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Utility and cost evaluation of multiparametric magnetic resonance imaging for the assessment of non-alcoholic fatty liver disease Running head: Evaluation of multiparametric MRI in NAFLDPeter J Eddowes*, Natasha McDonald*, Nigel Davies, Scott IK Semple, Timothy J Kendall, James Hodson, Phillip N Newsome, Robert B Flintham, Roman Wesolowski, Laurence Blake, Rui V Duarte, Catherine J Kelly, Amy H Herlihy, Matthew D Kelly, Simon P Olliff, Stefan G Hübscher, Jonathan A Fallowfield?, Gideon M Hirschfield1?.*Joint 1st authors?Joint senior authorsCentre for Liver Research and National Institute for Health Research Birmingham Biomedical Research Centre, University of Birmingham, Birmingham, UK and Institute of Translational Medicine, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.Corresponding authorProf. GM Hirschfield, Centre for Liver Research, University of Birmingham, Birmingham, B15 2TH, UK. E-mail: g.hirschfield@bham.ac.ukFinancial SupportThis work is supported by a grant from Innovate-UK (101679). The study sponsor was the University of Birmingham. Peter J Eddowes, Phillip N Newsome and Gideon M Hirschfield are supported by the National Institute of Health Research Birmingham Biomedical Research Centre. Jonathan A Fallowfield is supported by a NHS Research Scotland/Universities Senior Clinical Fellowship.This paper presents independent research supported by the National Institute for Health Research Birmingham Biomedical Research Centre. The views expressed are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health.DisclosuresThis is an academic led and reported study, with industry engagement. Funding for the project was from an Innovate-UK grant (101679). The role of Perspectum Diagnostics Ltd. was the provision of access to LiverMultiscanTM and blinded analysis of raw MRI data. All study investigations and data analysis was performed by the academic centres. Peter J Eddowes, Natasha McDonald, Nigel Davies, Scott IK Semple, Robert B Flintham, Roman Wesolowski, Laurence Blake, Rui V Duarte, Timothy J Kendall, James Hodson, Simon P Olliff, Stefan G Hübscher, Jonathan A Fallowfield and Gideon M Hirschfield have no relevant conflict of interest to declare. Philip N Newsome has consulted for EchoSens and was a member of the National Institute for Health and Clinical Excellence NAFLD guidelines committee. Catherine J Kelly, Amy H Herlihy and Matthew D Kelly are employees of Perspectum Diagnostics Limited, the developer of LiverMultiscanTM. AcknowledgementsProfessor Gideon Hirschfield is the guarantor for this workPeter J Eddowes wrote the study protocol, collected data, analysed data and wrote the manuscript. Natasha McDonald was involved in the design of the study, collected data and provided critical review of the manuscript. Nigel Davies, Scott IK Semple, Robert B Flintham and Roman Wesolowski were involved in study design and development of the MRI protocol. Timothy J Kendall and Stefan G Hübscher were involved in study design and analysed pathology specimens. James Hodson was the study statistician. Phillip N Newsome was involved in protocol design and?critical review of the manuscript. Laurence Blake and Rui V Duarte performed the cost analysis. Catherine J Kelly, Amy H Herlihy and Matthew D Kelly analysed MRI data. Simon P Olliff provided MRI safety reporting. Jonathan A Fallowfield and Gideon M Hirschfield devised the study, were involved in study design and critical review of the manuscript.All authors have reviewed and approved the final version of the manuscript.We are grateful to Professor Stefan Neubauer (University of Oxford and Perspectum Diagnostics Limited) for critical review of the manuscript and contribution to the award, and delivery of the Innovate-UK grant (101679).AbstractBackground: Validated diagnostic tools that are accurate, cost effective and acceptable to patients are required for disease stratification and monitoring in NAFLD. Aims: We investigated the performance and cost of multiparametric MRI alongside existing biomarkers in the assessment of NAFLD.Methods: Adult patients undergoing standard of care liver biopsy for NAFLD were prospectively recruited at two UK liver centres and underwent multiparametric MRI, blood sampling and transient elastography withing 2 weeks of liver biopsy. Non-invasive markers were compared to histology as the gold standard. Results: Data were obtained in 50 patients and 6 healthy volunteers. Corrected T1 (cT1) correlated with NAFLD activity score (Rho=0.514, p<0.001). cT1, enhanced liver fibrosis (ELF) test and liver stiffness differentiated patients with simple steatosis and NASH with AUROC (95% CI) of 0.69 (0.50-0.88), 0.87 (0.77-0.79) and 0.82 (0.70-0.94) respectively and healthy volunteers from patients with AUROC (95% CI) of 0.93 (0.86-1.00), 0.81 (0.69-0.92) and 0.89 (0.77-1.00) respectively. For the risk stratification of NAFLD, multiparametric MRI could save ?150,218.00 per 1000 patients compared to biopsy. Multiparametric MRI did not discriminate between individual histological fibrosis stages in this population (p=0.068).Conclusions: Multiparametric MRI accurately identified patients with steatosis, stratifies those with NASH or simple steatosis and reliably excludes clinically significant liver disease with superior negative predictive value (83.3%) to liver stiffness (42.9%) and ELF (57.1%). For the risk stratification of NAFLD multiparametric MRI was cost effective and, combined with transient elastography, had the lowest cost per correct diagnosis.Keywords: Non-alcoholic fatty liver disease; non-alcoholic steatohepatitis; hepatic fibrosis; magnetic resonance T1 mapping, cost effectiveness. IntroductionNon-alcoholic fatty liver disease (NAFLD) is an important and growing clinical concern associated with the increasing prevalence of obesity, type 2 diabetes, hypertension and dyslipidaemia. With the global prevalence of NAFLD estimated at 25.24%, ADDIN EN.CITE <EndNote><Cite><Author>Younossi</Author><Year>2016</Year><RecNum>1422</RecNum><DisplayText><style face="superscript">1</style></DisplayText><record><rec-number>1422</rec-number><foreign-keys><key app="EN" db-id="afxe29afq2sd5deff94p5ttttxser00ffrr2" timestamp="1469451689">1422</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Younossi, Z. M.</author><author>Koenig, A. B.</author><author>Abdelatif, D.</author><author>Fazel, Y.</author><author>Henry, L.</author><author>Wymer, M.</author></authors></contributors><auth-address>Center For Liver Disease, Department of Medicine, Inova Fairfax Hospital, Falls Church, VA.
Betty and Guy Beatty Center for Integrated Research, Inova Health System, Falls Church, VA.
Center for Outcomes Research in Liver Disease, Washington, DC.</auth-address><titles><title>Global epidemiology of nonalcoholic fatty liver disease-Meta-analytic assessment of prevalence, incidence, and outcomes</title><secondary-title>Hepatology</secondary-title><alt-title>Hepatology (Baltimore, Md.)</alt-title></titles><periodical><full-title>Hepatology</full-title><abbr-1>Hepatology</abbr-1></periodical><alt-periodical><full-title>Hepatology (Baltimore, Md.)</full-title></alt-periodical><pages>73-84</pages><volume>64</volume><number>1</number><edition>2015/12/29</edition><dates><year>2016</year><pub-dates><date>Jul</date></pub-dates></dates><isbn>0270-9139</isbn><accession-num>26707365</accession-num><urls><related