXVy

b2wgTmV1cm9zdXJnIFBzeWNoaWF0cnk8L3NlY29uZGFyeS10aXRsZT48L3RpdGxlcz48cGFnZXM+

MTA4MC0zPC9wYWdlcz48bnVtYmVyPjEyPC9udW1iZXI+PGNvbnRyaWJ1dG9ycz48YXV0aG9ycz48

YXV0aG9yPnZhbiBTd2lldGVuLCBKLiBDLjwvYXV0aG9yPjxhdXRob3I+SGlqZHJhLCBBLjwvYXV0

aG9yPjxhdXRob3I+S291ZHN0YWFsLCBQLiBKLjwvYXV0aG9yPjxhdXRob3I+dmFuIEdpam4sIEou

PC9hdXRob3I+PC9hdXRob3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5FTkc8L2xhbmd1YWdl

PjxhZGRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc4MTc3NjAwPC9hZGRlZC1kYXRlPjxyZWYtdHlw

ZSBuYW1lPSJKb3VybmFsIEFydGljbGUiPjE3PC9yZWYtdHlwZT48cmVjLW51bWJlcj41MzE8L3Jl

Yy1udW1iZXI+PGxhc3QtdXBkYXRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc4MTc3NjAwPC9sYXN0

LXVwZGF0ZWQtZGF0ZT48YWNjZXNzaW9uLW51bT4yMjkyNzAzPC9hY2Nlc3Npb24tbnVtPjx2b2x1

bWU+NTM8L3ZvbHVtZT48L3JlY29yZD48L0NpdGU+PC9FbmROb3RlPgAA

ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XYWhsdW5kPC9BdXRob3I+PFllYXI+MjAwMTwvWWVhcj48

SURUZXh0PkEgbmV3IHJhdGluZyBzY2FsZSBmb3IgYWdlLXJlbGF0ZWQgd2hpdGUgbWF0dGVyIGNo

YW5nZXMgYXBwbGljYWJsZSB0byBNUkkgYW5kIENULjwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5

bGUgZmFjZT0ic3VwZXJzY3JpcHQiPjEyLCAxNTwvc3R5bGU+PC9EaXNwbGF5VGV4dD48cmVjb3Jk

PjxkYXRlcz48cHViLWRhdGVzPjxkYXRlPkp1bjwvZGF0ZT48L3B1Yi1kYXRlcz48eWVhcj4yMDAx

PC95ZWFyPjwvZGF0ZXM+PGtleXdvcmRzPjxrZXl3b3JkPkFnaW5nPC9rZXl3b3JkPjxrZXl3b3Jk

PkJyYWluPC9rZXl3b3JkPjxrZXl3b3JkPkJyYWluIERpc2Vhc2VzPC9rZXl3b3JkPjxrZXl3b3Jk

PkNvZ25pdGlvbiBEaXNvcmRlcnM8L2tleXdvcmQ+PGtleXdvcmQ+RXVyb3BlPC9rZXl3b3JkPjxr

ZXl3b3JkPkh1bWFuczwva2V5d29yZD48a2V5d29yZD5NYWduZXRpYyBSZXNvbmFuY2UgSW1hZ2lu

Zzwva2V5d29yZD48a2V5d29yZD5NZW1vcnkgRGlzb3JkZXJzPC9rZXl3b3JkPjxrZXl3b3JkPk15

ZWxpbiBTaGVhdGg8L2tleXdvcmQ+PGtleXdvcmQ+T2JzZXJ2ZXIgVmFyaWF0aW9uPC9rZXl3b3Jk

PjxrZXl3b3JkPlByZWRpY3RpdmUgVmFsdWUgb2YgVGVzdHM8L2tleXdvcmQ+PGtleXdvcmQ+UmVw

cm9kdWNpYmlsaXR5IG9mIFJlc3VsdHM8L2tleXdvcmQ+PGtleXdvcmQ+U2Vuc2l0aXZpdHkgYW5k

IFNwZWNpZmljaXR5PC9rZXl3b3JkPjxrZXl3b3JkPlRvbW9ncmFwaHksIFgtUmF5IENvbXB1dGVk

PC9rZXl3b3JkPjwva2V5d29yZHM+PHVybHM+PHJlbGF0ZWQtdXJscz48dXJsPmh0dHA6Ly93d3cu

bmNiaS5ubG0ubmloLmdvdi9wdWJtZWQvMTEzODc0OTM8L3VybD48L3JlbGF0ZWQtdXJscz48L3Vy

bHM+PGlzYm4+MTUyNC00NjI4PC9pc2JuPjx0aXRsZXM+PHRpdGxlPkEgbmV3IHJhdGluZyBzY2Fs

ZSBmb3IgYWdlLXJlbGF0ZWQgd2hpdGUgbWF0dGVyIGNoYW5nZXMgYXBwbGljYWJsZSB0byBNUkkg

YW5kIENULjwvdGl0bGU+PHNlY29uZGFyeS10aXRsZT5TdHJva2U8L3NlY29uZGFyeS10aXRsZT48

L3RpdGxlcz48cGFnZXM+MTMxOC0yMjwvcGFnZXM+PG51bWJlcj42PC9udW1iZXI+PGNvbnRyaWJ1

dG9ycz48YXV0aG9ycz48YXV0aG9yPldhaGx1bmQsIEwuIE8uPC9hdXRob3I+PGF1dGhvcj5CYXJr

aG9mLCBGLjwvYXV0aG9yPjxhdXRob3I+RmF6ZWthcywgRi48L2F1dGhvcj48YXV0aG9yPkJyb25n

ZSwgTC48L2F1dGhvcj48YXV0aG9yPkF1Z3VzdGluLCBNLjwvYXV0aG9yPjxhdXRob3I+U2rDtmdy

ZW4sIE0uPC9hdXRob3I+PGF1dGhvcj5XYWxsaW4sIEEuPC9hdXRob3I+PGF1dGhvcj5BZGVyLCBI

LjwvYXV0aG9yPjxhdXRob3I+TGV5cywgRC48L2F1dGhvcj48YXV0aG9yPlBhbnRvbmksIEwuPC9h

dXRob3I+PGF1dGhvcj5QYXNxdWllciwgRi48L2F1dGhvcj48YXV0aG9yPkVya2luanVudHRpLCBU

LjwvYXV0aG9yPjxhdXRob3I+U2NoZWx0ZW5zLCBQLjwvYXV0aG9yPjxhdXRob3I+RXVyb3BlYW4g

VGFzayBGb3JjZSBvbiBBZ2UtUmVsYXRlZCBXaGl0ZSBNYXR0ZXIgQ2hhbmdlczwvYXV0aG9yPjwv

YXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3VhZ2U+ZW5nPC9sYW5ndWFnZT48YWRkZWQtZGF0

ZSBmb3JtYXQ9InV0YyI+MTMzNDkzNzY2NjwvYWRkZWQtZGF0ZT48cmVmLXR5cGUgbmFtZT0iSm91

cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PGF1dGgtYWRkcmVzcz5EZXBhcnRtZW50IG9mIENs

aW5pY2FsIE5ldXJvc2NpZW5jZSwgTkVVUk9URUMsIEthcm9saW5za2EgSW5zdGl0dXRldCBhdCBI

dWRkaW5nZSBVbml2ZXJzaXR5IEhvc3BpdGFsLCBIdWRkaW5nZSwgU3dlZGVuLiBsYXJzLW9sb2Yu

d2FobHVuZEBuZXVyb3RlYy5raS5zZTwvYXV0aC1hZGRyZXNzPjxyZWMtbnVtYmVyPjEzMzwvcmVj

LW51bWJlcj48bGFzdC11cGRhdGVkLWRhdGUgZm9ybWF0PSJ1dGMiPjEzMzQ5Mzc2NjY8L2xhc3Qt

dXBkYXRlZC1kYXRlPjxhY2Nlc3Npb24tbnVtPjExMzg3NDkzPC9hY2Nlc3Npb24tbnVtPjx2b2x1

bWU+MzI8L3ZvbHVtZT48L3JlY29yZD48L0NpdGU+PENpdGU+PEF1dGhvcj52YW4gU3dpZXRlbjwv

QXV0aG9yPjxZZWFyPjE5OTA8L1llYXI+PElEVGV4dD5HcmFkaW5nIHdoaXRlIG1hdHRlciBsZXNp

b25zIG9uIENUIGFuZCBNUkk6IGEgc2ltcGxlIHNjYWxlPC9JRFRleHQ+PHJlY29yZD48ZGF0ZXM+

PHB1Yi1kYXRlcz48ZGF0ZT5EZWM8L2RhdGU+PC9wdWItZGF0ZXM+PHllYXI+MTk5MDwveWVhcj48

L2RhdGVzPjxrZXl3b3Jkcz48a2V5d29yZD5CcmFpbjwva2V5d29yZD48a2V5d29yZD5CcmFpbiBE

aXNlYXNlczwva2V5d29yZD48a2V5d29yZD5Dcm9zcy1TZWN0aW9uYWwgU3R1ZGllczwva2V5d29y

ZD48a2V5d29yZD5EYXRhIEludGVycHJldGF0aW9uLCBTdGF0aXN0aWNhbDwva2V5d29yZD48a2V5

d29yZD5IdW1hbnM8L2tleXdvcmQ+PGtleXdvcmQ+SXNjaGVtaWMgQXR0YWNrLCBUcmFuc2llbnQ8

L2tleXdvcmQ+PGtleXdvcmQ+TG9uZ2l0dWRpbmFsIFN0dWRpZXM8L2tleXdvcmQ+PGtleXdvcmQ+

TWFnbmV0aWMgUmVzb25hbmNlIEltYWdpbmc8L2tleXdvcmQ+PGtleXdvcmQ+VG9tb2dyYXBoeSwg

WC1SYXkgQ29tcHV0ZWQ8L2tleXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1

cmw+aHR0cHM6Ly93d3cubmNiaS5ubG0ubmloLmdvdi9wdWJtZWQvMjI5MjcwMzwvdXJsPjwvcmVs

YXRlZC11cmxzPjwvdXJscz48aXNibj4wMDIyLTMwNTA8L2lzYm4+PGN1c3RvbTI+UE1DNDg4MzIw

PC9jdXN0b20yPjx0aXRsZXM+PHRpdGxlPkdyYWRpbmcgd2hpdGUgbWF0dGVyIGxlc2lvbnMgb24g

Q1QgYW5kIE1SSTogYSBzaW1wbGUgc2NhbGU8L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+SiBOZXVy

b2wgTmV1cm9zdXJnIFBzeWNoaWF0cnk8L3NlY29uZGFyeS10aXRsZT48L3RpdGxlcz48cGFnZXM+

MTA4MC0zPC9wYWdlcz48bnVtYmVyPjEyPC9udW1iZXI+PGNvbnRyaWJ1dG9ycz48YXV0aG9ycz48

YXV0aG9yPnZhbiBTd2lldGVuLCBKLiBDLjwvYXV0aG9yPjxhdXRob3I+SGlqZHJhLCBBLjwvYXV0

aG9yPjxhdXRob3I+S291ZHN0YWFsLCBQLiBKLjwvYXV0aG9yPjxhdXRob3I+dmFuIEdpam4sIEou

PC9hdXRob3I+PC9hdXRob3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5FTkc8L2xhbmd1YWdl

PjxhZGRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc4MTc3NjAwPC9hZGRlZC1kYXRlPjxyZWYtdHlw

ZSBuYW1lPSJKb3VybmFsIEFydGljbGUiPjE3PC9yZWYtdHlwZT48cmVjLW51bWJlcj41MzE8L3Jl

Yy1udW1iZXI+PGxhc3QtdXBkYXRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc4MTc3NjAwPC9sYXN0

LXVwZGF0ZWQtZGF0ZT48YWNjZXNzaW9uLW51bT4yMjkyNzAzPC9hY2Nlc3Npb24tbnVtPjx2b2x1

bWU+NTM8L3ZvbHVtZT48L3JlY29yZD48L0NpdGU+PC9FbmROb3RlPgAA

ADDIN EN.CITE.DATA 12, 15. For the drawing study, 60 CTs were selected randomly from the IC-thrombolysed cohort, and 60 from the IC CT-MRI cohort, whilst ensuring that there were equal proportions of absent/mild, moderate and severe SVD (based upon expert ratings). For the ratings study, ratings were obtained on all subjects from IC-thrombolysed cohort, and CT-MRI and IST-3 subsets (Fig. 1A; Table 1 describes subject characteristics, including imaging features, for each study.) CT images used for validation from IC were derived from two types of CT scanner (GE, Siemens); comprised a range of slice thicknesses (voxel resolutions: ~ 0.4 x 0.4 x [1 – 7] mm), that in 70% of cases differed between the top- and bottom-halves of the brain (i.e. two image files per patient); and in the remainder, were uniform volumetric images. IST-3 cohort CT images comprised an even more heterogeneous set (details provided in original reportPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5TYW5kZXJjb2NrPC9BdXRob3I+PFllYXI+MjAxMjwvWWVh

cj48SURUZXh0PlRoZSBiZW5lZml0cyBhbmQgaGFybXMgb2YgaW50cmF2ZW5vdXMgdGhyb21ib2x5

c2lzIHdpdGggcmVjb21iaW5hbnQgdGlzc3VlIHBsYXNtaW5vZ2VuIGFjdGl2YXRvciB3aXRoaW4g

NiBoIG9mIGFjdXRlIGlzY2hhZW1pYyBzdHJva2UgKHRoZSB0aGlyZCBpbnRlcm5hdGlvbmFsIHN0

cm9rZSB0cmlhbCBbSVNULTNdKTogYSByYW5kb21pc2VkIGNvbnRyb2xsZWQgdHJpYWw8L0lEVGV4

dD48RGlzcGxheVRleHQ+PHN0eWxlIGZhY2U9InN1cGVyc2NyaXB0Ij4xOTwvc3R5bGU+PC9EaXNw

bGF5VGV4dD48cmVjb3JkPjxkYXRlcz48cHViLWRhdGVzPjxkYXRlPkp1bjwvZGF0ZT48L3B1Yi1k

YXRlcz48eWVhcj4yMDEyPC95ZWFyPjwvZGF0ZXM+PGtleXdvcmRzPjxrZXl3b3JkPkFkb2xlc2Nl

bnQ8L2tleXdvcmQ+PGtleXdvcmQ+QWR1bHQ8L2tleXdvcmQ+PGtleXdvcmQ+QWdlIERpc3RyaWJ1

dGlvbjwva2V5d29yZD48a2V5d29yZD5BZ2VkPC9rZXl3b3JkPjxrZXl3b3JkPkFnZWQsIDgwIGFu

ZCBvdmVyPC9rZXl3b3JkPjxrZXl3b3JkPkJyYWluIElzY2hlbWlhPC9rZXl3b3JkPjxrZXl3b3Jk

PkRvdWJsZS1CbGluZCBNZXRob2Q8L2tleXdvcmQ+PGtleXdvcmQ+RHJ1ZyBBZG1pbmlzdHJhdGlv

biBTY2hlZHVsZTwva2V5d29yZD48a2V5d29yZD5GZW1hbGU8L2tleXdvcmQ+PGtleXdvcmQ+Rmli

cmlub2x5dGljIEFnZW50czwva2V5d29yZD48a2V5d29yZD5IdW1hbnM8L2tleXdvcmQ+PGtleXdv

cmQ+SW5mdXNpb25zLCBJbnRyYXZlbm91czwva2V5d29yZD48a2V5d29yZD5NYWxlPC9rZXl3b3Jk

PjxrZXl3b3JkPk1pZGRsZSBBZ2VkPC9rZXl3b3JkPjxrZXl3b3JkPlJlY29tYmluYW50IFByb3Rl

aW5zPC9rZXl3b3JkPjxrZXl3b3JkPlJlY3VycmVuY2U8L2tleXdvcmQ+PGtleXdvcmQ+U2V2ZXJp

dHkgb2YgSWxsbmVzcyBJbmRleDwva2V5d29yZD48a2V5d29yZD5TdHJva2U8L2tleXdvcmQ+PGtl

eXdvcmQ+VGhyb21ib2x5dGljIFRoZXJhcHk8L2tleXdvcmQ+PGtleXdvcmQ+VGlzc3VlIFBsYXNt

aW5vZ2VuIEFjdGl2YXRvcjwva2V5d29yZD48a2V5d29yZD5UcmVhdG1lbnQgT3V0Y29tZTwva2V5

d29yZD48a2V5d29yZD5Zb3VuZyBBZHVsdDwva2V5d29yZD48L2tleXdvcmRzPjx1cmxzPjxyZWxh

dGVkLXVybHM+PHVybD5odHRwOi8vd3d3Lm5jYmkubmxtLm5paC5nb3YvcHVibWVkLzIyNjMyOTA4

PC91cmw+PC9yZWxhdGVkLXVybHM+PC91cmxzPjxpc2JuPjE0NzQtNTQ3WDwvaXNibj48Y3VzdG9t

Mj5QTUMzMzg2NDk1PC9jdXN0b20yPjx0aXRsZXM+PHRpdGxlPlRoZSBiZW5lZml0cyBhbmQgaGFy

bXMgb2YgaW50cmF2ZW5vdXMgdGhyb21ib2x5c2lzIHdpdGggcmVjb21iaW5hbnQgdGlzc3VlIHBs

YXNtaW5vZ2VuIGFjdGl2YXRvciB3aXRoaW4gNiBoIG9mIGFjdXRlIGlzY2hhZW1pYyBzdHJva2Ug

KHRoZSB0aGlyZCBpbnRlcm5hdGlvbmFsIHN0cm9rZSB0cmlhbCBbSVNULTNdKTogYSByYW5kb21p

c2VkIGNvbnRyb2xsZWQgdHJpYWw8L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+TGFuY2V0PC9zZWNv

bmRhcnktdGl0bGU+PC90aXRsZXM+PHBhZ2VzPjIzNTItNjM8L3BhZ2VzPjxudW1iZXI+OTgzNDwv

bnVtYmVyPjxjb250cmlidXRvcnM+PGF1dGhvcnM+PGF1dGhvcj5TYW5kZXJjb2NrLCBQLjwvYXV0

aG9yPjxhdXRob3I+V2FyZGxhdywgSi4gTS48L2F1dGhvcj48YXV0aG9yPkxpbmRsZXksIFIuIEku

PC9hdXRob3I+PGF1dGhvcj5EZW5uaXMsIE0uPC9hdXRob3I+PGF1dGhvcj5Db2hlbiwgRy48L2F1

dGhvcj48YXV0aG9yPk11cnJheSwgRy48L2F1dGhvcj48YXV0aG9yPklubmVzLCBLLjwvYXV0aG9y

PjxhdXRob3I+VmVuYWJsZXMsIEcuPC9hdXRob3I+PGF1dGhvcj5Demxvbmtvd3NrYSwgQS48L2F1

dGhvcj48YXV0aG9yPktvYmF5YXNoaSwgQS48L2F1dGhvcj48YXV0aG9yPlJpY2NpLCBTLjwvYXV0

aG9yPjxhdXRob3I+TXVycmF5LCBWLjwvYXV0aG9yPjxhdXRob3I+QmVyZ2UsIEUuPC9hdXRob3I+

PGF1dGhvcj5TbG90LCBLLiBCLjwvYXV0aG9yPjxhdXRob3I+SGFua2V5LCBHLiBKLjwvYXV0aG9y

PjxhdXRob3I+Q29ycmVpYSwgTS48L2F1dGhvcj48YXV0aG9yPlBlZXRlcnMsIEEuPC9hdXRob3I+

PGF1dGhvcj5NYXR6LCBLLjwvYXV0aG9yPjxhdXRob3I+THlyZXIsIFAuPC9hdXRob3I+PGF1dGhv

cj5HdWJpdHosIEcuPC9hdXRob3I+PGF1dGhvcj5QaGlsbGlwcywgUy4gSi48L2F1dGhvcj48YXV0

aG9yPkFyYXV6LCBBLjwvYXV0aG9yPjxhdXRob3I+SVNULTMgY29sbGFib3JhdGl2ZSBncm91cDwv

YXV0aG9yPjwvYXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3VhZ2U+ZW5nPC9sYW5ndWFnZT48

YWRkZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTM4NzU0NzcyNzwvYWRkZWQtZGF0ZT48cmVmLXR5cGUg

bmFtZT0iSm91cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PHJlYy1udW1iZXI+MzUwPC9yZWMt

bnVtYmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTM4NzU0NzcyNzwvbGFzdC11

cGRhdGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MjI2MzI5MDg8L2FjY2Vzc2lvbi1udW0+PGVsZWN0

cm9uaWMtcmVzb3VyY2UtbnVtPjEwLjEwMTYvUzAxNDAtNjczNigxMik2MDc2OC01PC9lbGVjdHJv

bmljLXJlc291cmNlLW51bT48dm9sdW1lPjM3OTwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48L0Vu

ZE5vdGU+AAA=

ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5TYW5kZXJjb2NrPC9BdXRob3I+PFllYXI+MjAxMjwvWWVh

cj48SURUZXh0PlRoZSBiZW5lZml0cyBhbmQgaGFybXMgb2YgaW50cmF2ZW5vdXMgdGhyb21ib2x5

c2lzIHdpdGggcmVjb21iaW5hbnQgdGlzc3VlIHBsYXNtaW5vZ2VuIGFjdGl2YXRvciB3aXRoaW4g

NiBoIG9mIGFjdXRlIGlzY2hhZW1pYyBzdHJva2UgKHRoZSB0aGlyZCBpbnRlcm5hdGlvbmFsIHN0

cm9rZSB0cmlhbCBbSVNULTNdKTogYSByYW5kb21pc2VkIGNvbnRyb2xsZWQgdHJpYWw8L0lEVGV4

dD48RGlzcGxheVRleHQ+PHN0eWxlIGZhY2U9InN1cGVyc2NyaXB0Ij4xOTwvc3R5bGU+PC9EaXNw

bGF5VGV4dD48cmVjb3JkPjxkYXRlcz48cHViLWRhdGVzPjxkYXRlPkp1bjwvZGF0ZT48L3B1Yi1k

YXRlcz48eWVhcj4yMDEyPC95ZWFyPjwvZGF0ZXM+PGtleXdvcmRzPjxrZXl3b3JkPkFkb2xlc2Nl

bnQ8L2tleXdvcmQ+PGtleXdvcmQ+QWR1bHQ8L2tleXdvcmQ+PGtleXdvcmQ+QWdlIERpc3RyaWJ1

dGlvbjwva2V5d29yZD48a2V5d29yZD5BZ2VkPC9rZXl3b3JkPjxrZXl3b3JkPkFnZWQsIDgwIGFu

ZCBvdmVyPC9rZXl3b3JkPjxrZXl3b3JkPkJyYWluIElzY2hlbWlhPC9rZXl3b3JkPjxrZXl3b3Jk

PkRvdWJsZS1CbGluZCBNZXRob2Q8L2tleXdvcmQ+PGtleXdvcmQ+RHJ1ZyBBZG1pbmlzdHJhdGlv

biBTY2hlZHVsZTwva2V5d29yZD48a2V5d29yZD5GZW1hbGU8L2tleXdvcmQ+PGtleXdvcmQ+Rmli

cmlub2x5dGljIEFnZW50czwva2V5d29yZD48a2V5d29yZD5IdW1hbnM8L2tleXdvcmQ+PGtleXdv

cmQ+SW5mdXNpb25zLCBJbnRyYXZlbm91czwva2V5d29yZD48a2V5d29yZD5NYWxlPC9rZXl3b3Jk

PjxrZXl3b3JkPk1pZGRsZSBBZ2VkPC9rZXl3b3JkPjxrZXl3b3JkPlJlY29tYmluYW50IFByb3Rl

aW5zPC9rZXl3b3JkPjxrZXl3b3JkPlJlY3VycmVuY2U8L2tleXdvcmQ+PGtleXdvcmQ+U2V2ZXJp

dHkgb2YgSWxsbmVzcyBJbmRleDwva2V5d29yZD48a2V5d29yZD5TdHJva2U8L2tleXdvcmQ+PGtl

eXdvcmQ+VGhyb21ib2x5dGljIFRoZXJhcHk8L2tleXdvcmQ+PGtleXdvcmQ+VGlzc3VlIFBsYXNt

aW5vZ2VuIEFjdGl2YXRvcjwva2V5d29yZD48a2V5d29yZD5UcmVhdG1lbnQgT3V0Y29tZTwva2V5

d29yZD48a2V5d29yZD5Zb3VuZyBBZHVsdDwva2V5d29yZD48L2tleXdvcmRzPjx1cmxzPjxyZWxh

dGVkLXVybHM+PHVybD5odHRwOi8vd3d3Lm5jYmkubmxtLm5paC5nb3YvcHVibWVkLzIyNjMyOTA4

PC91cmw+PC9yZWxhdGVkLXVybHM+PC91cmxzPjxpc2JuPjE0NzQtNTQ3WDwvaXNibj48Y3VzdG9t

Mj5QTUMzMzg2NDk1PC9jdXN0b20yPjx0aXRsZXM+PHRpdGxlPlRoZSBiZW5lZml0cyBhbmQgaGFy

bXMgb2YgaW50cmF2ZW5vdXMgdGhyb21ib2x5c2lzIHdpdGggcmVjb21iaW5hbnQgdGlzc3VlIHBs

YXNtaW5vZ2VuIGFjdGl2YXRvciB3aXRoaW4gNiBoIG9mIGFjdXRlIGlzY2hhZW1pYyBzdHJva2Ug

KHRoZSB0aGlyZCBpbnRlcm5hdGlvbmFsIHN0cm9rZSB0cmlhbCBbSVNULTNdKTogYSByYW5kb21p

c2VkIGNvbnRyb2xsZWQgdHJpYWw8L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+TGFuY2V0PC9zZWNv

bmRhcnktdGl0bGU+PC90aXRsZXM+PHBhZ2VzPjIzNTItNjM8L3BhZ2VzPjxudW1iZXI+OTgzNDwv

bnVtYmVyPjxjb250cmlidXRvcnM+PGF1dGhvcnM+PGF1dGhvcj5TYW5kZXJjb2NrLCBQLjwvYXV0

aG9yPjxhdXRob3I+V2FyZGxhdywgSi4gTS48L2F1dGhvcj48YXV0aG9yPkxpbmRsZXksIFIuIEku

PC9hdXRob3I+PGF1dGhvcj5EZW5uaXMsIE0uPC9hdXRob3I+PGF1dGhvcj5Db2hlbiwgRy48L2F1

dGhvcj48YXV0aG9yPk11cnJheSwgRy48L2F1dGhvcj48YXV0aG9yPklubmVzLCBLLjwvYXV0aG9y

PjxhdXRob3I+VmVuYWJsZXMsIEcuPC9hdXRob3I+PGF1dGhvcj5Demxvbmtvd3NrYSwgQS48L2F1

dGhvcj48YXV0aG9yPktvYmF5YXNoaSwgQS48L2F1dGhvcj48YXV0aG9yPlJpY2NpLCBTLjwvYXV0

aG9yPjxhdXRob3I+TXVycmF5LCBWLjwvYXV0aG9yPjxhdXRob3I+QmVyZ2UsIEUuPC9hdXRob3I+

PGF1dGhvcj5TbG90LCBLLiBCLjwvYXV0aG9yPjxhdXRob3I+SGFua2V5LCBHLiBKLjwvYXV0aG9y

PjxhdXRob3I+Q29ycmVpYSwgTS48L2F1dGhvcj48YXV0aG9yPlBlZXRlcnMsIEEuPC9hdXRob3I+

PGF1dGhvcj5NYXR6LCBLLjwvYXV0aG9yPjxhdXRob3I+THlyZXIsIFAuPC9hdXRob3I+PGF1dGhv

cj5HdWJpdHosIEcuPC9hdXRob3I+PGF1dGhvcj5QaGlsbGlwcywgUy4gSi48L2F1dGhvcj48YXV0

aG9yPkFyYXV6LCBBLjwvYXV0aG9yPjxhdXRob3I+SVNULTMgY29sbGFib3JhdGl2ZSBncm91cDwv

YXV0aG9yPjwvYXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3VhZ2U+ZW5nPC9sYW5ndWFnZT48

YWRkZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTM4NzU0NzcyNzwvYWRkZWQtZGF0ZT48cmVmLXR5cGUg

bmFtZT0iSm91cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PHJlYy1udW1iZXI+MzUwPC9yZWMt

bnVtYmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTM4NzU0NzcyNzwvbGFzdC11

cGRhdGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MjI2MzI5MDg8L2FjY2Vzc2lvbi1udW0+PGVsZWN0

cm9uaWMtcmVzb3VyY2UtbnVtPjEwLjEwMTYvUzAxNDAtNjczNigxMik2MDc2OC01PC9lbGVjdHJv

bmljLXJlc291cmNlLW51bT48dm9sdW1lPjM3OTwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48L0Vu

ZE5vdGU+AAA=

ADDIN EN.CITE.DATA 19). Automated SVD quantification methodCerebral WML were segmented from CT images using a supervised machine learning method, based upon random forests, developed and described previouslyPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5DaGVuPC9BdXRob3I+PFllYXI+MjAxNTwvWWVhcj48SURU

ZXh0PklkZW50aWZpY2F0aW9uIG9mIENlcmVicmFsIFNtYWxsIFZlc3NlbCBEaXNlYXNlIFVzaW5n

IE11bHRpcGxlIEluc3RhbmNlIExlYXJuaW5nPC9JRFRleHQ+PERpc3BsYXlUZXh0PjxzdHlsZSBm

YWNlPSJzdXBlcnNjcmlwdCI+MTcsIDE4PC9zdHlsZT48L0Rpc3BsYXlUZXh0PjxyZWNvcmQ+PGlz

Ym4+MDMwMi05NzQzPC9pc2JuPjx0aXRsZXM+PHRpdGxlPklkZW50aWZpY2F0aW9uIG9mIENlcmVi

cmFsIFNtYWxsIFZlc3NlbCBEaXNlYXNlIFVzaW5nIE11bHRpcGxlIEluc3RhbmNlIExlYXJuaW5n

PC90aXRsZT48c2Vjb25kYXJ5LXRpdGxlPk1lZGljYWwgSW1hZ2UgQ29tcHV0aW5nIGFuZCBDb21w

dXRlci1Bc3Npc3RlZCBJbnRlcnZlbnRpb24gKE1JQ0NBSSAyMDE1KTwvc2Vjb25kYXJ5LXRpdGxl

PjwvdGl0bGVzPjxwYWdlcz41MjMtNTMwPC9wYWdlcz48Y29udHJpYnV0b3JzPjxhdXRob3JzPjxh

dXRob3I+Q2hlbiwgTGlhbmc8L2F1dGhvcj48YXV0aG9yPlRvbmcsIFRvbmc8L2F1dGhvcj48YXV0

aG9yPlBhbmcgSG8sIENoaW48L2F1dGhvcj48YXV0aG9yPlBhdGVsLCBSYWppdjwvYXV0aG9yPjxh

dXRob3I+Q29oZW4sIERhdmlkPC9hdXRob3I+PGF1dGhvcj5EYXdzb24sIEFuZ2VsYSBDPC9hdXRo

b3I+PGF1dGhvcj5IYWxzZSwgT21pZDwvYXV0aG9yPjxhdXRob3I+R2VyYWdodHksIE9saXZpYTwv

YXV0aG9yPjxhdXRob3I+UmlubmUsIFBhdWw8L2F1dGhvcj48YXV0aG9yPldoaXRlLCBDaHJpc3Rv

cGhlcjwvYXV0aG9yPjxhdXRob3I+TmFrb3JuY2hhaSwgVGFnb3JlPC9hdXRob3I+PGF1dGhvcj5C

ZW50bGV5LCBQYXVsPC9hdXRob3I+PGF1dGhvcj5SdWVja2VydCwgRGFuaWVsPC9hdXRob3I+PC9h

dXRob3JzPjwvY29udHJpYnV0b3JzPjxlZGl0aW9uPjE4IE5vdiAyMDE1PC9lZGl0aW9uPjxhZGRl

ZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc4MTgxNzkyPC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1l

PSJKb3VybmFsIEFydGljbGUiPjE3PC9yZWYtdHlwZT48ZGF0ZXM+PHllYXI+MjAxNTwveWVhcj48

L2RhdGVzPjxyZWMtbnVtYmVyPjUzNDwvcmVjLW51bWJlcj48bGFzdC11cGRhdGVkLWRhdGUgZm9y

bWF0PSJ1dGMiPjE0NzgxODIyMzE8L2xhc3QtdXBkYXRlZC1kYXRlPjxlbGVjdHJvbmljLXJlc291

cmNlLW51bT4xMC4xMDA3Lzk3OC0zLTMxOS0yNDU1My05XzY0PC9lbGVjdHJvbmljLXJlc291cmNl

LW51bT48dm9sdW1lPjkzNDk8L3ZvbHVtZT48L3JlY29yZD48L0NpdGU+PENpdGU+PEF1dGhvcj5N

YWllcjwvQXV0aG9yPjxZZWFyPjIwMTc8L1llYXI+PElEVGV4dD5JU0xFUyAyMDE1IC0gQSBwdWJs

aWMgZXZhbHVhdGlvbiBiZW5jaG1hcmsgZm9yIGlzY2hlbWljIHN0cm9rZSBsZXNpb24gc2VnbWVu

dGF0aW9uIGZyb20gbXVsdGlzcGVjdHJhbCBNUkk8L0lEVGV4dD48cmVjb3JkPjxkYXRlcz48cHVi

LWRhdGVzPjxkYXRlPkphbjwvZGF0ZT48L3B1Yi1kYXRlcz48eWVhcj4yMDE3PC95ZWFyPjwvZGF0

ZXM+PHVybHM+PHJlbGF0ZWQtdXJscz48dXJsPmh0dHBzOi8vd3d3Lm5jYmkubmxtLm5paC5nb3Yv

cHVibWVkLzI3NDc1OTExPC91cmw+PC9yZWxhdGVkLXVybHM+PC91cmxzPjxpc2JuPjEzNjEtODQx

NTwvaXNibj48Y3VzdG9tMj5QTUM1MDk5MTE4PC9jdXN0b20yPjx0aXRsZXM+PHRpdGxlPklTTEVT

IDIwMTUgLSBBIHB1YmxpYyBldmFsdWF0aW9uIGJlbmNobWFyayBmb3IgaXNjaGVtaWMgc3Ryb2tl

IGxlc2lvbiBzZWdtZW50YXRpb24gZnJvbSBtdWx0aXNwZWN0cmFsIE1SSTwvdGl0bGU+PHNlY29u

ZGFyeS10aXRsZT5NZWQgSW1hZ2UgQW5hbDwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0bGVzPjxwYWdl

cz4yNTAtMjY5PC9wYWdlcz48Y29udHJpYnV0b3JzPjxhdXRob3JzPjxhdXRob3I+TWFpZXIsIE8u

PC9hdXRob3I+PGF1dGhvcj5NZW56ZSwgQi4gSC48L2F1dGhvcj48YXV0aG9yPnZvbiBkZXIgR2Fi

bGVudHosIEouPC9hdXRob3I+PGF1dGhvcj5Iw6RuaSwgTC48L2F1dGhvcj48YXV0aG9yPkhlaW5y

aWNoLCBNLiBQLjwvYXV0aG9yPjxhdXRob3I+TGllYnJhbmQsIE0uPC9hdXRob3I+PGF1dGhvcj5X

aW56ZWNrLCBTLjwvYXV0aG9yPjxhdXRob3I+QmFzaXQsIEEuPC9hdXRob3I+PGF1dGhvcj5CZW50

bGV5LCBQLjwvYXV0aG9yPjxhdXRob3I+Q2hlbiwgTC48L2F1dGhvcj48YXV0aG9yPkNocmlzdGlh

ZW5zLCBELjwvYXV0aG9yPjxhdXRob3I+RHV0aWwsIEYuPC9hdXRob3I+PGF1dGhvcj5FZ2dlciwg

Sy48L2F1dGhvcj48YXV0aG9yPkZlbmcsIEMuPC9hdXRob3I+PGF1dGhvcj5HbG9ja2VyLCBCLjwv

YXV0aG9yPjxhdXRob3I+R8O2dHosIE0uPC9hdXRob3I+PGF1dGhvcj5IYWVjaywgVC48L2F1dGhv

cj48YXV0aG9yPkhhbG1lLCBILiBMLjwvYXV0aG9yPjxhdXRob3I+SGF2YWVpLCBNLjwvYXV0aG9y

PjxhdXRob3I+SWZ0ZWtoYXJ1ZGRpbiwgSy4gTS48L2F1dGhvcj48YXV0aG9yPkpvZG9pbiwgUC4g

TS48L2F1dGhvcj48YXV0aG9yPkthbW5pdHNhcywgSy48L2F1dGhvcj48YXV0aG9yPktlbGxuZXIs

IEUuPC9hdXRob3I+PGF1dGhvcj5Lb3J2ZW5vamEsIEEuPC9hdXRob3I+PGF1dGhvcj5MYXJvY2hl

bGxlLCBILjwvYXV0aG9yPjxhdXRob3I+TGVkaWcsIEMuPC9hdXRob3I+PGF1dGhvcj5MZWUsIEou

IEguPC9hdXRob3I+PGF1dGhvcj5NYWVzLCBGLjwvYXV0aG9yPjxhdXRob3I+TWFobW9vZCwgUS48

L2F1dGhvcj48YXV0aG9yPk1haWVyLUhlaW4sIEsuIEguPC9hdXRob3I+PGF1dGhvcj5NY0tpbmxl

eSwgUi48L2F1dGhvcj48YXV0aG9yPk11c2NoZWxsaSwgSi48L2F1dGhvcj48YXV0aG9yPlBhbCwg

Qy48L2F1dGhvcj48YXV0aG9yPlBlaSwgTC48L2F1dGhvcj48YXV0aG9yPlJhbmdhcmFqYW4sIEou

IFIuPC9hdXRob3I+PGF1dGhvcj5SZXphLCBTLiBNLjwvYXV0aG9yPjxhdXRob3I+Um9iYmVuLCBE

LjwvYXV0aG9yPjxhdXRob3I+UnVlY2tlcnQsIEQuPC9hdXRob3I+PGF1dGhvcj5TYWxsaSwgRS48

L2F1dGhvcj48YXV0aG9yPlN1ZXRlbnMsIFAuPC9hdXRob3I+PGF1dGhvcj5XYW5nLCBDLiBXLjwv

YXV0aG9yPjxhdXRob3I+V2lsbXMsIE0uPC9hdXRob3I+PGF1dGhvcj5LaXJzY2hrZSwgSi4gUy48

L2F1dGhvcj48YXV0aG9yPktyw6RtZXIsIFUuIE0uPC9hdXRob3I+PGF1dGhvcj5Nw7xudGUsIFQu

IEYuPC9hdXRob3I+PGF1dGhvcj5TY2hyYW1tLCBQLjwvYXV0aG9yPjxhdXRob3I+V2llc3QsIFIu

PC9hdXRob3I+PGF1dGhvcj5IYW5kZWxzLCBILjwvYXV0aG9yPjxhdXRob3I+UmV5ZXMsIE0uPC9h

dXRob3I+PC9hdXRob3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5FTkc8L2xhbmd1YWdlPjxh

ZGRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc5MjkzMjE4PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBu

YW1lPSJKb3VybmFsIEFydGljbGUiPjE3PC9yZWYtdHlwZT48cmVjLW51bWJlcj41NTU8L3JlYy1u

dW1iZXI+PGxhc3QtdXBkYXRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc5MjkzMjE4PC9sYXN0LXVw

ZGF0ZWQtZGF0ZT48YWNjZXNzaW9uLW51bT4yNzQ3NTkxMTwvYWNjZXNzaW9uLW51bT48ZWxlY3Ry

b25pYy1yZXNvdXJjZS1udW0+MTAuMTAxNi9qLm1lZGlhLjIwMTYuMDcuMDA5PC9lbGVjdHJvbmlj

LXJlc291cmNlLW51bT48dm9sdW1lPjM1PC92b2x1bWU+PC9yZWNvcmQ+PC9DaXRlPjwvRW5kTm90

ZT4AAAA=

ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5DaGVuPC9BdXRob3I+PFllYXI+MjAxNTwvWWVhcj48SURU

ZXh0PklkZW50aWZpY2F0aW9uIG9mIENlcmVicmFsIFNtYWxsIFZlc3NlbCBEaXNlYXNlIFVzaW5n

IE11bHRpcGxlIEluc3RhbmNlIExlYXJuaW5nPC9JRFRleHQ+PERpc3BsYXlUZXh0PjxzdHlsZSBm

YWNlPSJzdXBlcnNjcmlwdCI+MTcsIDE4PC9zdHlsZT48L0Rpc3BsYXlUZXh0PjxyZWNvcmQ+PGlz

Ym4+MDMwMi05NzQzPC9pc2JuPjx0aXRsZXM+PHRpdGxlPklkZW50aWZpY2F0aW9uIG9mIENlcmVi

cmFsIFNtYWxsIFZlc3NlbCBEaXNlYXNlIFVzaW5nIE11bHRpcGxlIEluc3RhbmNlIExlYXJuaW5n

PC90aXRsZT48c2Vjb25kYXJ5LXRpdGxlPk1lZGljYWwgSW1hZ2UgQ29tcHV0aW5nIGFuZCBDb21w

dXRlci1Bc3Npc3RlZCBJbnRlcnZlbnRpb24gKE1JQ0NBSSAyMDE1KTwvc2Vjb25kYXJ5LXRpdGxl

PjwvdGl0bGVzPjxwYWdlcz41MjMtNTMwPC9wYWdlcz48Y29udHJpYnV0b3JzPjxhdXRob3JzPjxh

dXRob3I+Q2hlbiwgTGlhbmc8L2F1dGhvcj48YXV0aG9yPlRvbmcsIFRvbmc8L2F1dGhvcj48YXV0

aG9yPlBhbmcgSG8sIENoaW48L2F1dGhvcj48YXV0aG9yPlBhdGVsLCBSYWppdjwvYXV0aG9yPjxh

dXRob3I+Q29oZW4sIERhdmlkPC9hdXRob3I+PGF1dGhvcj5EYXdzb24sIEFuZ2VsYSBDPC9hdXRo

b3I+PGF1dGhvcj5IYWxzZSwgT21pZDwvYXV0aG9yPjxhdXRob3I+R2VyYWdodHksIE9saXZpYTwv

YXV0aG9yPjxhdXRob3I+UmlubmUsIFBhdWw8L2F1dGhvcj48YXV0aG9yPldoaXRlLCBDaHJpc3Rv

cGhlcjwvYXV0aG9yPjxhdXRob3I+TmFrb3JuY2hhaSwgVGFnb3JlPC9hdXRob3I+PGF1dGhvcj5C

ZW50bGV5LCBQYXVsPC9hdXRob3I+PGF1dGhvcj5SdWVja2VydCwgRGFuaWVsPC9hdXRob3I+PC9h

dXRob3JzPjwvY29udHJpYnV0b3JzPjxlZGl0aW9uPjE4IE5vdiAyMDE1PC9lZGl0aW9uPjxhZGRl

ZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc4MTgxNzkyPC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1l

PSJKb3VybmFsIEFydGljbGUiPjE3PC9yZWYtdHlwZT48ZGF0ZXM+PHllYXI+MjAxNTwveWVhcj48

L2RhdGVzPjxyZWMtbnVtYmVyPjUzNDwvcmVjLW51bWJlcj48bGFzdC11cGRhdGVkLWRhdGUgZm9y

bWF0PSJ1dGMiPjE0NzgxODIyMzE8L2xhc3QtdXBkYXRlZC1kYXRlPjxlbGVjdHJvbmljLXJlc291

cmNlLW51bT4xMC4xMDA3Lzk3OC0zLTMxOS0yNDU1My05XzY0PC9lbGVjdHJvbmljLXJlc291cmNl

LW51bT48dm9sdW1lPjkzNDk8L3ZvbHVtZT48L3JlY29yZD48L0NpdGU+PENpdGU+PEF1dGhvcj5N

YWllcjwvQXV0aG9yPjxZZWFyPjIwMTc8L1llYXI+PElEVGV4dD5JU0xFUyAyMDE1IC0gQSBwdWJs

aWMgZXZhbHVhdGlvbiBiZW5jaG1hcmsgZm9yIGlzY2hlbWljIHN0cm9rZSBsZXNpb24gc2VnbWVu

dGF0aW9uIGZyb20gbXVsdGlzcGVjdHJhbCBNUkk8L0lEVGV4dD48cmVjb3JkPjxkYXRlcz48cHVi

LWRhdGVzPjxkYXRlPkphbjwvZGF0ZT48L3B1Yi1kYXRlcz48eWVhcj4yMDE3PC95ZWFyPjwvZGF0

ZXM+PHVybHM+PHJlbGF0ZWQtdXJscz48dXJsPmh0dHBzOi8vd3d3Lm5jYmkubmxtLm5paC5nb3Yv

cHVibWVkLzI3NDc1OTExPC91cmw+PC9yZWxhdGVkLXVybHM+PC91cmxzPjxpc2JuPjEzNjEtODQx

NTwvaXNibj48Y3VzdG9tMj5QTUM1MDk5MTE4PC9jdXN0b20yPjx0aXRsZXM+PHRpdGxlPklTTEVT

IDIwMTUgLSBBIHB1YmxpYyBldmFsdWF0aW9uIGJlbmNobWFyayBmb3IgaXNjaGVtaWMgc3Ryb2tl

IGxlc2lvbiBzZWdtZW50YXRpb24gZnJvbSBtdWx0aXNwZWN0cmFsIE1SSTwvdGl0bGU+PHNlY29u

ZGFyeS10aXRsZT5NZWQgSW1hZ2UgQW5hbDwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0bGVzPjxwYWdl

cz4yNTAtMjY5PC9wYWdlcz48Y29udHJpYnV0b3JzPjxhdXRob3JzPjxhdXRob3I+TWFpZXIsIE8u

PC9hdXRob3I+PGF1dGhvcj5NZW56ZSwgQi4gSC48L2F1dGhvcj48YXV0aG9yPnZvbiBkZXIgR2Fi

bGVudHosIEouPC9hdXRob3I+PGF1dGhvcj5Iw6RuaSwgTC48L2F1dGhvcj48YXV0aG9yPkhlaW5y

aWNoLCBNLiBQLjwvYXV0aG9yPjxhdXRob3I+TGllYnJhbmQsIE0uPC9hdXRob3I+PGF1dGhvcj5X

aW56ZWNrLCBTLjwvYXV0aG9yPjxhdXRob3I+QmFzaXQsIEEuPC9hdXRob3I+PGF1dGhvcj5CZW50

bGV5LCBQLjwvYXV0aG9yPjxhdXRob3I+Q2hlbiwgTC48L2F1dGhvcj48YXV0aG9yPkNocmlzdGlh

ZW5zLCBELjwvYXV0aG9yPjxhdXRob3I+RHV0aWwsIEYuPC9hdXRob3I+PGF1dGhvcj5FZ2dlciwg

Sy48L2F1dGhvcj48YXV0aG9yPkZlbmcsIEMuPC9hdXRob3I+PGF1dGhvcj5HbG9ja2VyLCBCLjwv

YXV0aG9yPjxhdXRob3I+R8O2dHosIE0uPC9hdXRob3I+PGF1dGhvcj5IYWVjaywgVC48L2F1dGhv

cj48YXV0aG9yPkhhbG1lLCBILiBMLjwvYXV0aG9yPjxhdXRob3I+SGF2YWVpLCBNLjwvYXV0aG9y

PjxhdXRob3I+SWZ0ZWtoYXJ1ZGRpbiwgSy4gTS48L2F1dGhvcj48YXV0aG9yPkpvZG9pbiwgUC4g

TS48L2F1dGhvcj48YXV0aG9yPkthbW5pdHNhcywgSy48L2F1dGhvcj48YXV0aG9yPktlbGxuZXIs

IEUuPC9hdXRob3I+PGF1dGhvcj5Lb3J2ZW5vamEsIEEuPC9hdXRob3I+PGF1dGhvcj5MYXJvY2hl

bGxlLCBILjwvYXV0aG9yPjxhdXRob3I+TGVkaWcsIEMuPC9hdXRob3I+PGF1dGhvcj5MZWUsIEou

IEguPC9hdXRob3I+PGF1dGhvcj5NYWVzLCBGLjwvYXV0aG9yPjxhdXRob3I+TWFobW9vZCwgUS48

L2F1dGhvcj48YXV0aG9yPk1haWVyLUhlaW4sIEsuIEguPC9hdXRob3I+PGF1dGhvcj5NY0tpbmxl

eSwgUi48L2F1dGhvcj48YXV0aG9yPk11c2NoZWxsaSwgSi48L2F1dGhvcj48YXV0aG9yPlBhbCwg

Qy48L2F1dGhvcj48YXV0aG9yPlBlaSwgTC48L2F1dGhvcj48YXV0aG9yPlJhbmdhcmFqYW4sIEou

IFIuPC9hdXRob3I+PGF1dGhvcj5SZXphLCBTLiBNLjwvYXV0aG9yPjxhdXRob3I+Um9iYmVuLCBE

LjwvYXV0aG9yPjxhdXRob3I+UnVlY2tlcnQsIEQuPC9hdXRob3I+PGF1dGhvcj5TYWxsaSwgRS48

L2F1dGhvcj48YXV0aG9yPlN1ZXRlbnMsIFAuPC9hdXRob3I+PGF1dGhvcj5XYW5nLCBDLiBXLjwv

YXV0aG9yPjxhdXRob3I+V2lsbXMsIE0uPC9hdXRob3I+PGF1dGhvcj5LaXJzY2hrZSwgSi4gUy48

L2F1dGhvcj48YXV0aG9yPktyw6RtZXIsIFUuIE0uPC9hdXRob3I+PGF1dGhvcj5Nw7xudGUsIFQu

IEYuPC9hdXRob3I+PGF1dGhvcj5TY2hyYW1tLCBQLjwvYXV0aG9yPjxhdXRob3I+V2llc3QsIFIu

PC9hdXRob3I+PGF1dGhvcj5IYW5kZWxzLCBILjwvYXV0aG9yPjxhdXRob3I+UmV5ZXMsIE0uPC9h

dXRob3I+PC9hdXRob3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5FTkc8L2xhbmd1YWdlPjxh

ZGRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc5MjkzMjE4PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBu

YW1lPSJKb3VybmFsIEFydGljbGUiPjE3PC9yZWYtdHlwZT48cmVjLW51bWJlcj41NTU8L3JlYy1u

dW1iZXI+PGxhc3QtdXBkYXRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc5MjkzMjE4PC9sYXN0LXVw

ZGF0ZWQtZGF0ZT48YWNjZXNzaW9uLW51bT4yNzQ3NTkxMTwvYWNjZXNzaW9uLW51bT48ZWxlY3Ry

b25pYy1yZXNvdXJjZS1udW0+MTAuMTAxNi9qLm1lZGlhLjIwMTYuMDcuMDA5PC9lbGVjdHJvbmlj

LXJlc291cmNlLW51bT48dm9sdW1lPjM1PC92b2x1bWU+PC9yZWNvcmQ+PC9DaXRlPjwvRW5kTm90

ZT4AAAA=

ADDIN EN.CITE.DATA 17, 18. Briefly, a training model was derived from expert manual delineations of CT WML (leukoaraiosis including areas with lacunar infarcts ADDIN EN.CITE <EndNote><Cite><Author>Rossi</Author><Year>2005</Year><IDText>Pathological validation of a CT-based scale for subcortical vascular disease. The OPTIMA Study</IDText><DisplayText><style face="superscript">2</style></DisplayText><record><keywords><keyword>Aged</keyword><keyword>Aged, 80 and over</keyword><keyword>Brain</keyword><keyword>Cerebral Angiography</keyword><keyword>Cerebral Arteries</keyword><keyword>Dementia, Multi-Infarct</keyword><keyword>Dementia, Vascular</keyword><keyword>Female</keyword><keyword>Humans</keyword><keyword>Leukoaraiosis</keyword><keyword>Longitudinal Studies</keyword><keyword>Male</keyword><keyword>Microcirculation</keyword><keyword>Middle Aged</keyword><keyword>Prospective Studies</keyword><keyword>Reproducibility of Results</keyword><keyword>Sensitivity and Specificity</keyword><keyword>Statistics as Topic</keyword><keyword>Tomography, X-Ray Computed</keyword></keywords><urls><related-urls><url> validation of a CT-based scale for subcortical vascular disease. The OPTIMA Study</title><secondary-title>Dement Geriatr Cogn Disord</secondary-title></titles><pages>61-6</pages><number>2-3</number><contributors><authors><author>Rossi, R.</author><author>Joachim, C.</author><author>Geroldi, C.</author><author>Esiri, M. M.</author><author>Smith, A. D.</author><author>Frisoni, G. B.</author></authors></contributors><language>ENG</language><added-date format="utc">1478697809</added-date><ref-type name="Journal Article">17</ref-type><dates><year>2005</year></dates><rec-number>543</rec-number><last-updated-date format="utc">1478697809</last-updated-date><accession-num>15572873</accession-num><electronic-resource-num>10.1159/000082350</electronic-resource-num><volume>19</volume></record></Cite></EndNote>2). These were taken from 90 representative slices, of 50 subjects, showing moderate or severe WML, selected from a pool of 1000 acute ischemic stroke CT images (< 4.5 hours from symptom onset) from a single stroke centre (Northwick Park Hospital). Increasing the number of training slices, or using alternative experts, did not influence model accuracy significantly ADDIN EN.CITE <EndNote><Cite><Author>Chen</Author><Year>2015</Year><IDText>Identification of Cerebral Small Vessel Disease Using Multiple Instance Learning</IDText><DisplayText><style face="superscript">17</style></DisplayText><record><isbn>0302-9743</isbn><titles><title>Identification of Cerebral Small Vessel Disease Using Multiple Instance Learning</title><secondary-title>Medical Image Computing and Computer-Assisted Intervention (MICCAI 2015)</secondary-title></titles><pages>523-530</pages><contributors><authors><author>Chen, Liang</author><author>Tong, Tong</author><author>Pang Ho, Chin</author><author>Patel, Rajiv</author><author>Cohen, David</author><author>Dawson, Angela C</author><author>Halse, Omid</author><author>Geraghty, Olivia</author><author>Rinne, Paul</author><author>White, Christopher</author><author>Nakornchai, Tagore</author><author>Bentley, Paul</author><author>Rueckert, Daniel</author></authors></contributors><edition>18 Nov 2015</edition><added-date format="utc">1478181792</added-date><ref-type name="Journal Article">17</ref-type><dates><year>2015</year></dates><rec-number>534</rec-number><last-updated-date format="utc">1478182231</last-updated-date><electronic-resource-num>10.1007/978-3-319-24553-9_64</electronic-resource-num><volume>9349</volume></record></Cite></EndNote>17. From these images, 106 multiscale patches were generated randomly, classified according to whether the central pixel is labelled SVD or not, thus enabling a random-forest classifier to be constructed ADDIN EN.CITE <EndNote><Cite><Author>Liaw</Author><Year>2002</Year><IDText>Classification and regression by randomForest</IDText><DisplayText><style face="superscript">20</style></DisplayText><record><isbn>1609-3631</isbn><titles><title>Classification and regression by randomForest</title><secondary-title>R News</secondary-title></titles><pages>18-22</pages><contributors><authors><author>Liaw, Andy</author><author>Wiener, Matthew</author></authors></contributors><added-date format="utc">1478263044</added-date><ref-type name="Journal Article">17</ref-type><dates><year>2002</year></dates><rec-number>536</rec-number><last-updated-date format="utc">1478263185</last-updated-date><volume>2/3</volume></record></Cite></EndNote>20. For test images, the classifier generates a voxelwise WML probability map, modified by a prior probability map of cerebral WML location. The latter was generated from a separate cohort of 277 expert WML drawings on FLAIR-MRI, normalized into a common space. Optimization of probability thresholds for WML classification is performed with reference to the original 90 image delineations. WML lesion volume is calculated from the sum of suprathreshold WML voxels. For comparison with ordinal rating scores, Auto-estimated WML volume was thresholded into ranks equivalent in number to the score systemPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XYWhsdW5kPC9BdXRob3I+PFllYXI+MjAwMTwvWWVhcj48

SURUZXh0PkEgbmV3IHJhdGluZyBzY2FsZSBmb3IgYWdlLXJlbGF0ZWQgd2hpdGUgbWF0dGVyIGNo

YW5nZXMgYXBwbGljYWJsZSB0byBNUkkgYW5kIENULjwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5

bGUgZmFjZT0ic3VwZXJzY3JpcHQiPjEyLCAxNTwvc3R5bGU+PC9EaXNwbGF5VGV4dD48cmVjb3Jk

PjxkYXRlcz48cHViLWRhdGVzPjxkYXRlPkp1bjwvZGF0ZT48L3B1Yi1kYXRlcz48eWVhcj4yMDAx

PC95ZWFyPjwvZGF0ZXM+PGtleXdvcmRzPjxrZXl3b3JkPkFnaW5nPC9rZXl3b3JkPjxrZXl3b3Jk

PkJyYWluPC9rZXl3b3JkPjxrZXl3b3JkPkJyYWluIERpc2Vhc2VzPC9rZXl3b3JkPjxrZXl3b3Jk

PkNvZ25pdGlvbiBEaXNvcmRlcnM8L2tleXdvcmQ+PGtleXdvcmQ+RXVyb3BlPC9rZXl3b3JkPjxr

ZXl3b3JkPkh1bWFuczwva2V5d29yZD48a2V5d29yZD5NYWduZXRpYyBSZXNvbmFuY2UgSW1hZ2lu

Zzwva2V5d29yZD48a2V5d29yZD5NZW1vcnkgRGlzb3JkZXJzPC9rZXl3b3JkPjxrZXl3b3JkPk15

ZWxpbiBTaGVhdGg8L2tleXdvcmQ+PGtleXdvcmQ+T2JzZXJ2ZXIgVmFyaWF0aW9uPC9rZXl3b3Jk

PjxrZXl3b3JkPlByZWRpY3RpdmUgVmFsdWUgb2YgVGVzdHM8L2tleXdvcmQ+PGtleXdvcmQ+UmVw

cm9kdWNpYmlsaXR5IG9mIFJlc3VsdHM8L2tleXdvcmQ+PGtleXdvcmQ+U2Vuc2l0aXZpdHkgYW5k

IFNwZWNpZmljaXR5PC9rZXl3b3JkPjxrZXl3b3JkPlRvbW9ncmFwaHksIFgtUmF5IENvbXB1dGVk

PC9rZXl3b3JkPjwva2V5d29yZHM+PHVybHM+PHJlbGF0ZWQtdXJscz48dXJsPmh0dHA6Ly93d3cu

bmNiaS5ubG0ubmloLmdvdi9wdWJtZWQvMTEzODc0OTM8L3VybD48L3JlbGF0ZWQtdXJscz48L3Vy

bHM+PGlzYm4+MTUyNC00NjI4PC9pc2JuPjx0aXRsZXM+PHRpdGxlPkEgbmV3IHJhdGluZyBzY2Fs

ZSBmb3IgYWdlLXJlbGF0ZWQgd2hpdGUgbWF0dGVyIGNoYW5nZXMgYXBwbGljYWJsZSB0byBNUkkg

YW5kIENULjwvdGl0bGU+PHNlY29uZGFyeS10aXRsZT5TdHJva2U8L3NlY29uZGFyeS10aXRsZT48

L3RpdGxlcz48cGFnZXM+MTMxOC0yMjwvcGFnZXM+PG51bWJlcj42PC9udW1iZXI+PGNvbnRyaWJ1

dG9ycz48YXV0aG9ycz48YXV0aG9yPldhaGx1bmQsIEwuIE8uPC9hdXRob3I+PGF1dGhvcj5CYXJr

aG9mLCBGLjwvYXV0aG9yPjxhdXRob3I+RmF6ZWthcywgRi48L2F1dGhvcj48YXV0aG9yPkJyb25n

ZSwgTC48L2F1dGhvcj48YXV0aG9yPkF1Z3VzdGluLCBNLjwvYXV0aG9yPjxhdXRob3I+U2rDtmdy

ZW4sIE0uPC9hdXRob3I+PGF1dGhvcj5XYWxsaW4sIEEuPC9hdXRob3I+PGF1dGhvcj5BZGVyLCBI

LjwvYXV0aG9yPjxhdXRob3I+TGV5cywgRC48L2F1dGhvcj48YXV0aG9yPlBhbnRvbmksIEwuPC9h

dXRob3I+PGF1dGhvcj5QYXNxdWllciwgRi48L2F1dGhvcj48YXV0aG9yPkVya2luanVudHRpLCBU

LjwvYXV0aG9yPjxhdXRob3I+U2NoZWx0ZW5zLCBQLjwvYXV0aG9yPjxhdXRob3I+RXVyb3BlYW4g

VGFzayBGb3JjZSBvbiBBZ2UtUmVsYXRlZCBXaGl0ZSBNYXR0ZXIgQ2hhbmdlczwvYXV0aG9yPjwv

YXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3VhZ2U+ZW5nPC9sYW5ndWFnZT48YWRkZWQtZGF0

ZSBmb3JtYXQ9InV0YyI+MTMzNDkzNzY2NjwvYWRkZWQtZGF0ZT48cmVmLXR5cGUgbmFtZT0iSm91

cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PGF1dGgtYWRkcmVzcz5EZXBhcnRtZW50IG9mIENs

aW5pY2FsIE5ldXJvc2NpZW5jZSwgTkVVUk9URUMsIEthcm9saW5za2EgSW5zdGl0dXRldCBhdCBI

dWRkaW5nZSBVbml2ZXJzaXR5IEhvc3BpdGFsLCBIdWRkaW5nZSwgU3dlZGVuLiBsYXJzLW9sb2Yu

d2FobHVuZEBuZXVyb3RlYy5raS5zZTwvYXV0aC1hZGRyZXNzPjxyZWMtbnVtYmVyPjEzMzwvcmVj

LW51bWJlcj48bGFzdC11cGRhdGVkLWRhdGUgZm9ybWF0PSJ1dGMiPjEzMzQ5Mzc2NjY8L2xhc3Qt

dXBkYXRlZC1kYXRlPjxhY2Nlc3Npb24tbnVtPjExMzg3NDkzPC9hY2Nlc3Npb24tbnVtPjx2b2x1

bWU+MzI8L3ZvbHVtZT48L3JlY29yZD48L0NpdGU+PENpdGU+PEF1dGhvcj52YW4gU3dpZXRlbjwv

QXV0aG9yPjxZZWFyPjE5OTA8L1llYXI+PElEVGV4dD5HcmFkaW5nIHdoaXRlIG1hdHRlciBsZXNp

b25zIG9uIENUIGFuZCBNUkk6IGEgc2ltcGxlIHNjYWxlPC9JRFRleHQ+PHJlY29yZD48ZGF0ZXM+

PHB1Yi1kYXRlcz48ZGF0ZT5EZWM8L2RhdGU+PC9wdWItZGF0ZXM+PHllYXI+MTk5MDwveWVhcj48

L2RhdGVzPjxrZXl3b3Jkcz48a2V5d29yZD5CcmFpbjwva2V5d29yZD48a2V5d29yZD5CcmFpbiBE

aXNlYXNlczwva2V5d29yZD48a2V5d29yZD5Dcm9zcy1TZWN0aW9uYWwgU3R1ZGllczwva2V5d29y

ZD48a2V5d29yZD5EYXRhIEludGVycHJldGF0aW9uLCBTdGF0aXN0aWNhbDwva2V5d29yZD48a2V5

d29yZD5IdW1hbnM8L2tleXdvcmQ+PGtleXdvcmQ+SXNjaGVtaWMgQXR0YWNrLCBUcmFuc2llbnQ8

L2tleXdvcmQ+PGtleXdvcmQ+TG9uZ2l0dWRpbmFsIFN0dWRpZXM8L2tleXdvcmQ+PGtleXdvcmQ+

TWFnbmV0aWMgUmVzb25hbmNlIEltYWdpbmc8L2tleXdvcmQ+PGtleXdvcmQ+VG9tb2dyYXBoeSwg

WC1SYXkgQ29tcHV0ZWQ8L2tleXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1

cmw+aHR0cHM6Ly93d3cubmNiaS5ubG0ubmloLmdvdi9wdWJtZWQvMjI5MjcwMzwvdXJsPjwvcmVs

YXRlZC11cmxzPjwvdXJscz48aXNibj4wMDIyLTMwNTA8L2lzYm4+PGN1c3RvbTI+UE1DNDg4MzIw

PC9jdXN0b20yPjx0aXRsZXM+PHRpdGxlPkdyYWRpbmcgd2hpdGUgbWF0dGVyIGxlc2lvbnMgb24g

Q1QgYW5kIE1SSTogYSBzaW1wbGUgc2NhbGU8L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+SiBOZXVy

b2wgTmV1cm9zdXJnIFBzeWNoaWF0cnk8L3NlY29uZGFyeS10aXRsZT48L3RpdGxlcz48cGFnZXM+

MTA4MC0zPC9wYWdlcz48bnVtYmVyPjEyPC9udW1iZXI+PGNvbnRyaWJ1dG9ycz48YXV0aG9ycz48

YXV0aG9yPnZhbiBTd2lldGVuLCBKLiBDLjwvYXV0aG9yPjxhdXRob3I+SGlqZHJhLCBBLjwvYXV0

aG9yPjxhdXRob3I+S291ZHN0YWFsLCBQLiBKLjwvYXV0aG9yPjxhdXRob3I+dmFuIEdpam4sIEou

PC9hdXRob3I+PC9hdXRob3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5FTkc8L2xhbmd1YWdl

PjxhZGRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc4MTc3NjAwPC9hZGRlZC1kYXRlPjxyZWYtdHlw

ZSBuYW1lPSJKb3VybmFsIEFydGljbGUiPjE3PC9yZWYtdHlwZT48cmVjLW51bWJlcj41MzE8L3Jl

Yy1udW1iZXI+PGxhc3QtdXBkYXRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc4MTc3NjAwPC9sYXN0

LXVwZGF0ZWQtZGF0ZT48YWNjZXNzaW9uLW51bT4yMjkyNzAzPC9hY2Nlc3Npb24tbnVtPjx2b2x1

bWU+NTM8L3ZvbHVtZT48L3JlY29yZD48L0NpdGU+PC9FbmROb3RlPgAA

ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XYWhsdW5kPC9BdXRob3I+PFllYXI+MjAwMTwvWWVhcj48

SURUZXh0PkEgbmV3IHJhdGluZyBzY2FsZSBmb3IgYWdlLXJlbGF0ZWQgd2hpdGUgbWF0dGVyIGNo

YW5nZXMgYXBwbGljYWJsZSB0byBNUkkgYW5kIENULjwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5

bGUgZmFjZT0ic3VwZXJzY3JpcHQiPjEyLCAxNTwvc3R5bGU+PC9EaXNwbGF5VGV4dD48cmVjb3Jk

PjxkYXRlcz48cHViLWRhdGVzPjxkYXRlPkp1bjwvZGF0ZT48L3B1Yi1kYXRlcz48eWVhcj4yMDAx

PC95ZWFyPjwvZGF0ZXM+PGtleXdvcmRzPjxrZXl3b3JkPkFnaW5nPC9rZXl3b3JkPjxrZXl3b3Jk

PkJyYWluPC9rZXl3b3JkPjxrZXl3b3JkPkJyYWluIERpc2Vhc2VzPC9rZXl3b3JkPjxrZXl3b3Jk

PkNvZ25pdGlvbiBEaXNvcmRlcnM8L2tleXdvcmQ+PGtleXdvcmQ+RXVyb3BlPC9rZXl3b3JkPjxr

ZXl3b3JkPkh1bWFuczwva2V5d29yZD48a2V5d29yZD5NYWduZXRpYyBSZXNvbmFuY2UgSW1hZ2lu

Zzwva2V5d29yZD48a2V5d29yZD5NZW1vcnkgRGlzb3JkZXJzPC9rZXl3b3JkPjxrZXl3b3JkPk15

ZWxpbiBTaGVhdGg8L2tleXdvcmQ+PGtleXdvcmQ+T2JzZXJ2ZXIgVmFyaWF0aW9uPC9rZXl3b3Jk

PjxrZXl3b3JkPlByZWRpY3RpdmUgVmFsdWUgb2YgVGVzdHM8L2tleXdvcmQ+PGtleXdvcmQ+UmVw

cm9kdWNpYmlsaXR5IG9mIFJlc3VsdHM8L2tleXdvcmQ+PGtleXdvcmQ+U2Vuc2l0aXZpdHkgYW5k

IFNwZWNpZmljaXR5PC9rZXl3b3JkPjxrZXl3b3JkPlRvbW9ncmFwaHksIFgtUmF5IENvbXB1dGVk

PC9rZXl3b3JkPjwva2V5d29yZHM+PHVybHM+PHJlbGF0ZWQtdXJscz48dXJsPmh0dHA6Ly93d3cu

bmNiaS5ubG0ubmloLmdvdi9wdWJtZWQvMTEzODc0OTM8L3VybD48L3JlbGF0ZWQtdXJscz48L3Vy

bHM+PGlzYm4+MTUyNC00NjI4PC9pc2JuPjx0aXRsZXM+PHRpdGxlPkEgbmV3IHJhdGluZyBzY2Fs

ZSBmb3IgYWdlLXJlbGF0ZWQgd2hpdGUgbWF0dGVyIGNoYW5nZXMgYXBwbGljYWJsZSB0byBNUkkg

YW5kIENULjwvdGl0bGU+PHNlY29uZGFyeS10aXRsZT5TdHJva2U8L3NlY29uZGFyeS10aXRsZT48

L3RpdGxlcz48cGFnZXM+MTMxOC0yMjwvcGFnZXM+PG51bWJlcj42PC9udW1iZXI+PGNvbnRyaWJ1

dG9ycz48YXV0aG9ycz48YXV0aG9yPldhaGx1bmQsIEwuIE8uPC9hdXRob3I+PGF1dGhvcj5CYXJr

aG9mLCBGLjwvYXV0aG9yPjxhdXRob3I+RmF6ZWthcywgRi48L2F1dGhvcj48YXV0aG9yPkJyb25n

ZSwgTC48L2F1dGhvcj48YXV0aG9yPkF1Z3VzdGluLCBNLjwvYXV0aG9yPjxhdXRob3I+U2rDtmdy

ZW4sIE0uPC9hdXRob3I+PGF1dGhvcj5XYWxsaW4sIEEuPC9hdXRob3I+PGF1dGhvcj5BZGVyLCBI

LjwvYXV0aG9yPjxhdXRob3I+TGV5cywgRC48L2F1dGhvcj48YXV0aG9yPlBhbnRvbmksIEwuPC9h

dXRob3I+PGF1dGhvcj5QYXNxdWllciwgRi48L2F1dGhvcj48YXV0aG9yPkVya2luanVudHRpLCBU

LjwvYXV0aG9yPjxhdXRob3I+U2NoZWx0ZW5zLCBQLjwvYXV0aG9yPjxhdXRob3I+RXVyb3BlYW4g

VGFzayBGb3JjZSBvbiBBZ2UtUmVsYXRlZCBXaGl0ZSBNYXR0ZXIgQ2hhbmdlczwvYXV0aG9yPjwv

YXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3VhZ2U+ZW5nPC9sYW5ndWFnZT48YWRkZWQtZGF0

ZSBmb3JtYXQ9InV0YyI+MTMzNDkzNzY2NjwvYWRkZWQtZGF0ZT48cmVmLXR5cGUgbmFtZT0iSm91

cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PGF1dGgtYWRkcmVzcz5EZXBhcnRtZW50IG9mIENs

aW5pY2FsIE5ldXJvc2NpZW5jZSwgTkVVUk9URUMsIEthcm9saW5za2EgSW5zdGl0dXRldCBhdCBI

dWRkaW5nZSBVbml2ZXJzaXR5IEhvc3BpdGFsLCBIdWRkaW5nZSwgU3dlZGVuLiBsYXJzLW9sb2Yu

d2FobHVuZEBuZXVyb3RlYy5raS5zZTwvYXV0aC1hZGRyZXNzPjxyZWMtbnVtYmVyPjEzMzwvcmVj

LW51bWJlcj48bGFzdC11cGRhdGVkLWRhdGUgZm9ybWF0PSJ1dGMiPjEzMzQ5Mzc2NjY8L2xhc3Qt

dXBkYXRlZC1kYXRlPjxhY2Nlc3Npb24tbnVtPjExMzg3NDkzPC9hY2Nlc3Npb24tbnVtPjx2b2x1

bWU+MzI8L3ZvbHVtZT48L3JlY29yZD48L0NpdGU+PENpdGU+PEF1dGhvcj52YW4gU3dpZXRlbjwv

QXV0aG9yPjxZZWFyPjE5OTA8L1llYXI+PElEVGV4dD5HcmFkaW5nIHdoaXRlIG1hdHRlciBsZXNp

b25zIG9uIENUIGFuZCBNUkk6IGEgc2ltcGxlIHNjYWxlPC9JRFRleHQ+PHJlY29yZD48ZGF0ZXM+

PHB1Yi1kYXRlcz48ZGF0ZT5EZWM8L2RhdGU+PC9wdWItZGF0ZXM+PHllYXI+MTk5MDwveWVhcj48

L2RhdGVzPjxrZXl3b3Jkcz48a2V5d29yZD5CcmFpbjwva2V5d29yZD48a2V5d29yZD5CcmFpbiBE

aXNlYXNlczwva2V5d29yZD48a2V5d29yZD5Dcm9zcy1TZWN0aW9uYWwgU3R1ZGllczwva2V5d29y

ZD48a2V5d29yZD5EYXRhIEludGVycHJldGF0aW9uLCBTdGF0aXN0aWNhbDwva2V5d29yZD48a2V5

d29yZD5IdW1hbnM8L2tleXdvcmQ+PGtleXdvcmQ+SXNjaGVtaWMgQXR0YWNrLCBUcmFuc2llbnQ8

L2tleXdvcmQ+PGtleXdvcmQ+TG9uZ2l0dWRpbmFsIFN0dWRpZXM8L2tleXdvcmQ+PGtleXdvcmQ+

TWFnbmV0aWMgUmVzb25hbmNlIEltYWdpbmc8L2tleXdvcmQ+PGtleXdvcmQ+VG9tb2dyYXBoeSwg

WC1SYXkgQ29tcHV0ZWQ8L2tleXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1

cmw+aHR0cHM6Ly93d3cubmNiaS5ubG0ubmloLmdvdi9wdWJtZWQvMjI5MjcwMzwvdXJsPjwvcmVs

YXRlZC11cmxzPjwvdXJscz48aXNibj4wMDIyLTMwNTA8L2lzYm4+PGN1c3RvbTI+UE1DNDg4MzIw

PC9jdXN0b20yPjx0aXRsZXM+PHRpdGxlPkdyYWRpbmcgd2hpdGUgbWF0dGVyIGxlc2lvbnMgb24g

Q1QgYW5kIE1SSTogYSBzaW1wbGUgc2NhbGU8L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+SiBOZXVy

b2wgTmV1cm9zdXJnIFBzeWNoaWF0cnk8L3NlY29uZGFyeS10aXRsZT48L3RpdGxlcz48cGFnZXM+

MTA4MC0zPC9wYWdlcz48bnVtYmVyPjEyPC9udW1iZXI+PGNvbnRyaWJ1dG9ycz48YXV0aG9ycz48

YXV0aG9yPnZhbiBTd2lldGVuLCBKLiBDLjwvYXV0aG9yPjxhdXRob3I+SGlqZHJhLCBBLjwvYXV0

aG9yPjxhdXRob3I+S291ZHN0YWFsLCBQLiBKLjwvYXV0aG9yPjxhdXRob3I+dmFuIEdpam4sIEou

PC9hdXRob3I+PC9hdXRob3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5FTkc8L2xhbmd1YWdl

PjxhZGRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc4MTc3NjAwPC9hZGRlZC1kYXRlPjxyZWYtdHlw

ZSBuYW1lPSJKb3VybmFsIEFydGljbGUiPjE3PC9yZWYtdHlwZT48cmVjLW51bWJlcj41MzE8L3Jl

Yy1udW1iZXI+PGxhc3QtdXBkYXRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc4MTc3NjAwPC9sYXN0

LXVwZGF0ZWQtZGF0ZT48YWNjZXNzaW9uLW51bT4yMjkyNzAzPC9hY2Nlc3Npb24tbnVtPjx2b2x1

bWU+NTM8L3ZvbHVtZT48L3JlY29yZD48L0NpdGU+PC9FbmROb3RlPgAA

ADDIN EN.CITE.DATA 12, 15 used by experts (4 or 3; see also next section). Thresholds were derived from both an unsupervised histogram method (for Wahlund ratingPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XYWhsdW5kPC9BdXRob3I+PFllYXI+MjAwMTwvWWVhcj48

SURUZXh0PkEgbmV3IHJhdGluZyBzY2FsZSBmb3IgYWdlLXJlbGF0ZWQgd2hpdGUgbWF0dGVyIGNo

YW5nZXMgYXBwbGljYWJsZSB0byBNUkkgYW5kIENULjwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5

bGUgZmFjZT0ic3VwZXJzY3JpcHQiPjEyPC9zdHlsZT48L0Rpc3BsYXlUZXh0PjxyZWNvcmQ+PGRh

dGVzPjxwdWItZGF0ZXM+PGRhdGU+SnVuPC9kYXRlPjwvcHViLWRhdGVzPjx5ZWFyPjIwMDE8L3ll

YXI+PC9kYXRlcz48a2V5d29yZHM+PGtleXdvcmQ+QWdpbmc8L2tleXdvcmQ+PGtleXdvcmQ+QnJh

aW48L2tleXdvcmQ+PGtleXdvcmQ+QnJhaW4gRGlzZWFzZXM8L2tleXdvcmQ+PGtleXdvcmQ+Q29n

bml0aW9uIERpc29yZGVyczwva2V5d29yZD48a2V5d29yZD5FdXJvcGU8L2tleXdvcmQ+PGtleXdv

cmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPk1hZ25ldGljIFJlc29uYW5jZSBJbWFnaW5nPC9r

ZXl3b3JkPjxrZXl3b3JkPk1lbW9yeSBEaXNvcmRlcnM8L2tleXdvcmQ+PGtleXdvcmQ+TXllbGlu

IFNoZWF0aDwva2V5d29yZD48a2V5d29yZD5PYnNlcnZlciBWYXJpYXRpb248L2tleXdvcmQ+PGtl

eXdvcmQ+UHJlZGljdGl2ZSBWYWx1ZSBvZiBUZXN0czwva2V5d29yZD48a2V5d29yZD5SZXByb2R1

Y2liaWxpdHkgb2YgUmVzdWx0czwva2V5d29yZD48a2V5d29yZD5TZW5zaXRpdml0eSBhbmQgU3Bl

Y2lmaWNpdHk8L2tleXdvcmQ+PGtleXdvcmQ+VG9tb2dyYXBoeSwgWC1SYXkgQ29tcHV0ZWQ8L2tl

eXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cDovL3d3dy5uY2Jp

Lm5sbS5uaWguZ292L3B1Ym1lZC8xMTM4NzQ5MzwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJscz48

aXNibj4xNTI0LTQ2Mjg8L2lzYm4+PHRpdGxlcz48dGl0bGU+QSBuZXcgcmF0aW5nIHNjYWxlIGZv

ciBhZ2UtcmVsYXRlZCB3aGl0ZSBtYXR0ZXIgY2hhbmdlcyBhcHBsaWNhYmxlIHRvIE1SSSBhbmQg

Q1QuPC90aXRsZT48c2Vjb25kYXJ5LXRpdGxlPlN0cm9rZTwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0

bGVzPjxwYWdlcz4xMzE4LTIyPC9wYWdlcz48bnVtYmVyPjY8L251bWJlcj48Y29udHJpYnV0b3Jz

PjxhdXRob3JzPjxhdXRob3I+V2FobHVuZCwgTC4gTy48L2F1dGhvcj48YXV0aG9yPkJhcmtob2Ys

IEYuPC9hdXRob3I+PGF1dGhvcj5GYXpla2FzLCBGLjwvYXV0aG9yPjxhdXRob3I+QnJvbmdlLCBM

LjwvYXV0aG9yPjxhdXRob3I+QXVndXN0aW4sIE0uPC9hdXRob3I+PGF1dGhvcj5TasO2Z3Jlbiwg

TS48L2F1dGhvcj48YXV0aG9yPldhbGxpbiwgQS48L2F1dGhvcj48YXV0aG9yPkFkZXIsIEguPC9h

dXRob3I+PGF1dGhvcj5MZXlzLCBELjwvYXV0aG9yPjxhdXRob3I+UGFudG9uaSwgTC48L2F1dGhv

cj48YXV0aG9yPlBhc3F1aWVyLCBGLjwvYXV0aG9yPjxhdXRob3I+RXJraW5qdW50dGksIFQuPC9h

dXRob3I+PGF1dGhvcj5TY2hlbHRlbnMsIFAuPC9hdXRob3I+PGF1dGhvcj5FdXJvcGVhbiBUYXNr

IEZvcmNlIG9uIEFnZS1SZWxhdGVkIFdoaXRlIE1hdHRlciBDaGFuZ2VzPC9hdXRob3I+PC9hdXRo

b3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5lbmc8L2xhbmd1YWdlPjxhZGRlZC1kYXRlIGZv

cm1hdD0idXRjIj4xMzM0OTM3NjY2PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1lPSJKb3VybmFs

IEFydGljbGUiPjE3PC9yZWYtdHlwZT48YXV0aC1hZGRyZXNzPkRlcGFydG1lbnQgb2YgQ2xpbmlj

YWwgTmV1cm9zY2llbmNlLCBORVVST1RFQywgS2Fyb2xpbnNrYSBJbnN0aXR1dGV0IGF0IEh1ZGRp

bmdlIFVuaXZlcnNpdHkgSG9zcGl0YWwsIEh1ZGRpbmdlLCBTd2VkZW4uIGxhcnMtb2xvZi53YWhs

dW5kQG5ldXJvdGVjLmtpLnNlPC9hdXRoLWFkZHJlc3M+PHJlYy1udW1iZXI+MTMzPC9yZWMtbnVt

YmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTMzNDkzNzY2NjwvbGFzdC11cGRh

dGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MTEzODc0OTM8L2FjY2Vzc2lvbi1udW0+PHZvbHVtZT4z

Mjwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48L0VuZE5vdGU+AAA=

ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XYWhsdW5kPC9BdXRob3I+PFllYXI+MjAwMTwvWWVhcj48

SURUZXh0PkEgbmV3IHJhdGluZyBzY2FsZSBmb3IgYWdlLXJlbGF0ZWQgd2hpdGUgbWF0dGVyIGNo

YW5nZXMgYXBwbGljYWJsZSB0byBNUkkgYW5kIENULjwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5

bGUgZmFjZT0ic3VwZXJzY3JpcHQiPjEyPC9zdHlsZT48L0Rpc3BsYXlUZXh0PjxyZWNvcmQ+PGRh

dGVzPjxwdWItZGF0ZXM+PGRhdGU+SnVuPC9kYXRlPjwvcHViLWRhdGVzPjx5ZWFyPjIwMDE8L3ll

YXI+PC9kYXRlcz48a2V5d29yZHM+PGtleXdvcmQ+QWdpbmc8L2tleXdvcmQ+PGtleXdvcmQ+QnJh

aW48L2tleXdvcmQ+PGtleXdvcmQ+QnJhaW4gRGlzZWFzZXM8L2tleXdvcmQ+PGtleXdvcmQ+Q29n

bml0aW9uIERpc29yZGVyczwva2V5d29yZD48a2V5d29yZD5FdXJvcGU8L2tleXdvcmQ+PGtleXdv

cmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPk1hZ25ldGljIFJlc29uYW5jZSBJbWFnaW5nPC9r

ZXl3b3JkPjxrZXl3b3JkPk1lbW9yeSBEaXNvcmRlcnM8L2tleXdvcmQ+PGtleXdvcmQ+TXllbGlu

IFNoZWF0aDwva2V5d29yZD48a2V5d29yZD5PYnNlcnZlciBWYXJpYXRpb248L2tleXdvcmQ+PGtl

eXdvcmQ+UHJlZGljdGl2ZSBWYWx1ZSBvZiBUZXN0czwva2V5d29yZD48a2V5d29yZD5SZXByb2R1

Y2liaWxpdHkgb2YgUmVzdWx0czwva2V5d29yZD48a2V5d29yZD5TZW5zaXRpdml0eSBhbmQgU3Bl

Y2lmaWNpdHk8L2tleXdvcmQ+PGtleXdvcmQ+VG9tb2dyYXBoeSwgWC1SYXkgQ29tcHV0ZWQ8L2tl

eXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cDovL3d3dy5uY2Jp

Lm5sbS5uaWguZ292L3B1Ym1lZC8xMTM4NzQ5MzwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJscz48

aXNibj4xNTI0LTQ2Mjg8L2lzYm4+PHRpdGxlcz48dGl0bGU+QSBuZXcgcmF0aW5nIHNjYWxlIGZv

ciBhZ2UtcmVsYXRlZCB3aGl0ZSBtYXR0ZXIgY2hhbmdlcyBhcHBsaWNhYmxlIHRvIE1SSSBhbmQg

Q1QuPC90aXRsZT48c2Vjb25kYXJ5LXRpdGxlPlN0cm9rZTwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0

bGVzPjxwYWdlcz4xMzE4LTIyPC9wYWdlcz48bnVtYmVyPjY8L251bWJlcj48Y29udHJpYnV0b3Jz

PjxhdXRob3JzPjxhdXRob3I+V2FobHVuZCwgTC4gTy48L2F1dGhvcj48YXV0aG9yPkJhcmtob2Ys

IEYuPC9hdXRob3I+PGF1dGhvcj5GYXpla2FzLCBGLjwvYXV0aG9yPjxhdXRob3I+QnJvbmdlLCBM

LjwvYXV0aG9yPjxhdXRob3I+QXVndXN0aW4sIE0uPC9hdXRob3I+PGF1dGhvcj5TasO2Z3Jlbiwg

TS48L2F1dGhvcj48YXV0aG9yPldhbGxpbiwgQS48L2F1dGhvcj48YXV0aG9yPkFkZXIsIEguPC9h

dXRob3I+PGF1dGhvcj5MZXlzLCBELjwvYXV0aG9yPjxhdXRob3I+UGFudG9uaSwgTC48L2F1dGhv

cj48YXV0aG9yPlBhc3F1aWVyLCBGLjwvYXV0aG9yPjxhdXRob3I+RXJraW5qdW50dGksIFQuPC9h

dXRob3I+PGF1dGhvcj5TY2hlbHRlbnMsIFAuPC9hdXRob3I+PGF1dGhvcj5FdXJvcGVhbiBUYXNr

IEZvcmNlIG9uIEFnZS1SZWxhdGVkIFdoaXRlIE1hdHRlciBDaGFuZ2VzPC9hdXRob3I+PC9hdXRo

b3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5lbmc8L2xhbmd1YWdlPjxhZGRlZC1kYXRlIGZv

cm1hdD0idXRjIj4xMzM0OTM3NjY2PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1lPSJKb3VybmFs

IEFydGljbGUiPjE3PC9yZWYtdHlwZT48YXV0aC1hZGRyZXNzPkRlcGFydG1lbnQgb2YgQ2xpbmlj

YWwgTmV1cm9zY2llbmNlLCBORVVST1RFQywgS2Fyb2xpbnNrYSBJbnN0aXR1dGV0IGF0IEh1ZGRp

bmdlIFVuaXZlcnNpdHkgSG9zcGl0YWwsIEh1ZGRpbmdlLCBTd2VkZW4uIGxhcnMtb2xvZi53YWhs

dW5kQG5ldXJvdGVjLmtpLnNlPC9hdXRoLWFkZHJlc3M+PHJlYy1udW1iZXI+MTMzPC9yZWMtbnVt

YmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTMzNDkzNzY2NjwvbGFzdC11cGRh

dGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MTEzODc0OTM8L2FjY2Vzc2lvbi1udW0+PHZvbHVtZT4z

Mjwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48L0VuZE5vdGU+AAA=

ADDIN EN.CITE.DATA 12 validation); and a supervised method using ratings from half the dataset to optimize thresholds for the other half (for van Swieten ADDIN EN.CITE <EndNote><Cite><Author>van Swieten</Author><Year>1990</Year><IDText>Grading white matter lesions on CT and MRI: a simple scale</IDText><DisplayText><style face="superscript">15</style></DisplayText><record><dates><pub-dates><date>Dec</date></pub-dates><year>1990</year></dates><keywords><keyword>Brain</keyword><keyword>Brain Diseases</keyword><keyword>Cross-Sectional Studies</keyword><keyword>Data Interpretation, Statistical</keyword><keyword>Humans</keyword><keyword>Ischemic Attack, Transient</keyword><keyword>Longitudinal Studies</keyword><keyword>Magnetic Resonance Imaging</keyword><keyword>Tomography, X-Ray Computed</keyword></keywords><urls><related-urls><url> white matter lesions on CT and MRI: a simple scale</title><secondary-title>J Neurol Neurosurg Psychiatry</secondary-title></titles><pages>1080-3</pages><number>12</number><contributors><authors><author>van Swieten, J. C.</author><author>Hijdra, A.</author><author>Koudstaal, P. J.</author><author>van Gijn, J.</author></authors></contributors><language>ENG</language><added-date format="utc">1478177600</added-date><ref-type name="Journal Article">17</ref-type><rec-number>531</rec-number><last-updated-date format="utc">1478177600</last-updated-date><accession-num>2292703</accession-num><volume>53</volume></record></Cite></EndNote>15 rating method: these were excluded for validation testing of Auto ratings; but all cases were used for correlations of ratings with Auto volumes). All images used for training and testing were first resampled into a common dimensional space (allowing for differences in slice thickness within and between images), skull-stripped, and co-registered into a common template space ADDIN EN.CITE <EndNote><Cite><Author>Rueckert</Author><Year>1999</Year><IDText>Nonrigid registration using free-form deformations: application to breast MR images</IDText><DisplayText><style face="superscript">21</style></DisplayText><record><dates><pub-dates><date>Aug</date></pub-dates><year>1999</year></dates><keywords><keyword>Breast</keyword><keyword>Female</keyword><keyword>Humans</keyword><keyword>Image Processing, Computer-Assisted</keyword><keyword>Magnetic Resonance Imaging</keyword></keywords><urls><related-urls><url> registration using free-form deformations: application to breast MR images</title><secondary-title>IEEE Trans Med Imaging</secondary-title></titles><pages>712-21</pages><number>8</number><contributors><authors><author>Rueckert, D.</author><author>Sonoda, L. I.</author><author>Hayes, C.</author><author>Hill, D. L.</author><author>Leach, M. O.</author><author>Hawkes, D. J.</author></authors></contributors><language>ENG</language><added-date format="utc">1478259678</added-date><ref-type name="Journal Article">17</ref-type><rec-number>535</rec-number><last-updated-date format="utc">1478259678</last-updated-date><accession-num>10534053</accession-num><electronic-resource-num>10.1109/42.796284</electronic-resource-num><volume>18</volume></record></Cite></EndNote>21 (Fig. 1B). Expert WML drawings and ratingsExperts were neuroradiologists or stroke physicians with >5 years of regular stroke experience. Those who performed validation drawings or ratings of WML were different to those who contributed to model training. Experts were trained in WML rating scores and/or digital lesion drawings prior to their assessments. Digital drawings were performed using MRICroN software (mccauslandcenter.sc.edu/crnl/mricron/), wherein CT window settings could be adjusted by the expert to their own preference. FLAIR-MRIs were also annotated for WML, after first being aligned with each patient’s contemporaneous CT ADDIN EN.CITE <EndNote><Cite><Author>Rueckert</Author><Year>1999</Year><IDText>Nonrigid registration using free-form deformations: application to breast MR images</IDText><DisplayText><style face="superscript">21</style></DisplayText><record><dates><pub-dates><date>Aug</date></pub-dates><year>1999</year></dates><keywords><keyword>Breast</keyword><keyword>Female</keyword><keyword>Humans</keyword><keyword>Image Processing, Computer-Assisted</keyword><keyword>Magnetic Resonance Imaging</keyword></keywords><urls><related-urls><url> registration using free-form deformations: application to breast MR images</title><secondary-title>IEEE Trans Med Imaging</secondary-title></titles><pages>712-21</pages><number>8</number><contributors><authors><author>Rueckert, D.</author><author>Sonoda, L. I.</author><author>Hayes, C.</author><author>Hill, D. L.</author><author>Leach, M. O.</author><author>Hawkes, D. J.</author></authors></contributors><language>ENG</language><added-date format="utc">1478259678</added-date><ref-type name="Journal Article">17</ref-type><rec-number>535</rec-number><last-updated-date format="utc">1478259678</last-updated-date><accession-num>10534053</accession-num><electronic-resource-num>10.1109/42.796284</electronic-resource-num><volume>18</volume></record></Cite></EndNote>21, so as to minimise CT/MRI differences in WML appearances caused by variations in slice orientation. CT WML ratings used either the WahlundPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XYWhsdW5kPC9BdXRob3I+PFllYXI+MjAwMTwvWWVhcj48

SURUZXh0PkEgbmV3IHJhdGluZyBzY2FsZSBmb3IgYWdlLXJlbGF0ZWQgd2hpdGUgbWF0dGVyIGNo

YW5nZXMgYXBwbGljYWJsZSB0byBNUkkgYW5kIENULjwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5

bGUgZmFjZT0ic3VwZXJzY3JpcHQiPjEyPC9zdHlsZT48L0Rpc3BsYXlUZXh0PjxyZWNvcmQ+PGRh

dGVzPjxwdWItZGF0ZXM+PGRhdGU+SnVuPC9kYXRlPjwvcHViLWRhdGVzPjx5ZWFyPjIwMDE8L3ll

YXI+PC9kYXRlcz48a2V5d29yZHM+PGtleXdvcmQ+QWdpbmc8L2tleXdvcmQ+PGtleXdvcmQ+QnJh

aW48L2tleXdvcmQ+PGtleXdvcmQ+QnJhaW4gRGlzZWFzZXM8L2tleXdvcmQ+PGtleXdvcmQ+Q29n

bml0aW9uIERpc29yZGVyczwva2V5d29yZD48a2V5d29yZD5FdXJvcGU8L2tleXdvcmQ+PGtleXdv

cmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPk1hZ25ldGljIFJlc29uYW5jZSBJbWFnaW5nPC9r

ZXl3b3JkPjxrZXl3b3JkPk1lbW9yeSBEaXNvcmRlcnM8L2tleXdvcmQ+PGtleXdvcmQ+TXllbGlu

IFNoZWF0aDwva2V5d29yZD48a2V5d29yZD5PYnNlcnZlciBWYXJpYXRpb248L2tleXdvcmQ+PGtl

eXdvcmQ+UHJlZGljdGl2ZSBWYWx1ZSBvZiBUZXN0czwva2V5d29yZD48a2V5d29yZD5SZXByb2R1

Y2liaWxpdHkgb2YgUmVzdWx0czwva2V5d29yZD48a2V5d29yZD5TZW5zaXRpdml0eSBhbmQgU3Bl

Y2lmaWNpdHk8L2tleXdvcmQ+PGtleXdvcmQ+VG9tb2dyYXBoeSwgWC1SYXkgQ29tcHV0ZWQ8L2tl

eXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cDovL3d3dy5uY2Jp

Lm5sbS5uaWguZ292L3B1Ym1lZC8xMTM4NzQ5MzwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJscz48

aXNibj4xNTI0LTQ2Mjg8L2lzYm4+PHRpdGxlcz48dGl0bGU+QSBuZXcgcmF0aW5nIHNjYWxlIGZv

ciBhZ2UtcmVsYXRlZCB3aGl0ZSBtYXR0ZXIgY2hhbmdlcyBhcHBsaWNhYmxlIHRvIE1SSSBhbmQg

Q1QuPC90aXRsZT48c2Vjb25kYXJ5LXRpdGxlPlN0cm9rZTwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0

bGVzPjxwYWdlcz4xMzE4LTIyPC9wYWdlcz48bnVtYmVyPjY8L251bWJlcj48Y29udHJpYnV0b3Jz

PjxhdXRob3JzPjxhdXRob3I+V2FobHVuZCwgTC4gTy48L2F1dGhvcj48YXV0aG9yPkJhcmtob2Ys

IEYuPC9hdXRob3I+PGF1dGhvcj5GYXpla2FzLCBGLjwvYXV0aG9yPjxhdXRob3I+QnJvbmdlLCBM

LjwvYXV0aG9yPjxhdXRob3I+QXVndXN0aW4sIE0uPC9hdXRob3I+PGF1dGhvcj5TasO2Z3Jlbiwg

TS48L2F1dGhvcj48YXV0aG9yPldhbGxpbiwgQS48L2F1dGhvcj48YXV0aG9yPkFkZXIsIEguPC9h

dXRob3I+PGF1dGhvcj5MZXlzLCBELjwvYXV0aG9yPjxhdXRob3I+UGFudG9uaSwgTC48L2F1dGhv

cj48YXV0aG9yPlBhc3F1aWVyLCBGLjwvYXV0aG9yPjxhdXRob3I+RXJraW5qdW50dGksIFQuPC9h

dXRob3I+PGF1dGhvcj5TY2hlbHRlbnMsIFAuPC9hdXRob3I+PGF1dGhvcj5FdXJvcGVhbiBUYXNr

IEZvcmNlIG9uIEFnZS1SZWxhdGVkIFdoaXRlIE1hdHRlciBDaGFuZ2VzPC9hdXRob3I+PC9hdXRo

b3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5lbmc8L2xhbmd1YWdlPjxhZGRlZC1kYXRlIGZv

cm1hdD0idXRjIj4xMzM0OTM3NjY2PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1lPSJKb3VybmFs

IEFydGljbGUiPjE3PC9yZWYtdHlwZT48YXV0aC1hZGRyZXNzPkRlcGFydG1lbnQgb2YgQ2xpbmlj

YWwgTmV1cm9zY2llbmNlLCBORVVST1RFQywgS2Fyb2xpbnNrYSBJbnN0aXR1dGV0IGF0IEh1ZGRp

bmdlIFVuaXZlcnNpdHkgSG9zcGl0YWwsIEh1ZGRpbmdlLCBTd2VkZW4uIGxhcnMtb2xvZi53YWhs

dW5kQG5ldXJvdGVjLmtpLnNlPC9hdXRoLWFkZHJlc3M+PHJlYy1udW1iZXI+MTMzPC9yZWMtbnVt

YmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTMzNDkzNzY2NjwvbGFzdC11cGRh

dGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MTEzODc0OTM8L2FjY2Vzc2lvbi1udW0+PHZvbHVtZT4z

Mjwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48L0VuZE5vdGU+AAA=

ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XYWhsdW5kPC9BdXRob3I+PFllYXI+MjAwMTwvWWVhcj48

SURUZXh0PkEgbmV3IHJhdGluZyBzY2FsZSBmb3IgYWdlLXJlbGF0ZWQgd2hpdGUgbWF0dGVyIGNo

YW5nZXMgYXBwbGljYWJsZSB0byBNUkkgYW5kIENULjwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5

bGUgZmFjZT0ic3VwZXJzY3JpcHQiPjEyPC9zdHlsZT48L0Rpc3BsYXlUZXh0PjxyZWNvcmQ+PGRh

dGVzPjxwdWItZGF0ZXM+PGRhdGU+SnVuPC9kYXRlPjwvcHViLWRhdGVzPjx5ZWFyPjIwMDE8L3ll

YXI+PC9kYXRlcz48a2V5d29yZHM+PGtleXdvcmQ+QWdpbmc8L2tleXdvcmQ+PGtleXdvcmQ+QnJh

aW48L2tleXdvcmQ+PGtleXdvcmQ+QnJhaW4gRGlzZWFzZXM8L2tleXdvcmQ+PGtleXdvcmQ+Q29n

bml0aW9uIERpc29yZGVyczwva2V5d29yZD48a2V5d29yZD5FdXJvcGU8L2tleXdvcmQ+PGtleXdv

cmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPk1hZ25ldGljIFJlc29uYW5jZSBJbWFnaW5nPC9r

ZXl3b3JkPjxrZXl3b3JkPk1lbW9yeSBEaXNvcmRlcnM8L2tleXdvcmQ+PGtleXdvcmQ+TXllbGlu

IFNoZWF0aDwva2V5d29yZD48a2V5d29yZD5PYnNlcnZlciBWYXJpYXRpb248L2tleXdvcmQ+PGtl

eXdvcmQ+UHJlZGljdGl2ZSBWYWx1ZSBvZiBUZXN0czwva2V5d29yZD48a2V5d29yZD5SZXByb2R1

Y2liaWxpdHkgb2YgUmVzdWx0czwva2V5d29yZD48a2V5d29yZD5TZW5zaXRpdml0eSBhbmQgU3Bl

Y2lmaWNpdHk8L2tleXdvcmQ+PGtleXdvcmQ+VG9tb2dyYXBoeSwgWC1SYXkgQ29tcHV0ZWQ8L2tl

eXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cDovL3d3dy5uY2Jp

Lm5sbS5uaWguZ292L3B1Ym1lZC8xMTM4NzQ5MzwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJscz48

aXNibj4xNTI0LTQ2Mjg8L2lzYm4+PHRpdGxlcz48dGl0bGU+QSBuZXcgcmF0aW5nIHNjYWxlIGZv

ciBhZ2UtcmVsYXRlZCB3aGl0ZSBtYXR0ZXIgY2hhbmdlcyBhcHBsaWNhYmxlIHRvIE1SSSBhbmQg

Q1QuPC90aXRsZT48c2Vjb25kYXJ5LXRpdGxlPlN0cm9rZTwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0

bGVzPjxwYWdlcz4xMzE4LTIyPC9wYWdlcz48bnVtYmVyPjY8L251bWJlcj48Y29udHJpYnV0b3Jz

PjxhdXRob3JzPjxhdXRob3I+V2FobHVuZCwgTC4gTy48L2F1dGhvcj48YXV0aG9yPkJhcmtob2Ys

IEYuPC9hdXRob3I+PGF1dGhvcj5GYXpla2FzLCBGLjwvYXV0aG9yPjxhdXRob3I+QnJvbmdlLCBM

LjwvYXV0aG9yPjxhdXRob3I+QXVndXN0aW4sIE0uPC9hdXRob3I+PGF1dGhvcj5TasO2Z3Jlbiwg

TS48L2F1dGhvcj48YXV0aG9yPldhbGxpbiwgQS48L2F1dGhvcj48YXV0aG9yPkFkZXIsIEguPC9h

dXRob3I+PGF1dGhvcj5MZXlzLCBELjwvYXV0aG9yPjxhdXRob3I+UGFudG9uaSwgTC48L2F1dGhv

cj48YXV0aG9yPlBhc3F1aWVyLCBGLjwvYXV0aG9yPjxhdXRob3I+RXJraW5qdW50dGksIFQuPC9h

dXRob3I+PGF1dGhvcj5TY2hlbHRlbnMsIFAuPC9hdXRob3I+PGF1dGhvcj5FdXJvcGVhbiBUYXNr

IEZvcmNlIG9uIEFnZS1SZWxhdGVkIFdoaXRlIE1hdHRlciBDaGFuZ2VzPC9hdXRob3I+PC9hdXRo

b3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5lbmc8L2xhbmd1YWdlPjxhZGRlZC1kYXRlIGZv

cm1hdD0idXRjIj4xMzM0OTM3NjY2PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1lPSJKb3VybmFs

IEFydGljbGUiPjE3PC9yZWYtdHlwZT48YXV0aC1hZGRyZXNzPkRlcGFydG1lbnQgb2YgQ2xpbmlj

YWwgTmV1cm9zY2llbmNlLCBORVVST1RFQywgS2Fyb2xpbnNrYSBJbnN0aXR1dGV0IGF0IEh1ZGRp

bmdlIFVuaXZlcnNpdHkgSG9zcGl0YWwsIEh1ZGRpbmdlLCBTd2VkZW4uIGxhcnMtb2xvZi53YWhs

dW5kQG5ldXJvdGVjLmtpLnNlPC9hdXRoLWFkZHJlc3M+PHJlYy1udW1iZXI+MTMzPC9yZWMtbnVt

YmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTMzNDkzNzY2NjwvbGFzdC11cGRh

dGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MTEzODc0OTM8L2FjY2Vzc2lvbi1udW0+PHZvbHVtZT4z

Mjwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48L0VuZE5vdGU+AAA=

ADDIN EN.CITE.DATA 12 or van Swieten ADDIN EN.CITE <EndNote><Cite><Author>van Swieten</Author><Year>1990</Year><IDText>Grading white matter lesions on CT and MRI: a simple scale</IDText><DisplayText><style face="superscript">15</style></DisplayText><record><dates><pub-dates><date>Dec</date></pub-dates><year>1990</year></dates><keywords><keyword>Brain</keyword><keyword>Brain Diseases</keyword><keyword>Cross-Sectional Studies</keyword><keyword>Data Interpretation, Statistical</keyword><keyword>Humans</keyword><keyword>Ischemic Attack, Transient</keyword><keyword>Longitudinal Studies</keyword><keyword>Magnetic Resonance Imaging</keyword><keyword>Tomography, X-Ray Computed</keyword></keywords><urls><related-urls><url> white matter lesions on CT and MRI: a simple scale</title><secondary-title>J Neurol Neurosurg Psychiatry</secondary-title></titles><pages>1080-3</pages><number>12</number><contributors><authors><author>van Swieten, J. C.</author><author>Hijdra, A.</author><author>Koudstaal, P. J.</author><author>van Gijn, J.</author></authors></contributors><language>ENG</language><added-date format="utc">1478177600</added-date><ref-type name="Journal Article">17</ref-type><rec-number>531</rec-number><last-updated-date format="utc">1478177600</last-updated-date><accession-num>2292703</accession-num><volume>53</volume></record></Cite></EndNote>15 scoring systems, reflecting 4 or 3 grades of WML severity respectively. For the Wahlund system, experts were asked to record the median WML score across frontal, parieto-occipital and temporal regionsPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XYWhsdW5kPC9BdXRob3I+PFllYXI+MjAwMTwvWWVhcj48

SURUZXh0PkEgbmV3IHJhdGluZyBzY2FsZSBmb3IgYWdlLXJlbGF0ZWQgd2hpdGUgbWF0dGVyIGNo

YW5nZXMgYXBwbGljYWJsZSB0byBNUkkgYW5kIENULjwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5

bGUgZmFjZT0ic3VwZXJzY3JpcHQiPjEyPC9zdHlsZT48L0Rpc3BsYXlUZXh0PjxyZWNvcmQ+PGRh

dGVzPjxwdWItZGF0ZXM+PGRhdGU+SnVuPC9kYXRlPjwvcHViLWRhdGVzPjx5ZWFyPjIwMDE8L3ll

YXI+PC9kYXRlcz48a2V5d29yZHM+PGtleXdvcmQ+QWdpbmc8L2tleXdvcmQ+PGtleXdvcmQ+QnJh

aW48L2tleXdvcmQ+PGtleXdvcmQ+QnJhaW4gRGlzZWFzZXM8L2tleXdvcmQ+PGtleXdvcmQ+Q29n

bml0aW9uIERpc29yZGVyczwva2V5d29yZD48a2V5d29yZD5FdXJvcGU8L2tleXdvcmQ+PGtleXdv

cmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPk1hZ25ldGljIFJlc29uYW5jZSBJbWFnaW5nPC9r

ZXl3b3JkPjxrZXl3b3JkPk1lbW9yeSBEaXNvcmRlcnM8L2tleXdvcmQ+PGtleXdvcmQ+TXllbGlu

IFNoZWF0aDwva2V5d29yZD48a2V5d29yZD5PYnNlcnZlciBWYXJpYXRpb248L2tleXdvcmQ+PGtl

eXdvcmQ+UHJlZGljdGl2ZSBWYWx1ZSBvZiBUZXN0czwva2V5d29yZD48a2V5d29yZD5SZXByb2R1

Y2liaWxpdHkgb2YgUmVzdWx0czwva2V5d29yZD48a2V5d29yZD5TZW5zaXRpdml0eSBhbmQgU3Bl

Y2lmaWNpdHk8L2tleXdvcmQ+PGtleXdvcmQ+VG9tb2dyYXBoeSwgWC1SYXkgQ29tcHV0ZWQ8L2tl

eXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cDovL3d3dy5uY2Jp

Lm5sbS5uaWguZ292L3B1Ym1lZC8xMTM4NzQ5MzwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJscz48

aXNibj4xNTI0LTQ2Mjg8L2lzYm4+PHRpdGxlcz48dGl0bGU+QSBuZXcgcmF0aW5nIHNjYWxlIGZv

ciBhZ2UtcmVsYXRlZCB3aGl0ZSBtYXR0ZXIgY2hhbmdlcyBhcHBsaWNhYmxlIHRvIE1SSSBhbmQg

Q1QuPC90aXRsZT48c2Vjb25kYXJ5LXRpdGxlPlN0cm9rZTwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0

bGVzPjxwYWdlcz4xMzE4LTIyPC9wYWdlcz48bnVtYmVyPjY8L251bWJlcj48Y29udHJpYnV0b3Jz

PjxhdXRob3JzPjxhdXRob3I+V2FobHVuZCwgTC4gTy48L2F1dGhvcj48YXV0aG9yPkJhcmtob2Ys

IEYuPC9hdXRob3I+PGF1dGhvcj5GYXpla2FzLCBGLjwvYXV0aG9yPjxhdXRob3I+QnJvbmdlLCBM

LjwvYXV0aG9yPjxhdXRob3I+QXVndXN0aW4sIE0uPC9hdXRob3I+PGF1dGhvcj5TasO2Z3Jlbiwg

TS48L2F1dGhvcj48YXV0aG9yPldhbGxpbiwgQS48L2F1dGhvcj48YXV0aG9yPkFkZXIsIEguPC9h

dXRob3I+PGF1dGhvcj5MZXlzLCBELjwvYXV0aG9yPjxhdXRob3I+UGFudG9uaSwgTC48L2F1dGhv

cj48YXV0aG9yPlBhc3F1aWVyLCBGLjwvYXV0aG9yPjxhdXRob3I+RXJraW5qdW50dGksIFQuPC9h

dXRob3I+PGF1dGhvcj5TY2hlbHRlbnMsIFAuPC9hdXRob3I+PGF1dGhvcj5FdXJvcGVhbiBUYXNr

IEZvcmNlIG9uIEFnZS1SZWxhdGVkIFdoaXRlIE1hdHRlciBDaGFuZ2VzPC9hdXRob3I+PC9hdXRo

b3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5lbmc8L2xhbmd1YWdlPjxhZGRlZC1kYXRlIGZv

cm1hdD0idXRjIj4xMzM0OTM3NjY2PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1lPSJKb3VybmFs

IEFydGljbGUiPjE3PC9yZWYtdHlwZT48YXV0aC1hZGRyZXNzPkRlcGFydG1lbnQgb2YgQ2xpbmlj

YWwgTmV1cm9zY2llbmNlLCBORVVST1RFQywgS2Fyb2xpbnNrYSBJbnN0aXR1dGV0IGF0IEh1ZGRp

bmdlIFVuaXZlcnNpdHkgSG9zcGl0YWwsIEh1ZGRpbmdlLCBTd2VkZW4uIGxhcnMtb2xvZi53YWhs

dW5kQG5ldXJvdGVjLmtpLnNlPC9hdXRoLWFkZHJlc3M+PHJlYy1udW1iZXI+MTMzPC9yZWMtbnVt

YmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTMzNDkzNzY2NjwvbGFzdC11cGRh

dGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MTEzODc0OTM8L2FjY2Vzc2lvbi1udW0+PHZvbHVtZT4z

Mjwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48L0VuZE5vdGU+AAA=

ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XYWhsdW5kPC9BdXRob3I+PFllYXI+MjAwMTwvWWVhcj48

SURUZXh0PkEgbmV3IHJhdGluZyBzY2FsZSBmb3IgYWdlLXJlbGF0ZWQgd2hpdGUgbWF0dGVyIGNo

YW5nZXMgYXBwbGljYWJsZSB0byBNUkkgYW5kIENULjwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5

bGUgZmFjZT0ic3VwZXJzY3JpcHQiPjEyPC9zdHlsZT48L0Rpc3BsYXlUZXh0PjxyZWNvcmQ+PGRh

dGVzPjxwdWItZGF0ZXM+PGRhdGU+SnVuPC9kYXRlPjwvcHViLWRhdGVzPjx5ZWFyPjIwMDE8L3ll

YXI+PC9kYXRlcz48a2V5d29yZHM+PGtleXdvcmQ+QWdpbmc8L2tleXdvcmQ+PGtleXdvcmQ+QnJh

aW48L2tleXdvcmQ+PGtleXdvcmQ+QnJhaW4gRGlzZWFzZXM8L2tleXdvcmQ+PGtleXdvcmQ+Q29n

bml0aW9uIERpc29yZGVyczwva2V5d29yZD48a2V5d29yZD5FdXJvcGU8L2tleXdvcmQ+PGtleXdv

cmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPk1hZ25ldGljIFJlc29uYW5jZSBJbWFnaW5nPC9r

ZXl3b3JkPjxrZXl3b3JkPk1lbW9yeSBEaXNvcmRlcnM8L2tleXdvcmQ+PGtleXdvcmQ+TXllbGlu

IFNoZWF0aDwva2V5d29yZD48a2V5d29yZD5PYnNlcnZlciBWYXJpYXRpb248L2tleXdvcmQ+PGtl

eXdvcmQ+UHJlZGljdGl2ZSBWYWx1ZSBvZiBUZXN0czwva2V5d29yZD48a2V5d29yZD5SZXByb2R1

Y2liaWxpdHkgb2YgUmVzdWx0czwva2V5d29yZD48a2V5d29yZD5TZW5zaXRpdml0eSBhbmQgU3Bl

Y2lmaWNpdHk8L2tleXdvcmQ+PGtleXdvcmQ+VG9tb2dyYXBoeSwgWC1SYXkgQ29tcHV0ZWQ8L2tl

eXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cDovL3d3dy5uY2Jp

Lm5sbS5uaWguZ292L3B1Ym1lZC8xMTM4NzQ5MzwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJscz48

aXNibj4xNTI0LTQ2Mjg8L2lzYm4+PHRpdGxlcz48dGl0bGU+QSBuZXcgcmF0aW5nIHNjYWxlIGZv

ciBhZ2UtcmVsYXRlZCB3aGl0ZSBtYXR0ZXIgY2hhbmdlcyBhcHBsaWNhYmxlIHRvIE1SSSBhbmQg

Q1QuPC90aXRsZT48c2Vjb25kYXJ5LXRpdGxlPlN0cm9rZTwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0

bGVzPjxwYWdlcz4xMzE4LTIyPC9wYWdlcz48bnVtYmVyPjY8L251bWJlcj48Y29udHJpYnV0b3Jz

PjxhdXRob3JzPjxhdXRob3I+V2FobHVuZCwgTC4gTy48L2F1dGhvcj48YXV0aG9yPkJhcmtob2Ys

IEYuPC9hdXRob3I+PGF1dGhvcj5GYXpla2FzLCBGLjwvYXV0aG9yPjxhdXRob3I+QnJvbmdlLCBM

LjwvYXV0aG9yPjxhdXRob3I+QXVndXN0aW4sIE0uPC9hdXRob3I+PGF1dGhvcj5TasO2Z3Jlbiwg

TS48L2F1dGhvcj48YXV0aG9yPldhbGxpbiwgQS48L2F1dGhvcj48YXV0aG9yPkFkZXIsIEguPC9h

dXRob3I+PGF1dGhvcj5MZXlzLCBELjwvYXV0aG9yPjxhdXRob3I+UGFudG9uaSwgTC48L2F1dGhv

cj48YXV0aG9yPlBhc3F1aWVyLCBGLjwvYXV0aG9yPjxhdXRob3I+RXJraW5qdW50dGksIFQuPC9h

dXRob3I+PGF1dGhvcj5TY2hlbHRlbnMsIFAuPC9hdXRob3I+PGF1dGhvcj5FdXJvcGVhbiBUYXNr

IEZvcmNlIG9uIEFnZS1SZWxhdGVkIFdoaXRlIE1hdHRlciBDaGFuZ2VzPC9hdXRob3I+PC9hdXRo

b3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5lbmc8L2xhbmd1YWdlPjxhZGRlZC1kYXRlIGZv

cm1hdD0idXRjIj4xMzM0OTM3NjY2PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1lPSJKb3VybmFs

IEFydGljbGUiPjE3PC9yZWYtdHlwZT48YXV0aC1hZGRyZXNzPkRlcGFydG1lbnQgb2YgQ2xpbmlj

YWwgTmV1cm9zY2llbmNlLCBORVVST1RFQywgS2Fyb2xpbnNrYSBJbnN0aXR1dGV0IGF0IEh1ZGRp

bmdlIFVuaXZlcnNpdHkgSG9zcGl0YWwsIEh1ZGRpbmdlLCBTd2VkZW4uIGxhcnMtb2xvZi53YWhs

dW5kQG5ldXJvdGVjLmtpLnNlPC9hdXRoLWFkZHJlc3M+PHJlYy1udW1iZXI+MTMzPC9yZWMtbnVt

YmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTMzNDkzNzY2NjwvbGFzdC11cGRh

dGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MTEzODc0OTM8L2FjY2Vzc2lvbi1udW0+PHZvbHVtZT4z

Mjwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48L0VuZE5vdGU+AAA=

ADDIN EN.CITE.DATA 12. For the van Swieten system, anterior and posterior scores ADDIN EN.CITE <EndNote><Cite><Author>van Swieten</Author><Year>1990</Year><IDText>Grading white matter lesions on CT and MRI: a simple scale</IDText><DisplayText><style face="superscript">15</style></DisplayText><record><dates><pub-dates><date>Dec</date></pub-dates><year>1990</year></dates><keywords><keyword>Brain</keyword><keyword>Brain Diseases</keyword><keyword>Cross-Sectional Studies</keyword><keyword>Data Interpretation, Statistical</keyword><keyword>Humans</keyword><keyword>Ischemic Attack, Transient</keyword><keyword>Longitudinal Studies</keyword><keyword>Magnetic Resonance Imaging</keyword><keyword>Tomography, X-Ray Computed</keyword></keywords><urls><related-urls><url> white matter lesions on CT and MRI: a simple scale</title><secondary-title>J Neurol Neurosurg Psychiatry</secondary-title></titles><pages>1080-3</pages><number>12</number><contributors><authors><author>van Swieten, J. C.</author><author>Hijdra, A.</author><author>Koudstaal, P. J.</author><author>van Gijn, J.</author></authors></contributors><language>ENG</language><added-date format="utc">1478177600</added-date><ref-type name="Journal Article">17</ref-type><rec-number>531</rec-number><last-updated-date format="utc">1478177600</last-updated-date><accession-num>2292703</accession-num><volume>53</volume></record></Cite></EndNote>15 (3 grades each) were averaged and rounded. CT drawings and ratings were performed by 3 experts for each case, drawn from a pool of 3-13 for each experiment, allowing a consensus to be deduced for WML volume and rating score (mean and median respectively). Comparisons between each combination of rater pairs was performed to identify any experts who differed significantly (p<0.05) in their performance.D. Validation testsFrom expert drawings of cerebral WML on CT or MRI, total lesion volume was calculated, and correlated with Auto-estimated WML volume, using Spearman’s correlation. Comparisons of Spearman correlation coefficients were performed using an appropriate Fisher Z transformation ADDIN EN.CITE <EndNote><Cite><Author>Myers</Author><Year>2006</Year><IDText>Spearman Correlation Coefficients, Difference between</IDText><DisplayText><style face="superscript">22</style></DisplayText><record><titles><title>Spearman Correlation Coefficients, Difference between</title><secondary-title>Encyclopedia of Statistical Sciences</secondary-title></titles><contributors><authors><author>Myers, Leann</author><author>Sirois, Maria J</author></authors></contributors><added-date format="utc">1478276922</added-date><ref-type name="Journal Article">17</ref-type><dates><year>2006</year></dates><rec-number>537</rec-number><last-updated-date format="utc">1478277029</last-updated-date><electronic-resource-num>10.1002/0471667196.ess5050.pub2</electronic-resource-num><volume>12</volume></record></Cite></EndNote>22. Drawings (of WML on CT and MRI) were also compared for spatial similarity with Auto segmentations using patch-based evaluation of imaging similarity (PEIS), that is an unbiased version of the Dice scorePEVuZE5vdGU+PENpdGU+PEF1dGhvcj5MZWRpZzwvQXV0aG9yPjxZZWFyPjIwMTQ8L1llYXI+PElE

VGV4dD5QYXRjaC1iYXNlZCBFdmFsdWF0aW9uIG9mIEltYWdlIFNlZ21lbnRhdGlvbjwvSURUZXh0

PjxEaXNwbGF5VGV4dD48c3R5bGUgZmFjZT0ic3VwZXJzY3JpcHQiPjIzLCAyNDwvc3R5bGU+PC9E

aXNwbGF5VGV4dD48cmVjb3JkPjx0aXRsZXM+PHRpdGxlPlBhdGNoLWJhc2VkIEV2YWx1YXRpb24g

b2YgSW1hZ2UgU2VnbWVudGF0aW9uPC90aXRsZT48c2Vjb25kYXJ5LXRpdGxlPlByb2NlZWRpbmdz

IG9mIENWUFI8L3NlY29uZGFyeS10aXRsZT48L3RpdGxlcz48cGFnZXM+MzA2NS0zMDcyPC9wYWdl

cz48Y29udHJpYnV0b3JzPjxhdXRob3JzPjxhdXRob3I+TGVkaWcsIENocmlzdGlhbjwvYXV0aG9y

PjxhdXRob3I+U2hpLCBXZW56aGU8L2F1dGhvcj48YXV0aG9yPkJhaSwgV2VuamlhPC9hdXRob3I+

PGF1dGhvcj5SdWVja2VydCwgRGFuaWVsPC9hdXRob3I+PC9hdXRob3JzPjwvY29udHJpYnV0b3Jz

PjxhZGRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDczMDc2ODAyPC9hZGRlZC1kYXRlPjxyZWYtdHlw

ZSBuYW1lPSJKb3VybmFsIEFydGljbGUiPjE3PC9yZWYtdHlwZT48ZGF0ZXM+PHllYXI+MjAxNDwv

eWVhcj48L2RhdGVzPjxyZWMtbnVtYmVyPjUxNzwvcmVjLW51bWJlcj48bGFzdC11cGRhdGVkLWRh

dGUgZm9ybWF0PSJ1dGMiPjE0NzMwNzczMjI8L2xhc3QtdXBkYXRlZC1kYXRlPjxlbGVjdHJvbmlj

LXJlc291cmNlLW51bT4xMC4xMTA5L0NWUFIuMjAxNC4zOTI8L2VsZWN0cm9uaWMtcmVzb3VyY2Ut

bnVtPjwvcmVjb3JkPjwvQ2l0ZT48Q2l0ZT48QXV0aG9yPkxlZGlnPC9BdXRob3I+PFllYXI+MjAx

NTwvWWVhcj48SURUZXh0PlJvYnVzdCB3aG9sZS1icmFpbiBzZWdtZW50YXRpb246IGFwcGxpY2F0

aW9uIHRvIHRyYXVtYXRpYyBicmFpbiBpbmp1cnk8L0lEVGV4dD48cmVjb3JkPjxkYXRlcz48cHVi

LWRhdGVzPjxkYXRlPkFwcjwvZGF0ZT48L3B1Yi1kYXRlcz48eWVhcj4yMDE1PC95ZWFyPjwvZGF0

ZXM+PGtleXdvcmRzPjxrZXl3b3JkPkFkdWx0PC9rZXl3b3JkPjxrZXl3b3JkPkFsZ29yaXRobXM8

L2tleXdvcmQ+PGtleXdvcmQ+QXJ0aWZpY2lhbCBJbnRlbGxpZ2VuY2U8L2tleXdvcmQ+PGtleXdv

cmQ+QnJhaW48L2tleXdvcmQ+PGtleXdvcmQ+QnJhaW4gSW5qdXJpZXM8L2tleXdvcmQ+PGtleXdv

cmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPkltYWdlIEVuaGFuY2VtZW50PC9rZXl3b3JkPjxr

ZXl3b3JkPkltYWdlIEludGVycHJldGF0aW9uLCBDb21wdXRlci1Bc3Npc3RlZDwva2V5d29yZD48

a2V5d29yZD5NYWduZXRpYyBSZXNvbmFuY2UgSW1hZ2luZzwva2V5d29yZD48a2V5d29yZD5Nb2Rl

bHMsIEJpb2xvZ2ljYWw8L2tleXdvcmQ+PGtleXdvcmQ+TW9kZWxzLCBTdGF0aXN0aWNhbDwva2V5

d29yZD48a2V5d29yZD5QYXR0ZXJuIFJlY29nbml0aW9uLCBBdXRvbWF0ZWQ8L2tleXdvcmQ+PGtl

eXdvcmQ+UmVwcm9kdWNpYmlsaXR5IG9mIFJlc3VsdHM8L2tleXdvcmQ+PGtleXdvcmQ+U2Vuc2l0

aXZpdHkgYW5kIFNwZWNpZmljaXR5PC9rZXl3b3JkPjxrZXl3b3JkPlN1YnRyYWN0aW9uIFRlY2hu

aXF1ZTwva2V5d29yZD48L2tleXdvcmRzPjx1cmxzPjxyZWxhdGVkLXVybHM+PHVybD5odHRwczov

L3d3dy5uY2JpLm5sbS5uaWguZ292L3B1Ym1lZC8yNTU5Njc2NTwvdXJsPjwvcmVsYXRlZC11cmxz

PjwvdXJscz48aXNibj4xMzYxLTg0MjM8L2lzYm4+PHRpdGxlcz48dGl0bGU+Um9idXN0IHdob2xl

LWJyYWluIHNlZ21lbnRhdGlvbjogYXBwbGljYXRpb24gdG8gdHJhdW1hdGljIGJyYWluIGluanVy

eTwvdGl0bGU+PHNlY29uZGFyeS10aXRsZT5NZWQgSW1hZ2UgQW5hbDwvc2Vjb25kYXJ5LXRpdGxl

PjwvdGl0bGVzPjxwYWdlcz40MC01ODwvcGFnZXM+PG51bWJlcj4xPC9udW1iZXI+PGNvbnRyaWJ1

dG9ycz48YXV0aG9ycz48YXV0aG9yPkxlZGlnLCBDLjwvYXV0aG9yPjxhdXRob3I+SGVja2VtYW5u

LCBSLiBBLjwvYXV0aG9yPjxhdXRob3I+SGFtbWVycywgQS48L2F1dGhvcj48YXV0aG9yPkxvcGV6

LCBKLiBDLjwvYXV0aG9yPjxhdXRob3I+TmV3Y29tYmUsIFYuIEYuPC9hdXRob3I+PGF1dGhvcj5N

YWtyb3BvdWxvcywgQS48L2F1dGhvcj48YXV0aG9yPkzDtnRqw7ZuZW4sIEouPC9hdXRob3I+PGF1

dGhvcj5NZW5vbiwgRC4gSy48L2F1dGhvcj48YXV0aG9yPlJ1ZWNrZXJ0LCBELjwvYXV0aG9yPjwv

YXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3VhZ2U+ZW5nPC9sYW5ndWFnZT48YWRkZWQtZGF0

ZSBmb3JtYXQ9InV0YyI+MTQ3MzA3NzQxNTwvYWRkZWQtZGF0ZT48cmVmLXR5cGUgbmFtZT0iSm91

cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PHJlYy1udW1iZXI+NTE4PC9yZWMtbnVtYmVyPjxs

YXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3MzA3NzQxNTwvbGFzdC11cGRhdGVkLWRh

dGU+PGFjY2Vzc2lvbi1udW0+MjU1OTY3NjU8L2FjY2Vzc2lvbi1udW0+PGVsZWN0cm9uaWMtcmVz

b3VyY2UtbnVtPjEwLjEwMTYvai5tZWRpYS4yMDE0LjEyLjAwMzwvZWxlY3Ryb25pYy1yZXNvdXJj

ZS1udW0+PHZvbHVtZT4yMTwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48L0VuZE5vdGU+AAA=

ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5MZWRpZzwvQXV0aG9yPjxZZWFyPjIwMTQ8L1llYXI+PElE

VGV4dD5QYXRjaC1iYXNlZCBFdmFsdWF0aW9uIG9mIEltYWdlIFNlZ21lbnRhdGlvbjwvSURUZXh0

PjxEaXNwbGF5VGV4dD48c3R5bGUgZmFjZT0ic3VwZXJzY3JpcHQiPjIzLCAyNDwvc3R5bGU+PC9E

aXNwbGF5VGV4dD48cmVjb3JkPjx0aXRsZXM+PHRpdGxlPlBhdGNoLWJhc2VkIEV2YWx1YXRpb24g

b2YgSW1hZ2UgU2VnbWVudGF0aW9uPC90aXRsZT48c2Vjb25kYXJ5LXRpdGxlPlByb2NlZWRpbmdz

IG9mIENWUFI8L3NlY29uZGFyeS10aXRsZT48L3RpdGxlcz48cGFnZXM+MzA2NS0zMDcyPC9wYWdl

cz48Y29udHJpYnV0b3JzPjxhdXRob3JzPjxhdXRob3I+TGVkaWcsIENocmlzdGlhbjwvYXV0aG9y

PjxhdXRob3I+U2hpLCBXZW56aGU8L2F1dGhvcj48YXV0aG9yPkJhaSwgV2VuamlhPC9hdXRob3I+

PGF1dGhvcj5SdWVja2VydCwgRGFuaWVsPC9hdXRob3I+PC9hdXRob3JzPjwvY29udHJpYnV0b3Jz

PjxhZGRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDczMDc2ODAyPC9hZGRlZC1kYXRlPjxyZWYtdHlw

ZSBuYW1lPSJKb3VybmFsIEFydGljbGUiPjE3PC9yZWYtdHlwZT48ZGF0ZXM+PHllYXI+MjAxNDwv

eWVhcj48L2RhdGVzPjxyZWMtbnVtYmVyPjUxNzwvcmVjLW51bWJlcj48bGFzdC11cGRhdGVkLWRh

dGUgZm9ybWF0PSJ1dGMiPjE0NzMwNzczMjI8L2xhc3QtdXBkYXRlZC1kYXRlPjxlbGVjdHJvbmlj

LXJlc291cmNlLW51bT4xMC4xMTA5L0NWUFIuMjAxNC4zOTI8L2VsZWN0cm9uaWMtcmVzb3VyY2Ut

bnVtPjwvcmVjb3JkPjwvQ2l0ZT48Q2l0ZT48QXV0aG9yPkxlZGlnPC9BdXRob3I+PFllYXI+MjAx

NTwvWWVhcj48SURUZXh0PlJvYnVzdCB3aG9sZS1icmFpbiBzZWdtZW50YXRpb246IGFwcGxpY2F0

aW9uIHRvIHRyYXVtYXRpYyBicmFpbiBpbmp1cnk8L0lEVGV4dD48cmVjb3JkPjxkYXRlcz48cHVi

LWRhdGVzPjxkYXRlPkFwcjwvZGF0ZT48L3B1Yi1kYXRlcz48eWVhcj4yMDE1PC95ZWFyPjwvZGF0

ZXM+PGtleXdvcmRzPjxrZXl3b3JkPkFkdWx0PC9rZXl3b3JkPjxrZXl3b3JkPkFsZ29yaXRobXM8

L2tleXdvcmQ+PGtleXdvcmQ+QXJ0aWZpY2lhbCBJbnRlbGxpZ2VuY2U8L2tleXdvcmQ+PGtleXdv

cmQ+QnJhaW48L2tleXdvcmQ+PGtleXdvcmQ+QnJhaW4gSW5qdXJpZXM8L2tleXdvcmQ+PGtleXdv

cmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPkltYWdlIEVuaGFuY2VtZW50PC9rZXl3b3JkPjxr

ZXl3b3JkPkltYWdlIEludGVycHJldGF0aW9uLCBDb21wdXRlci1Bc3Npc3RlZDwva2V5d29yZD48

a2V5d29yZD5NYWduZXRpYyBSZXNvbmFuY2UgSW1hZ2luZzwva2V5d29yZD48a2V5d29yZD5Nb2Rl

bHMsIEJpb2xvZ2ljYWw8L2tleXdvcmQ+PGtleXdvcmQ+TW9kZWxzLCBTdGF0aXN0aWNhbDwva2V5

d29yZD48a2V5d29yZD5QYXR0ZXJuIFJlY29nbml0aW9uLCBBdXRvbWF0ZWQ8L2tleXdvcmQ+PGtl

eXdvcmQ+UmVwcm9kdWNpYmlsaXR5IG9mIFJlc3VsdHM8L2tleXdvcmQ+PGtleXdvcmQ+U2Vuc2l0

aXZpdHkgYW5kIFNwZWNpZmljaXR5PC9rZXl3b3JkPjxrZXl3b3JkPlN1YnRyYWN0aW9uIFRlY2hu

aXF1ZTwva2V5d29yZD48L2tleXdvcmRzPjx1cmxzPjxyZWxhdGVkLXVybHM+PHVybD5odHRwczov

L3d3dy5uY2JpLm5sbS5uaWguZ292L3B1Ym1lZC8yNTU5Njc2NTwvdXJsPjwvcmVsYXRlZC11cmxz

PjwvdXJscz48aXNibj4xMzYxLTg0MjM8L2lzYm4+PHRpdGxlcz48dGl0bGU+Um9idXN0IHdob2xl

LWJyYWluIHNlZ21lbnRhdGlvbjogYXBwbGljYXRpb24gdG8gdHJhdW1hdGljIGJyYWluIGluanVy

eTwvdGl0bGU+PHNlY29uZGFyeS10aXRsZT5NZWQgSW1hZ2UgQW5hbDwvc2Vjb25kYXJ5LXRpdGxl

PjwvdGl0bGVzPjxwYWdlcz40MC01ODwvcGFnZXM+PG51bWJlcj4xPC9udW1iZXI+PGNvbnRyaWJ1

dG9ycz48YXV0aG9ycz48YXV0aG9yPkxlZGlnLCBDLjwvYXV0aG9yPjxhdXRob3I+SGVja2VtYW5u

LCBSLiBBLjwvYXV0aG9yPjxhdXRob3I+SGFtbWVycywgQS48L2F1dGhvcj48YXV0aG9yPkxvcGV6

LCBKLiBDLjwvYXV0aG9yPjxhdXRob3I+TmV3Y29tYmUsIFYuIEYuPC9hdXRob3I+PGF1dGhvcj5N

YWtyb3BvdWxvcywgQS48L2F1dGhvcj48YXV0aG9yPkzDtnRqw7ZuZW4sIEouPC9hdXRob3I+PGF1

dGhvcj5NZW5vbiwgRC4gSy48L2F1dGhvcj48YXV0aG9yPlJ1ZWNrZXJ0LCBELjwvYXV0aG9yPjwv

YXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3VhZ2U+ZW5nPC9sYW5ndWFnZT48YWRkZWQtZGF0

ZSBmb3JtYXQ9InV0YyI+MTQ3MzA3NzQxNTwvYWRkZWQtZGF0ZT48cmVmLXR5cGUgbmFtZT0iSm91

cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PHJlYy1udW1iZXI+NTE4PC9yZWMtbnVtYmVyPjxs

YXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3MzA3NzQxNTwvbGFzdC11cGRhdGVkLWRh

dGU+PGFjY2Vzc2lvbi1udW0+MjU1OTY3NjU8L2FjY2Vzc2lvbi1udW0+PGVsZWN0cm9uaWMtcmVz

b3VyY2UtbnVtPjEwLjEwMTYvai5tZWRpYS4yMDE0LjEyLjAwMzwvZWxlY3Ryb25pYy1yZXNvdXJj

ZS1udW0+PHZvbHVtZT4yMTwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48L0VuZE5vdGU+AAA=

ADDIN EN.CITE.DATA 23, 24; and tested for group differences with the ranksum test. Agreements between Auto versus expert ratings were assessed with linear weighted-kappa scores (kw), while comparisons between agreements were tested with validated bootstrap methods ADDIN EN.CITE <EndNote><Cite><Author>Vanbelle</Author><Year>2008</Year><IDText>A bootstrap method for comparing correlated</IDText><DisplayText><style face="superscript">25</style></DisplayText><record><titles><title>A bootstrap method for comparing correlated kappa coefficients</title><secondary-title>Journal of Statistical Computation and Simulation</secondary-title></titles><pages>1009-1015</pages><number>11</number><contributors><authors><author>Vanbelle, S</author><author>Albert, A</author></authors></contributors><added-date format="utc">1478277330</added-date><ref-type name="Journal Article">17</ref-type><dates><year>2008</year></dates><rec-number>539</rec-number><last-updated-date format="utc">1478277822</last-updated-date><electronic-resource-num>10.1080/00949650701410249</electronic-resource-num><volume>78</volume></record></Cite></EndNote>25. Statistical analyses were conducted in Matlab vR2012b.ResultsImage pre-processing Image pre-processing failures occurred in 39/882 hospital-derived CTs, and 4/200 trial-derived CTs (3.98% total failure rate; Fig. 1). Inspection of these cases identified poor image quality, due to inappropriate intensity windowing, incomplete brain coverage, extensive movement, beam-hardening artefact, or extreme head tilt - in 18/43 (42%). Pre-processing time took 77.3s (± 25s; mean ±95% confidence intervals). Median age in the four study samples was 76, 76, 75 and 82 years. Sample size, and proportions with acute/old ischemic lesions (proceeding to analysis) were 120 (19%/38%), 60 (22%/38%), 650 (36%/42%) and 196 (0%/59%) (i.e. numbers with acute ischemia or old infarcts were 257 and 319 respectively). Drawing validationWML volumes estimated using Auto correlated closely with those derived from expert CT-drawings (n=120, r2: 0.71; Table 2, Fig. 2A). Correlation between expert CT-volumes themselves was higher (r2: 0.85; ?r: Z=3.1, p<0.01), but the range of expert CT-volumes per scan was wide (median range: 91% of mean expert estimate; IQR: 55-148%; shown as vertical lines in Fig. 2A). Correlation of Auto WML volumes with expert drawings of WML volumes improved when the latter were based upon coregistered FLAIR-MRI (r2: 0.85), than CT (?r: Z=3.8; p<0.001); and was comparable to the correlation between expert-CT versus expert-MRI WML volumes (r2 0.82; ?r: Z=0.54, p>0.1; Fig. 2B; examples shown in Fig. 3). Auto-volumes of WML were more conservative than experts’, being lower than the lowest of three expert estimates in 43% (p<0.001), and taking 61% the value of mean expert CT-volumes (IQR: 40-112%). However, spatial similarityPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5MZWRpZzwvQXV0aG9yPjxZZWFyPjIwMTQ8L1llYXI+PElE

VGV4dD5QYXRjaC1iYXNlZCBFdmFsdWF0aW9uIG9mIEltYWdlIFNlZ21lbnRhdGlvbjwvSURUZXh0

PjxEaXNwbGF5VGV4dD48c3R5bGUgZmFjZT0ic3VwZXJzY3JpcHQiPjIzLCAyNDwvc3R5bGU+PC9E

aXNwbGF5VGV4dD48cmVjb3JkPjx0aXRsZXM+PHRpdGxlPlBhdGNoLWJhc2VkIEV2YWx1YXRpb24g

b2YgSW1hZ2UgU2VnbWVudGF0aW9uPC90aXRsZT48c2Vjb25kYXJ5LXRpdGxlPlByb2NlZWRpbmdz

IG9mIENWUFI8L3NlY29uZGFyeS10aXRsZT48L3RpdGxlcz48cGFnZXM+MzA2NS0zMDcyPC9wYWdl

cz48Y29udHJpYnV0b3JzPjxhdXRob3JzPjxhdXRob3I+TGVkaWcsIENocmlzdGlhbjwvYXV0aG9y

PjxhdXRob3I+U2hpLCBXZW56aGU8L2F1dGhvcj48YXV0aG9yPkJhaSwgV2VuamlhPC9hdXRob3I+

PGF1dGhvcj5SdWVja2VydCwgRGFuaWVsPC9hdXRob3I+PC9hdXRob3JzPjwvY29udHJpYnV0b3Jz

PjxhZGRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDczMDc2ODAyPC9hZGRlZC1kYXRlPjxyZWYtdHlw

ZSBuYW1lPSJKb3VybmFsIEFydGljbGUiPjE3PC9yZWYtdHlwZT48ZGF0ZXM+PHllYXI+MjAxNDwv

eWVhcj48L2RhdGVzPjxyZWMtbnVtYmVyPjUxNzwvcmVjLW51bWJlcj48bGFzdC11cGRhdGVkLWRh

dGUgZm9ybWF0PSJ1dGMiPjE0NzMwNzczMjI8L2xhc3QtdXBkYXRlZC1kYXRlPjxlbGVjdHJvbmlj

LXJlc291cmNlLW51bT4xMC4xMTA5L0NWUFIuMjAxNC4zOTI8L2VsZWN0cm9uaWMtcmVzb3VyY2Ut

bnVtPjwvcmVjb3JkPjwvQ2l0ZT48Q2l0ZT48QXV0aG9yPkxlZGlnPC9BdXRob3I+PFllYXI+MjAx

NTwvWWVhcj48SURUZXh0PlJvYnVzdCB3aG9sZS1icmFpbiBzZWdtZW50YXRpb246IGFwcGxpY2F0

aW9uIHRvIHRyYXVtYXRpYyBicmFpbiBpbmp1cnk8L0lEVGV4dD48cmVjb3JkPjxkYXRlcz48cHVi

LWRhdGVzPjxkYXRlPkFwcjwvZGF0ZT48L3B1Yi1kYXRlcz48eWVhcj4yMDE1PC95ZWFyPjwvZGF0

ZXM+PGtleXdvcmRzPjxrZXl3b3JkPkFkdWx0PC9rZXl3b3JkPjxrZXl3b3JkPkFsZ29yaXRobXM8

L2tleXdvcmQ+PGtleXdvcmQ+QXJ0aWZpY2lhbCBJbnRlbGxpZ2VuY2U8L2tleXdvcmQ+PGtleXdv

cmQ+QnJhaW48L2tleXdvcmQ+PGtleXdvcmQ+QnJhaW4gSW5qdXJpZXM8L2tleXdvcmQ+PGtleXdv

cmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPkltYWdlIEVuaGFuY2VtZW50PC9rZXl3b3JkPjxr

ZXl3b3JkPkltYWdlIEludGVycHJldGF0aW9uLCBDb21wdXRlci1Bc3Npc3RlZDwva2V5d29yZD48

a2V5d29yZD5NYWduZXRpYyBSZXNvbmFuY2UgSW1hZ2luZzwva2V5d29yZD48a2V5d29yZD5Nb2Rl

bHMsIEJpb2xvZ2ljYWw8L2tleXdvcmQ+PGtleXdvcmQ+TW9kZWxzLCBTdGF0aXN0aWNhbDwva2V5

d29yZD48a2V5d29yZD5QYXR0ZXJuIFJlY29nbml0aW9uLCBBdXRvbWF0ZWQ8L2tleXdvcmQ+PGtl

eXdvcmQ+UmVwcm9kdWNpYmlsaXR5IG9mIFJlc3VsdHM8L2tleXdvcmQ+PGtleXdvcmQ+U2Vuc2l0

aXZpdHkgYW5kIFNwZWNpZmljaXR5PC9rZXl3b3JkPjxrZXl3b3JkPlN1YnRyYWN0aW9uIFRlY2hu

aXF1ZTwva2V5d29yZD48L2tleXdvcmRzPjx1cmxzPjxyZWxhdGVkLXVybHM+PHVybD5odHRwczov

L3d3dy5uY2JpLm5sbS5uaWguZ292L3B1Ym1lZC8yNTU5Njc2NTwvdXJsPjwvcmVsYXRlZC11cmxz

PjwvdXJscz48aXNibj4xMzYxLTg0MjM8L2lzYm4+PHRpdGxlcz48dGl0bGU+Um9idXN0IHdob2xl

LWJyYWluIHNlZ21lbnRhdGlvbjogYXBwbGljYXRpb24gdG8gdHJhdW1hdGljIGJyYWluIGluanVy

eTwvdGl0bGU+PHNlY29uZGFyeS10aXRsZT5NZWQgSW1hZ2UgQW5hbDwvc2Vjb25kYXJ5LXRpdGxl

PjwvdGl0bGVzPjxwYWdlcz40MC01ODwvcGFnZXM+PG51bWJlcj4xPC9udW1iZXI+PGNvbnRyaWJ1

dG9ycz48YXV0aG9ycz48YXV0aG9yPkxlZGlnLCBDLjwvYXV0aG9yPjxhdXRob3I+SGVja2VtYW5u

LCBSLiBBLjwvYXV0aG9yPjxhdXRob3I+SGFtbWVycywgQS48L2F1dGhvcj48YXV0aG9yPkxvcGV6

LCBKLiBDLjwvYXV0aG9yPjxhdXRob3I+TmV3Y29tYmUsIFYuIEYuPC9hdXRob3I+PGF1dGhvcj5N

YWtyb3BvdWxvcywgQS48L2F1dGhvcj48YXV0aG9yPkzDtnRqw7ZuZW4sIEouPC9hdXRob3I+PGF1

dGhvcj5NZW5vbiwgRC4gSy48L2F1dGhvcj48YXV0aG9yPlJ1ZWNrZXJ0LCBELjwvYXV0aG9yPjwv

YXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3VhZ2U+ZW5nPC9sYW5ndWFnZT48YWRkZWQtZGF0

ZSBmb3JtYXQ9InV0YyI+MTQ3MzA3NzQxNTwvYWRkZWQtZGF0ZT48cmVmLXR5cGUgbmFtZT0iSm91

cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PHJlYy1udW1iZXI+NTE4PC9yZWMtbnVtYmVyPjxs

YXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3MzA3NzQxNTwvbGFzdC11cGRhdGVkLWRh

dGU+PGFjY2Vzc2lvbi1udW0+MjU1OTY3NjU8L2FjY2Vzc2lvbi1udW0+PGVsZWN0cm9uaWMtcmVz

b3VyY2UtbnVtPjEwLjEwMTYvai5tZWRpYS4yMDE0LjEyLjAwMzwvZWxlY3Ryb25pYy1yZXNvdXJj

ZS1udW0+PHZvbHVtZT4yMTwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48L0VuZE5vdGU+AAA=

ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5MZWRpZzwvQXV0aG9yPjxZZWFyPjIwMTQ8L1llYXI+PElE

VGV4dD5QYXRjaC1iYXNlZCBFdmFsdWF0aW9uIG9mIEltYWdlIFNlZ21lbnRhdGlvbjwvSURUZXh0

PjxEaXNwbGF5VGV4dD48c3R5bGUgZmFjZT0ic3VwZXJzY3JpcHQiPjIzLCAyNDwvc3R5bGU+PC9E

aXNwbGF5VGV4dD48cmVjb3JkPjx0aXRsZXM+PHRpdGxlPlBhdGNoLWJhc2VkIEV2YWx1YXRpb24g

b2YgSW1hZ2UgU2VnbWVudGF0aW9uPC90aXRsZT48c2Vjb25kYXJ5LXRpdGxlPlByb2NlZWRpbmdz

IG9mIENWUFI8L3NlY29uZGFyeS10aXRsZT48L3RpdGxlcz48cGFnZXM+MzA2NS0zMDcyPC9wYWdl

cz48Y29udHJpYnV0b3JzPjxhdXRob3JzPjxhdXRob3I+TGVkaWcsIENocmlzdGlhbjwvYXV0aG9y

PjxhdXRob3I+U2hpLCBXZW56aGU8L2F1dGhvcj48YXV0aG9yPkJhaSwgV2VuamlhPC9hdXRob3I+

PGF1dGhvcj5SdWVja2VydCwgRGFuaWVsPC9hdXRob3I+PC9hdXRob3JzPjwvY29udHJpYnV0b3Jz

PjxhZGRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDczMDc2ODAyPC9hZGRlZC1kYXRlPjxyZWYtdHlw

ZSBuYW1lPSJKb3VybmFsIEFydGljbGUiPjE3PC9yZWYtdHlwZT48ZGF0ZXM+PHllYXI+MjAxNDwv

eWVhcj48L2RhdGVzPjxyZWMtbnVtYmVyPjUxNzwvcmVjLW51bWJlcj48bGFzdC11cGRhdGVkLWRh

dGUgZm9ybWF0PSJ1dGMiPjE0NzMwNzczMjI8L2xhc3QtdXBkYXRlZC1kYXRlPjxlbGVjdHJvbmlj

LXJlc291cmNlLW51bT4xMC4xMTA5L0NWUFIuMjAxNC4zOTI8L2VsZWN0cm9uaWMtcmVzb3VyY2Ut

bnVtPjwvcmVjb3JkPjwvQ2l0ZT48Q2l0ZT48QXV0aG9yPkxlZGlnPC9BdXRob3I+PFllYXI+MjAx

NTwvWWVhcj48SURUZXh0PlJvYnVzdCB3aG9sZS1icmFpbiBzZWdtZW50YXRpb246IGFwcGxpY2F0

aW9uIHRvIHRyYXVtYXRpYyBicmFpbiBpbmp1cnk8L0lEVGV4dD48cmVjb3JkPjxkYXRlcz48cHVi

LWRhdGVzPjxkYXRlPkFwcjwvZGF0ZT48L3B1Yi1kYXRlcz48eWVhcj4yMDE1PC95ZWFyPjwvZGF0

ZXM+PGtleXdvcmRzPjxrZXl3b3JkPkFkdWx0PC9rZXl3b3JkPjxrZXl3b3JkPkFsZ29yaXRobXM8

L2tleXdvcmQ+PGtleXdvcmQ+QXJ0aWZpY2lhbCBJbnRlbGxpZ2VuY2U8L2tleXdvcmQ+PGtleXdv

cmQ+QnJhaW48L2tleXdvcmQ+PGtleXdvcmQ+QnJhaW4gSW5qdXJpZXM8L2tleXdvcmQ+PGtleXdv

cmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPkltYWdlIEVuaGFuY2VtZW50PC9rZXl3b3JkPjxr

ZXl3b3JkPkltYWdlIEludGVycHJldGF0aW9uLCBDb21wdXRlci1Bc3Npc3RlZDwva2V5d29yZD48

a2V5d29yZD5NYWduZXRpYyBSZXNvbmFuY2UgSW1hZ2luZzwva2V5d29yZD48a2V5d29yZD5Nb2Rl

bHMsIEJpb2xvZ2ljYWw8L2tleXdvcmQ+PGtleXdvcmQ+TW9kZWxzLCBTdGF0aXN0aWNhbDwva2V5

d29yZD48a2V5d29yZD5QYXR0ZXJuIFJlY29nbml0aW9uLCBBdXRvbWF0ZWQ8L2tleXdvcmQ+PGtl

eXdvcmQ+UmVwcm9kdWNpYmlsaXR5IG9mIFJlc3VsdHM8L2tleXdvcmQ+PGtleXdvcmQ+U2Vuc2l0

aXZpdHkgYW5kIFNwZWNpZmljaXR5PC9rZXl3b3JkPjxrZXl3b3JkPlN1YnRyYWN0aW9uIFRlY2hu

aXF1ZTwva2V5d29yZD48L2tleXdvcmRzPjx1cmxzPjxyZWxhdGVkLXVybHM+PHVybD5odHRwczov

L3d3dy5uY2JpLm5sbS5uaWguZ292L3B1Ym1lZC8yNTU5Njc2NTwvdXJsPjwvcmVsYXRlZC11cmxz

PjwvdXJscz48aXNibj4xMzYxLTg0MjM8L2lzYm4+PHRpdGxlcz48dGl0bGU+Um9idXN0IHdob2xl

LWJyYWluIHNlZ21lbnRhdGlvbjogYXBwbGljYXRpb24gdG8gdHJhdW1hdGljIGJyYWluIGluanVy

eTwvdGl0bGU+PHNlY29uZGFyeS10aXRsZT5NZWQgSW1hZ2UgQW5hbDwvc2Vjb25kYXJ5LXRpdGxl

PjwvdGl0bGVzPjxwYWdlcz40MC01ODwvcGFnZXM+PG51bWJlcj4xPC9udW1iZXI+PGNvbnRyaWJ1

dG9ycz48YXV0aG9ycz48YXV0aG9yPkxlZGlnLCBDLjwvYXV0aG9yPjxhdXRob3I+SGVja2VtYW5u

LCBSLiBBLjwvYXV0aG9yPjxhdXRob3I+SGFtbWVycywgQS48L2F1dGhvcj48YXV0aG9yPkxvcGV6

LCBKLiBDLjwvYXV0aG9yPjxhdXRob3I+TmV3Y29tYmUsIFYuIEYuPC9hdXRob3I+PGF1dGhvcj5N

YWtyb3BvdWxvcywgQS48L2F1dGhvcj48YXV0aG9yPkzDtnRqw7ZuZW4sIEouPC9hdXRob3I+PGF1

dGhvcj5NZW5vbiwgRC4gSy48L2F1dGhvcj48YXV0aG9yPlJ1ZWNrZXJ0LCBELjwvYXV0aG9yPjwv

YXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3VhZ2U+ZW5nPC9sYW5ndWFnZT48YWRkZWQtZGF0

ZSBmb3JtYXQ9InV0YyI+MTQ3MzA3NzQxNTwvYWRkZWQtZGF0ZT48cmVmLXR5cGUgbmFtZT0iSm91

cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PHJlYy1udW1iZXI+NTE4PC9yZWMtbnVtYmVyPjxs

YXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3MzA3NzQxNTwvbGFzdC11cGRhdGVkLWRh

dGU+PGFjY2Vzc2lvbi1udW0+MjU1OTY3NjU8L2FjY2Vzc2lvbi1udW0+PGVsZWN0cm9uaWMtcmVz

b3VyY2UtbnVtPjEwLjEwMTYvai5tZWRpYS4yMDE0LjEyLjAwMzwvZWxlY3Ryb25pYy1yZXNvdXJj

ZS1udW0+PHZvbHVtZT4yMTwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48L0VuZE5vdGU+AAA=

ADDIN EN.CITE.DATA 23, 24 between Auto WML and expert MRI-WML drawings (median PEIS: 0.53, IQR: 0.48-0.57) was not significantly different to that between expert CT-WML and MRI-WML drawings (median PEIS: 0.54; IQR: 0.49-0.58; ranksum test, Z=1.0; p>0.1). Strength of correlation between Auto CT and expert drawings (CT or MRI) were not significantly influenced by age, sex, or co-existence of the following commonly-associated CT features: acute ischemic change, old infarct, central or peripheral atrophy, or other lesion (Z≤2.3, p>0.05 corrected; Table 1 lists frequencies of these features; see last example in Fig. 3 of WML segmentation adjacent to a co-existing old territorial infarct). Expert drawings took a median of 7.9 minutes per scan (range: 6.9 – 9.4), whereas Auto method (after pre-processing) took a median of 32s (95% CIs: 31-33s) per scan. Correlation coefficients between rater pairs (CT-CT or CT-MRI) were not significantly different from one another (?r: Z<1.8; p>0.1 corrected). Ordinal rating validationAgreement between Auto-derived ratings (i.e. thresholded WML-volume estimates) and individual experts’ ratings, using the Wahlund systemPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XYWhsdW5kPC9BdXRob3I+PFllYXI+MjAwMTwvWWVhcj48

SURUZXh0PkEgbmV3IHJhdGluZyBzY2FsZSBmb3IgYWdlLXJlbGF0ZWQgd2hpdGUgbWF0dGVyIGNo

YW5nZXMgYXBwbGljYWJsZSB0byBNUkkgYW5kIENULjwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5

bGUgZmFjZT0ic3VwZXJzY3JpcHQiPjEyPC9zdHlsZT48L0Rpc3BsYXlUZXh0PjxyZWNvcmQ+PGRh

dGVzPjxwdWItZGF0ZXM+PGRhdGU+SnVuPC9kYXRlPjwvcHViLWRhdGVzPjx5ZWFyPjIwMDE8L3ll

YXI+PC9kYXRlcz48a2V5d29yZHM+PGtleXdvcmQ+QWdpbmc8L2tleXdvcmQ+PGtleXdvcmQ+QnJh

aW48L2tleXdvcmQ+PGtleXdvcmQ+QnJhaW4gRGlzZWFzZXM8L2tleXdvcmQ+PGtleXdvcmQ+Q29n

bml0aW9uIERpc29yZGVyczwva2V5d29yZD48a2V5d29yZD5FdXJvcGU8L2tleXdvcmQ+PGtleXdv

cmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPk1hZ25ldGljIFJlc29uYW5jZSBJbWFnaW5nPC9r

ZXl3b3JkPjxrZXl3b3JkPk1lbW9yeSBEaXNvcmRlcnM8L2tleXdvcmQ+PGtleXdvcmQ+TXllbGlu

IFNoZWF0aDwva2V5d29yZD48a2V5d29yZD5PYnNlcnZlciBWYXJpYXRpb248L2tleXdvcmQ+PGtl

eXdvcmQ+UHJlZGljdGl2ZSBWYWx1ZSBvZiBUZXN0czwva2V5d29yZD48a2V5d29yZD5SZXByb2R1

Y2liaWxpdHkgb2YgUmVzdWx0czwva2V5d29yZD48a2V5d29yZD5TZW5zaXRpdml0eSBhbmQgU3Bl

Y2lmaWNpdHk8L2tleXdvcmQ+PGtleXdvcmQ+VG9tb2dyYXBoeSwgWC1SYXkgQ29tcHV0ZWQ8L2tl

eXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cDovL3d3dy5uY2Jp

Lm5sbS5uaWguZ292L3B1Ym1lZC8xMTM4NzQ5MzwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJscz48

aXNibj4xNTI0LTQ2Mjg8L2lzYm4+PHRpdGxlcz48dGl0bGU+QSBuZXcgcmF0aW5nIHNjYWxlIGZv

ciBhZ2UtcmVsYXRlZCB3aGl0ZSBtYXR0ZXIgY2hhbmdlcyBhcHBsaWNhYmxlIHRvIE1SSSBhbmQg

Q1QuPC90aXRsZT48c2Vjb25kYXJ5LXRpdGxlPlN0cm9rZTwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0

bGVzPjxwYWdlcz4xMzE4LTIyPC9wYWdlcz48bnVtYmVyPjY8L251bWJlcj48Y29udHJpYnV0b3Jz

PjxhdXRob3JzPjxhdXRob3I+V2FobHVuZCwgTC4gTy48L2F1dGhvcj48YXV0aG9yPkJhcmtob2Ys

IEYuPC9hdXRob3I+PGF1dGhvcj5GYXpla2FzLCBGLjwvYXV0aG9yPjxhdXRob3I+QnJvbmdlLCBM

LjwvYXV0aG9yPjxhdXRob3I+QXVndXN0aW4sIE0uPC9hdXRob3I+PGF1dGhvcj5TasO2Z3Jlbiwg

TS48L2F1dGhvcj48YXV0aG9yPldhbGxpbiwgQS48L2F1dGhvcj48YXV0aG9yPkFkZXIsIEguPC9h

dXRob3I+PGF1dGhvcj5MZXlzLCBELjwvYXV0aG9yPjxhdXRob3I+UGFudG9uaSwgTC48L2F1dGhv

cj48YXV0aG9yPlBhc3F1aWVyLCBGLjwvYXV0aG9yPjxhdXRob3I+RXJraW5qdW50dGksIFQuPC9h

dXRob3I+PGF1dGhvcj5TY2hlbHRlbnMsIFAuPC9hdXRob3I+PGF1dGhvcj5FdXJvcGVhbiBUYXNr

IEZvcmNlIG9uIEFnZS1SZWxhdGVkIFdoaXRlIE1hdHRlciBDaGFuZ2VzPC9hdXRob3I+PC9hdXRo

b3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5lbmc8L2xhbmd1YWdlPjxhZGRlZC1kYXRlIGZv

cm1hdD0idXRjIj4xMzM0OTM3NjY2PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1lPSJKb3VybmFs

IEFydGljbGUiPjE3PC9yZWYtdHlwZT48YXV0aC1hZGRyZXNzPkRlcGFydG1lbnQgb2YgQ2xpbmlj

YWwgTmV1cm9zY2llbmNlLCBORVVST1RFQywgS2Fyb2xpbnNrYSBJbnN0aXR1dGV0IGF0IEh1ZGRp

bmdlIFVuaXZlcnNpdHkgSG9zcGl0YWwsIEh1ZGRpbmdlLCBTd2VkZW4uIGxhcnMtb2xvZi53YWhs

dW5kQG5ldXJvdGVjLmtpLnNlPC9hdXRoLWFkZHJlc3M+PHJlYy1udW1iZXI+MTMzPC9yZWMtbnVt

YmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTMzNDkzNzY2NjwvbGFzdC11cGRh

dGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MTEzODc0OTM8L2FjY2Vzc2lvbi1udW0+PHZvbHVtZT4z

Mjwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48L0VuZE5vdGU+AAA=

ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XYWhsdW5kPC9BdXRob3I+PFllYXI+MjAwMTwvWWVhcj48

SURUZXh0PkEgbmV3IHJhdGluZyBzY2FsZSBmb3IgYWdlLXJlbGF0ZWQgd2hpdGUgbWF0dGVyIGNo

YW5nZXMgYXBwbGljYWJsZSB0byBNUkkgYW5kIENULjwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5

bGUgZmFjZT0ic3VwZXJzY3JpcHQiPjEyPC9zdHlsZT48L0Rpc3BsYXlUZXh0PjxyZWNvcmQ+PGRh

dGVzPjxwdWItZGF0ZXM+PGRhdGU+SnVuPC9kYXRlPjwvcHViLWRhdGVzPjx5ZWFyPjIwMDE8L3ll

YXI+PC9kYXRlcz48a2V5d29yZHM+PGtleXdvcmQ+QWdpbmc8L2tleXdvcmQ+PGtleXdvcmQ+QnJh

aW48L2tleXdvcmQ+PGtleXdvcmQ+QnJhaW4gRGlzZWFzZXM8L2tleXdvcmQ+PGtleXdvcmQ+Q29n

bml0aW9uIERpc29yZGVyczwva2V5d29yZD48a2V5d29yZD5FdXJvcGU8L2tleXdvcmQ+PGtleXdv

cmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPk1hZ25ldGljIFJlc29uYW5jZSBJbWFnaW5nPC9r

ZXl3b3JkPjxrZXl3b3JkPk1lbW9yeSBEaXNvcmRlcnM8L2tleXdvcmQ+PGtleXdvcmQ+TXllbGlu

IFNoZWF0aDwva2V5d29yZD48a2V5d29yZD5PYnNlcnZlciBWYXJpYXRpb248L2tleXdvcmQ+PGtl

eXdvcmQ+UHJlZGljdGl2ZSBWYWx1ZSBvZiBUZXN0czwva2V5d29yZD48a2V5d29yZD5SZXByb2R1

Y2liaWxpdHkgb2YgUmVzdWx0czwva2V5d29yZD48a2V5d29yZD5TZW5zaXRpdml0eSBhbmQgU3Bl

Y2lmaWNpdHk8L2tleXdvcmQ+PGtleXdvcmQ+VG9tb2dyYXBoeSwgWC1SYXkgQ29tcHV0ZWQ8L2tl

eXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cDovL3d3dy5uY2Jp

Lm5sbS5uaWguZ292L3B1Ym1lZC8xMTM4NzQ5MzwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJscz48

aXNibj4xNTI0LTQ2Mjg8L2lzYm4+PHRpdGxlcz48dGl0bGU+QSBuZXcgcmF0aW5nIHNjYWxlIGZv

ciBhZ2UtcmVsYXRlZCB3aGl0ZSBtYXR0ZXIgY2hhbmdlcyBhcHBsaWNhYmxlIHRvIE1SSSBhbmQg

Q1QuPC90aXRsZT48c2Vjb25kYXJ5LXRpdGxlPlN0cm9rZTwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0

bGVzPjxwYWdlcz4xMzE4LTIyPC9wYWdlcz48bnVtYmVyPjY8L251bWJlcj48Y29udHJpYnV0b3Jz

PjxhdXRob3JzPjxhdXRob3I+V2FobHVuZCwgTC4gTy48L2F1dGhvcj48YXV0aG9yPkJhcmtob2Ys

IEYuPC9hdXRob3I+PGF1dGhvcj5GYXpla2FzLCBGLjwvYXV0aG9yPjxhdXRob3I+QnJvbmdlLCBM

LjwvYXV0aG9yPjxhdXRob3I+QXVndXN0aW4sIE0uPC9hdXRob3I+PGF1dGhvcj5TasO2Z3Jlbiwg

TS48L2F1dGhvcj48YXV0aG9yPldhbGxpbiwgQS48L2F1dGhvcj48YXV0aG9yPkFkZXIsIEguPC9h

dXRob3I+PGF1dGhvcj5MZXlzLCBELjwvYXV0aG9yPjxhdXRob3I+UGFudG9uaSwgTC48L2F1dGhv

cj48YXV0aG9yPlBhc3F1aWVyLCBGLjwvYXV0aG9yPjxhdXRob3I+RXJraW5qdW50dGksIFQuPC9h

dXRob3I+PGF1dGhvcj5TY2hlbHRlbnMsIFAuPC9hdXRob3I+PGF1dGhvcj5FdXJvcGVhbiBUYXNr

IEZvcmNlIG9uIEFnZS1SZWxhdGVkIFdoaXRlIE1hdHRlciBDaGFuZ2VzPC9hdXRob3I+PC9hdXRo

b3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5lbmc8L2xhbmd1YWdlPjxhZGRlZC1kYXRlIGZv

cm1hdD0idXRjIj4xMzM0OTM3NjY2PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1lPSJKb3VybmFs

IEFydGljbGUiPjE3PC9yZWYtdHlwZT48YXV0aC1hZGRyZXNzPkRlcGFydG1lbnQgb2YgQ2xpbmlj

YWwgTmV1cm9zY2llbmNlLCBORVVST1RFQywgS2Fyb2xpbnNrYSBJbnN0aXR1dGV0IGF0IEh1ZGRp

bmdlIFVuaXZlcnNpdHkgSG9zcGl0YWwsIEh1ZGRpbmdlLCBTd2VkZW4uIGxhcnMtb2xvZi53YWhs

dW5kQG5ldXJvdGVjLmtpLnNlPC9hdXRoLWFkZHJlc3M+PHJlYy1udW1iZXI+MTMzPC9yZWMtbnVt

YmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTMzNDkzNzY2NjwvbGFzdC11cGRh

dGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MTEzODc0OTM8L2FjY2Vzc2lvbi1udW0+PHZvbHVtZT4z

Mjwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48L0VuZE5vdGU+AAA=

ADDIN EN.CITE.DATA 12, was moderate (kw=0.529), but not significantly different to agreements between expert pairs (kw=0.506; ?kw p>0.10; n=650; Table 3). However, agreement between Auto and expert consensus (kw=0.599) was superior to agreements between expert pairs (?kw p<0.001; Fig. 4A). Correlations of Auto WML volume with expert ratings was also greater using consensus (r2=0.582), than individual expert ratings (r2=0.506; ?r: Z=2.05, p<0.05).Using the alternative van Swieten grading system ADDIN EN.CITE <EndNote><Cite><Author>van Swieten</Author><Year>1990</Year><IDText>Grading white matter lesions on CT and MRI: a simple scale</IDText><DisplayText><style face="superscript">15</style></DisplayText><record><dates><pub-dates><date>Dec</date></pub-dates><year>1990</year></dates><keywords><keyword>Brain</keyword><keyword>Brain Diseases</keyword><keyword>Cross-Sectional Studies</keyword><keyword>Data Interpretation, Statistical</keyword><keyword>Humans</keyword><keyword>Ischemic Attack, Transient</keyword><keyword>Longitudinal Studies</keyword><keyword>Magnetic Resonance Imaging</keyword><keyword>Tomography, X-Ray Computed</keyword></keywords><urls><related-urls><url> white matter lesions on CT and MRI: a simple scale</title><secondary-title>J Neurol Neurosurg Psychiatry</secondary-title></titles><pages>1080-3</pages><number>12</number><contributors><authors><author>van Swieten, J. C.</author><author>Hijdra, A.</author><author>Koudstaal, P. J.</author><author>van Gijn, J.</author></authors></contributors><language>ENG</language><added-date format="utc">1478177600</added-date><ref-type name="Journal Article">17</ref-type><rec-number>531</rec-number><last-updated-date format="utc">1478177600</last-updated-date><accession-num>2292703</accession-num><volume>53</volume></record></Cite></EndNote>15, inter-expert agreements were higher (kw=0.665) than using the Wahlund system (?kw p<0.01), and also higher than the agreement between Auto method and individual experts (kw=0.571; ?kw p<0.05). However, inter-expert agreement was not significantly different to the agreement between Auto and expert consensus (kw=0.636; ?kw p>0.10). Correlations between Auto WML volume and expert consensus van Swieten ratings (r2=0.629) did not differ to that between Auto and expert-consensus Wahlund ratings, and individual-expert van Swieten ratings (p>0.10, for both). The proportion of cases in which Auto rating was >1 point different from expert consensus, i.e. strong disagreement, was 0.046, and 0.020, for Wahlund and van Swieten ratings, respectively (representing 72% false positives, and 28% false-negatives; outliers in Fig. 4B, D). Inter-rater agreements between any particular expert pairs, using either rating system, did not differ significantly from one another (p>0.05). Time-charts of raters (for Wahlund ratings) suggested that 30 scans took ~45-60 minutes to rate, ie about 1.5 to 2 mins each in total (including image-file selection, contrast adjustment, and judgements of three cerebral locations).DiscussionWe validate a novel machine-learning software that enables accurate, fully-automated, and rapid quantification of cerebral leukoaraiosis (WML) on CT. The automated method performed similarly to detailed, expert CT WML delineations – both in terms of lesion volume and spatial similarity - relative to a gold-standard of expert delineation of white-matter hyperintensities on coregistered T2-FLAIRPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XYXJkbGF3PC9BdXRob3I+PFllYXI+MjAxMzwvWWVhcj48

SURUZXh0Pk5ldXJvaW1hZ2luZyBzdGFuZGFyZHMgZm9yIHJlc2VhcmNoIGludG8gc21hbGwgdmVz

c2VsIGRpc2Vhc2UgYW5kIGl0cyBjb250cmlidXRpb24gdG8gYWdlaW5nIGFuZCBuZXVyb2RlZ2Vu

ZXJhdGlvbjwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5bGUgZmFjZT0ic3VwZXJzY3JpcHQiPjE8

L3N0eWxlPjwvRGlzcGxheVRleHQ+PHJlY29yZD48ZGF0ZXM+PHB1Yi1kYXRlcz48ZGF0ZT5BdWc8

L2RhdGU+PC9wdWItZGF0ZXM+PHllYXI+MjAxMzwveWVhcj48L2RhdGVzPjxrZXl3b3Jkcz48a2V5

d29yZD5BZ2luZzwva2V5d29yZD48a2V5d29yZD5DZXJlYnJhbCBTbWFsbCBWZXNzZWwgRGlzZWFz

ZXM8L2tleXdvcmQ+PGtleXdvcmQ+RmVtYWxlPC9rZXl3b3JkPjxrZXl3b3JkPkd1aWRlbGluZXMg

YXMgVG9waWM8L2tleXdvcmQ+PGtleXdvcmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPkltYWdl

IFByb2Nlc3NpbmcsIENvbXB1dGVyLUFzc2lzdGVkPC9rZXl3b3JkPjxrZXl3b3JkPkludGVybmF0

aW9uYWwgQ29vcGVyYXRpb248L2tleXdvcmQ+PGtleXdvcmQ+TWFsZTwva2V5d29yZD48a2V5d29y

ZD5OZXVyb2RlZ2VuZXJhdGl2ZSBEaXNlYXNlczwva2V5d29yZD48a2V5d29yZD5OZXVyb2ltYWdp

bmc8L2tleXdvcmQ+PGtleXdvcmQ+VGVybWlub2xvZ3kgYXMgVG9waWM8L2tleXdvcmQ+PC9rZXl3

b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cHM6Ly93d3cubmNiaS5ubG0ubmloLmdv

di9wdWJtZWQvMjM4NjcyMDA8L3VybD48L3JlbGF0ZWQtdXJscz48L3VybHM+PGlzYm4+MTQ3NC00

NDY1PC9pc2JuPjxjdXN0b20yPlBNQzM3MTQ0Mzc8L2N1c3RvbTI+PHRpdGxlcz48dGl0bGU+TmV1

cm9pbWFnaW5nIHN0YW5kYXJkcyBmb3IgcmVzZWFyY2ggaW50byBzbWFsbCB2ZXNzZWwgZGlzZWFz

ZSBhbmQgaXRzIGNvbnRyaWJ1dGlvbiB0byBhZ2VpbmcgYW5kIG5ldXJvZGVnZW5lcmF0aW9uPC90

aXRsZT48c2Vjb25kYXJ5LXRpdGxlPkxhbmNldCBOZXVyb2w8L3NlY29uZGFyeS10aXRsZT48L3Rp

dGxlcz48cGFnZXM+ODIyLTM4PC9wYWdlcz48bnVtYmVyPjg8L251bWJlcj48Y29udHJpYnV0b3Jz

PjxhdXRob3JzPjxhdXRob3I+V2FyZGxhdywgSi4gTS48L2F1dGhvcj48YXV0aG9yPlNtaXRoLCBF

LiBFLjwvYXV0aG9yPjxhdXRob3I+Qmllc3NlbHMsIEcuIEouPC9hdXRob3I+PGF1dGhvcj5Db3Jk

b25uaWVyLCBDLjwvYXV0aG9yPjxhdXRob3I+RmF6ZWthcywgRi48L2F1dGhvcj48YXV0aG9yPkZy

YXluZSwgUi48L2F1dGhvcj48YXV0aG9yPkxpbmRsZXksIFIuIEkuPC9hdXRob3I+PGF1dGhvcj5P

JmFwb3M7QnJpZW4sIEouIFQuPC9hdXRob3I+PGF1dGhvcj5CYXJraG9mLCBGLjwvYXV0aG9yPjxh

dXRob3I+QmVuYXZlbnRlLCBPLiBSLjwvYXV0aG9yPjxhdXRob3I+QmxhY2ssIFMuIEUuPC9hdXRo

b3I+PGF1dGhvcj5CcmF5bmUsIEMuPC9hdXRob3I+PGF1dGhvcj5CcmV0ZWxlciwgTS48L2F1dGhv

cj48YXV0aG9yPkNoYWJyaWF0LCBILjwvYXV0aG9yPjxhdXRob3I+RGVjYXJsaSwgQy48L2F1dGhv

cj48YXV0aG9yPmRlIExlZXV3LCBGLiBFLjwvYXV0aG9yPjxhdXRob3I+RG91YmFsLCBGLjwvYXV0

aG9yPjxhdXRob3I+RHVlcmluZywgTS48L2F1dGhvcj48YXV0aG9yPkZveCwgTi4gQy48L2F1dGhv

cj48YXV0aG9yPkdyZWVuYmVyZywgUy48L2F1dGhvcj48YXV0aG9yPkhhY2hpbnNraSwgVi48L2F1

dGhvcj48YXV0aG9yPktpbGltYW5uLCBJLjwvYXV0aG9yPjxhdXRob3I+TW9rLCBWLjwvYXV0aG9y

PjxhdXRob3I+T29zdGVuYnJ1Z2dlLCBSLjwvYXV0aG9yPjxhdXRob3I+UGFudG9uaSwgTC48L2F1

dGhvcj48YXV0aG9yPlNwZWNrLCBPLjwvYXV0aG9yPjxhdXRob3I+U3RlcGhhbiwgQi4gQy48L2F1

dGhvcj48YXV0aG9yPlRlaXBlbCwgUy48L2F1dGhvcj48YXV0aG9yPlZpc3dhbmF0aGFuLCBBLjwv

YXV0aG9yPjxhdXRob3I+V2VycmluZywgRC48L2F1dGhvcj48YXV0aG9yPkNoZW4sIEMuPC9hdXRo

b3I+PGF1dGhvcj5TbWl0aCwgQy48L2F1dGhvcj48YXV0aG9yPnZhbiBCdWNoZW0sIE0uPC9hdXRo

b3I+PGF1dGhvcj5Ob3JydmluZywgQi48L2F1dGhvcj48YXV0aG9yPkdvcmVsaWNrLCBQLiBCLjwv

YXV0aG9yPjxhdXRob3I+RGljaGdhbnMsIE0uPC9hdXRob3I+PGF1dGhvcj5TVGFuZGFyZHMgZm9y

IFJlcG9ydEluZyBWYXNjdWxhciBjaGFuZ2VzIG9uIG5FdXJvaW1hZ2luZyAoU1RSSVZFIHYxKTwv

YXV0aG9yPjwvYXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3VhZ2U+RU5HPC9sYW5ndWFnZT48

YWRkZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3ODE3NDU3MzwvYWRkZWQtZGF0ZT48cmVmLXR5cGUg

bmFtZT0iSm91cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PHJlYy1udW1iZXI+NTI0PC9yZWMt

bnVtYmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3ODE3NDU3MzwvbGFzdC11

cGRhdGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MjM4NjcyMDA8L2FjY2Vzc2lvbi1udW0+PGVsZWN0

cm9uaWMtcmVzb3VyY2UtbnVtPjEwLjEwMTYvUzE0NzQtNDQyMigxMyk3MDEyNC04PC9lbGVjdHJv

bmljLXJlc291cmNlLW51bT48dm9sdW1lPjEyPC92b2x1bWU+PC9yZWNvcmQ+PC9DaXRlPjwvRW5k

Tm90ZT4AAD==

ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XYXJkbGF3PC9BdXRob3I+PFllYXI+MjAxMzwvWWVhcj48

SURUZXh0Pk5ldXJvaW1hZ2luZyBzdGFuZGFyZHMgZm9yIHJlc2VhcmNoIGludG8gc21hbGwgdmVz

c2VsIGRpc2Vhc2UgYW5kIGl0cyBjb250cmlidXRpb24gdG8gYWdlaW5nIGFuZCBuZXVyb2RlZ2Vu

ZXJhdGlvbjwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5bGUgZmFjZT0ic3VwZXJzY3JpcHQiPjE8

L3N0eWxlPjwvRGlzcGxheVRleHQ+PHJlY29yZD48ZGF0ZXM+PHB1Yi1kYXRlcz48ZGF0ZT5BdWc8

L2RhdGU+PC9wdWItZGF0ZXM+PHllYXI+MjAxMzwveWVhcj48L2RhdGVzPjxrZXl3b3Jkcz48a2V5

d29yZD5BZ2luZzwva2V5d29yZD48a2V5d29yZD5DZXJlYnJhbCBTbWFsbCBWZXNzZWwgRGlzZWFz

ZXM8L2tleXdvcmQ+PGtleXdvcmQ+RmVtYWxlPC9rZXl3b3JkPjxrZXl3b3JkPkd1aWRlbGluZXMg

YXMgVG9waWM8L2tleXdvcmQ+PGtleXdvcmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPkltYWdl

IFByb2Nlc3NpbmcsIENvbXB1dGVyLUFzc2lzdGVkPC9rZXl3b3JkPjxrZXl3b3JkPkludGVybmF0

aW9uYWwgQ29vcGVyYXRpb248L2tleXdvcmQ+PGtleXdvcmQ+TWFsZTwva2V5d29yZD48a2V5d29y

ZD5OZXVyb2RlZ2VuZXJhdGl2ZSBEaXNlYXNlczwva2V5d29yZD48a2V5d29yZD5OZXVyb2ltYWdp

bmc8L2tleXdvcmQ+PGtleXdvcmQ+VGVybWlub2xvZ3kgYXMgVG9waWM8L2tleXdvcmQ+PC9rZXl3

b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cHM6Ly93d3cubmNiaS5ubG0ubmloLmdv

di9wdWJtZWQvMjM4NjcyMDA8L3VybD48L3JlbGF0ZWQtdXJscz48L3VybHM+PGlzYm4+MTQ3NC00

NDY1PC9pc2JuPjxjdXN0b20yPlBNQzM3MTQ0Mzc8L2N1c3RvbTI+PHRpdGxlcz48dGl0bGU+TmV1

cm9pbWFnaW5nIHN0YW5kYXJkcyBmb3IgcmVzZWFyY2ggaW50byBzbWFsbCB2ZXNzZWwgZGlzZWFz

ZSBhbmQgaXRzIGNvbnRyaWJ1dGlvbiB0byBhZ2VpbmcgYW5kIG5ldXJvZGVnZW5lcmF0aW9uPC90

aXRsZT48c2Vjb25kYXJ5LXRpdGxlPkxhbmNldCBOZXVyb2w8L3NlY29uZGFyeS10aXRsZT48L3Rp

dGxlcz48cGFnZXM+ODIyLTM4PC9wYWdlcz48bnVtYmVyPjg8L251bWJlcj48Y29udHJpYnV0b3Jz

PjxhdXRob3JzPjxhdXRob3I+V2FyZGxhdywgSi4gTS48L2F1dGhvcj48YXV0aG9yPlNtaXRoLCBF

LiBFLjwvYXV0aG9yPjxhdXRob3I+Qmllc3NlbHMsIEcuIEouPC9hdXRob3I+PGF1dGhvcj5Db3Jk

b25uaWVyLCBDLjwvYXV0aG9yPjxhdXRob3I+RmF6ZWthcywgRi48L2F1dGhvcj48YXV0aG9yPkZy

YXluZSwgUi48L2F1dGhvcj48YXV0aG9yPkxpbmRsZXksIFIuIEkuPC9hdXRob3I+PGF1dGhvcj5P

JmFwb3M7QnJpZW4sIEouIFQuPC9hdXRob3I+PGF1dGhvcj5CYXJraG9mLCBGLjwvYXV0aG9yPjxh

dXRob3I+QmVuYXZlbnRlLCBPLiBSLjwvYXV0aG9yPjxhdXRob3I+QmxhY2ssIFMuIEUuPC9hdXRo

b3I+PGF1dGhvcj5CcmF5bmUsIEMuPC9hdXRob3I+PGF1dGhvcj5CcmV0ZWxlciwgTS48L2F1dGhv

cj48YXV0aG9yPkNoYWJyaWF0LCBILjwvYXV0aG9yPjxhdXRob3I+RGVjYXJsaSwgQy48L2F1dGhv

cj48YXV0aG9yPmRlIExlZXV3LCBGLiBFLjwvYXV0aG9yPjxhdXRob3I+RG91YmFsLCBGLjwvYXV0

aG9yPjxhdXRob3I+RHVlcmluZywgTS48L2F1dGhvcj48YXV0aG9yPkZveCwgTi4gQy48L2F1dGhv

cj48YXV0aG9yPkdyZWVuYmVyZywgUy48L2F1dGhvcj48YXV0aG9yPkhhY2hpbnNraSwgVi48L2F1

dGhvcj48YXV0aG9yPktpbGltYW5uLCBJLjwvYXV0aG9yPjxhdXRob3I+TW9rLCBWLjwvYXV0aG9y

PjxhdXRob3I+T29zdGVuYnJ1Z2dlLCBSLjwvYXV0aG9yPjxhdXRob3I+UGFudG9uaSwgTC48L2F1

dGhvcj48YXV0aG9yPlNwZWNrLCBPLjwvYXV0aG9yPjxhdXRob3I+U3RlcGhhbiwgQi4gQy48L2F1

dGhvcj48YXV0aG9yPlRlaXBlbCwgUy48L2F1dGhvcj48YXV0aG9yPlZpc3dhbmF0aGFuLCBBLjwv

YXV0aG9yPjxhdXRob3I+V2VycmluZywgRC48L2F1dGhvcj48YXV0aG9yPkNoZW4sIEMuPC9hdXRo

b3I+PGF1dGhvcj5TbWl0aCwgQy48L2F1dGhvcj48YXV0aG9yPnZhbiBCdWNoZW0sIE0uPC9hdXRo

b3I+PGF1dGhvcj5Ob3JydmluZywgQi48L2F1dGhvcj48YXV0aG9yPkdvcmVsaWNrLCBQLiBCLjwv

YXV0aG9yPjxhdXRob3I+RGljaGdhbnMsIE0uPC9hdXRob3I+PGF1dGhvcj5TVGFuZGFyZHMgZm9y

IFJlcG9ydEluZyBWYXNjdWxhciBjaGFuZ2VzIG9uIG5FdXJvaW1hZ2luZyAoU1RSSVZFIHYxKTwv

YXV0aG9yPjwvYXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3VhZ2U+RU5HPC9sYW5ndWFnZT48

YWRkZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3ODE3NDU3MzwvYWRkZWQtZGF0ZT48cmVmLXR5cGUg

bmFtZT0iSm91cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PHJlYy1udW1iZXI+NTI0PC9yZWMt

bnVtYmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3ODE3NDU3MzwvbGFzdC11

cGRhdGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MjM4NjcyMDA8L2FjY2Vzc2lvbi1udW0+PGVsZWN0

cm9uaWMtcmVzb3VyY2UtbnVtPjEwLjEwMTYvUzE0NzQtNDQyMigxMyk3MDEyNC04PC9lbGVjdHJv

bmljLXJlc291cmNlLW51bT48dm9sdW1lPjEyPC92b2x1bWU+PC9yZWNvcmQ+PC9DaXRlPjwvRW5k

Tm90ZT4AAD==

ADDIN EN.CITE.DATA 1. Additionally, by thresholding automated WML volumes into ‘ratings’, agreements with experts’ CT-WML visual ratings were similar to those comparing agreements between expert pairs themselves. In the largest of our cohorts, agreement was greater for comparisons of automated method versus expert consensus ratings, than versus expert individual ratings (or agreements between expert individuals themselves) - which supports the automated method, given that consensus opinions generally lie closer to the truth ADDIN EN.CITE <EndNote><Cite><Author>Galton</Author><Year>1907</Year><IDText>Vox populi</IDText><DisplayText><style face="superscript">26</style></DisplayText><record><titles><title>Vox populi</title><secondary-title>Nature</secondary-title></titles><pages>450-451</pages><contributors><authors><author>Galton, Francis</author></authors></contributors><added-date format="utc">1478519585</added-date><ref-type name="Journal Article">17</ref-type><dates><year>1907</year></dates><rec-number>540</rec-number><last-updated-date format="utc">1478519954</last-updated-date><volume>75</volume></record></Cite></EndNote>26. Images comprised a range of image resolutions, scanner qualities, and hospital origins, and were derived from centres separate to that which contributed training images – indicating the technique’s robustness. Furthermore, accuracy of automated WML estimation was not hindered by common, co-existing hypoattenuating lesions e.g. acute or chronic ischemia (seen in 27% and 45% of our entire sample; equivalent to n=257 and 434 respectively). At the same time, our study confirmed previous findings that standard WML estimation methods, using CT images, result in relatively modest interrater agreement: with kappa values of 0.5 – 0.6 being typical for common rating systemsPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XYWhsdW5kPC9BdXRob3I+PFllYXI+MjAwMTwvWWVhcj48

SURUZXh0PkEgbmV3IHJhdGluZyBzY2FsZSBmb3IgYWdlLXJlbGF0ZWQgd2hpdGUgbWF0dGVyIGNo

YW5nZXMgYXBwbGljYWJsZSB0byBNUkkgYW5kIENULjwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5

bGUgZmFjZT0ic3VwZXJzY3JpcHQiPjEyLTE1PC9zdHlsZT48L0Rpc3BsYXlUZXh0PjxyZWNvcmQ+

PGRhdGVzPjxwdWItZGF0ZXM+PGRhdGU+SnVuPC9kYXRlPjwvcHViLWRhdGVzPjx5ZWFyPjIwMDE8

L3llYXI+PC9kYXRlcz48a2V5d29yZHM+PGtleXdvcmQ+QWdpbmc8L2tleXdvcmQ+PGtleXdvcmQ+

QnJhaW48L2tleXdvcmQ+PGtleXdvcmQ+QnJhaW4gRGlzZWFzZXM8L2tleXdvcmQ+PGtleXdvcmQ+

Q29nbml0aW9uIERpc29yZGVyczwva2V5d29yZD48a2V5d29yZD5FdXJvcGU8L2tleXdvcmQ+PGtl

eXdvcmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPk1hZ25ldGljIFJlc29uYW5jZSBJbWFnaW5n

PC9rZXl3b3JkPjxrZXl3b3JkPk1lbW9yeSBEaXNvcmRlcnM8L2tleXdvcmQ+PGtleXdvcmQ+TXll

bGluIFNoZWF0aDwva2V5d29yZD48a2V5d29yZD5PYnNlcnZlciBWYXJpYXRpb248L2tleXdvcmQ+

PGtleXdvcmQ+UHJlZGljdGl2ZSBWYWx1ZSBvZiBUZXN0czwva2V5d29yZD48a2V5d29yZD5SZXBy

b2R1Y2liaWxpdHkgb2YgUmVzdWx0czwva2V5d29yZD48a2V5d29yZD5TZW5zaXRpdml0eSBhbmQg

U3BlY2lmaWNpdHk8L2tleXdvcmQ+PGtleXdvcmQ+VG9tb2dyYXBoeSwgWC1SYXkgQ29tcHV0ZWQ8

L2tleXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cDovL3d3dy5u

Y2JpLm5sbS5uaWguZ292L3B1Ym1lZC8xMTM4NzQ5MzwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJs

cz48aXNibj4xNTI0LTQ2Mjg8L2lzYm4+PHRpdGxlcz48dGl0bGU+QSBuZXcgcmF0aW5nIHNjYWxl

IGZvciBhZ2UtcmVsYXRlZCB3aGl0ZSBtYXR0ZXIgY2hhbmdlcyBhcHBsaWNhYmxlIHRvIE1SSSBh

bmQgQ1QuPC90aXRsZT48c2Vjb25kYXJ5LXRpdGxlPlN0cm9rZTwvc2Vjb25kYXJ5LXRpdGxlPjwv

dGl0bGVzPjxwYWdlcz4xMzE4LTIyPC9wYWdlcz48bnVtYmVyPjY8L251bWJlcj48Y29udHJpYnV0

b3JzPjxhdXRob3JzPjxhdXRob3I+V2FobHVuZCwgTC4gTy48L2F1dGhvcj48YXV0aG9yPkJhcmto

b2YsIEYuPC9hdXRob3I+PGF1dGhvcj5GYXpla2FzLCBGLjwvYXV0aG9yPjxhdXRob3I+QnJvbmdl

LCBMLjwvYXV0aG9yPjxhdXRob3I+QXVndXN0aW4sIE0uPC9hdXRob3I+PGF1dGhvcj5TasO2Z3Jl

biwgTS48L2F1dGhvcj48YXV0aG9yPldhbGxpbiwgQS48L2F1dGhvcj48YXV0aG9yPkFkZXIsIEgu

PC9hdXRob3I+PGF1dGhvcj5MZXlzLCBELjwvYXV0aG9yPjxhdXRob3I+UGFudG9uaSwgTC48L2F1

dGhvcj48YXV0aG9yPlBhc3F1aWVyLCBGLjwvYXV0aG9yPjxhdXRob3I+RXJraW5qdW50dGksIFQu

PC9hdXRob3I+PGF1dGhvcj5TY2hlbHRlbnMsIFAuPC9hdXRob3I+PGF1dGhvcj5FdXJvcGVhbiBU

YXNrIEZvcmNlIG9uIEFnZS1SZWxhdGVkIFdoaXRlIE1hdHRlciBDaGFuZ2VzPC9hdXRob3I+PC9h

dXRob3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5lbmc8L2xhbmd1YWdlPjxhZGRlZC1kYXRl

IGZvcm1hdD0idXRjIj4xMzM0OTM3NjY2PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1lPSJKb3Vy

bmFsIEFydGljbGUiPjE3PC9yZWYtdHlwZT48YXV0aC1hZGRyZXNzPkRlcGFydG1lbnQgb2YgQ2xp

bmljYWwgTmV1cm9zY2llbmNlLCBORVVST1RFQywgS2Fyb2xpbnNrYSBJbnN0aXR1dGV0IGF0IEh1

ZGRpbmdlIFVuaXZlcnNpdHkgSG9zcGl0YWwsIEh1ZGRpbmdlLCBTd2VkZW4uIGxhcnMtb2xvZi53

YWhsdW5kQG5ldXJvdGVjLmtpLnNlPC9hdXRoLWFkZHJlc3M+PHJlYy1udW1iZXI+MTMzPC9yZWMt

bnVtYmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTMzNDkzNzY2NjwvbGFzdC11

cGRhdGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MTEzODc0OTM8L2FjY2Vzc2lvbi1udW0+PHZvbHVt

ZT4zMjwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48Q2l0ZT48QXV0aG9yPnZhbiBTd2lldGVuPC9B

dXRob3I+PFllYXI+MTk5MDwvWWVhcj48SURUZXh0PkdyYWRpbmcgd2hpdGUgbWF0dGVyIGxlc2lv

bnMgb24gQ1QgYW5kIE1SSTogYSBzaW1wbGUgc2NhbGU8L0lEVGV4dD48cmVjb3JkPjxkYXRlcz48

cHViLWRhdGVzPjxkYXRlPkRlYzwvZGF0ZT48L3B1Yi1kYXRlcz48eWVhcj4xOTkwPC95ZWFyPjwv

ZGF0ZXM+PGtleXdvcmRzPjxrZXl3b3JkPkJyYWluPC9rZXl3b3JkPjxrZXl3b3JkPkJyYWluIERp

c2Vhc2VzPC9rZXl3b3JkPjxrZXl3b3JkPkNyb3NzLVNlY3Rpb25hbCBTdHVkaWVzPC9rZXl3b3Jk

PjxrZXl3b3JkPkRhdGEgSW50ZXJwcmV0YXRpb24sIFN0YXRpc3RpY2FsPC9rZXl3b3JkPjxrZXl3

b3JkPkh1bWFuczwva2V5d29yZD48a2V5d29yZD5Jc2NoZW1pYyBBdHRhY2ssIFRyYW5zaWVudDwv

a2V5d29yZD48a2V5d29yZD5Mb25naXR1ZGluYWwgU3R1ZGllczwva2V5d29yZD48a2V5d29yZD5N

YWduZXRpYyBSZXNvbmFuY2UgSW1hZ2luZzwva2V5d29yZD48a2V5d29yZD5Ub21vZ3JhcGh5LCBY

LVJheSBDb21wdXRlZDwva2V5d29yZD48L2tleXdvcmRzPjx1cmxzPjxyZWxhdGVkLXVybHM+PHVy

bD5odHRwczovL3d3dy5uY2JpLm5sbS5uaWguZ292L3B1Ym1lZC8yMjkyNzAzPC91cmw+PC9yZWxh

dGVkLXVybHM+PC91cmxzPjxpc2JuPjAwMjItMzA1MDwvaXNibj48Y3VzdG9tMj5QTUM0ODgzMjA8

L2N1c3RvbTI+PHRpdGxlcz48dGl0bGU+R3JhZGluZyB3aGl0ZSBtYXR0ZXIgbGVzaW9ucyBvbiBD

VCBhbmQgTVJJOiBhIHNpbXBsZSBzY2FsZTwvdGl0bGU+PHNlY29uZGFyeS10aXRsZT5KIE5ldXJv

bCBOZXVyb3N1cmcgUHN5Y2hpYXRyeTwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0bGVzPjxwYWdlcz4x

MDgwLTM8L3BhZ2VzPjxudW1iZXI+MTI8L251bWJlcj48Y29udHJpYnV0b3JzPjxhdXRob3JzPjxh

dXRob3I+dmFuIFN3aWV0ZW4sIEouIEMuPC9hdXRob3I+PGF1dGhvcj5IaWpkcmEsIEEuPC9hdXRo

b3I+PGF1dGhvcj5Lb3Vkc3RhYWwsIFAuIEouPC9hdXRob3I+PGF1dGhvcj52YW4gR2lqbiwgSi48

L2F1dGhvcj48L2F1dGhvcnM+PC9jb250cmlidXRvcnM+PGxhbmd1YWdlPkVORzwvbGFuZ3VhZ2U+

PGFkZGVkLWRhdGUgZm9ybWF0PSJ1dGMiPjE0NzgxNzc2MDA8L2FkZGVkLWRhdGU+PHJlZi10eXBl

IG5hbWU9IkpvdXJuYWwgQXJ0aWNsZSI+MTc8L3JlZi10eXBlPjxyZWMtbnVtYmVyPjUzMTwvcmVj

LW51bWJlcj48bGFzdC11cGRhdGVkLWRhdGUgZm9ybWF0PSJ1dGMiPjE0NzgxNzc2MDA8L2xhc3Qt

dXBkYXRlZC1kYXRlPjxhY2Nlc3Npb24tbnVtPjIyOTI3MDM8L2FjY2Vzc2lvbi1udW0+PHZvbHVt

ZT41Mzwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48Q2l0ZT48QXV0aG9yPlNpbW9uaTwvQXV0aG9y

PjxZZWFyPjIwMTI8L1llYXI+PElEVGV4dD5BZ2UtIGFuZCBzZXgtc3BlY2lmaWMgcmF0ZXMgb2Yg

bGV1a29hcmFpb3NpcyBpbiBUSUEgYW5kIHN0cm9rZSBwYXRpZW50czogcG9wdWxhdGlvbi1iYXNl

ZCBzdHVkeTwvSURUZXh0PjxyZWNvcmQ+PGRhdGVzPjxwdWItZGF0ZXM+PGRhdGU+U2VwPC9kYXRl

PjwvcHViLWRhdGVzPjx5ZWFyPjIwMTI8L3llYXI+PC9kYXRlcz48a2V5d29yZHM+PGtleXdvcmQ+

QWdlIEZhY3RvcnM8L2tleXdvcmQ+PGtleXdvcmQ+QWdlZDwva2V5d29yZD48a2V5d29yZD5BZ2Vk

LCA4MCBhbmQgb3Zlcjwva2V5d29yZD48a2V5d29yZD5CcmFpbjwva2V5d29yZD48a2V5d29yZD5G

ZW1hbGU8L2tleXdvcmQ+PGtleXdvcmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPkluY2lkZW5j

ZTwva2V5d29yZD48a2V5d29yZD5Jc2NoZW1pYyBBdHRhY2ssIFRyYW5zaWVudDwva2V5d29yZD48

a2V5d29yZD5MZXVrb2FyYWlvc2lzPC9rZXl3b3JkPjxrZXl3b3JkPk1hZ25ldGljIFJlc29uYW5j

ZSBJbWFnaW5nPC9rZXl3b3JkPjxrZXl3b3JkPk1hbGU8L2tleXdvcmQ+PGtleXdvcmQ+TWlkZGxl

IEFnZWQ8L2tleXdvcmQ+PGtleXdvcmQ+TmVydmUgRmliZXJzLCBNeWVsaW5hdGVkPC9rZXl3b3Jk

PjxrZXl3b3JkPlByZXZhbGVuY2U8L2tleXdvcmQ+PGtleXdvcmQ+U2V4IENoYXJhY3RlcmlzdGlj

czwva2V5d29yZD48a2V5d29yZD5TdHJva2U8L2tleXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVs

YXRlZC11cmxzPjx1cmw+aHR0cHM6Ly93d3cubmNiaS5ubG0ubmloLmdvdi9wdWJtZWQvMjI5NTUx

Mzg8L3VybD48L3JlbGF0ZWQtdXJscz48L3VybHM+PGlzYm4+MTUyNi02MzJYPC9pc2JuPjxjdXN0

b20yPlBNQzM0NDA0NDc8L2N1c3RvbTI+PHRpdGxlcz48dGl0bGU+QWdlLSBhbmQgc2V4LXNwZWNp

ZmljIHJhdGVzIG9mIGxldWtvYXJhaW9zaXMgaW4gVElBIGFuZCBzdHJva2UgcGF0aWVudHM6IHBv

cHVsYXRpb24tYmFzZWQgc3R1ZHk8L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+TmV1cm9sb2d5PC9z

ZWNvbmRhcnktdGl0bGU+PC90aXRsZXM+PHBhZ2VzPjEyMTUtMjI8L3BhZ2VzPjxudW1iZXI+MTI8

L251bWJlcj48Y29udHJpYnV0b3JzPjxhdXRob3JzPjxhdXRob3I+U2ltb25pLCBNLjwvYXV0aG9y

PjxhdXRob3I+TGksIEwuPC9hdXRob3I+PGF1dGhvcj5QYXVsLCBOLiBMLjwvYXV0aG9yPjxhdXRo

b3I+R3J1dGVyLCBCLiBFLjwvYXV0aG9yPjxhdXRob3I+U2NodWx6LCBVLiBHLjwvYXV0aG9yPjxh

dXRob3I+S8O8a2VyLCBXLjwvYXV0aG9yPjxhdXRob3I+Um90aHdlbGwsIFAuIE0uPC9hdXRob3I+

PC9hdXRob3JzPjwvY29udHJpYnV0b3JzPjxlZGl0aW9uPjIwMTIvMDkvMDU8L2VkaXRpb24+PGxh

bmd1YWdlPmVuZzwvbGFuZ3VhZ2U+PGFkZGVkLWRhdGUgZm9ybWF0PSJ1dGMiPjE0ODg0NTcxMjg8

L2FkZGVkLWRhdGU+PHJlZi10eXBlIG5hbWU9IkpvdXJuYWwgQXJ0aWNsZSI+MTc8L3JlZi10eXBl

PjxyZWMtbnVtYmVyPjU3MTwvcmVjLW51bWJlcj48bGFzdC11cGRhdGVkLWRhdGUgZm9ybWF0PSJ1

dGMiPjE0ODg0NTcxMjg8L2xhc3QtdXBkYXRlZC1kYXRlPjxhY2Nlc3Npb24tbnVtPjIyOTU1MTM4

PC9hY2Nlc3Npb24tbnVtPjxlbGVjdHJvbmljLXJlc291cmNlLW51bT4xMC4xMjEyL1dOTC4wYjAx

M2UzMTgyNmI5NTFlPC9lbGVjdHJvbmljLXJlc291cmNlLW51bT48dm9sdW1lPjc5PC92b2x1bWU+

PC9yZWNvcmQ+PC9DaXRlPjxDaXRlPjxBdXRob3I+U2NoZWx0ZW5zPC9BdXRob3I+PFllYXI+MTk5

ODwvWWVhcj48SURUZXh0PldoaXRlIG1hdHRlciBjaGFuZ2VzIG9uIENUIGFuZCBNUkk6IGFuIG92

ZXJ2aWV3IG9mIHZpc3VhbCByYXRpbmcgc2NhbGVzLiBFdXJvcGVhbiBUYXNrIEZvcmNlIG9uIEFn

ZS1SZWxhdGVkIFdoaXRlIE1hdHRlciBDaGFuZ2VzPC9JRFRleHQ+PHJlY29yZD48a2V5d29yZHM+

PGtleXdvcmQ+QnJhaW4gSXNjaGVtaWE8L2tleXdvcmQ+PGtleXdvcmQ+RGVtZW50aWE8L2tleXdv

cmQ+PGtleXdvcmQ+RGlzYWJpbGl0eSBFdmFsdWF0aW9uPC9rZXl3b3JkPjxrZXl3b3JkPkh1bWFu

czwva2V5d29yZD48a2V5d29yZD5NYWduZXRpYyBSZXNvbmFuY2UgSW1hZ2luZzwva2V5d29yZD48

a2V5d29yZD5PYnNlcnZlciBWYXJpYXRpb248L2tleXdvcmQ+PGtleXdvcmQ+VG9tb2dyYXBoeSwg

WC1SYXkgQ29tcHV0ZWQ8L2tleXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1

cmw+aHR0cHM6Ly93d3cubmNiaS5ubG0ubmloLmdvdi9wdWJtZWQvOTUyMDA2ODwvdXJsPjwvcmVs

YXRlZC11cmxzPjwvdXJscz48aXNibj4wMDE0LTMwMjI8L2lzYm4+PHRpdGxlcz48dGl0bGU+V2hp

dGUgbWF0dGVyIGNoYW5nZXMgb24gQ1QgYW5kIE1SSTogYW4gb3ZlcnZpZXcgb2YgdmlzdWFsIHJh

dGluZyBzY2FsZXMuIEV1cm9wZWFuIFRhc2sgRm9yY2Ugb24gQWdlLVJlbGF0ZWQgV2hpdGUgTWF0

dGVyIENoYW5nZXM8L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+RXVyIE5ldXJvbDwvc2Vjb25kYXJ5

LXRpdGxlPjwvdGl0bGVzPjxwYWdlcz44MC05PC9wYWdlcz48bnVtYmVyPjI8L251bWJlcj48Y29u

dHJpYnV0b3JzPjxhdXRob3JzPjxhdXRob3I+U2NoZWx0ZW5zLCBQLjwvYXV0aG9yPjxhdXRob3I+

RXJraW5qdW50aSwgVC48L2F1dGhvcj48YXV0aG9yPkxleXMsIEQuPC9hdXRob3I+PGF1dGhvcj5X

YWhsdW5kLCBMLiBPLjwvYXV0aG9yPjxhdXRob3I+SW56aXRhcmksIEQuPC9hdXRob3I+PGF1dGhv

cj5kZWwgU2VyLCBULjwvYXV0aG9yPjxhdXRob3I+UGFzcXVpZXIsIEYuPC9hdXRob3I+PGF1dGhv

cj5CYXJraG9mLCBGLjwvYXV0aG9yPjxhdXRob3I+TcOkbnR5bMOkLCBSLjwvYXV0aG9yPjxhdXRo

b3I+Qm93bGVyLCBKLjwvYXV0aG9yPjxhdXRob3I+V2FsbGluLCBBLjwvYXV0aG9yPjxhdXRob3I+

R2hpa2EsIEouPC9hdXRob3I+PGF1dGhvcj5GYXpla2FzLCBGLjwvYXV0aG9yPjxhdXRob3I+UGFu

dG9uaSwgTC48L2F1dGhvcj48L2F1dGhvcnM+PC9jb250cmlidXRvcnM+PGxhbmd1YWdlPkVORzwv

bGFuZ3VhZ2U+PGFkZGVkLWRhdGUgZm9ybWF0PSJ1dGMiPjE0Nzg2OTkwNjQ8L2FkZGVkLWRhdGU+

PHJlZi10eXBlIG5hbWU9IkpvdXJuYWwgQXJ0aWNsZSI+MTc8L3JlZi10eXBlPjxkYXRlcz48eWVh

cj4xOTk4PC95ZWFyPjwvZGF0ZXM+PHJlYy1udW1iZXI+NTQ4PC9yZWMtbnVtYmVyPjxsYXN0LXVw

ZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3ODY5OTA2NDwvbGFzdC11cGRhdGVkLWRhdGU+PGFj

Y2Vzc2lvbi1udW0+OTUyMDA2ODwvYWNjZXNzaW9uLW51bT48dm9sdW1lPjM5PC92b2x1bWU+PC9y

ZWNvcmQ+PC9DaXRlPjwvRW5kTm90ZT4AAD==

ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XYWhsdW5kPC9BdXRob3I+PFllYXI+MjAwMTwvWWVhcj48

SURUZXh0PkEgbmV3IHJhdGluZyBzY2FsZSBmb3IgYWdlLXJlbGF0ZWQgd2hpdGUgbWF0dGVyIGNo

YW5nZXMgYXBwbGljYWJsZSB0byBNUkkgYW5kIENULjwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5

bGUgZmFjZT0ic3VwZXJzY3JpcHQiPjEyLTE1PC9zdHlsZT48L0Rpc3BsYXlUZXh0PjxyZWNvcmQ+

PGRhdGVzPjxwdWItZGF0ZXM+PGRhdGU+SnVuPC9kYXRlPjwvcHViLWRhdGVzPjx5ZWFyPjIwMDE8

L3llYXI+PC9kYXRlcz48a2V5d29yZHM+PGtleXdvcmQ+QWdpbmc8L2tleXdvcmQ+PGtleXdvcmQ+

QnJhaW48L2tleXdvcmQ+PGtleXdvcmQ+QnJhaW4gRGlzZWFzZXM8L2tleXdvcmQ+PGtleXdvcmQ+

Q29nbml0aW9uIERpc29yZGVyczwva2V5d29yZD48a2V5d29yZD5FdXJvcGU8L2tleXdvcmQ+PGtl

eXdvcmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPk1hZ25ldGljIFJlc29uYW5jZSBJbWFnaW5n

PC9rZXl3b3JkPjxrZXl3b3JkPk1lbW9yeSBEaXNvcmRlcnM8L2tleXdvcmQ+PGtleXdvcmQ+TXll

bGluIFNoZWF0aDwva2V5d29yZD48a2V5d29yZD5PYnNlcnZlciBWYXJpYXRpb248L2tleXdvcmQ+

PGtleXdvcmQ+UHJlZGljdGl2ZSBWYWx1ZSBvZiBUZXN0czwva2V5d29yZD48a2V5d29yZD5SZXBy

b2R1Y2liaWxpdHkgb2YgUmVzdWx0czwva2V5d29yZD48a2V5d29yZD5TZW5zaXRpdml0eSBhbmQg

U3BlY2lmaWNpdHk8L2tleXdvcmQ+PGtleXdvcmQ+VG9tb2dyYXBoeSwgWC1SYXkgQ29tcHV0ZWQ8

L2tleXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cDovL3d3dy5u

Y2JpLm5sbS5uaWguZ292L3B1Ym1lZC8xMTM4NzQ5MzwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJs

cz48aXNibj4xNTI0LTQ2Mjg8L2lzYm4+PHRpdGxlcz48dGl0bGU+QSBuZXcgcmF0aW5nIHNjYWxl

IGZvciBhZ2UtcmVsYXRlZCB3aGl0ZSBtYXR0ZXIgY2hhbmdlcyBhcHBsaWNhYmxlIHRvIE1SSSBh

bmQgQ1QuPC90aXRsZT48c2Vjb25kYXJ5LXRpdGxlPlN0cm9rZTwvc2Vjb25kYXJ5LXRpdGxlPjwv

dGl0bGVzPjxwYWdlcz4xMzE4LTIyPC9wYWdlcz48bnVtYmVyPjY8L251bWJlcj48Y29udHJpYnV0

b3JzPjxhdXRob3JzPjxhdXRob3I+V2FobHVuZCwgTC4gTy48L2F1dGhvcj48YXV0aG9yPkJhcmto

b2YsIEYuPC9hdXRob3I+PGF1dGhvcj5GYXpla2FzLCBGLjwvYXV0aG9yPjxhdXRob3I+QnJvbmdl

LCBMLjwvYXV0aG9yPjxhdXRob3I+QXVndXN0aW4sIE0uPC9hdXRob3I+PGF1dGhvcj5TasO2Z3Jl

biwgTS48L2F1dGhvcj48YXV0aG9yPldhbGxpbiwgQS48L2F1dGhvcj48YXV0aG9yPkFkZXIsIEgu

PC9hdXRob3I+PGF1dGhvcj5MZXlzLCBELjwvYXV0aG9yPjxhdXRob3I+UGFudG9uaSwgTC48L2F1

dGhvcj48YXV0aG9yPlBhc3F1aWVyLCBGLjwvYXV0aG9yPjxhdXRob3I+RXJraW5qdW50dGksIFQu

PC9hdXRob3I+PGF1dGhvcj5TY2hlbHRlbnMsIFAuPC9hdXRob3I+PGF1dGhvcj5FdXJvcGVhbiBU

YXNrIEZvcmNlIG9uIEFnZS1SZWxhdGVkIFdoaXRlIE1hdHRlciBDaGFuZ2VzPC9hdXRob3I+PC9h

dXRob3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5lbmc8L2xhbmd1YWdlPjxhZGRlZC1kYXRl

IGZvcm1hdD0idXRjIj4xMzM0OTM3NjY2PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1lPSJKb3Vy

bmFsIEFydGljbGUiPjE3PC9yZWYtdHlwZT48YXV0aC1hZGRyZXNzPkRlcGFydG1lbnQgb2YgQ2xp

bmljYWwgTmV1cm9zY2llbmNlLCBORVVST1RFQywgS2Fyb2xpbnNrYSBJbnN0aXR1dGV0IGF0IEh1

ZGRpbmdlIFVuaXZlcnNpdHkgSG9zcGl0YWwsIEh1ZGRpbmdlLCBTd2VkZW4uIGxhcnMtb2xvZi53

YWhsdW5kQG5ldXJvdGVjLmtpLnNlPC9hdXRoLWFkZHJlc3M+PHJlYy1udW1iZXI+MTMzPC9yZWMt

bnVtYmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTMzNDkzNzY2NjwvbGFzdC11

cGRhdGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MTEzODc0OTM8L2FjY2Vzc2lvbi1udW0+PHZvbHVt

ZT4zMjwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48Q2l0ZT48QXV0aG9yPnZhbiBTd2lldGVuPC9B

dXRob3I+PFllYXI+MTk5MDwvWWVhcj48SURUZXh0PkdyYWRpbmcgd2hpdGUgbWF0dGVyIGxlc2lv

bnMgb24gQ1QgYW5kIE1SSTogYSBzaW1wbGUgc2NhbGU8L0lEVGV4dD48cmVjb3JkPjxkYXRlcz48

cHViLWRhdGVzPjxkYXRlPkRlYzwvZGF0ZT48L3B1Yi1kYXRlcz48eWVhcj4xOTkwPC95ZWFyPjwv

ZGF0ZXM+PGtleXdvcmRzPjxrZXl3b3JkPkJyYWluPC9rZXl3b3JkPjxrZXl3b3JkPkJyYWluIERp

c2Vhc2VzPC9rZXl3b3JkPjxrZXl3b3JkPkNyb3NzLVNlY3Rpb25hbCBTdHVkaWVzPC9rZXl3b3Jk

PjxrZXl3b3JkPkRhdGEgSW50ZXJwcmV0YXRpb24sIFN0YXRpc3RpY2FsPC9rZXl3b3JkPjxrZXl3

b3JkPkh1bWFuczwva2V5d29yZD48a2V5d29yZD5Jc2NoZW1pYyBBdHRhY2ssIFRyYW5zaWVudDwv

a2V5d29yZD48a2V5d29yZD5Mb25naXR1ZGluYWwgU3R1ZGllczwva2V5d29yZD48a2V5d29yZD5N

YWduZXRpYyBSZXNvbmFuY2UgSW1hZ2luZzwva2V5d29yZD48a2V5d29yZD5Ub21vZ3JhcGh5LCBY

LVJheSBDb21wdXRlZDwva2V5d29yZD48L2tleXdvcmRzPjx1cmxzPjxyZWxhdGVkLXVybHM+PHVy

bD5odHRwczovL3d3dy5uY2JpLm5sbS5uaWguZ292L3B1Ym1lZC8yMjkyNzAzPC91cmw+PC9yZWxh

dGVkLXVybHM+PC91cmxzPjxpc2JuPjAwMjItMzA1MDwvaXNibj48Y3VzdG9tMj5QTUM0ODgzMjA8

L2N1c3RvbTI+PHRpdGxlcz48dGl0bGU+R3JhZGluZyB3aGl0ZSBtYXR0ZXIgbGVzaW9ucyBvbiBD

VCBhbmQgTVJJOiBhIHNpbXBsZSBzY2FsZTwvdGl0bGU+PHNlY29uZGFyeS10aXRsZT5KIE5ldXJv

bCBOZXVyb3N1cmcgUHN5Y2hpYXRyeTwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0bGVzPjxwYWdlcz4x

MDgwLTM8L3BhZ2VzPjxudW1iZXI+MTI8L251bWJlcj48Y29udHJpYnV0b3JzPjxhdXRob3JzPjxh

dXRob3I+dmFuIFN3aWV0ZW4sIEouIEMuPC9hdXRob3I+PGF1dGhvcj5IaWpkcmEsIEEuPC9hdXRo

b3I+PGF1dGhvcj5Lb3Vkc3RhYWwsIFAuIEouPC9hdXRob3I+PGF1dGhvcj52YW4gR2lqbiwgSi48

L2F1dGhvcj48L2F1dGhvcnM+PC9jb250cmlidXRvcnM+PGxhbmd1YWdlPkVORzwvbGFuZ3VhZ2U+

PGFkZGVkLWRhdGUgZm9ybWF0PSJ1dGMiPjE0NzgxNzc2MDA8L2FkZGVkLWRhdGU+PHJlZi10eXBl

IG5hbWU9IkpvdXJuYWwgQXJ0aWNsZSI+MTc8L3JlZi10eXBlPjxyZWMtbnVtYmVyPjUzMTwvcmVj

LW51bWJlcj48bGFzdC11cGRhdGVkLWRhdGUgZm9ybWF0PSJ1dGMiPjE0NzgxNzc2MDA8L2xhc3Qt

dXBkYXRlZC1kYXRlPjxhY2Nlc3Npb24tbnVtPjIyOTI3MDM8L2FjY2Vzc2lvbi1udW0+PHZvbHVt

ZT41Mzwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48Q2l0ZT48QXV0aG9yPlNpbW9uaTwvQXV0aG9y

PjxZZWFyPjIwMTI8L1llYXI+PElEVGV4dD5BZ2UtIGFuZCBzZXgtc3BlY2lmaWMgcmF0ZXMgb2Yg

bGV1a29hcmFpb3NpcyBpbiBUSUEgYW5kIHN0cm9rZSBwYXRpZW50czogcG9wdWxhdGlvbi1iYXNl

ZCBzdHVkeTwvSURUZXh0PjxyZWNvcmQ+PGRhdGVzPjxwdWItZGF0ZXM+PGRhdGU+U2VwPC9kYXRl

PjwvcHViLWRhdGVzPjx5ZWFyPjIwMTI8L3llYXI+PC9kYXRlcz48a2V5d29yZHM+PGtleXdvcmQ+

QWdlIEZhY3RvcnM8L2tleXdvcmQ+PGtleXdvcmQ+QWdlZDwva2V5d29yZD48a2V5d29yZD5BZ2Vk

LCA4MCBhbmQgb3Zlcjwva2V5d29yZD48a2V5d29yZD5CcmFpbjwva2V5d29yZD48a2V5d29yZD5G

ZW1hbGU8L2tleXdvcmQ+PGtleXdvcmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPkluY2lkZW5j

ZTwva2V5d29yZD48a2V5d29yZD5Jc2NoZW1pYyBBdHRhY2ssIFRyYW5zaWVudDwva2V5d29yZD48

a2V5d29yZD5MZXVrb2FyYWlvc2lzPC9rZXl3b3JkPjxrZXl3b3JkPk1hZ25ldGljIFJlc29uYW5j

ZSBJbWFnaW5nPC9rZXl3b3JkPjxrZXl3b3JkPk1hbGU8L2tleXdvcmQ+PGtleXdvcmQ+TWlkZGxl

IEFnZWQ8L2tleXdvcmQ+PGtleXdvcmQ+TmVydmUgRmliZXJzLCBNeWVsaW5hdGVkPC9rZXl3b3Jk

PjxrZXl3b3JkPlByZXZhbGVuY2U8L2tleXdvcmQ+PGtleXdvcmQ+U2V4IENoYXJhY3RlcmlzdGlj

czwva2V5d29yZD48a2V5d29yZD5TdHJva2U8L2tleXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVs

YXRlZC11cmxzPjx1cmw+aHR0cHM6Ly93d3cubmNiaS5ubG0ubmloLmdvdi9wdWJtZWQvMjI5NTUx

Mzg8L3VybD48L3JlbGF0ZWQtdXJscz48L3VybHM+PGlzYm4+MTUyNi02MzJYPC9pc2JuPjxjdXN0

b20yPlBNQzM0NDA0NDc8L2N1c3RvbTI+PHRpdGxlcz48dGl0bGU+QWdlLSBhbmQgc2V4LXNwZWNp

ZmljIHJhdGVzIG9mIGxldWtvYXJhaW9zaXMgaW4gVElBIGFuZCBzdHJva2UgcGF0aWVudHM6IHBv

cHVsYXRpb24tYmFzZWQgc3R1ZHk8L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+TmV1cm9sb2d5PC9z

ZWNvbmRhcnktdGl0bGU+PC90aXRsZXM+PHBhZ2VzPjEyMTUtMjI8L3BhZ2VzPjxudW1iZXI+MTI8

L251bWJlcj48Y29udHJpYnV0b3JzPjxhdXRob3JzPjxhdXRob3I+U2ltb25pLCBNLjwvYXV0aG9y

PjxhdXRob3I+TGksIEwuPC9hdXRob3I+PGF1dGhvcj5QYXVsLCBOLiBMLjwvYXV0aG9yPjxhdXRo

b3I+R3J1dGVyLCBCLiBFLjwvYXV0aG9yPjxhdXRob3I+U2NodWx6LCBVLiBHLjwvYXV0aG9yPjxh

dXRob3I+S8O8a2VyLCBXLjwvYXV0aG9yPjxhdXRob3I+Um90aHdlbGwsIFAuIE0uPC9hdXRob3I+

PC9hdXRob3JzPjwvY29udHJpYnV0b3JzPjxlZGl0aW9uPjIwMTIvMDkvMDU8L2VkaXRpb24+PGxh

bmd1YWdlPmVuZzwvbGFuZ3VhZ2U+PGFkZGVkLWRhdGUgZm9ybWF0PSJ1dGMiPjE0ODg0NTcxMjg8

L2FkZGVkLWRhdGU+PHJlZi10eXBlIG5hbWU9IkpvdXJuYWwgQXJ0aWNsZSI+MTc8L3JlZi10eXBl

PjxyZWMtbnVtYmVyPjU3MTwvcmVjLW51bWJlcj48bGFzdC11cGRhdGVkLWRhdGUgZm9ybWF0PSJ1

dGMiPjE0ODg0NTcxMjg8L2xhc3QtdXBkYXRlZC1kYXRlPjxhY2Nlc3Npb24tbnVtPjIyOTU1MTM4

PC9hY2Nlc3Npb24tbnVtPjxlbGVjdHJvbmljLXJlc291cmNlLW51bT4xMC4xMjEyL1dOTC4wYjAx

M2UzMTgyNmI5NTFlPC9lbGVjdHJvbmljLXJlc291cmNlLW51bT48dm9sdW1lPjc5PC92b2x1bWU+

PC9yZWNvcmQ+PC9DaXRlPjxDaXRlPjxBdXRob3I+U2NoZWx0ZW5zPC9BdXRob3I+PFllYXI+MTk5

ODwvWWVhcj48SURUZXh0PldoaXRlIG1hdHRlciBjaGFuZ2VzIG9uIENUIGFuZCBNUkk6IGFuIG92

ZXJ2aWV3IG9mIHZpc3VhbCByYXRpbmcgc2NhbGVzLiBFdXJvcGVhbiBUYXNrIEZvcmNlIG9uIEFn

ZS1SZWxhdGVkIFdoaXRlIE1hdHRlciBDaGFuZ2VzPC9JRFRleHQ+PHJlY29yZD48a2V5d29yZHM+

PGtleXdvcmQ+QnJhaW4gSXNjaGVtaWE8L2tleXdvcmQ+PGtleXdvcmQ+RGVtZW50aWE8L2tleXdv

cmQ+PGtleXdvcmQ+RGlzYWJpbGl0eSBFdmFsdWF0aW9uPC9rZXl3b3JkPjxrZXl3b3JkPkh1bWFu

czwva2V5d29yZD48a2V5d29yZD5NYWduZXRpYyBSZXNvbmFuY2UgSW1hZ2luZzwva2V5d29yZD48

a2V5d29yZD5PYnNlcnZlciBWYXJpYXRpb248L2tleXdvcmQ+PGtleXdvcmQ+VG9tb2dyYXBoeSwg

WC1SYXkgQ29tcHV0ZWQ8L2tleXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1

cmw+aHR0cHM6Ly93d3cubmNiaS5ubG0ubmloLmdvdi9wdWJtZWQvOTUyMDA2ODwvdXJsPjwvcmVs

YXRlZC11cmxzPjwvdXJscz48aXNibj4wMDE0LTMwMjI8L2lzYm4+PHRpdGxlcz48dGl0bGU+V2hp

dGUgbWF0dGVyIGNoYW5nZXMgb24gQ1QgYW5kIE1SSTogYW4gb3ZlcnZpZXcgb2YgdmlzdWFsIHJh

dGluZyBzY2FsZXMuIEV1cm9wZWFuIFRhc2sgRm9yY2Ugb24gQWdlLVJlbGF0ZWQgV2hpdGUgTWF0

dGVyIENoYW5nZXM8L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+RXVyIE5ldXJvbDwvc2Vjb25kYXJ5

LXRpdGxlPjwvdGl0bGVzPjxwYWdlcz44MC05PC9wYWdlcz48bnVtYmVyPjI8L251bWJlcj48Y29u

dHJpYnV0b3JzPjxhdXRob3JzPjxhdXRob3I+U2NoZWx0ZW5zLCBQLjwvYXV0aG9yPjxhdXRob3I+

RXJraW5qdW50aSwgVC48L2F1dGhvcj48YXV0aG9yPkxleXMsIEQuPC9hdXRob3I+PGF1dGhvcj5X

YWhsdW5kLCBMLiBPLjwvYXV0aG9yPjxhdXRob3I+SW56aXRhcmksIEQuPC9hdXRob3I+PGF1dGhv

cj5kZWwgU2VyLCBULjwvYXV0aG9yPjxhdXRob3I+UGFzcXVpZXIsIEYuPC9hdXRob3I+PGF1dGhv

cj5CYXJraG9mLCBGLjwvYXV0aG9yPjxhdXRob3I+TcOkbnR5bMOkLCBSLjwvYXV0aG9yPjxhdXRo

b3I+Qm93bGVyLCBKLjwvYXV0aG9yPjxhdXRob3I+V2FsbGluLCBBLjwvYXV0aG9yPjxhdXRob3I+

R2hpa2EsIEouPC9hdXRob3I+PGF1dGhvcj5GYXpla2FzLCBGLjwvYXV0aG9yPjxhdXRob3I+UGFu

dG9uaSwgTC48L2F1dGhvcj48L2F1dGhvcnM+PC9jb250cmlidXRvcnM+PGxhbmd1YWdlPkVORzwv

bGFuZ3VhZ2U+PGFkZGVkLWRhdGUgZm9ybWF0PSJ1dGMiPjE0Nzg2OTkwNjQ8L2FkZGVkLWRhdGU+

PHJlZi10eXBlIG5hbWU9IkpvdXJuYWwgQXJ0aWNsZSI+MTc8L3JlZi10eXBlPjxkYXRlcz48eWVh

cj4xOTk4PC95ZWFyPjwvZGF0ZXM+PHJlYy1udW1iZXI+NTQ4PC9yZWMtbnVtYmVyPjxsYXN0LXVw

ZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3ODY5OTA2NDwvbGFzdC11cGRhdGVkLWRhdGU+PGFj

Y2Vzc2lvbi1udW0+OTUyMDA2ODwvYWNjZXNzaW9uLW51bT48dm9sdW1lPjM5PC92b2x1bWU+PC9y

ZWNvcmQ+PC9DaXRlPjwvRW5kTm90ZT4AAD==

ADDIN EN.CITE.DATA 12-15. This was also shown by the finding that expert CT delineations resulted in a wide range of estimated WML-volumes (mean range of 3 experts: 91% of expert mean), even though they correlated strongly with each other (r2: 0.85). By contrast, the automated method always results in the same estimate of WML volume, once model parameters have been set. Importantly, the parameters of the model tested here did not alter, and were based upon an independent prior dataset. Thus the automated method allows for a reduction in variable noise compared to existing WML scoring techniques, potentially enabling more reliable diagnostic and prognostic models to be developed. A further asset of the automated method is that processing time averaged 109 s (including image pre-processing), with the range being < 3 minutes (similar to experts performing visual ratings). Considering that images originated from a number of centres, and CT-scanners, this performance metric suggests that the automated method could be used widely in emergency-rooms for rapid estimation of background WML from CT. The technique’s option of superimposing machine-identified WML (Fig. 3) can provide extra physician reassurance regarding the algorithm’s output, and assist imaging interpretation by clinicians who are not so experienced in this. Notwithstanding the automated method’s advantages, we also draw attention to its limitations. CT images could not be processed in ~ 4% of cases, that were only partially accountable by poor image-quality issues. Additionally, among images that were processed, significant errors were made (>1 point from consensus rating) in~4%. Although smaller discrepancies with consensus (±1 point from consensus rating) were made in ~30% of cases, it is important to note that expert ratings were based upon judging categorical features (e.g. focal versus confluent lesions; extension to cortex or not) that are not directly proportional to lesion volume. Hence a better judge of Auto method’s accuracy is measuring discrepancy of automated estimates from volumes of expert drawings. In this regard, while Auto-versus-expert drawing correlations were strong, there is also a consistent underestimation of Auto WML volume relative to expert volumes (seen increasingly as WML volume increases: Fig. 2). The fact that this underestimate was of a predictable size relative to the ground-truth of MRI-estimated WML, suggests a suitable scaling factor could be applied. Furthermore, the fact that Auto WML segmentations spatial similarity to MRI-WML was not significantly different to experts’ CT annotations, despite the former being smaller, indicates that the additional areas annotated by experts are not as accurate as the core areas identified by both Auto and expert. The main reason for wishing to quantify WML on CT, rather than MRI, is practicality. CT is the principle neuroimaging modality for emergencies such as acute stroke ADDIN EN.CITE <EndNote><Cite><Author>Sanossian</Author><Year>2016</Year><IDText>Utilization of Emergent Neuroimaging for Thrombolysis-Eligible Stroke Patients</IDText><DisplayText><style face="superscript">3</style></DisplayText><record><dates><pub-dates><date>Jun</date></pub-dates><year>2016</year></dates><urls><related-urls><url> of Emergent Neuroimaging for Thrombolysis-Eligible Stroke Patients</title><secondary-title>J Neuroimaging</secondary-title></titles><contributors><authors><author>Sanossian, N.</author><author>Fu, K. A.</author><author>Liebeskind, D. S.</author><author>Starkman, S.</author><author>Hamilton, S.</author><author>Villablanca, J. P.</author><author>Burgos, A. M.</author><author>Conwit, R.</author><author>Saver, J. L.</author></authors></contributors><language>ENG</language><added-date format="utc">1478706286</added-date><ref-type name="Journal Article">17</ref-type><rec-number>552</rec-number><last-updated-date format="utc">1478706286</last-updated-date><accession-num>27300498</accession-num><electronic-resource-num>10.1111/jon.12369</electronic-resource-num></record></Cite></EndNote>3, and head trauma; and is often the sole imaging technique for investigation of dementiaPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5LdXJ1dmlsbGE8L0F1dGhvcj48WWVhcj4yMDE0PC9ZZWFy

PjxJRFRleHQ+TmV1cm9pbWFnaW5nIGluIGEgbWVtb3J5IGFzc2Vzc21lbnQgc2VydmljZTogYSBj

b21wbGV0ZWQgYXVkaXQgY3ljbGU8L0lEVGV4dD48RGlzcGxheVRleHQ+PHN0eWxlIGZhY2U9InN1

cGVyc2NyaXB0Ij45LTExPC9zdHlsZT48L0Rpc3BsYXlUZXh0PjxyZWNvcmQ+PGRhdGVzPjxwdWIt

ZGF0ZXM+PGRhdGU+RmViPC9kYXRlPjwvcHViLWRhdGVzPjx5ZWFyPjIwMTQ8L3llYXI+PC9kYXRl

cz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cHM6Ly93d3cubmNiaS5ubG0ubmloLmdvdi9w

dWJtZWQvMjUyMzc0ODY8L3VybD48L3JlbGF0ZWQtdXJscz48L3VybHM+PGlzYm4+MjA1My00ODY4

PC9pc2JuPjxjdXN0b20yPlBNQzQwNjc4NDQ8L2N1c3RvbTI+PHRpdGxlcz48dGl0bGU+TmV1cm9p

bWFnaW5nIGluIGEgbWVtb3J5IGFzc2Vzc21lbnQgc2VydmljZTogYSBjb21wbGV0ZWQgYXVkaXQg

Y3ljbGU8L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+UHN5Y2hpYXRyIEJ1bGwgKDIwMTQpPC9zZWNv

bmRhcnktdGl0bGU+PC90aXRsZXM+PHBhZ2VzPjI0LTg8L3BhZ2VzPjxudW1iZXI+MTwvbnVtYmVy

Pjxjb250cmlidXRvcnM+PGF1dGhvcnM+PGF1dGhvcj5LdXJ1dmlsbGEsIFQuPC9hdXRob3I+PGF1

dGhvcj5aaGVuZywgUi48L2F1dGhvcj48YXV0aG9yPlNvZGVuLCBCLjwvYXV0aG9yPjxhdXRob3I+

R3JlZWYsIFMuPC9hdXRob3I+PGF1dGhvcj5MeWJ1cm4sIEkuPC9hdXRob3I+PC9hdXRob3JzPjwv

Y29udHJpYnV0b3JzPjxsYW5ndWFnZT5FTkc8L2xhbmd1YWdlPjxhZGRlZC1kYXRlIGZvcm1hdD0i

dXRjIj4xNDc4MTc1MzMxPC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1lPSJKb3VybmFsIEFydGlj

bGUiPjE3PC9yZWYtdHlwZT48cmVjLW51bWJlcj41Mjc8L3JlYy1udW1iZXI+PGxhc3QtdXBkYXRl

ZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc4MTc1MzMxPC9sYXN0LXVwZGF0ZWQtZGF0ZT48YWNjZXNz

aW9uLW51bT4yNTIzNzQ4NjwvYWNjZXNzaW9uLW51bT48ZWxlY3Ryb25pYy1yZXNvdXJjZS1udW0+

MTAuMTE5Mi9wYi5icC4xMTMuMDQzMzk4PC9lbGVjdHJvbmljLXJlc291cmNlLW51bT48dm9sdW1l

PjM4PC92b2x1bWU+PC9yZWNvcmQ+PC9DaXRlPjxDaXRlPjxBdXRob3I+UmllbGxvPC9BdXRob3I+

PFllYXI+MjAwMzwvWWVhcj48SURUZXh0PlByZXNjcmlwdGlvbiBwcmFjdGljZXMgb2YgZGlhZ25v

c3RpYyBpbWFnaW5nIGluIGRlbWVudGlhOiBhIHN1cnZleSBvZiA0NyBBbHpoZWltZXImYXBvcztz

IENlbnRyZXMgaW4gTm9ydGhlcm4gSXRhbHk8L0lEVGV4dD48cmVjb3JkPjxkYXRlcz48cHViLWRh

dGVzPjxkYXRlPkp1bDwvZGF0ZT48L3B1Yi1kYXRlcz48eWVhcj4yMDAzPC95ZWFyPjwvZGF0ZXM+

PGtleXdvcmRzPjxrZXl3b3JkPkRlbWVudGlhPC9rZXl3b3JkPjxrZXl3b3JkPkRpYWdub3N0aWMg

SW1hZ2luZzwva2V5d29yZD48a2V5d29yZD5IdW1hbnM8L2tleXdvcmQ+PGtleXdvcmQ+SXRhbHk8

L2tleXdvcmQ+PGtleXdvcmQ+TWFnbmV0aWMgUmVzb25hbmNlIEltYWdpbmc8L2tleXdvcmQ+PGtl

eXdvcmQ+U3VydmV5cyBhbmQgUXVlc3Rpb25uYWlyZXM8L2tleXdvcmQ+PGtleXdvcmQ+VG9tb2dy

YXBoeSwgRW1pc3Npb24tQ29tcHV0ZWQsIFNpbmdsZS1QaG90b248L2tleXdvcmQ+PGtleXdvcmQ+

VG9tb2dyYXBoeSwgWC1SYXkgQ29tcHV0ZWQ8L2tleXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVs

YXRlZC11cmxzPjx1cmw+aHR0cHM6Ly93d3cubmNiaS5ubG0ubmloLmdvdi9wdWJtZWQvMTI4MzMz

MDE8L3VybD48L3JlbGF0ZWQtdXJscz48L3VybHM+PGlzYm4+MDg4NS02MjMwPC9pc2JuPjx0aXRs

ZXM+PHRpdGxlPlByZXNjcmlwdGlvbiBwcmFjdGljZXMgb2YgZGlhZ25vc3RpYyBpbWFnaW5nIGlu

IGRlbWVudGlhOiBhIHN1cnZleSBvZiA0NyBBbHpoZWltZXImYXBvcztzIENlbnRyZXMgaW4gTm9y

dGhlcm4gSXRhbHk8L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+SW50IEogR2VyaWF0ciBQc3ljaGlh

dHJ5PC9zZWNvbmRhcnktdGl0bGU+PC90aXRsZXM+PHBhZ2VzPjU3Ny04NTwvcGFnZXM+PG51bWJl

cj43PC9udW1iZXI+PGNvbnRyaWJ1dG9ycz48YXV0aG9ycz48YXV0aG9yPlJpZWxsbywgUi48L2F1

dGhvcj48YXV0aG9yPkFsYmluaSwgQy48L2F1dGhvcj48YXV0aG9yPkdhbGx1enppLCBTLjwvYXV0

aG9yPjxhdXRob3I+UGFzcXVhbGV0dGksIFAuPC9hdXRob3I+PGF1dGhvcj5Gcmlzb25pLCBHLiBC

LjwvYXV0aG9yPjwvYXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3VhZ2U+RU5HPC9sYW5ndWFn

ZT48YWRkZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3ODY5Nzk0NzwvYWRkZWQtZGF0ZT48cmVmLXR5

cGUgbmFtZT0iSm91cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PHJlYy1udW1iZXI+NTQ1PC9y

ZWMtbnVtYmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3ODY5Nzk0NzwvbGFz

dC11cGRhdGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MTI4MzMzMDE8L2FjY2Vzc2lvbi1udW0+PGVs

ZWN0cm9uaWMtcmVzb3VyY2UtbnVtPjEwLjEwMDIvZ3BzLjg5MzwvZWxlY3Ryb25pYy1yZXNvdXJj

ZS1udW0+PHZvbHVtZT4xODwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48Q2l0ZT48QXV0aG9yPkFs

YWNoa2FyPC9BdXRob3I+PFllYXI+MjAxNDwvWWVhcj48SURUZXh0Pk5ldXJvaW1hZ2luZyBpbiBk

ZW1lbnRpYTogaG93IGJlc3QgdG8gdXNlIHRoZSBndWlkZWxpbmVzPzwvSURUZXh0PjxyZWNvcmQ+

PGRhdGVzPjxwdWItZGF0ZXM+PGRhdGU+SnVuPC9kYXRlPjwvcHViLWRhdGVzPjx5ZWFyPjIwMTQ8

L3llYXI+PC9kYXRlcz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cHM6Ly93d3cubmNiaS5u

bG0ubmloLmdvdi9wdWJtZWQvMjUyMzc1MjU8L3VybD48L3JlbGF0ZWQtdXJscz48L3VybHM+PGlz

Ym4+MjA1My00ODY4PC9pc2JuPjxjdXN0b20yPlBNQzQxMTUzODQ8L2N1c3RvbTI+PHRpdGxlcz48

dGl0bGU+TmV1cm9pbWFnaW5nIGluIGRlbWVudGlhOiBob3cgYmVzdCB0byB1c2UgdGhlIGd1aWRl

bGluZXM/PC90aXRsZT48c2Vjb25kYXJ5LXRpdGxlPlBzeWNoaWF0ciBCdWxsICgyMDE0KTwvc2Vj

b25kYXJ5LXRpdGxlPjwvdGl0bGVzPjxwYWdlcz4xMzctODwvcGFnZXM+PG51bWJlcj4zPC9udW1i

ZXI+PGNvbnRyaWJ1dG9ycz48YXV0aG9ycz48YXV0aG9yPkFsYWNoa2FyLCBNLjwvYXV0aG9yPjwv

YXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3VhZ2U+RU5HPC9sYW5ndWFnZT48YWRkZWQtZGF0

ZSBmb3JtYXQ9InV0YyI+MTQ3ODE3NTQzMjwvYWRkZWQtZGF0ZT48cmVmLXR5cGUgbmFtZT0iSm91

cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PHJlYy1udW1iZXI+NTI4PC9yZWMtbnVtYmVyPjxs

YXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3ODE3NTQzMjwvbGFzdC11cGRhdGVkLWRh

dGU+PGFjY2Vzc2lvbi1udW0+MjUyMzc1MjU8L2FjY2Vzc2lvbi1udW0+PGVsZWN0cm9uaWMtcmVz

b3VyY2UtbnVtPjEwLjExOTIvcGIuMzguMy4xMzdhPC9lbGVjdHJvbmljLXJlc291cmNlLW51bT48

dm9sdW1lPjM4PC92b2x1bWU+PC9yZWNvcmQ+PC9DaXRlPjwvRW5kTm90ZT4AAAA=

ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5LdXJ1dmlsbGE8L0F1dGhvcj48WWVhcj4yMDE0PC9ZZWFy

PjxJRFRleHQ+TmV1cm9pbWFnaW5nIGluIGEgbWVtb3J5IGFzc2Vzc21lbnQgc2VydmljZTogYSBj

b21wbGV0ZWQgYXVkaXQgY3ljbGU8L0lEVGV4dD48RGlzcGxheVRleHQ+PHN0eWxlIGZhY2U9InN1

cGVyc2NyaXB0Ij45LTExPC9zdHlsZT48L0Rpc3BsYXlUZXh0PjxyZWNvcmQ+PGRhdGVzPjxwdWIt

ZGF0ZXM+PGRhdGU+RmViPC9kYXRlPjwvcHViLWRhdGVzPjx5ZWFyPjIwMTQ8L3llYXI+PC9kYXRl

cz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cHM6Ly93d3cubmNiaS5ubG0ubmloLmdvdi9w

dWJtZWQvMjUyMzc0ODY8L3VybD48L3JlbGF0ZWQtdXJscz48L3VybHM+PGlzYm4+MjA1My00ODY4

PC9pc2JuPjxjdXN0b20yPlBNQzQwNjc4NDQ8L2N1c3RvbTI+PHRpdGxlcz48dGl0bGU+TmV1cm9p

bWFnaW5nIGluIGEgbWVtb3J5IGFzc2Vzc21lbnQgc2VydmljZTogYSBjb21wbGV0ZWQgYXVkaXQg

Y3ljbGU8L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+UHN5Y2hpYXRyIEJ1bGwgKDIwMTQpPC9zZWNv

bmRhcnktdGl0bGU+PC90aXRsZXM+PHBhZ2VzPjI0LTg8L3BhZ2VzPjxudW1iZXI+MTwvbnVtYmVy

Pjxjb250cmlidXRvcnM+PGF1dGhvcnM+PGF1dGhvcj5LdXJ1dmlsbGEsIFQuPC9hdXRob3I+PGF1

dGhvcj5aaGVuZywgUi48L2F1dGhvcj48YXV0aG9yPlNvZGVuLCBCLjwvYXV0aG9yPjxhdXRob3I+

R3JlZWYsIFMuPC9hdXRob3I+PGF1dGhvcj5MeWJ1cm4sIEkuPC9hdXRob3I+PC9hdXRob3JzPjwv

Y29udHJpYnV0b3JzPjxsYW5ndWFnZT5FTkc8L2xhbmd1YWdlPjxhZGRlZC1kYXRlIGZvcm1hdD0i

dXRjIj4xNDc4MTc1MzMxPC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1lPSJKb3VybmFsIEFydGlj

bGUiPjE3PC9yZWYtdHlwZT48cmVjLW51bWJlcj41Mjc8L3JlYy1udW1iZXI+PGxhc3QtdXBkYXRl

ZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc4MTc1MzMxPC9sYXN0LXVwZGF0ZWQtZGF0ZT48YWNjZXNz

aW9uLW51bT4yNTIzNzQ4NjwvYWNjZXNzaW9uLW51bT48ZWxlY3Ryb25pYy1yZXNvdXJjZS1udW0+

MTAuMTE5Mi9wYi5icC4xMTMuMDQzMzk4PC9lbGVjdHJvbmljLXJlc291cmNlLW51bT48dm9sdW1l

PjM4PC92b2x1bWU+PC9yZWNvcmQ+PC9DaXRlPjxDaXRlPjxBdXRob3I+UmllbGxvPC9BdXRob3I+

PFllYXI+MjAwMzwvWWVhcj48SURUZXh0PlByZXNjcmlwdGlvbiBwcmFjdGljZXMgb2YgZGlhZ25v

c3RpYyBpbWFnaW5nIGluIGRlbWVudGlhOiBhIHN1cnZleSBvZiA0NyBBbHpoZWltZXImYXBvcztz

IENlbnRyZXMgaW4gTm9ydGhlcm4gSXRhbHk8L0lEVGV4dD48cmVjb3JkPjxkYXRlcz48cHViLWRh

dGVzPjxkYXRlPkp1bDwvZGF0ZT48L3B1Yi1kYXRlcz48eWVhcj4yMDAzPC95ZWFyPjwvZGF0ZXM+

PGtleXdvcmRzPjxrZXl3b3JkPkRlbWVudGlhPC9rZXl3b3JkPjxrZXl3b3JkPkRpYWdub3N0aWMg

SW1hZ2luZzwva2V5d29yZD48a2V5d29yZD5IdW1hbnM8L2tleXdvcmQ+PGtleXdvcmQ+SXRhbHk8

L2tleXdvcmQ+PGtleXdvcmQ+TWFnbmV0aWMgUmVzb25hbmNlIEltYWdpbmc8L2tleXdvcmQ+PGtl

eXdvcmQ+U3VydmV5cyBhbmQgUXVlc3Rpb25uYWlyZXM8L2tleXdvcmQ+PGtleXdvcmQ+VG9tb2dy

YXBoeSwgRW1pc3Npb24tQ29tcHV0ZWQsIFNpbmdsZS1QaG90b248L2tleXdvcmQ+PGtleXdvcmQ+

VG9tb2dyYXBoeSwgWC1SYXkgQ29tcHV0ZWQ8L2tleXdvcmQ+PC9rZXl3b3Jkcz48dXJscz48cmVs

YXRlZC11cmxzPjx1cmw+aHR0cHM6Ly93d3cubmNiaS5ubG0ubmloLmdvdi9wdWJtZWQvMTI4MzMz

MDE8L3VybD48L3JlbGF0ZWQtdXJscz48L3VybHM+PGlzYm4+MDg4NS02MjMwPC9pc2JuPjx0aXRs

ZXM+PHRpdGxlPlByZXNjcmlwdGlvbiBwcmFjdGljZXMgb2YgZGlhZ25vc3RpYyBpbWFnaW5nIGlu

IGRlbWVudGlhOiBhIHN1cnZleSBvZiA0NyBBbHpoZWltZXImYXBvcztzIENlbnRyZXMgaW4gTm9y

dGhlcm4gSXRhbHk8L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+SW50IEogR2VyaWF0ciBQc3ljaGlh

dHJ5PC9zZWNvbmRhcnktdGl0bGU+PC90aXRsZXM+PHBhZ2VzPjU3Ny04NTwvcGFnZXM+PG51bWJl

cj43PC9udW1iZXI+PGNvbnRyaWJ1dG9ycz48YXV0aG9ycz48YXV0aG9yPlJpZWxsbywgUi48L2F1

dGhvcj48YXV0aG9yPkFsYmluaSwgQy48L2F1dGhvcj48YXV0aG9yPkdhbGx1enppLCBTLjwvYXV0

aG9yPjxhdXRob3I+UGFzcXVhbGV0dGksIFAuPC9hdXRob3I+PGF1dGhvcj5Gcmlzb25pLCBHLiBC

LjwvYXV0aG9yPjwvYXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3VhZ2U+RU5HPC9sYW5ndWFn

ZT48YWRkZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3ODY5Nzk0NzwvYWRkZWQtZGF0ZT48cmVmLXR5

cGUgbmFtZT0iSm91cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PHJlYy1udW1iZXI+NTQ1PC9y

ZWMtbnVtYmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3ODY5Nzk0NzwvbGFz

dC11cGRhdGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MTI4MzMzMDE8L2FjY2Vzc2lvbi1udW0+PGVs

ZWN0cm9uaWMtcmVzb3VyY2UtbnVtPjEwLjEwMDIvZ3BzLjg5MzwvZWxlY3Ryb25pYy1yZXNvdXJj

ZS1udW0+PHZvbHVtZT4xODwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48Q2l0ZT48QXV0aG9yPkFs

YWNoa2FyPC9BdXRob3I+PFllYXI+MjAxNDwvWWVhcj48SURUZXh0Pk5ldXJvaW1hZ2luZyBpbiBk

ZW1lbnRpYTogaG93IGJlc3QgdG8gdXNlIHRoZSBndWlkZWxpbmVzPzwvSURUZXh0PjxyZWNvcmQ+

PGRhdGVzPjxwdWItZGF0ZXM+PGRhdGU+SnVuPC9kYXRlPjwvcHViLWRhdGVzPjx5ZWFyPjIwMTQ8

L3llYXI+PC9kYXRlcz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cHM6Ly93d3cubmNiaS5u

bG0ubmloLmdvdi9wdWJtZWQvMjUyMzc1MjU8L3VybD48L3JlbGF0ZWQtdXJscz48L3VybHM+PGlz

Ym4+MjA1My00ODY4PC9pc2JuPjxjdXN0b20yPlBNQzQxMTUzODQ8L2N1c3RvbTI+PHRpdGxlcz48

dGl0bGU+TmV1cm9pbWFnaW5nIGluIGRlbWVudGlhOiBob3cgYmVzdCB0byB1c2UgdGhlIGd1aWRl

bGluZXM/PC90aXRsZT48c2Vjb25kYXJ5LXRpdGxlPlBzeWNoaWF0ciBCdWxsICgyMDE0KTwvc2Vj

b25kYXJ5LXRpdGxlPjwvdGl0bGVzPjxwYWdlcz4xMzctODwvcGFnZXM+PG51bWJlcj4zPC9udW1i

ZXI+PGNvbnRyaWJ1dG9ycz48YXV0aG9ycz48YXV0aG9yPkFsYWNoa2FyLCBNLjwvYXV0aG9yPjwv

YXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3VhZ2U+RU5HPC9sYW5ndWFnZT48YWRkZWQtZGF0

ZSBmb3JtYXQ9InV0YyI+MTQ3ODE3NTQzMjwvYWRkZWQtZGF0ZT48cmVmLXR5cGUgbmFtZT0iSm91

cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PHJlYy1udW1iZXI+NTI4PC9yZWMtbnVtYmVyPjxs

YXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3ODE3NTQzMjwvbGFzdC11cGRhdGVkLWRh

dGU+PGFjY2Vzc2lvbi1udW0+MjUyMzc1MjU8L2FjY2Vzc2lvbi1udW0+PGVsZWN0cm9uaWMtcmVz

b3VyY2UtbnVtPjEwLjExOTIvcGIuMzguMy4xMzdhPC9lbGVjdHJvbmljLXJlc291cmNlLW51bT48

dm9sdW1lPjM4PC92b2x1bWU+PC9yZWNvcmQ+PC9DaXRlPjwvRW5kTm90ZT4AAAA=

ADDIN EN.CITE.DATA 9-11. CT-analytic software have been developed recently to try to delineate chronic ADDIN EN.CITE <EndNote><Cite><Author>Gillebert</Author><Year>2014</Year><IDText>Automated delineation of stroke lesions using brain CT images</IDText><DisplayText><style face="superscript">27</style></DisplayText><record><keywords><keyword>Aged</keyword><keyword>Aged, 80 and over</keyword><keyword>Algorithms</keyword><keyword>Brain</keyword><keyword>Female</keyword><keyword>Humans</keyword><keyword>Information Storage and Retrieval</keyword><keyword>Male</keyword><keyword>Middle Aged</keyword><keyword>Pattern Recognition, Automated</keyword><keyword>Radiographic Image Enhancement</keyword><keyword>Radiographic Image Interpretation, Computer-Assisted</keyword><keyword>Reproducibility of Results</keyword><keyword>Sensitivity and Specificity</keyword><keyword>Software</keyword><keyword>Stroke</keyword><keyword>Tomography, X-Ray Computed</keyword></keywords><urls><related-urls><url> delineation of stroke lesions using brain CT images</title><secondary-title>Neuroimage Clin</secondary-title></titles><pages>540-8</pages><contributors><authors><author>Gillebert, C. R.</author><author>Humphreys, G. W.</author><author>Mantini, D.</author></authors></contributors><language>ENG</language><added-date format="utc">1478697855</added-date><ref-type name="Journal Article">17</ref-type><dates><year>2014</year></dates><rec-number>544</rec-number><last-updated-date format="utc">1478697855</last-updated-date><accession-num>24818079</accession-num><electronic-resource-num>10.1016/j.nicl.2014.03.009</electronic-resource-num><volume>4</volume></record></Cite></EndNote>27, and acute ischemia ADDIN EN.CITE <EndNote><Cite><Author>Herweh</Author><Year>2016</Year><IDText>Performance of e-ASPECTS software in comparison to that of stroke physicians on assessing CT scans of acute ischemic stroke patients</IDText><DisplayText><style face="superscript">28</style></DisplayText><record><dates><pub-dates><date>Jun</date></pub-dates><year>2016</year></dates><urls><related-urls><url> of e-ASPECTS software in comparison to that of stroke physicians on assessing CT scans of acute ischemic stroke patients</title><secondary-title>Int J Stroke</secondary-title></titles><pages>438-45</pages><number>4</number><contributors><authors><author>Herweh, C.</author><author>Ringleb, P. A.</author><author>Rauch, G.</author><author>Gerry, S.</author><author>Behrens, L.</author><author>M?hlenbruch, M.</author><author>Gottorf, R.</author><author>Richter, D.</author><author>Schieber, S.</author><author>Nagel, S.</author></authors></contributors><language>ENG</language><added-date format="utc">1478701794</added-date><ref-type name="Journal Article">17</ref-type><rec-number>549</rec-number><last-updated-date format="utc">1478701794</last-updated-date><accession-num>26880058</accession-num><electronic-resource-num>10.1177/1747493016632244</electronic-resource-num><volume>11</volume></record></Cite></EndNote>28, as well as to predict hemorrhagic transformation after ischemic stroke ADDIN EN.CITE <EndNote><Cite><Author>Bentley</Author><Year>2014</Year><IDText>Prediction of stroke thrombolysis outcome using CT brain machine learning</IDText><DisplayText><style face="superscript">29</style></DisplayText><record><keywords><keyword>Area Under Curve</keyword><keyword>Artificial Intelligence</keyword><keyword>Brain</keyword><keyword>Female</keyword><keyword>Fibrinolytic Agents</keyword><keyword>Humans</keyword><keyword>Male</keyword><keyword>Outcome Assessment (Health Care)</keyword><keyword>Predictive Value of Tests</keyword><keyword>Retrospective Studies</keyword><keyword>Severity of Illness Index</keyword><keyword>Stroke</keyword><keyword>Tissue Plasminogen Activator</keyword><keyword>Tomography, X-Ray Computed</keyword></keywords><urls><related-urls><url> of stroke thrombolysis outcome using CT brain machine learning</title><secondary-title>Neuroimage Clin</secondary-title></titles><pages>635-40</pages><contributors><authors><author>Bentley, P.</author><author>Ganesalingam, J.</author><author>Carlton Jones, A. L.</author><author>Mahady, K.</author><author>Epton, S.</author><author>Rinne, P.</author><author>Sharma, P.</author><author>Halse, O.</author><author>Mehta, A.</author><author>Rueckert, D.</author></authors></contributors><language>ENG</language><added-date format="utc">1478701914</added-date><ref-type name="Journal Article">17</ref-type><dates><year>2014</year></dates><rec-number>550</rec-number><last-updated-date format="utc">1478701914</last-updated-date><accession-num>24936414</accession-num><electronic-resource-num>10.1016/j.nicl.2014.02.003</electronic-resource-num><volume>4</volume></record></Cite></EndNote>29. One promising application for WML quantification is treatment-selection for acute ischemic stroke, given that cerebral WML load predicts poor functional outcomePEVuZE5vdGU+PENpdGU+PEF1dGhvcj5JU1QtMzwvQXV0aG9yPjxZZWFyPjIwMTU8L1llYXI+PElE

VGV4dD5Bc3NvY2lhdGlvbiBiZXR3ZWVuIGJyYWluIGltYWdpbmcgc2lnbnMsIGVhcmx5IGFuZCBs

YXRlIG91dGNvbWVzLCBhbmQgcmVzcG9uc2UgdG8gaW50cmF2ZW5vdXMgYWx0ZXBsYXNlIGFmdGVy

IGFjdXRlIGlzY2hhZW1pYyBzdHJva2UgaW4gdGhlIHRoaXJkIEludGVybmF0aW9uYWwgU3Ryb2tl

IFRyaWFsIChJU1QtMyk6IHNlY29uZGFyeSBhbmFseXNpcyBvZiBhIHJhbmRvbWlzZWQgY29udHJv

bGxlZCB0cmlhbDwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5bGUgZmFjZT0ic3VwZXJzY3JpcHQi

PjQsIDU8L3N0eWxlPjwvRGlzcGxheVRleHQ+PHJlY29yZD48ZGF0ZXM+PHB1Yi1kYXRlcz48ZGF0

ZT5NYXk8L2RhdGU+PC9wdWItZGF0ZXM+PHllYXI+MjAxNTwveWVhcj48L2RhdGVzPjxrZXl3b3Jk

cz48a2V5d29yZD5BZHVsdDwva2V5d29yZD48a2V5d29yZD5BZ2VkPC9rZXl3b3JkPjxrZXl3b3Jk

PkFnZWQsIDgwIGFuZCBvdmVyPC9rZXl3b3JkPjxrZXl3b3JkPkJyYWluIElzY2hlbWlhPC9rZXl3

b3JkPjxrZXl3b3JkPkRhdGEgSW50ZXJwcmV0YXRpb24sIFN0YXRpc3RpY2FsPC9rZXl3b3JkPjxr

ZXl3b3JkPkZlbWFsZTwva2V5d29yZD48a2V5d29yZD5GaWJyaW5vbHl0aWMgQWdlbnRzPC9rZXl3

b3JkPjxrZXl3b3JkPkh1bWFuczwva2V5d29yZD48a2V5d29yZD5NYWduZXRpYyBSZXNvbmFuY2Ug

SW1hZ2luZywgQ2luZTwva2V5d29yZD48a2V5d29yZD5NYWxlPC9rZXl3b3JkPjxrZXl3b3JkPk1p

ZGRsZSBBZ2VkPC9rZXl3b3JkPjxrZXl3b3JkPk91dGNvbWUgQXNzZXNzbWVudCAoSGVhbHRoIENh

cmUpPC9rZXl3b3JkPjxrZXl3b3JkPlNpbmdsZS1CbGluZCBNZXRob2Q8L2tleXdvcmQ+PGtleXdv

cmQ+U3Ryb2tlPC9rZXl3b3JkPjxrZXl3b3JkPlRocm9tYm9seXRpYyBUaGVyYXB5PC9rZXl3b3Jk

PjxrZXl3b3JkPlRpc3N1ZSBQbGFzbWlub2dlbiBBY3RpdmF0b3I8L2tleXdvcmQ+PC9rZXl3b3Jk

cz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cHM6Ly93d3cubmNiaS5ubG0ubmloLmdvdi9w

dWJtZWQvMjU4MTk0ODQ8L3VybD48L3JlbGF0ZWQtdXJscz48L3VybHM+PGlzYm4+MTQ3NC00NDY1

PC9pc2JuPjxjdXN0b20yPlBNQzQ1MTMxOTA8L2N1c3RvbTI+PHRpdGxlcz48dGl0bGU+QXNzb2Np

YXRpb24gYmV0d2VlbiBicmFpbiBpbWFnaW5nIHNpZ25zLCBlYXJseSBhbmQgbGF0ZSBvdXRjb21l

cywgYW5kIHJlc3BvbnNlIHRvIGludHJhdmVub3VzIGFsdGVwbGFzZSBhZnRlciBhY3V0ZSBpc2No

YWVtaWMgc3Ryb2tlIGluIHRoZSB0aGlyZCBJbnRlcm5hdGlvbmFsIFN0cm9rZSBUcmlhbCAoSVNU

LTMpOiBzZWNvbmRhcnkgYW5hbHlzaXMgb2YgYSByYW5kb21pc2VkIGNvbnRyb2xsZWQgdHJpYWw8

L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+TGFuY2V0IE5ldXJvbDwvc2Vjb25kYXJ5LXRpdGxlPjwv

dGl0bGVzPjxwYWdlcz40ODUtOTY8L3BhZ2VzPjxudW1iZXI+NTwvbnVtYmVyPjxjb250cmlidXRv

cnM+PGF1dGhvcnM+PGF1dGhvcj5JU1QtMyBjb2xsYWJvcmF0aXZlIGdyb3VwPC9hdXRob3I+PC9h

dXRob3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5FTkc8L2xhbmd1YWdlPjxhZGRlZC1kYXRl

IGZvcm1hdD0idXRjIj4xNDc4MTc4ODY3PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1lPSJKb3Vy

bmFsIEFydGljbGUiPjE3PC9yZWYtdHlwZT48cmVjLW51bWJlcj41MzM8L3JlYy1udW1iZXI+PGxh

c3QtdXBkYXRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc4MTc4ODY3PC9sYXN0LXVwZGF0ZWQtZGF0

ZT48YWNjZXNzaW9uLW51bT4yNTgxOTQ4NDwvYWNjZXNzaW9uLW51bT48ZWxlY3Ryb25pYy1yZXNv

dXJjZS1udW0+MTAuMTAxNi9TMTQ3NC00NDIyKDE1KTAwMDEyLTU8L2VsZWN0cm9uaWMtcmVzb3Vy

Y2UtbnVtPjx2b2x1bWU+MTQ8L3ZvbHVtZT48L3JlY29yZD48L0NpdGU+PENpdGU+PEF1dGhvcj5S

eXU8L0F1dGhvcj48WWVhcj4yMDE3PC9ZZWFyPjxJRFRleHQ+U3Ryb2tlIG91dGNvbWVzIGFyZSB3

b3JzZSB3aXRoIGxhcmdlciBsZXVrb2FyYWlvc2lzIHZvbHVtZXM8L0lEVGV4dD48cmVjb3JkPjxk

YXRlcz48cHViLWRhdGVzPjxkYXRlPkphbjwvZGF0ZT48L3B1Yi1kYXRlcz48eWVhcj4yMDE3PC95

ZWFyPjwvZGF0ZXM+PHVybHM+PHJlbGF0ZWQtdXJscz48dXJsPmh0dHBzOi8vd3d3Lm5jYmkubmxt

Lm5paC5nb3YvcHVibWVkLzI4MDA4MDAwPC91cmw+PC9yZWxhdGVkLXVybHM+PC91cmxzPjxpc2Ju

PjE0NjAtMjE1NjwvaXNibj48dGl0bGVzPjx0aXRsZT5TdHJva2Ugb3V0Y29tZXMgYXJlIHdvcnNl

IHdpdGggbGFyZ2VyIGxldWtvYXJhaW9zaXMgdm9sdW1lczwvdGl0bGU+PHNlY29uZGFyeS10aXRs

ZT5CcmFpbjwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0bGVzPjxwYWdlcz4xNTgtMTcwPC9wYWdlcz48

bnVtYmVyPlB0IDE8L251bWJlcj48Y29udHJpYnV0b3JzPjxhdXRob3JzPjxhdXRob3I+Unl1LCBX

LiBTLjwvYXV0aG9yPjxhdXRob3I+V29vLCBTLiBILjwvYXV0aG9yPjxhdXRob3I+U2NoZWxsaW5n

ZXJob3V0LCBELjwvYXV0aG9yPjxhdXRob3I+SmFuZywgTS4gVS48L2F1dGhvcj48YXV0aG9yPlBh

cmssIEsuIEouPC9hdXRob3I+PGF1dGhvcj5Ib25nLCBLLiBTLjwvYXV0aG9yPjxhdXRob3I+SmVv

bmcsIFMuIFcuPC9hdXRob3I+PGF1dGhvcj5OYSwgSi4gWS48L2F1dGhvcj48YXV0aG9yPkNobywg

Sy4gSC48L2F1dGhvcj48YXV0aG9yPktpbSwgSi4gVC48L2F1dGhvcj48YXV0aG9yPktpbSwgQi4g

Si48L2F1dGhvcj48YXV0aG9yPkhhbiwgTS4gSy48L2F1dGhvcj48YXV0aG9yPkxlZSwgSi48L2F1

dGhvcj48YXV0aG9yPkNoYSwgSi4gSy48L2F1dGhvcj48YXV0aG9yPktpbSwgRC4gSC48L2F1dGhv

cj48YXV0aG9yPkxlZSwgUy4gSi48L2F1dGhvcj48YXV0aG9yPktvLCBZLjwvYXV0aG9yPjxhdXRo

b3I+Q2hvLCBZLiBKLjwvYXV0aG9yPjxhdXRob3I+TGVlLCBCLiBDLjwvYXV0aG9yPjxhdXRob3I+

WXUsIEsuIEguPC9hdXRob3I+PGF1dGhvcj5PaCwgTS4gUy48L2F1dGhvcj48YXV0aG9yPlBhcmss

IEouIE0uPC9hdXRob3I+PGF1dGhvcj5LYW5nLCBLLjwvYXV0aG9yPjxhdXRob3I+TGVlLCBLLiBC

LjwvYXV0aG9yPjxhdXRob3I+UGFyaywgVC4gSC48L2F1dGhvcj48YXV0aG9yPkNob2ksIEguIEsu

PC9hdXRob3I+PGF1dGhvcj5MZWUsIEsuPC9hdXRob3I+PGF1dGhvcj5CYWUsIEguIEouPC9hdXRo

b3I+PGF1dGhvcj5LaW0sIEQuIEUuPC9hdXRob3I+PC9hdXRob3JzPjwvY29udHJpYnV0b3JzPjxl

ZGl0aW9uPjIwMTYvMTIvMjI8L2VkaXRpb24+PGxhbmd1YWdlPmVuZzwvbGFuZ3VhZ2U+PGFkZGVk

LWRhdGUgZm9ybWF0PSJ1dGMiPjE0ODU0MzEzMzg8L2FkZGVkLWRhdGU+PHJlZi10eXBlIG5hbWU9

IkpvdXJuYWwgQXJ0aWNsZSI+MTc8L3JlZi10eXBlPjxyZWMtbnVtYmVyPjU2ODwvcmVjLW51bWJl

cj48bGFzdC11cGRhdGVkLWRhdGUgZm9ybWF0PSJ1dGMiPjE0ODU0MzEzMzg8L2xhc3QtdXBkYXRl

ZC1kYXRlPjxhY2Nlc3Npb24tbnVtPjI4MDA4MDAwPC9hY2Nlc3Npb24tbnVtPjxlbGVjdHJvbmlj

LXJlc291cmNlLW51bT4xMC4xMDkzL2JyYWluL2F3dzI1OTwvZWxlY3Ryb25pYy1yZXNvdXJjZS1u

dW0+PHZvbHVtZT4xNDA8L3ZvbHVtZT48L3JlY29yZD48L0NpdGU+PC9FbmROb3RlPgAAAA==

ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5JU1QtMzwvQXV0aG9yPjxZZWFyPjIwMTU8L1llYXI+PElE

VGV4dD5Bc3NvY2lhdGlvbiBiZXR3ZWVuIGJyYWluIGltYWdpbmcgc2lnbnMsIGVhcmx5IGFuZCBs

YXRlIG91dGNvbWVzLCBhbmQgcmVzcG9uc2UgdG8gaW50cmF2ZW5vdXMgYWx0ZXBsYXNlIGFmdGVy

IGFjdXRlIGlzY2hhZW1pYyBzdHJva2UgaW4gdGhlIHRoaXJkIEludGVybmF0aW9uYWwgU3Ryb2tl

IFRyaWFsIChJU1QtMyk6IHNlY29uZGFyeSBhbmFseXNpcyBvZiBhIHJhbmRvbWlzZWQgY29udHJv

bGxlZCB0cmlhbDwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5bGUgZmFjZT0ic3VwZXJzY3JpcHQi

PjQsIDU8L3N0eWxlPjwvRGlzcGxheVRleHQ+PHJlY29yZD48ZGF0ZXM+PHB1Yi1kYXRlcz48ZGF0

ZT5NYXk8L2RhdGU+PC9wdWItZGF0ZXM+PHllYXI+MjAxNTwveWVhcj48L2RhdGVzPjxrZXl3b3Jk

cz48a2V5d29yZD5BZHVsdDwva2V5d29yZD48a2V5d29yZD5BZ2VkPC9rZXl3b3JkPjxrZXl3b3Jk

PkFnZWQsIDgwIGFuZCBvdmVyPC9rZXl3b3JkPjxrZXl3b3JkPkJyYWluIElzY2hlbWlhPC9rZXl3

b3JkPjxrZXl3b3JkPkRhdGEgSW50ZXJwcmV0YXRpb24sIFN0YXRpc3RpY2FsPC9rZXl3b3JkPjxr

ZXl3b3JkPkZlbWFsZTwva2V5d29yZD48a2V5d29yZD5GaWJyaW5vbHl0aWMgQWdlbnRzPC9rZXl3

b3JkPjxrZXl3b3JkPkh1bWFuczwva2V5d29yZD48a2V5d29yZD5NYWduZXRpYyBSZXNvbmFuY2Ug

SW1hZ2luZywgQ2luZTwva2V5d29yZD48a2V5d29yZD5NYWxlPC9rZXl3b3JkPjxrZXl3b3JkPk1p

ZGRsZSBBZ2VkPC9rZXl3b3JkPjxrZXl3b3JkPk91dGNvbWUgQXNzZXNzbWVudCAoSGVhbHRoIENh

cmUpPC9rZXl3b3JkPjxrZXl3b3JkPlNpbmdsZS1CbGluZCBNZXRob2Q8L2tleXdvcmQ+PGtleXdv

cmQ+U3Ryb2tlPC9rZXl3b3JkPjxrZXl3b3JkPlRocm9tYm9seXRpYyBUaGVyYXB5PC9rZXl3b3Jk

PjxrZXl3b3JkPlRpc3N1ZSBQbGFzbWlub2dlbiBBY3RpdmF0b3I8L2tleXdvcmQ+PC9rZXl3b3Jk

cz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cHM6Ly93d3cubmNiaS5ubG0ubmloLmdvdi9w

dWJtZWQvMjU4MTk0ODQ8L3VybD48L3JlbGF0ZWQtdXJscz48L3VybHM+PGlzYm4+MTQ3NC00NDY1

PC9pc2JuPjxjdXN0b20yPlBNQzQ1MTMxOTA8L2N1c3RvbTI+PHRpdGxlcz48dGl0bGU+QXNzb2Np

YXRpb24gYmV0d2VlbiBicmFpbiBpbWFnaW5nIHNpZ25zLCBlYXJseSBhbmQgbGF0ZSBvdXRjb21l

cywgYW5kIHJlc3BvbnNlIHRvIGludHJhdmVub3VzIGFsdGVwbGFzZSBhZnRlciBhY3V0ZSBpc2No

YWVtaWMgc3Ryb2tlIGluIHRoZSB0aGlyZCBJbnRlcm5hdGlvbmFsIFN0cm9rZSBUcmlhbCAoSVNU

LTMpOiBzZWNvbmRhcnkgYW5hbHlzaXMgb2YgYSByYW5kb21pc2VkIGNvbnRyb2xsZWQgdHJpYWw8

L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+TGFuY2V0IE5ldXJvbDwvc2Vjb25kYXJ5LXRpdGxlPjwv

dGl0bGVzPjxwYWdlcz40ODUtOTY8L3BhZ2VzPjxudW1iZXI+NTwvbnVtYmVyPjxjb250cmlidXRv

cnM+PGF1dGhvcnM+PGF1dGhvcj5JU1QtMyBjb2xsYWJvcmF0aXZlIGdyb3VwPC9hdXRob3I+PC9h

dXRob3JzPjwvY29udHJpYnV0b3JzPjxsYW5ndWFnZT5FTkc8L2xhbmd1YWdlPjxhZGRlZC1kYXRl

IGZvcm1hdD0idXRjIj4xNDc4MTc4ODY3PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1lPSJKb3Vy

bmFsIEFydGljbGUiPjE3PC9yZWYtdHlwZT48cmVjLW51bWJlcj41MzM8L3JlYy1udW1iZXI+PGxh

c3QtdXBkYXRlZC1kYXRlIGZvcm1hdD0idXRjIj4xNDc4MTc4ODY3PC9sYXN0LXVwZGF0ZWQtZGF0

ZT48YWNjZXNzaW9uLW51bT4yNTgxOTQ4NDwvYWNjZXNzaW9uLW51bT48ZWxlY3Ryb25pYy1yZXNv

dXJjZS1udW0+MTAuMTAxNi9TMTQ3NC00NDIyKDE1KTAwMDEyLTU8L2VsZWN0cm9uaWMtcmVzb3Vy

Y2UtbnVtPjx2b2x1bWU+MTQ8L3ZvbHVtZT48L3JlY29yZD48L0NpdGU+PENpdGU+PEF1dGhvcj5S

eXU8L0F1dGhvcj48WWVhcj4yMDE3PC9ZZWFyPjxJRFRleHQ+U3Ryb2tlIG91dGNvbWVzIGFyZSB3

b3JzZSB3aXRoIGxhcmdlciBsZXVrb2FyYWlvc2lzIHZvbHVtZXM8L0lEVGV4dD48cmVjb3JkPjxk

YXRlcz48cHViLWRhdGVzPjxkYXRlPkphbjwvZGF0ZT48L3B1Yi1kYXRlcz48eWVhcj4yMDE3PC95

ZWFyPjwvZGF0ZXM+PHVybHM+PHJlbGF0ZWQtdXJscz48dXJsPmh0dHBzOi8vd3d3Lm5jYmkubmxt

Lm5paC5nb3YvcHVibWVkLzI4MDA4MDAwPC91cmw+PC9yZWxhdGVkLXVybHM+PC91cmxzPjxpc2Ju

PjE0NjAtMjE1NjwvaXNibj48dGl0bGVzPjx0aXRsZT5TdHJva2Ugb3V0Y29tZXMgYXJlIHdvcnNl

IHdpdGggbGFyZ2VyIGxldWtvYXJhaW9zaXMgdm9sdW1lczwvdGl0bGU+PHNlY29uZGFyeS10aXRs

ZT5CcmFpbjwvc2Vjb25kYXJ5LXRpdGxlPjwvdGl0bGVzPjxwYWdlcz4xNTgtMTcwPC9wYWdlcz48

bnVtYmVyPlB0IDE8L251bWJlcj48Y29udHJpYnV0b3JzPjxhdXRob3JzPjxhdXRob3I+Unl1LCBX

LiBTLjwvYXV0aG9yPjxhdXRob3I+V29vLCBTLiBILjwvYXV0aG9yPjxhdXRob3I+U2NoZWxsaW5n

ZXJob3V0LCBELjwvYXV0aG9yPjxhdXRob3I+SmFuZywgTS4gVS48L2F1dGhvcj48YXV0aG9yPlBh

cmssIEsuIEouPC9hdXRob3I+PGF1dGhvcj5Ib25nLCBLLiBTLjwvYXV0aG9yPjxhdXRob3I+SmVv

bmcsIFMuIFcuPC9hdXRob3I+PGF1dGhvcj5OYSwgSi4gWS48L2F1dGhvcj48YXV0aG9yPkNobywg

Sy4gSC48L2F1dGhvcj48YXV0aG9yPktpbSwgSi4gVC48L2F1dGhvcj48YXV0aG9yPktpbSwgQi4g

Si48L2F1dGhvcj48YXV0aG9yPkhhbiwgTS4gSy48L2F1dGhvcj48YXV0aG9yPkxlZSwgSi48L2F1

dGhvcj48YXV0aG9yPkNoYSwgSi4gSy48L2F1dGhvcj48YXV0aG9yPktpbSwgRC4gSC48L2F1dGhv

cj48YXV0aG9yPkxlZSwgUy4gSi48L2F1dGhvcj48YXV0aG9yPktvLCBZLjwvYXV0aG9yPjxhdXRo

b3I+Q2hvLCBZLiBKLjwvYXV0aG9yPjxhdXRob3I+TGVlLCBCLiBDLjwvYXV0aG9yPjxhdXRob3I+

WXUsIEsuIEguPC9hdXRob3I+PGF1dGhvcj5PaCwgTS4gUy48L2F1dGhvcj48YXV0aG9yPlBhcmss

IEouIE0uPC9hdXRob3I+PGF1dGhvcj5LYW5nLCBLLjwvYXV0aG9yPjxhdXRob3I+TGVlLCBLLiBC

LjwvYXV0aG9yPjxhdXRob3I+UGFyaywgVC4gSC48L2F1dGhvcj48YXV0aG9yPkNob2ksIEguIEsu

PC9hdXRob3I+PGF1dGhvcj5MZWUsIEsuPC9hdXRob3I+PGF1dGhvcj5CYWUsIEguIEouPC9hdXRo

b3I+PGF1dGhvcj5LaW0sIEQuIEUuPC9hdXRob3I+PC9hdXRob3JzPjwvY29udHJpYnV0b3JzPjxl

ZGl0aW9uPjIwMTYvMTIvMjI8L2VkaXRpb24+PGxhbmd1YWdlPmVuZzwvbGFuZ3VhZ2U+PGFkZGVk

LWRhdGUgZm9ybWF0PSJ1dGMiPjE0ODU0MzEzMzg8L2FkZGVkLWRhdGU+PHJlZi10eXBlIG5hbWU9

IkpvdXJuYWwgQXJ0aWNsZSI+MTc8L3JlZi10eXBlPjxyZWMtbnVtYmVyPjU2ODwvcmVjLW51bWJl

cj48bGFzdC11cGRhdGVkLWRhdGUgZm9ybWF0PSJ1dGMiPjE0ODU0MzEzMzg8L2xhc3QtdXBkYXRl

ZC1kYXRlPjxhY2Nlc3Npb24tbnVtPjI4MDA4MDAwPC9hY2Nlc3Npb24tbnVtPjxlbGVjdHJvbmlj

LXJlc291cmNlLW51bT4xMC4xMDkzL2JyYWluL2F3dzI1OTwvZWxlY3Ryb25pYy1yZXNvdXJjZS1u

dW0+PHZvbHVtZT4xNDA8L3ZvbHVtZT48L3JlY29yZD48L0NpdGU+PC9FbmROb3RlPgAAAA==

ADDIN EN.CITE.DATA 4, 5 and intracranial hemorrhagic (ICH) transformationPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5DaGFyaWRpbW91PC9BdXRob3I+PFllYXI+MjAxNjwvWWVh

cj48SURUZXh0PkxldWtvYXJhaW9zaXMsIENlcmVicmFsIEhlbW9ycmhhZ2UsIGFuZCBPdXRjb21l

IEFmdGVyIEludHJhdmVub3VzIFRocm9tYm9seXNpcyBmb3IgQWN1dGUgSXNjaGVtaWMgU3Ryb2tl

OiBBIE1ldGEtQW5hbHlzaXMgKHYxKTwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5bGUgZmFjZT0i

c3VwZXJzY3JpcHQiPjcsIDg8L3N0eWxlPjwvRGlzcGxheVRleHQ+PHJlY29yZD48ZGF0ZXM+PHB1

Yi1kYXRlcz48ZGF0ZT5TZXA8L2RhdGU+PC9wdWItZGF0ZXM+PHllYXI+MjAxNjwveWVhcj48L2Rh

dGVzPjx1cmxzPjxyZWxhdGVkLXVybHM+PHVybD5odHRwczovL3d3dy5uY2JpLm5sbS5uaWguZ292

L3B1Ym1lZC8yNzQ5MTczODwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJscz48aXNibj4xNTI0LTQ2

Mjg8L2lzYm4+PGN1c3RvbTI+UE1DNDk5NTExOTwvY3VzdG9tMj48dGl0bGVzPjx0aXRsZT5MZXVr

b2FyYWlvc2lzLCBDZXJlYnJhbCBIZW1vcnJoYWdlLCBhbmQgT3V0Y29tZSBBZnRlciBJbnRyYXZl

bm91cyBUaHJvbWJvbHlzaXMgZm9yIEFjdXRlIElzY2hlbWljIFN0cm9rZTogQSBNZXRhLUFuYWx5

c2lzICh2MSk8L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+U3Ryb2tlPC9zZWNvbmRhcnktdGl0bGU+

PC90aXRsZXM+PHBhZ2VzPjIzNjQtNzI8L3BhZ2VzPjxudW1iZXI+OTwvbnVtYmVyPjxjb250cmli

dXRvcnM+PGF1dGhvcnM+PGF1dGhvcj5DaGFyaWRpbW91LCBBLjwvYXV0aG9yPjxhdXRob3I+UGFz

aSwgTS48L2F1dGhvcj48YXV0aG9yPkZpb3JlbGxpLCBNLjwvYXV0aG9yPjxhdXRob3I+U2hhbXMs

IFMuPC9hdXRob3I+PGF1dGhvcj52b24gS3VtbWVyLCBSLjwvYXV0aG9yPjxhdXRob3I+UGFudG9u

aSwgTC48L2F1dGhvcj48YXV0aG9yPlJvc3QsIE4uPC9hdXRob3I+PC9hdXRob3JzPjwvY29udHJp

YnV0b3JzPjxsYW5ndWFnZT5FTkc8L2xhbmd1YWdlPjxhZGRlZC1kYXRlIGZvcm1hdD0idXRjIj4x

NDc4MTc0ODA4PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1lPSJKb3VybmFsIEFydGljbGUiPjE3

PC9yZWYtdHlwZT48cmVjLW51bWJlcj41MjY8L3JlYy1udW1iZXI+PGxhc3QtdXBkYXRlZC1kYXRl

IGZvcm1hdD0idXRjIj4xNDc4MTc0ODA4PC9sYXN0LXVwZGF0ZWQtZGF0ZT48YWNjZXNzaW9uLW51

bT4yNzQ5MTczODwvYWNjZXNzaW9uLW51bT48ZWxlY3Ryb25pYy1yZXNvdXJjZS1udW0+MTAuMTE2

MS9TVFJPS0VBSEEuMTE2LjAxNDA5NjwvZWxlY3Ryb25pYy1yZXNvdXJjZS1udW0+PHZvbHVtZT40

Nzwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48Q2l0ZT48QXV0aG9yPldpbGxlcjwvQXV0aG9yPjxZ

ZWFyPjIwMTU8L1llYXI+PElEVGV4dD5Db21wdXRlZCBUb21vZ3JhcGh5LS1WZXJpZmllZCBMZXVr

b2FyYWlvc2lzIElzIGEgUmlzayBGYWN0b3IgZm9yIFBvc3QtdGhyb21ib2x5dGljIEhlbW9ycmhh

Z2U8L0lEVGV4dD48cmVjb3JkPjxkYXRlcz48cHViLWRhdGVzPjxkYXRlPkp1bjwvZGF0ZT48L3B1

Yi1kYXRlcz48eWVhcj4yMDE1PC95ZWFyPjwvZGF0ZXM+PGtleXdvcmRzPjxrZXl3b3JkPkFnZWQ8

L2tleXdvcmQ+PGtleXdvcmQ+QnJhaW4gSXNjaGVtaWE8L2tleXdvcmQ+PGtleXdvcmQ+RmVtYWxl

PC9rZXl3b3JkPjxrZXl3b3JkPkZpYnJpbm9seXRpYyBBZ2VudHM8L2tleXdvcmQ+PGtleXdvcmQ+

SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPkludHJhY3JhbmlhbCBIZW1vcnJoYWdlczwva2V5d29y

ZD48a2V5d29yZD5MZXVrb2FyYWlvc2lzPC9rZXl3b3JkPjxrZXl3b3JkPk1hbGU8L2tleXdvcmQ+

PGtleXdvcmQ+TWlkZGxlIEFnZWQ8L2tleXdvcmQ+PGtleXdvcmQ+UmV0cm9zcGVjdGl2ZSBTdHVk

aWVzPC9rZXl3b3JkPjxrZXl3b3JkPlJpc2sgRmFjdG9yczwva2V5d29yZD48a2V5d29yZD5TdHJv

a2U8L2tleXdvcmQ+PGtleXdvcmQ+VGhyb21ib2x5dGljIFRoZXJhcHk8L2tleXdvcmQ+PGtleXdv

cmQ+VGlzc3VlIFBsYXNtaW5vZ2VuIEFjdGl2YXRvcjwva2V5d29yZD48L2tleXdvcmRzPjx1cmxz

PjxyZWxhdGVkLXVybHM+PHVybD5odHRwczovL3d3dy5uY2JpLm5sbS5uaWguZ292L3B1Ym1lZC8y

NTkyMDc1NjwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJscz48aXNibj4xNTMyLTg1MTE8L2lzYm4+

PHRpdGxlcz48dGl0bGU+Q29tcHV0ZWQgVG9tb2dyYXBoeS0tVmVyaWZpZWQgTGV1a29hcmFpb3Np

cyBJcyBhIFJpc2sgRmFjdG9yIGZvciBQb3N0LXRocm9tYm9seXRpYyBIZW1vcnJoYWdlPC90aXRs

ZT48c2Vjb25kYXJ5LXRpdGxlPkogU3Ryb2tlIENlcmVicm92YXNjIERpczwvc2Vjb25kYXJ5LXRp

dGxlPjwvdGl0bGVzPjxwYWdlcz4xMTI2LTMwPC9wYWdlcz48bnVtYmVyPjY8L251bWJlcj48Y29u

dHJpYnV0b3JzPjxhdXRob3JzPjxhdXRob3I+V2lsbGVyLCBMLjwvYXV0aG9yPjxhdXRob3I+SGF2

c3RlZW4sIEkuPC9hdXRob3I+PGF1dGhvcj5PdmVzZW4sIEMuPC9hdXRob3I+PGF1dGhvcj5DaHJp

c3RlbnNlbiwgQS4gRi48L2F1dGhvcj48YXV0aG9yPkNocmlzdGVuc2VuLCBILjwvYXV0aG9yPjwv

YXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3VhZ2U+RU5HPC9sYW5ndWFnZT48YWRkZWQtZGF0

ZSBmb3JtYXQ9InV0YyI+MTQ3ODcxMTUyNjwvYWRkZWQtZGF0ZT48cmVmLXR5cGUgbmFtZT0iSm91

cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PHJlYy1udW1iZXI+NTUzPC9yZWMtbnVtYmVyPjxs

YXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3ODcxMTUyNjwvbGFzdC11cGRhdGVkLWRh

dGU+PGFjY2Vzc2lvbi1udW0+MjU5MjA3NTY8L2FjY2Vzc2lvbi1udW0+PGVsZWN0cm9uaWMtcmVz

b3VyY2UtbnVtPjEwLjEwMTYvai5qc3Ryb2tlY2VyZWJyb3Zhc2Rpcy4yMDE0LjEyLjAxODwvZWxl

Y3Ryb25pYy1yZXNvdXJjZS1udW0+PHZvbHVtZT4yNDwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48

L0VuZE5vdGU+AAAA

ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5DaGFyaWRpbW91PC9BdXRob3I+PFllYXI+MjAxNjwvWWVh

cj48SURUZXh0PkxldWtvYXJhaW9zaXMsIENlcmVicmFsIEhlbW9ycmhhZ2UsIGFuZCBPdXRjb21l

IEFmdGVyIEludHJhdmVub3VzIFRocm9tYm9seXNpcyBmb3IgQWN1dGUgSXNjaGVtaWMgU3Ryb2tl

OiBBIE1ldGEtQW5hbHlzaXMgKHYxKTwvSURUZXh0PjxEaXNwbGF5VGV4dD48c3R5bGUgZmFjZT0i

c3VwZXJzY3JpcHQiPjcsIDg8L3N0eWxlPjwvRGlzcGxheVRleHQ+PHJlY29yZD48ZGF0ZXM+PHB1

Yi1kYXRlcz48ZGF0ZT5TZXA8L2RhdGU+PC9wdWItZGF0ZXM+PHllYXI+MjAxNjwveWVhcj48L2Rh

dGVzPjx1cmxzPjxyZWxhdGVkLXVybHM+PHVybD5odHRwczovL3d3dy5uY2JpLm5sbS5uaWguZ292

L3B1Ym1lZC8yNzQ5MTczODwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJscz48aXNibj4xNTI0LTQ2

Mjg8L2lzYm4+PGN1c3RvbTI+UE1DNDk5NTExOTwvY3VzdG9tMj48dGl0bGVzPjx0aXRsZT5MZXVr

b2FyYWlvc2lzLCBDZXJlYnJhbCBIZW1vcnJoYWdlLCBhbmQgT3V0Y29tZSBBZnRlciBJbnRyYXZl

bm91cyBUaHJvbWJvbHlzaXMgZm9yIEFjdXRlIElzY2hlbWljIFN0cm9rZTogQSBNZXRhLUFuYWx5

c2lzICh2MSk8L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+U3Ryb2tlPC9zZWNvbmRhcnktdGl0bGU+

PC90aXRsZXM+PHBhZ2VzPjIzNjQtNzI8L3BhZ2VzPjxudW1iZXI+OTwvbnVtYmVyPjxjb250cmli

dXRvcnM+PGF1dGhvcnM+PGF1dGhvcj5DaGFyaWRpbW91LCBBLjwvYXV0aG9yPjxhdXRob3I+UGFz

aSwgTS48L2F1dGhvcj48YXV0aG9yPkZpb3JlbGxpLCBNLjwvYXV0aG9yPjxhdXRob3I+U2hhbXMs

IFMuPC9hdXRob3I+PGF1dGhvcj52b24gS3VtbWVyLCBSLjwvYXV0aG9yPjxhdXRob3I+UGFudG9u

aSwgTC48L2F1dGhvcj48YXV0aG9yPlJvc3QsIE4uPC9hdXRob3I+PC9hdXRob3JzPjwvY29udHJp

YnV0b3JzPjxsYW5ndWFnZT5FTkc8L2xhbmd1YWdlPjxhZGRlZC1kYXRlIGZvcm1hdD0idXRjIj4x

NDc4MTc0ODA4PC9hZGRlZC1kYXRlPjxyZWYtdHlwZSBuYW1lPSJKb3VybmFsIEFydGljbGUiPjE3

PC9yZWYtdHlwZT48cmVjLW51bWJlcj41MjY8L3JlYy1udW1iZXI+PGxhc3QtdXBkYXRlZC1kYXRl

IGZvcm1hdD0idXRjIj4xNDc4MTc0ODA4PC9sYXN0LXVwZGF0ZWQtZGF0ZT48YWNjZXNzaW9uLW51

bT4yNzQ5MTczODwvYWNjZXNzaW9uLW51bT48ZWxlY3Ryb25pYy1yZXNvdXJjZS1udW0+MTAuMTE2

MS9TVFJPS0VBSEEuMTE2LjAxNDA5NjwvZWxlY3Ryb25pYy1yZXNvdXJjZS1udW0+PHZvbHVtZT40

Nzwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48Q2l0ZT48QXV0aG9yPldpbGxlcjwvQXV0aG9yPjxZ

ZWFyPjIwMTU8L1llYXI+PElEVGV4dD5Db21wdXRlZCBUb21vZ3JhcGh5LS1WZXJpZmllZCBMZXVr

b2FyYWlvc2lzIElzIGEgUmlzayBGYWN0b3IgZm9yIFBvc3QtdGhyb21ib2x5dGljIEhlbW9ycmhh

Z2U8L0lEVGV4dD48cmVjb3JkPjxkYXRlcz48cHViLWRhdGVzPjxkYXRlPkp1bjwvZGF0ZT48L3B1

Yi1kYXRlcz48eWVhcj4yMDE1PC95ZWFyPjwvZGF0ZXM+PGtleXdvcmRzPjxrZXl3b3JkPkFnZWQ8

L2tleXdvcmQ+PGtleXdvcmQ+QnJhaW4gSXNjaGVtaWE8L2tleXdvcmQ+PGtleXdvcmQ+RmVtYWxl

PC9rZXl3b3JkPjxrZXl3b3JkPkZpYnJpbm9seXRpYyBBZ2VudHM8L2tleXdvcmQ+PGtleXdvcmQ+

SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPkludHJhY3JhbmlhbCBIZW1vcnJoYWdlczwva2V5d29y

ZD48a2V5d29yZD5MZXVrb2FyYWlvc2lzPC9rZXl3b3JkPjxrZXl3b3JkPk1hbGU8L2tleXdvcmQ+

PGtleXdvcmQ+TWlkZGxlIEFnZWQ8L2tleXdvcmQ+PGtleXdvcmQ+UmV0cm9zcGVjdGl2ZSBTdHVk

aWVzPC9rZXl3b3JkPjxrZXl3b3JkPlJpc2sgRmFjdG9yczwva2V5d29yZD48a2V5d29yZD5TdHJv

a2U8L2tleXdvcmQ+PGtleXdvcmQ+VGhyb21ib2x5dGljIFRoZXJhcHk8L2tleXdvcmQ+PGtleXdv

cmQ+VGlzc3VlIFBsYXNtaW5vZ2VuIEFjdGl2YXRvcjwva2V5d29yZD48L2tleXdvcmRzPjx1cmxz

PjxyZWxhdGVkLXVybHM+PHVybD5odHRwczovL3d3dy5uY2JpLm5sbS5uaWguZ292L3B1Ym1lZC8y

NTkyMDc1NjwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJscz48aXNibj4xNTMyLTg1MTE8L2lzYm4+

PHRpdGxlcz48dGl0bGU+Q29tcHV0ZWQgVG9tb2dyYXBoeS0tVmVyaWZpZWQgTGV1a29hcmFpb3Np

cyBJcyBhIFJpc2sgRmFjdG9yIGZvciBQb3N0LXRocm9tYm9seXRpYyBIZW1vcnJoYWdlPC90aXRs

ZT48c2Vjb25kYXJ5LXRpdGxlPkogU3Ryb2tlIENlcmVicm92YXNjIERpczwvc2Vjb25kYXJ5LXRp

dGxlPjwvdGl0bGVzPjxwYWdlcz4xMTI2LTMwPC9wYWdlcz48bnVtYmVyPjY8L251bWJlcj48Y29u

dHJpYnV0b3JzPjxhdXRob3JzPjxhdXRob3I+V2lsbGVyLCBMLjwvYXV0aG9yPjxhdXRob3I+SGF2

c3RlZW4sIEkuPC9hdXRob3I+PGF1dGhvcj5PdmVzZW4sIEMuPC9hdXRob3I+PGF1dGhvcj5DaHJp

c3RlbnNlbiwgQS4gRi48L2F1dGhvcj48YXV0aG9yPkNocmlzdGVuc2VuLCBILjwvYXV0aG9yPjwv

YXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3VhZ2U+RU5HPC9sYW5ndWFnZT48YWRkZWQtZGF0

ZSBmb3JtYXQ9InV0YyI+MTQ3ODcxMTUyNjwvYWRkZWQtZGF0ZT48cmVmLXR5cGUgbmFtZT0iSm91

cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PHJlYy1udW1iZXI+NTUzPC9yZWMtbnVtYmVyPjxs

YXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3ODcxMTUyNjwvbGFzdC11cGRhdGVkLWRh

dGU+PGFjY2Vzc2lvbi1udW0+MjU5MjA3NTY8L2FjY2Vzc2lvbi1udW0+PGVsZWN0cm9uaWMtcmVz

b3VyY2UtbnVtPjEwLjEwMTYvai5qc3Ryb2tlY2VyZWJyb3Zhc2Rpcy4yMDE0LjEyLjAxODwvZWxl

Y3Ryb25pYy1yZXNvdXJjZS1udW0+PHZvbHVtZT4yNDwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48

L0VuZE5vdGU+AAAA

ADDIN EN.CITE.DATA 7, 8. Currently though this CT-imaging predictor, and others e.g. acute ischemia extent, have not been found to interact with thrombolysis (or thrombectomy) treatment in their association with ICH – and so are not recommended for hyperacute treatment stratificationPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XaGl0ZWxleTwvQXV0aG9yPjxZZWFyPjIwMTI8L1llYXI+

PElEVGV4dD5SaXNrIGZhY3RvcnMgZm9yIGludHJhY3JhbmlhbCBoZW1vcnJoYWdlIGluIGFjdXRl

IGlzY2hlbWljIHN0cm9rZSBwYXRpZW50cyB0cmVhdGVkIHdpdGggcmVjb21iaW5hbnQgdGlzc3Vl

IHBsYXNtaW5vZ2VuIGFjdGl2YXRvcjogYSBzeXN0ZW1hdGljIHJldmlldyBhbmQgbWV0YS1hbmFs

eXNpcyBvZiA1NSBzdHVkaWVzPC9JRFRleHQ+PERpc3BsYXlUZXh0PjxzdHlsZSBmYWNlPSJzdXBl

cnNjcmlwdCI+NCwgMzA8L3N0eWxlPjwvRGlzcGxheVRleHQ+PHJlY29yZD48ZGF0ZXM+PHB1Yi1k

YXRlcz48ZGF0ZT5Ob3Y8L2RhdGU+PC9wdWItZGF0ZXM+PHllYXI+MjAxMjwveWVhcj48L2RhdGVz

PjxrZXl3b3Jkcz48a2V5d29yZD5BZ2UgRmFjdG9yczwva2V5d29yZD48a2V5d29yZD5BZ2VkPC9r

ZXl3b3JkPjxrZXl3b3JkPkFnZWQsIDgwIGFuZCBvdmVyPC9rZXl3b3JkPjxrZXl3b3JkPkJyYWlu

IElzY2hlbWlhPC9rZXl3b3JkPjxrZXl3b3JkPkZpYnJpbm9seXRpYyBBZ2VudHM8L2tleXdvcmQ+

PGtleXdvcmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPkludHJhY3JhbmlhbCBIZW1vcnJoYWdl

czwva2V5d29yZD48a2V5d29yZD5SaXNrIEZhY3RvcnM8L2tleXdvcmQ+PGtleXdvcmQ+U3Ryb2tl

PC9rZXl3b3JkPjxrZXl3b3JkPlRpc3N1ZSBQbGFzbWlub2dlbiBBY3RpdmF0b3I8L2tleXdvcmQ+

PC9rZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cDovL3d3dy5uY2JpLm5sbS5u

aWguZ292L3B1Ym1lZC8yMjk5Njk1OTwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJscz48aXNibj4x

NTI0LTQ2Mjg8L2lzYm4+PHRpdGxlcz48dGl0bGU+UmlzayBmYWN0b3JzIGZvciBpbnRyYWNyYW5p

YWwgaGVtb3JyaGFnZSBpbiBhY3V0ZSBpc2NoZW1pYyBzdHJva2UgcGF0aWVudHMgdHJlYXRlZCB3

aXRoIHJlY29tYmluYW50IHRpc3N1ZSBwbGFzbWlub2dlbiBhY3RpdmF0b3I6IGEgc3lzdGVtYXRp

YyByZXZpZXcgYW5kIG1ldGEtYW5hbHlzaXMgb2YgNTUgc3R1ZGllczwvdGl0bGU+PHNlY29uZGFy

eS10aXRsZT5TdHJva2U8L3NlY29uZGFyeS10aXRsZT48L3RpdGxlcz48cGFnZXM+MjkwNC05PC9w

YWdlcz48bnVtYmVyPjExPC9udW1iZXI+PGNvbnRyaWJ1dG9ycz48YXV0aG9ycz48YXV0aG9yPldo

aXRlbGV5LCBXLiBOLjwvYXV0aG9yPjxhdXRob3I+U2xvdCwgSy4gQi48L2F1dGhvcj48YXV0aG9y

PkZlcm5hbmRlcywgUC48L2F1dGhvcj48YXV0aG9yPlNhbmRlcmNvY2ssIFAuPC9hdXRob3I+PGF1

dGhvcj5XYXJkbGF3LCBKLjwvYXV0aG9yPjwvYXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3Vh

Z2U+ZW5nPC9sYW5ndWFnZT48YWRkZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTM3MjQzNjQzNDwvYWRk

ZWQtZGF0ZT48cmVmLXR5cGUgbmFtZT0iSm91cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PGF1

dGgtYWRkcmVzcz5EaXZpc2lvbiBvZiBDbGluaWNhbCBOZXVyb3NjaWVuY2VzLCBVbml2ZXJzaXR5

IG9mIEVkaW5idXJnaCwgV2VzdGVybiBHZW5lcmFsIEhvc3BpdGFsLCBFZGluYnVyZ2gsIEVINCAy

WFUsIFVLLiB3aWxsaWFtLndoaXRlbGV5QGVkLmFjLnVrPC9hdXRoLWFkZHJlc3M+PHJlYy1udW1i

ZXI+MzE0PC9yZWMtbnVtYmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTM3MjQz

NjQzNDwvbGFzdC11cGRhdGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MjI5OTY5NTk8L2FjY2Vzc2lv

bi1udW0+PGVsZWN0cm9uaWMtcmVzb3VyY2UtbnVtPjEwLjExNjEvU1RST0tFQUhBLjExMi42NjUz

MzE8L2VsZWN0cm9uaWMtcmVzb3VyY2UtbnVtPjx2b2x1bWU+NDM8L3ZvbHVtZT48L3JlY29yZD48

L0NpdGU+PENpdGU+PEF1dGhvcj5JU1QtMzwvQXV0aG9yPjxZZWFyPjIwMTU8L1llYXI+PElEVGV4

dD5Bc3NvY2lhdGlvbiBiZXR3ZWVuIGJyYWluIGltYWdpbmcgc2lnbnMsIGVhcmx5IGFuZCBsYXRl

IG91dGNvbWVzLCBhbmQgcmVzcG9uc2UgdG8gaW50cmF2ZW5vdXMgYWx0ZXBsYXNlIGFmdGVyIGFj

dXRlIGlzY2hhZW1pYyBzdHJva2UgaW4gdGhlIHRoaXJkIEludGVybmF0aW9uYWwgU3Ryb2tlIFRy

aWFsIChJU1QtMyk6IHNlY29uZGFyeSBhbmFseXNpcyBvZiBhIHJhbmRvbWlzZWQgY29udHJvbGxl

ZCB0cmlhbDwvSURUZXh0PjxyZWNvcmQ+PGRhdGVzPjxwdWItZGF0ZXM+PGRhdGU+TWF5PC9kYXRl

PjwvcHViLWRhdGVzPjx5ZWFyPjIwMTU8L3llYXI+PC9kYXRlcz48a2V5d29yZHM+PGtleXdvcmQ+

QWR1bHQ8L2tleXdvcmQ+PGtleXdvcmQ+QWdlZDwva2V5d29yZD48a2V5d29yZD5BZ2VkLCA4MCBh

bmQgb3Zlcjwva2V5d29yZD48a2V5d29yZD5CcmFpbiBJc2NoZW1pYTwva2V5d29yZD48a2V5d29y

ZD5EYXRhIEludGVycHJldGF0aW9uLCBTdGF0aXN0aWNhbDwva2V5d29yZD48a2V5d29yZD5GZW1h

bGU8L2tleXdvcmQ+PGtleXdvcmQ+Rmlicmlub2x5dGljIEFnZW50czwva2V5d29yZD48a2V5d29y

ZD5IdW1hbnM8L2tleXdvcmQ+PGtleXdvcmQ+TWFnbmV0aWMgUmVzb25hbmNlIEltYWdpbmcsIENp

bmU8L2tleXdvcmQ+PGtleXdvcmQ+TWFsZTwva2V5d29yZD48a2V5d29yZD5NaWRkbGUgQWdlZDwv

a2V5d29yZD48a2V5d29yZD5PdXRjb21lIEFzc2Vzc21lbnQgKEhlYWx0aCBDYXJlKTwva2V5d29y

ZD48a2V5d29yZD5TaW5nbGUtQmxpbmQgTWV0aG9kPC9rZXl3b3JkPjxrZXl3b3JkPlN0cm9rZTwv

a2V5d29yZD48a2V5d29yZD5UaHJvbWJvbHl0aWMgVGhlcmFweTwva2V5d29yZD48a2V5d29yZD5U

aXNzdWUgUGxhc21pbm9nZW4gQWN0aXZhdG9yPC9rZXl3b3JkPjwva2V5d29yZHM+PHVybHM+PHJl

bGF0ZWQtdXJscz48dXJsPmh0dHBzOi8vd3d3Lm5jYmkubmxtLm5paC5nb3YvcHVibWVkLzI1ODE5

NDg0PC91cmw+PC9yZWxhdGVkLXVybHM+PC91cmxzPjxpc2JuPjE0NzQtNDQ2NTwvaXNibj48Y3Vz

dG9tMj5QTUM0NTEzMTkwPC9jdXN0b20yPjx0aXRsZXM+PHRpdGxlPkFzc29jaWF0aW9uIGJldHdl

ZW4gYnJhaW4gaW1hZ2luZyBzaWducywgZWFybHkgYW5kIGxhdGUgb3V0Y29tZXMsIGFuZCByZXNw

b25zZSB0byBpbnRyYXZlbm91cyBhbHRlcGxhc2UgYWZ0ZXIgYWN1dGUgaXNjaGFlbWljIHN0cm9r

ZSBpbiB0aGUgdGhpcmQgSW50ZXJuYXRpb25hbCBTdHJva2UgVHJpYWwgKElTVC0zKTogc2Vjb25k

YXJ5IGFuYWx5c2lzIG9mIGEgcmFuZG9taXNlZCBjb250cm9sbGVkIHRyaWFsPC90aXRsZT48c2Vj

b25kYXJ5LXRpdGxlPkxhbmNldCBOZXVyb2w8L3NlY29uZGFyeS10aXRsZT48L3RpdGxlcz48cGFn

ZXM+NDg1LTk2PC9wYWdlcz48bnVtYmVyPjU8L251bWJlcj48Y29udHJpYnV0b3JzPjxhdXRob3Jz

PjxhdXRob3I+SVNULTMgY29sbGFib3JhdGl2ZSBncm91cDwvYXV0aG9yPjwvYXV0aG9ycz48L2Nv

bnRyaWJ1dG9ycz48bGFuZ3VhZ2U+RU5HPC9sYW5ndWFnZT48YWRkZWQtZGF0ZSBmb3JtYXQ9InV0

YyI+MTQ3ODE3ODg2NzwvYWRkZWQtZGF0ZT48cmVmLXR5cGUgbmFtZT0iSm91cm5hbCBBcnRpY2xl

Ij4xNzwvcmVmLXR5cGU+PHJlYy1udW1iZXI+NTMzPC9yZWMtbnVtYmVyPjxsYXN0LXVwZGF0ZWQt

ZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3ODE3ODg2NzwvbGFzdC11cGRhdGVkLWRhdGU+PGFjY2Vzc2lv

bi1udW0+MjU4MTk0ODQ8L2FjY2Vzc2lvbi1udW0+PGVsZWN0cm9uaWMtcmVzb3VyY2UtbnVtPjEw

LjEwMTYvUzE0NzQtNDQyMigxNSkwMDAxMi01PC9lbGVjdHJvbmljLXJlc291cmNlLW51bT48dm9s

dW1lPjE0PC92b2x1bWU+PC9yZWNvcmQ+PC9DaXRlPjwvRW5kTm90ZT4AAAA=

ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XaGl0ZWxleTwvQXV0aG9yPjxZZWFyPjIwMTI8L1llYXI+

PElEVGV4dD5SaXNrIGZhY3RvcnMgZm9yIGludHJhY3JhbmlhbCBoZW1vcnJoYWdlIGluIGFjdXRl

IGlzY2hlbWljIHN0cm9rZSBwYXRpZW50cyB0cmVhdGVkIHdpdGggcmVjb21iaW5hbnQgdGlzc3Vl

IHBsYXNtaW5vZ2VuIGFjdGl2YXRvcjogYSBzeXN0ZW1hdGljIHJldmlldyBhbmQgbWV0YS1hbmFs

eXNpcyBvZiA1NSBzdHVkaWVzPC9JRFRleHQ+PERpc3BsYXlUZXh0PjxzdHlsZSBmYWNlPSJzdXBl

cnNjcmlwdCI+NCwgMzA8L3N0eWxlPjwvRGlzcGxheVRleHQ+PHJlY29yZD48ZGF0ZXM+PHB1Yi1k

YXRlcz48ZGF0ZT5Ob3Y8L2RhdGU+PC9wdWItZGF0ZXM+PHllYXI+MjAxMjwveWVhcj48L2RhdGVz

PjxrZXl3b3Jkcz48a2V5d29yZD5BZ2UgRmFjdG9yczwva2V5d29yZD48a2V5d29yZD5BZ2VkPC9r

ZXl3b3JkPjxrZXl3b3JkPkFnZWQsIDgwIGFuZCBvdmVyPC9rZXl3b3JkPjxrZXl3b3JkPkJyYWlu

IElzY2hlbWlhPC9rZXl3b3JkPjxrZXl3b3JkPkZpYnJpbm9seXRpYyBBZ2VudHM8L2tleXdvcmQ+

PGtleXdvcmQ+SHVtYW5zPC9rZXl3b3JkPjxrZXl3b3JkPkludHJhY3JhbmlhbCBIZW1vcnJoYWdl

czwva2V5d29yZD48a2V5d29yZD5SaXNrIEZhY3RvcnM8L2tleXdvcmQ+PGtleXdvcmQ+U3Ryb2tl

PC9rZXl3b3JkPjxrZXl3b3JkPlRpc3N1ZSBQbGFzbWlub2dlbiBBY3RpdmF0b3I8L2tleXdvcmQ+

PC9rZXl3b3Jkcz48dXJscz48cmVsYXRlZC11cmxzPjx1cmw+aHR0cDovL3d3dy5uY2JpLm5sbS5u

aWguZ292L3B1Ym1lZC8yMjk5Njk1OTwvdXJsPjwvcmVsYXRlZC11cmxzPjwvdXJscz48aXNibj4x

NTI0LTQ2Mjg8L2lzYm4+PHRpdGxlcz48dGl0bGU+UmlzayBmYWN0b3JzIGZvciBpbnRyYWNyYW5p

YWwgaGVtb3JyaGFnZSBpbiBhY3V0ZSBpc2NoZW1pYyBzdHJva2UgcGF0aWVudHMgdHJlYXRlZCB3

aXRoIHJlY29tYmluYW50IHRpc3N1ZSBwbGFzbWlub2dlbiBhY3RpdmF0b3I6IGEgc3lzdGVtYXRp

YyByZXZpZXcgYW5kIG1ldGEtYW5hbHlzaXMgb2YgNTUgc3R1ZGllczwvdGl0bGU+PHNlY29uZGFy

eS10aXRsZT5TdHJva2U8L3NlY29uZGFyeS10aXRsZT48L3RpdGxlcz48cGFnZXM+MjkwNC05PC9w

YWdlcz48bnVtYmVyPjExPC9udW1iZXI+PGNvbnRyaWJ1dG9ycz48YXV0aG9ycz48YXV0aG9yPldo

aXRlbGV5LCBXLiBOLjwvYXV0aG9yPjxhdXRob3I+U2xvdCwgSy4gQi48L2F1dGhvcj48YXV0aG9y

PkZlcm5hbmRlcywgUC48L2F1dGhvcj48YXV0aG9yPlNhbmRlcmNvY2ssIFAuPC9hdXRob3I+PGF1

dGhvcj5XYXJkbGF3LCBKLjwvYXV0aG9yPjwvYXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3Vh

Z2U+ZW5nPC9sYW5ndWFnZT48YWRkZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTM3MjQzNjQzNDwvYWRk

ZWQtZGF0ZT48cmVmLXR5cGUgbmFtZT0iSm91cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PGF1

dGgtYWRkcmVzcz5EaXZpc2lvbiBvZiBDbGluaWNhbCBOZXVyb3NjaWVuY2VzLCBVbml2ZXJzaXR5

IG9mIEVkaW5idXJnaCwgV2VzdGVybiBHZW5lcmFsIEhvc3BpdGFsLCBFZGluYnVyZ2gsIEVINCAy

WFUsIFVLLiB3aWxsaWFtLndoaXRlbGV5QGVkLmFjLnVrPC9hdXRoLWFkZHJlc3M+PHJlYy1udW1i

ZXI+MzE0PC9yZWMtbnVtYmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTM3MjQz

NjQzNDwvbGFzdC11cGRhdGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MjI5OTY5NTk8L2FjY2Vzc2lv

bi1udW0+PGVsZWN0cm9uaWMtcmVzb3VyY2UtbnVtPjEwLjExNjEvU1RST0tFQUhBLjExMi42NjUz

MzE8L2VsZWN0cm9uaWMtcmVzb3VyY2UtbnVtPjx2b2x1bWU+NDM8L3ZvbHVtZT48L3JlY29yZD48

L0NpdGU+PENpdGU+PEF1dGhvcj5JU1QtMzwvQXV0aG9yPjxZZWFyPjIwMTU8L1llYXI+PElEVGV4

dD5Bc3NvY2lhdGlvbiBiZXR3ZWVuIGJyYWluIGltYWdpbmcgc2lnbnMsIGVhcmx5IGFuZCBsYXRl

IG91dGNvbWVzLCBhbmQgcmVzcG9uc2UgdG8gaW50cmF2ZW5vdXMgYWx0ZXBsYXNlIGFmdGVyIGFj

dXRlIGlzY2hhZW1pYyBzdHJva2UgaW4gdGhlIHRoaXJkIEludGVybmF0aW9uYWwgU3Ryb2tlIFRy

aWFsIChJU1QtMyk6IHNlY29uZGFyeSBhbmFseXNpcyBvZiBhIHJhbmRvbWlzZWQgY29udHJvbGxl

ZCB0cmlhbDwvSURUZXh0PjxyZWNvcmQ+PGRhdGVzPjxwdWItZGF0ZXM+PGRhdGU+TWF5PC9kYXRl

PjwvcHViLWRhdGVzPjx5ZWFyPjIwMTU8L3llYXI+PC9kYXRlcz48a2V5d29yZHM+PGtleXdvcmQ+

QWR1bHQ8L2tleXdvcmQ+PGtleXdvcmQ+QWdlZDwva2V5d29yZD48a2V5d29yZD5BZ2VkLCA4MCBh

bmQgb3Zlcjwva2V5d29yZD48a2V5d29yZD5CcmFpbiBJc2NoZW1pYTwva2V5d29yZD48a2V5d29y

ZD5EYXRhIEludGVycHJldGF0aW9uLCBTdGF0aXN0aWNhbDwva2V5d29yZD48a2V5d29yZD5GZW1h

bGU8L2tleXdvcmQ+PGtleXdvcmQ+Rmlicmlub2x5dGljIEFnZW50czwva2V5d29yZD48a2V5d29y

ZD5IdW1hbnM8L2tleXdvcmQ+PGtleXdvcmQ+TWFnbmV0aWMgUmVzb25hbmNlIEltYWdpbmcsIENp

bmU8L2tleXdvcmQ+PGtleXdvcmQ+TWFsZTwva2V5d29yZD48a2V5d29yZD5NaWRkbGUgQWdlZDwv

a2V5d29yZD48a2V5d29yZD5PdXRjb21lIEFzc2Vzc21lbnQgKEhlYWx0aCBDYXJlKTwva2V5d29y

ZD48a2V5d29yZD5TaW5nbGUtQmxpbmQgTWV0aG9kPC9rZXl3b3JkPjxrZXl3b3JkPlN0cm9rZTwv

a2V5d29yZD48a2V5d29yZD5UaHJvbWJvbHl0aWMgVGhlcmFweTwva2V5d29yZD48a2V5d29yZD5U

aXNzdWUgUGxhc21pbm9nZW4gQWN0aXZhdG9yPC9rZXl3b3JkPjwva2V5d29yZHM+PHVybHM+PHJl

bGF0ZWQtdXJscz48dXJsPmh0dHBzOi8vd3d3Lm5jYmkubmxtLm5paC5nb3YvcHVibWVkLzI1ODE5

NDg0PC91cmw+PC9yZWxhdGVkLXVybHM+PC91cmxzPjxpc2JuPjE0NzQtNDQ2NTwvaXNibj48Y3Vz

dG9tMj5QTUM0NTEzMTkwPC9jdXN0b20yPjx0aXRsZXM+PHRpdGxlPkFzc29jaWF0aW9uIGJldHdl

ZW4gYnJhaW4gaW1hZ2luZyBzaWducywgZWFybHkgYW5kIGxhdGUgb3V0Y29tZXMsIGFuZCByZXNw

b25zZSB0byBpbnRyYXZlbm91cyBhbHRlcGxhc2UgYWZ0ZXIgYWN1dGUgaXNjaGFlbWljIHN0cm9r

ZSBpbiB0aGUgdGhpcmQgSW50ZXJuYXRpb25hbCBTdHJva2UgVHJpYWwgKElTVC0zKTogc2Vjb25k

YXJ5IGFuYWx5c2lzIG9mIGEgcmFuZG9taXNlZCBjb250cm9sbGVkIHRyaWFsPC90aXRsZT48c2Vj

b25kYXJ5LXRpdGxlPkxhbmNldCBOZXVyb2w8L3NlY29uZGFyeS10aXRsZT48L3RpdGxlcz48cGFn

ZXM+NDg1LTk2PC9wYWdlcz48bnVtYmVyPjU8L251bWJlcj48Y29udHJpYnV0b3JzPjxhdXRob3Jz

PjxhdXRob3I+SVNULTMgY29sbGFib3JhdGl2ZSBncm91cDwvYXV0aG9yPjwvYXV0aG9ycz48L2Nv

bnRyaWJ1dG9ycz48bGFuZ3VhZ2U+RU5HPC9sYW5ndWFnZT48YWRkZWQtZGF0ZSBmb3JtYXQ9InV0

YyI+MTQ3ODE3ODg2NzwvYWRkZWQtZGF0ZT48cmVmLXR5cGUgbmFtZT0iSm91cm5hbCBBcnRpY2xl

Ij4xNzwvcmVmLXR5cGU+PHJlYy1udW1iZXI+NTMzPC9yZWMtbnVtYmVyPjxsYXN0LXVwZGF0ZWQt

ZGF0ZSBmb3JtYXQ9InV0YyI+MTQ3ODE3ODg2NzwvbGFzdC11cGRhdGVkLWRhdGU+PGFjY2Vzc2lv

bi1udW0+MjU4MTk0ODQ8L2FjY2Vzc2lvbi1udW0+PGVsZWN0cm9uaWMtcmVzb3VyY2UtbnVtPjEw

LjEwMTYvUzE0NzQtNDQyMigxNSkwMDAxMi01PC9lbGVjdHJvbmljLXJlc291cmNlLW51bT48dm9s

dW1lPjE0PC92b2x1bWU+PC9yZWNvcmQ+PC9DaXRlPjwvRW5kTm90ZT4AAAA=

ADDIN EN.CITE.DATA 4, 30. Since automated CT feature extraction, as presented here for WML, offers a reduction in variable noise relative to expert ratings, it would be interesting to explore whether such machine-learning methods can identify treatment-specific ICH or functional outcomes. A related application would be to see if CT WML quantification could be used to predict anticoagulant-associated intracranial haemorrhage ADDIN EN.CITE <EndNote><Cite><Author>Smith</Author><Year>2002</Year><IDText>Leukoaraiosis is associated with warfarin-related hemorrhage following ischemic stroke</IDText><DisplayText><style face="superscript">31</style></DisplayText><record><dates><pub-dates><date>Jul</date></pub-dates><year>2002</year></dates><keywords><keyword>Aged</keyword><keyword>Aged, 80 and over</keyword><keyword>Anticoagulants</keyword><keyword>Brain</keyword><keyword>Brain Ischemia</keyword><keyword>Case-Control Studies</keyword><keyword>Cerebral Hemorrhage</keyword><keyword>Female</keyword><keyword>Humans</keyword><keyword>International Normalized Ratio</keyword><keyword>Male</keyword><keyword>Middle Aged</keyword><keyword>Risk Factors</keyword><keyword>Severity of Illness Index</keyword><keyword>Warfarin</keyword></keywords><urls><related-urls><url> is associated with warfarin-related hemorrhage following ischemic stroke</title><secondary-title>Neurology</secondary-title></titles><pages>193-7</pages><number>2</number><contributors><authors><author>Smith, E. E.</author><author>Rosand, J.</author><author>Knudsen, K. A.</author><author>Hylek, E. M.</author><author>Greenberg, S. M.</author></authors></contributors><language>ENG</language><added-date format="utc">1478712503</added-date><ref-type name="Journal Article">17</ref-type><rec-number>554</rec-number><last-updated-date format="utc">1478712503</last-updated-date><accession-num>12136056</accession-num><volume>59</volume></record></Cite></EndNote>31 or hematoma growth and early deterioration after primary intracranial haemorrhage ADDIN EN.CITE <EndNote><Cite><Author>Lou</Author><Year>2010</Year><IDText>Relationship between white-matter hyperintensities and hematoma volume and growth in patients with intracerebral hemorrhage</IDText><DisplayText><style face="superscript">32</style></DisplayText><record><dates><pub-dates><date>Jan</date></pub-dates><year>2010</year></dates><keywords><keyword>Aged</keyword><keyword>Aged, 80 and over</keyword><keyword>Cerebral Hemorrhage</keyword><keyword>Female</keyword><keyword>Hematoma, Epidural, Cranial</keyword><keyword>Humans</keyword><keyword>Leukoaraiosis</keyword><keyword>Male</keyword><keyword>Middle Aged</keyword><keyword>Nerve Fibers, Myelinated</keyword><keyword>Prospective Studies</keyword><keyword>Retrospective Studies</keyword><keyword>Risk Factors</keyword></keywords><urls><related-urls><url> between white-matter hyperintensities and hematoma volume and growth in patients with intracerebral hemorrhage</title><secondary-title>Stroke</secondary-title></titles><pages>34-40</pages><number>1</number><contributors><authors><author>Lou, M.</author><author>Al-Hazzani, A.</author><author>Goddeau, R. P.</author><author>Novak, V.</author><author>Selim, M.</author></authors></contributors><edition>2009/11/19</edition><language>eng</language><added-date format="utc">1486061768</added-date><ref-type name="Journal Article">17</ref-type><rec-number>570</rec-number><last-updated-date format="utc">1486061768</last-updated-date><accession-num>19926840</accession-num><electronic-resource-num>10.1161/STROKEAHA.109.564955</electronic-resource-num><volume>41</volume></record></Cite></EndNote>32. More generally, WML quantification may be important in diagnosing, grading and monitoring vascular dementia (and possibly other types of dementia); and for prognosis after head injury ADDIN EN.CITE <EndNote><Cite><Author>Henninger</Author><Year>2014</Year><IDText>Severe leukoaraiosis portends a poor outcome after traumatic brain injury</IDText><DisplayText><style face="superscript">6</style></DisplayText><record><dates><pub-dates><date>Dec</date></pub-dates><year>2014</year></dates><keywords><keyword>Age Factors</keyword><keyword>Aged</keyword><keyword>Aged, 80 and over</keyword><keyword>Brain Injuries</keyword><keyword>Cohort Studies</keyword><keyword>Female</keyword><keyword>Glasgow Coma Scale</keyword><keyword>Glasgow Outcome Scale</keyword><keyword>Humans</keyword><keyword>Leukoaraiosis</keyword><keyword>Male</keyword><keyword>Middle Aged</keyword><keyword>Prognosis</keyword><keyword>Retrospective Studies</keyword><keyword>Severity of Illness Index</keyword><keyword>Tomography, X-Ray Computed</keyword><keyword>White Matter</keyword></keywords><urls><related-urls><url> leukoaraiosis portends a poor outcome after traumatic brain injury</title><secondary-title>Neurocrit Care</secondary-title></titles><pages>483-95</pages><number>3</number><contributors><authors><author>Henninger, N.</author><author>Izzy, S.</author><author>Carandang, R.</author><author>Hall, W.</author><author>Muehlschlegel, S.</author></authors></contributors><language>eng</language><added-date format="utc">1486060288</added-date><ref-type name="Journal Article">17</ref-type><rec-number>569</rec-number><last-updated-date format="utc">1486060288</last-updated-date><accession-num>24752459</accession-num><electronic-resource-num>10.1007/s12028-014-9980-0</electronic-resource-num><volume>21</volume></record></Cite></EndNote>6. In summary, automated WML quantification enables reliable parameterization of a common and clinically-relevant neuroimaging biomarker. Clinical research into cerebral white-matter lesions, in contexts where CT is the predominant imaging modality, may benefit from the method more than existing observer-dependent visual ratings. AcknowledgementsThis work was supported by NIHR Grant i4i: Decision-assist software for management of acute ischaemic stroke using brain-imaging machine-learning (Ref: II-LA-0814-20007).Funding sources for IST-3 trial are listed elsewherePEVuZE5vdGU+PENpdGU+PEF1dGhvcj5TYW5kZXJjb2NrPC9BdXRob3I+PFllYXI+MjAxMjwvWWVh

cj48SURUZXh0PlRoZSBiZW5lZml0cyBhbmQgaGFybXMgb2YgaW50cmF2ZW5vdXMgdGhyb21ib2x5

c2lzIHdpdGggcmVjb21iaW5hbnQgdGlzc3VlIHBsYXNtaW5vZ2VuIGFjdGl2YXRvciB3aXRoaW4g

NiBoIG9mIGFjdXRlIGlzY2hhZW1pYyBzdHJva2UgKHRoZSB0aGlyZCBpbnRlcm5hdGlvbmFsIHN0

cm9rZSB0cmlhbCBbSVNULTNdKTogYSByYW5kb21pc2VkIGNvbnRyb2xsZWQgdHJpYWw8L0lEVGV4

dD48RGlzcGxheVRleHQ+PHN0eWxlIGZhY2U9InN1cGVyc2NyaXB0Ij4xOTwvc3R5bGU+PC9EaXNw

bGF5VGV4dD48cmVjb3JkPjxkYXRlcz48cHViLWRhdGVzPjxkYXRlPkp1bjwvZGF0ZT48L3B1Yi1k

YXRlcz48eWVhcj4yMDEyPC95ZWFyPjwvZGF0ZXM+PGtleXdvcmRzPjxrZXl3b3JkPkFkb2xlc2Nl

bnQ8L2tleXdvcmQ+PGtleXdvcmQ+QWR1bHQ8L2tleXdvcmQ+PGtleXdvcmQ+QWdlIERpc3RyaWJ1

dGlvbjwva2V5d29yZD48a2V5d29yZD5BZ2VkPC9rZXl3b3JkPjxrZXl3b3JkPkFnZWQsIDgwIGFu

ZCBvdmVyPC9rZXl3b3JkPjxrZXl3b3JkPkJyYWluIElzY2hlbWlhPC9rZXl3b3JkPjxrZXl3b3Jk

PkRvdWJsZS1CbGluZCBNZXRob2Q8L2tleXdvcmQ+PGtleXdvcmQ+RHJ1ZyBBZG1pbmlzdHJhdGlv

biBTY2hlZHVsZTwva2V5d29yZD48a2V5d29yZD5GZW1hbGU8L2tleXdvcmQ+PGtleXdvcmQ+Rmli

cmlub2x5dGljIEFnZW50czwva2V5d29yZD48a2V5d29yZD5IdW1hbnM8L2tleXdvcmQ+PGtleXdv

cmQ+SW5mdXNpb25zLCBJbnRyYXZlbm91czwva2V5d29yZD48a2V5d29yZD5NYWxlPC9rZXl3b3Jk

PjxrZXl3b3JkPk1pZGRsZSBBZ2VkPC9rZXl3b3JkPjxrZXl3b3JkPlJlY29tYmluYW50IFByb3Rl

aW5zPC9rZXl3b3JkPjxrZXl3b3JkPlJlY3VycmVuY2U8L2tleXdvcmQ+PGtleXdvcmQ+U2V2ZXJp

dHkgb2YgSWxsbmVzcyBJbmRleDwva2V5d29yZD48a2V5d29yZD5TdHJva2U8L2tleXdvcmQ+PGtl

eXdvcmQ+VGhyb21ib2x5dGljIFRoZXJhcHk8L2tleXdvcmQ+PGtleXdvcmQ+VGlzc3VlIFBsYXNt

aW5vZ2VuIEFjdGl2YXRvcjwva2V5d29yZD48a2V5d29yZD5UcmVhdG1lbnQgT3V0Y29tZTwva2V5

d29yZD48a2V5d29yZD5Zb3VuZyBBZHVsdDwva2V5d29yZD48L2tleXdvcmRzPjx1cmxzPjxyZWxh

dGVkLXVybHM+PHVybD5odHRwOi8vd3d3Lm5jYmkubmxtLm5paC5nb3YvcHVibWVkLzIyNjMyOTA4

PC91cmw+PC9yZWxhdGVkLXVybHM+PC91cmxzPjxpc2JuPjE0NzQtNTQ3WDwvaXNibj48Y3VzdG9t

Mj5QTUMzMzg2NDk1PC9jdXN0b20yPjx0aXRsZXM+PHRpdGxlPlRoZSBiZW5lZml0cyBhbmQgaGFy

bXMgb2YgaW50cmF2ZW5vdXMgdGhyb21ib2x5c2lzIHdpdGggcmVjb21iaW5hbnQgdGlzc3VlIHBs

YXNtaW5vZ2VuIGFjdGl2YXRvciB3aXRoaW4gNiBoIG9mIGFjdXRlIGlzY2hhZW1pYyBzdHJva2Ug

KHRoZSB0aGlyZCBpbnRlcm5hdGlvbmFsIHN0cm9rZSB0cmlhbCBbSVNULTNdKTogYSByYW5kb21p

c2VkIGNvbnRyb2xsZWQgdHJpYWw8L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+TGFuY2V0PC9zZWNv

bmRhcnktdGl0bGU+PC90aXRsZXM+PHBhZ2VzPjIzNTItNjM8L3BhZ2VzPjxudW1iZXI+OTgzNDwv

bnVtYmVyPjxjb250cmlidXRvcnM+PGF1dGhvcnM+PGF1dGhvcj5TYW5kZXJjb2NrLCBQLjwvYXV0

aG9yPjxhdXRob3I+V2FyZGxhdywgSi4gTS48L2F1dGhvcj48YXV0aG9yPkxpbmRsZXksIFIuIEku

PC9hdXRob3I+PGF1dGhvcj5EZW5uaXMsIE0uPC9hdXRob3I+PGF1dGhvcj5Db2hlbiwgRy48L2F1

dGhvcj48YXV0aG9yPk11cnJheSwgRy48L2F1dGhvcj48YXV0aG9yPklubmVzLCBLLjwvYXV0aG9y

PjxhdXRob3I+VmVuYWJsZXMsIEcuPC9hdXRob3I+PGF1dGhvcj5Demxvbmtvd3NrYSwgQS48L2F1

dGhvcj48YXV0aG9yPktvYmF5YXNoaSwgQS48L2F1dGhvcj48YXV0aG9yPlJpY2NpLCBTLjwvYXV0

aG9yPjxhdXRob3I+TXVycmF5LCBWLjwvYXV0aG9yPjxhdXRob3I+QmVyZ2UsIEUuPC9hdXRob3I+

PGF1dGhvcj5TbG90LCBLLiBCLjwvYXV0aG9yPjxhdXRob3I+SGFua2V5LCBHLiBKLjwvYXV0aG9y

PjxhdXRob3I+Q29ycmVpYSwgTS48L2F1dGhvcj48YXV0aG9yPlBlZXRlcnMsIEEuPC9hdXRob3I+

PGF1dGhvcj5NYXR6LCBLLjwvYXV0aG9yPjxhdXRob3I+THlyZXIsIFAuPC9hdXRob3I+PGF1dGhv

cj5HdWJpdHosIEcuPC9hdXRob3I+PGF1dGhvcj5QaGlsbGlwcywgUy4gSi48L2F1dGhvcj48YXV0

aG9yPkFyYXV6LCBBLjwvYXV0aG9yPjxhdXRob3I+SVNULTMgY29sbGFib3JhdGl2ZSBncm91cDwv

YXV0aG9yPjwvYXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3VhZ2U+ZW5nPC9sYW5ndWFnZT48

YWRkZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTM4NzU0NzU0MjwvYWRkZWQtZGF0ZT48cmVmLXR5cGUg

bmFtZT0iSm91cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PHJlYy1udW1iZXI+MzQ5PC9yZWMt

bnVtYmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTM4NzU0NzU0MjwvbGFzdC11

cGRhdGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MjI2MzI5MDg8L2FjY2Vzc2lvbi1udW0+PGVsZWN0

cm9uaWMtcmVzb3VyY2UtbnVtPjEwLjEwMTYvUzAxNDAtNjczNigxMik2MDc2OC01PC9lbGVjdHJv

bmljLXJlc291cmNlLW51bT48dm9sdW1lPjM3OTwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48L0Vu

ZE5vdGU+AAA=

ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5TYW5kZXJjb2NrPC9BdXRob3I+PFllYXI+MjAxMjwvWWVh

cj48SURUZXh0PlRoZSBiZW5lZml0cyBhbmQgaGFybXMgb2YgaW50cmF2ZW5vdXMgdGhyb21ib2x5

c2lzIHdpdGggcmVjb21iaW5hbnQgdGlzc3VlIHBsYXNtaW5vZ2VuIGFjdGl2YXRvciB3aXRoaW4g

NiBoIG9mIGFjdXRlIGlzY2hhZW1pYyBzdHJva2UgKHRoZSB0aGlyZCBpbnRlcm5hdGlvbmFsIHN0

cm9rZSB0cmlhbCBbSVNULTNdKTogYSByYW5kb21pc2VkIGNvbnRyb2xsZWQgdHJpYWw8L0lEVGV4

dD48RGlzcGxheVRleHQ+PHN0eWxlIGZhY2U9InN1cGVyc2NyaXB0Ij4xOTwvc3R5bGU+PC9EaXNw

bGF5VGV4dD48cmVjb3JkPjxkYXRlcz48cHViLWRhdGVzPjxkYXRlPkp1bjwvZGF0ZT48L3B1Yi1k

YXRlcz48eWVhcj4yMDEyPC95ZWFyPjwvZGF0ZXM+PGtleXdvcmRzPjxrZXl3b3JkPkFkb2xlc2Nl

bnQ8L2tleXdvcmQ+PGtleXdvcmQ+QWR1bHQ8L2tleXdvcmQ+PGtleXdvcmQ+QWdlIERpc3RyaWJ1

dGlvbjwva2V5d29yZD48a2V5d29yZD5BZ2VkPC9rZXl3b3JkPjxrZXl3b3JkPkFnZWQsIDgwIGFu

ZCBvdmVyPC9rZXl3b3JkPjxrZXl3b3JkPkJyYWluIElzY2hlbWlhPC9rZXl3b3JkPjxrZXl3b3Jk

PkRvdWJsZS1CbGluZCBNZXRob2Q8L2tleXdvcmQ+PGtleXdvcmQ+RHJ1ZyBBZG1pbmlzdHJhdGlv

biBTY2hlZHVsZTwva2V5d29yZD48a2V5d29yZD5GZW1hbGU8L2tleXdvcmQ+PGtleXdvcmQ+Rmli

cmlub2x5dGljIEFnZW50czwva2V5d29yZD48a2V5d29yZD5IdW1hbnM8L2tleXdvcmQ+PGtleXdv

cmQ+SW5mdXNpb25zLCBJbnRyYXZlbm91czwva2V5d29yZD48a2V5d29yZD5NYWxlPC9rZXl3b3Jk

PjxrZXl3b3JkPk1pZGRsZSBBZ2VkPC9rZXl3b3JkPjxrZXl3b3JkPlJlY29tYmluYW50IFByb3Rl

aW5zPC9rZXl3b3JkPjxrZXl3b3JkPlJlY3VycmVuY2U8L2tleXdvcmQ+PGtleXdvcmQ+U2V2ZXJp

dHkgb2YgSWxsbmVzcyBJbmRleDwva2V5d29yZD48a2V5d29yZD5TdHJva2U8L2tleXdvcmQ+PGtl

eXdvcmQ+VGhyb21ib2x5dGljIFRoZXJhcHk8L2tleXdvcmQ+PGtleXdvcmQ+VGlzc3VlIFBsYXNt

aW5vZ2VuIEFjdGl2YXRvcjwva2V5d29yZD48a2V5d29yZD5UcmVhdG1lbnQgT3V0Y29tZTwva2V5

d29yZD48a2V5d29yZD5Zb3VuZyBBZHVsdDwva2V5d29yZD48L2tleXdvcmRzPjx1cmxzPjxyZWxh

dGVkLXVybHM+PHVybD5odHRwOi8vd3d3Lm5jYmkubmxtLm5paC5nb3YvcHVibWVkLzIyNjMyOTA4

PC91cmw+PC9yZWxhdGVkLXVybHM+PC91cmxzPjxpc2JuPjE0NzQtNTQ3WDwvaXNibj48Y3VzdG9t

Mj5QTUMzMzg2NDk1PC9jdXN0b20yPjx0aXRsZXM+PHRpdGxlPlRoZSBiZW5lZml0cyBhbmQgaGFy

bXMgb2YgaW50cmF2ZW5vdXMgdGhyb21ib2x5c2lzIHdpdGggcmVjb21iaW5hbnQgdGlzc3VlIHBs

YXNtaW5vZ2VuIGFjdGl2YXRvciB3aXRoaW4gNiBoIG9mIGFjdXRlIGlzY2hhZW1pYyBzdHJva2Ug

KHRoZSB0aGlyZCBpbnRlcm5hdGlvbmFsIHN0cm9rZSB0cmlhbCBbSVNULTNdKTogYSByYW5kb21p

c2VkIGNvbnRyb2xsZWQgdHJpYWw8L3RpdGxlPjxzZWNvbmRhcnktdGl0bGU+TGFuY2V0PC9zZWNv

bmRhcnktdGl0bGU+PC90aXRsZXM+PHBhZ2VzPjIzNTItNjM8L3BhZ2VzPjxudW1iZXI+OTgzNDwv

bnVtYmVyPjxjb250cmlidXRvcnM+PGF1dGhvcnM+PGF1dGhvcj5TYW5kZXJjb2NrLCBQLjwvYXV0

aG9yPjxhdXRob3I+V2FyZGxhdywgSi4gTS48L2F1dGhvcj48YXV0aG9yPkxpbmRsZXksIFIuIEku

PC9hdXRob3I+PGF1dGhvcj5EZW5uaXMsIE0uPC9hdXRob3I+PGF1dGhvcj5Db2hlbiwgRy48L2F1

dGhvcj48YXV0aG9yPk11cnJheSwgRy48L2F1dGhvcj48YXV0aG9yPklubmVzLCBLLjwvYXV0aG9y

PjxhdXRob3I+VmVuYWJsZXMsIEcuPC9hdXRob3I+PGF1dGhvcj5Demxvbmtvd3NrYSwgQS48L2F1

dGhvcj48YXV0aG9yPktvYmF5YXNoaSwgQS48L2F1dGhvcj48YXV0aG9yPlJpY2NpLCBTLjwvYXV0

aG9yPjxhdXRob3I+TXVycmF5LCBWLjwvYXV0aG9yPjxhdXRob3I+QmVyZ2UsIEUuPC9hdXRob3I+

PGF1dGhvcj5TbG90LCBLLiBCLjwvYXV0aG9yPjxhdXRob3I+SGFua2V5LCBHLiBKLjwvYXV0aG9y

PjxhdXRob3I+Q29ycmVpYSwgTS48L2F1dGhvcj48YXV0aG9yPlBlZXRlcnMsIEEuPC9hdXRob3I+

PGF1dGhvcj5NYXR6LCBLLjwvYXV0aG9yPjxhdXRob3I+THlyZXIsIFAuPC9hdXRob3I+PGF1dGhv

cj5HdWJpdHosIEcuPC9hdXRob3I+PGF1dGhvcj5QaGlsbGlwcywgUy4gSi48L2F1dGhvcj48YXV0

aG9yPkFyYXV6LCBBLjwvYXV0aG9yPjxhdXRob3I+SVNULTMgY29sbGFib3JhdGl2ZSBncm91cDwv

YXV0aG9yPjwvYXV0aG9ycz48L2NvbnRyaWJ1dG9ycz48bGFuZ3VhZ2U+ZW5nPC9sYW5ndWFnZT48

YWRkZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTM4NzU0NzU0MjwvYWRkZWQtZGF0ZT48cmVmLXR5cGUg

bmFtZT0iSm91cm5hbCBBcnRpY2xlIj4xNzwvcmVmLXR5cGU+PHJlYy1udW1iZXI+MzQ5PC9yZWMt

bnVtYmVyPjxsYXN0LXVwZGF0ZWQtZGF0ZSBmb3JtYXQ9InV0YyI+MTM4NzU0NzU0MjwvbGFzdC11

cGRhdGVkLWRhdGU+PGFjY2Vzc2lvbi1udW0+MjI2MzI5MDg8L2FjY2Vzc2lvbi1udW0+PGVsZWN0

cm9uaWMtcmVzb3VyY2UtbnVtPjEwLjEwMTYvUzAxNDAtNjczNigxMik2MDc2OC01PC9lbGVjdHJv

bmljLXJlc291cmNlLW51bT48dm9sdW1lPjM3OTwvdm9sdW1lPjwvcmVjb3JkPjwvQ2l0ZT48L0Vu

ZE5vdGU+AAA=

ADDIN EN.CITE.DATA 19 : primarily the UK Medical Research Council (MRC G0400069 and EME 09-800-15). We thank the IST-3 Investigators. Conflicts of interestNone declared.TablesTable 1: Sample characteristics of four validation studiesDrawing volume studiesOrdinal rating studiesCT only CT-MRI pairs Wahlund Scorevan Swieten ScoreN112060650196Population descriptionRandom selection of patients presenting to acute stroke ward; equal proportions of SVD severity: absent-mild/moderate/severeAll, unselected thrombolysed patients (+ CT-MRI pairs cohort)Random selection of participants from, thrombolysis trial IST-34Age (median, IQR)76 (66-85)76 (67-84)75 (63-82)82 (77-86)Male (%)52585445CT features:-- acute parenchymal Ischemia (%)1922360- old infarcts (%)38384259- central atrophy2 (%)72756787- peripheral atrophy2 (%)82877585- other lesions3 (%)6850Expert Raters (n) – pool number33613 – per scan33331 Numbers able to be processed by Auto WML quantification method (i.e. excluding image processing failures) 2 using atrophy grading system described in ADDIN EN.CITE <EndNote><Cite><Author>Farrell</Author><Year>2009</Year><IDText>Development and initial testing of normal reference MR images for the brain at ages 65-70 and 75-80 years</IDText><DisplayText><style face="superscript">33</style></DisplayText><record><dates><pub-dates><date>Jan</date></pub-dates><year>2009</year></dates><keywords><keyword>Aged</keyword><keyword>Aged, 80 and over</keyword><keyword>Aging</keyword><keyword>Atrophy</keyword><keyword>Brain</keyword><keyword>Female</keyword><keyword>Great Britain</keyword><keyword>Humans</keyword><keyword>Image Interpretation, Computer-Assisted</keyword><keyword>Magnetic Resonance Imaging</keyword><keyword>Male</keyword><keyword>Reference Values</keyword><keyword>Reproducibility of Results</keyword><keyword>Sensitivity and Specificity</keyword></keywords><urls><related-urls><url> and initial testing of normal reference MR images for the brain at ages 65-70 and 75-80 years</title><secondary-title>Eur Radiol</secondary-title></titles><pages>177-83</pages><number>1</number><contributors><authors><author>Farrell, C.</author><author>Chappell, F.</author><author>Armitage, P. A.</author><author>Keston, P.</author><author>Maclullich, A.</author><author>Shenkin, S.</author><author>Wardlaw, J. M.</author></authors></contributors><language>ENG</language><added-date format="utc">1478621838</added-date><ref-type name="Journal Article">17</ref-type><rec-number>541</rec-number><last-updated-date format="utc">1478621838</last-updated-date><accession-num>18690455</accession-num><electronic-resource-num>10.1007/s00330-008-1119-2</electronic-resource-num><volume>19</volume></record></Cite></EndNote>33. 3 e.g. hydrocephalus, arachnoid cyst, meningioma, aneurysm, haemorrhage. 4 patients with acute ischemic parenchymal changes were excluded in advanceTable 2: Correlations between expert drawing and Auto volumesStudyCorrelation of lesion volume between:-r2RangeCT onlyAuto versus consensus-Expert CT lesion volumes (mean of 3)0.7100.645-0.713*Expert CT drawings between themselves (x3)0.8450.813-0.867CT-MRI pairsAuto versus consensus-Expert MR lesion volumes (mean of 2) 0.8500.823-0.833*Expert CT drawings with Expert MRI drawings0.8190.767-0.856Expert MR drawings between each other (x2)0.937-*range here refers to Auto vs individual expert drawing volumes All correlations are significant at p<0.001Table 3: Agreements and correlations between expert scores and Auto scores or volumesStudyAgreement (weighted Kappa) of SVD score ratings between:-KwRangeWahlundScore (0-3) Experts amongst themselves (x6) [see Fig. 4A.]0.5060.473-0.552 Auto versus Experts (individuals)0.5290.465-0.579 Auto versus Expert (consensus) [see Fig. 4B.]0.5990.586-0.611Correlation of Expert SVD score rating and Auto volumer2 Expert individuals0.5060.462-0.549 Expert consensus0.582-Van Swieten Score (0-4)Agreement (weighted Kappa) of SVD score ratings between:-KwRange Experts amongst themselves (x3) [see Fig. 4C.]0.6650.648-0.674 Auto versus Experts (individuals)0.5710.534-0.597 Auto versus Expert (consensus) [see Fig. 4D.]0.6360.517-0.747Correlation of Expert SVD score rating and Auto volumer2 Expert individuals0.5710.522-0.614 Expert consensus0.629-FiguresFigure 1. Flow-chart of validation cohorts (A.), and image-processing (B.) stepsFigure 2. A : Correlations of Auto WML volumes with Expert drawings on CT. Each of three experts is indicated by a ‘X’, with a connected line showing range of expert values. B : Correlations of gold-standard WML volumes (expert drawings on FLAIR-MRI) with Auto-estimated volumes (blue squares), and expert drawings on CT (each of 3 experts marked by ‘X’; range shown by vertical line). Line of equality shown in each case, indicating that estimated WML volumes for any one patient tend be in order: Auto WML < expert CT WML < expert MRI WML.Figure 3: Examples of WML delineations by Auto method and Expert drawings (three colors represent specific experts’ annotations). The final column shows WML on co-registered FLAIRs, that were also delineated by experts (not shown here) and provided the ground-truth. Figure 4. Agreement plots of expert-expert and Auto-expert consensus for two WML scoring systems. Auto score based upon thresholding of Auto-delineated WML volumes26098560960Expert?Expert consensus?Expert?Expert?Auto?Auto?Van Swieten score?Expert?Expert consensus?Wahlund scoreA.B.C.D.00Expert?Expert consensus?Expert?Expert?Auto?Auto?Van Swieten score?Expert?Expert consensus?Wahlund scoreA.B.C.D.References ADDIN EN.REFLIST 1.Wardlaw JM, Smith EE, Biessels GJ, Cordonnier C, Fazekas F, Frayne R, et al. Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration. Lancet Neurol. 2013;12:822-8382.Rossi R, Joachim C, Geroldi C, Esiri MM, Smith AD, Frisoni GB. Pathological validation of a ct-based scale for subcortical vascular disease. The optima study. Dement Geriatr Cogn Disord. 2005;19:61-663.Sanossian N, Fu KA, Liebeskind DS, Starkman S, Hamilton S, Villablanca JP, et al. Utilization of emergent neuroimaging for thrombolysis-eligible stroke patients. J Neuroimaging. 20164.group I-c. Association between brain imaging signs, early and late outcomes, and response to intravenous alteplase after acute ischaemic stroke in the third international stroke trial (ist-3): Secondary analysis of a randomised controlled trial. Lancet Neurol. 2015;14:485-4965.Ryu WS, Woo SH, Schellingerhout D, Jang MU, Park KJ, Hong KS, et al. Stroke outcomes are worse with larger leukoaraiosis volumes. Brain. 2017;140:158-1706.Henninger N, Izzy S, Carandang R, Hall W, Muehlschlegel S. Severe leukoaraiosis portends a poor outcome after traumatic brain injury. Neurocrit Care. 2014;21:483-4957.Charidimou A, Pasi M, Fiorelli M, Shams S, von Kummer R, Pantoni L, et al. Leukoaraiosis, cerebral hemorrhage, and outcome after intravenous thrombolysis for acute ischemic stroke: A meta-analysis (v1). Stroke. 2016;47:2364-23728.Willer L, Havsteen I, Ovesen C, Christensen AF, Christensen H. Computed tomography--verified leukoaraiosis is a risk factor for post-thrombolytic hemorrhage. J Stroke Cerebrovasc Dis. 2015;24:1126-11309.Alachkar M. Neuroimaging in dementia: How best to use the guidelines? Psychiatr Bull (2014). 2014;38:137-13810.Kuruvilla T, Zheng R, Soden B, Greef S, Lyburn I. Neuroimaging in a memory assessment service: A completed audit cycle. Psychiatr Bull (2014). 2014;38:24-2811.Riello R, Albini C, Galluzzi S, Pasqualetti P, Frisoni GB. Prescription practices of diagnostic imaging in dementia: A survey of 47 alzheimer's centres in northern italy. Int J Geriatr Psychiatry. 2003;18:577-58512.Wahlund LO, Barkhof F, Fazekas F, Bronge L, Augustin M, Sj?gren M, et al. A new rating scale for age-related white matter changes applicable to mri and ct. Stroke. 2001;32:1318-132213.Simoni M, Li L, Paul NL, Gruter BE, Schulz UG, Küker W, et al. Age- and sex-specific rates of leukoaraiosis in tia and stroke patients: Population-based study. Neurology. 2012;79:1215-122214.Scheltens P, Erkinjunti T, Leys D, Wahlund LO, Inzitari D, del Ser T, et al. White matter changes on ct and mri: An overview of visual rating scales. European task force on age-related white matter changes. Eur Neurol. 1998;39:80-8915.van Swieten JC, Hijdra A, Koudstaal PJ, van Gijn J. Grading white matter lesions on ct and mri: A simple scale. J Neurol Neurosurg Psychiatry. 1990;53:1080-108316.Pantoni L, Simoni M, Pracucci G, Schmidt R, Barkhof F, Inzitari D. Visual rating scales for age-related white matter changes (leukoaraiosis): Can the heterogeneity be reduced? Stroke. 2002;33:2827-283317.Chen L, Tong T, Pang Ho C, Patel R, Cohen D, Dawson AC, et al. Identification of cerebral small vessel disease using multiple instance learning. Medical Image Computing and Computer-Assisted Intervention (MICCAI 2015). 2015;9349:523-53018.Maier O, Menze BH, von der Gablentz J, H?ni L, Heinrich MP, Liebrand M, et al. Isles 2015 - a public evaluation benchmark for ischemic stroke lesion segmentation from multispectral mri. Med Image Anal. 2017;35:250-26919.Sandercock P, Wardlaw JM, Lindley RI, Dennis M, Cohen G, Murray G, et al. The benefits and harms of intravenous thrombolysis with recombinant tissue plasminogen activator within 6 h of acute ischaemic stroke (the third international stroke trial [ist-3]): A randomised controlled trial. Lancet. 2012;379:2352-236320.Liaw A, Wiener M. Classification and regression by randomforest. R News. 2002;2/3:18-2221.Rueckert D, Sonoda LI, Hayes C, Hill DL, Leach MO, Hawkes DJ. Nonrigid registration using free-form deformations: Application to breast mr images. IEEE Trans Med Imaging. 1999;18:712-72122.Myers L, Sirois MJ. Spearman correlation coefficients, difference between. Encyclopedia of Statistical Sciences. 2006;1223.Ledig C, Shi W, Bai W, Rueckert D. Patch-based evaluation of image segmentation. Proceedings of CVPR. 2014:3065-307224.Ledig C, Heckemann RA, Hammers A, Lopez JC, Newcombe VF, Makropoulos A, et al. Robust whole-brain segmentation: Application to traumatic brain injury. Med Image Anal. 2015;21:40-5825.Vanbelle S, Albert A. A bootstrap method for comparing correlated kappa coefficients. Journal of Statistical Computation and Simulation. 2008;78:1009-101526.Galton F. Vox populi. Nature. 1907;75:450-45127.Gillebert CR, Humphreys GW, Mantini D. Automated delineation of stroke lesions using brain ct images. Neuroimage Clin. 2014;4:540-54828.Herweh C, Ringleb PA, Rauch G, Gerry S, Behrens L, M?hlenbruch M, et al. Performance of e-aspects software in comparison to that of stroke physicians on assessing ct scans of acute ischemic stroke patients. Int J Stroke. 2016;11:438-44529.Bentley P, Ganesalingam J, Carlton Jones AL, Mahady K, Epton S, Rinne P, et al. Prediction of stroke thrombolysis outcome using ct brain machine learning. Neuroimage Clin. 2014;4:635-64030.Whiteley WN, Slot KB, Fernandes P, Sandercock P, Wardlaw J. Risk factors for intracranial hemorrhage in acute ischemic stroke patients treated with recombinant tissue plasminogen activator: A systematic review and meta-analysis of 55 studies. Stroke. 2012;43:2904-290931.Smith EE, Rosand J, Knudsen KA, Hylek EM, Greenberg SM. Leukoaraiosis is associated with warfarin-related hemorrhage following ischemic stroke. Neurology. 2002;59:193-19732.Lou M, Al-Hazzani A, Goddeau RP, Novak V, Selim M. Relationship between white-matter hyperintensities and hematoma volume and growth in patients with intracerebral hemorrhage. Stroke. 2010;41:34-4033.Farrell C, Chappell F, Armitage PA, Keston P, Maclullich A, Shenkin S, et al. Development and initial testing of normal reference mr images for the brain at ages 65-70 and 75-80 years. Eur Radiol. 2009;19:177-183 ................
................

In order to avoid copyright disputes, this page is only a partial summary.

Google Online Preview   Download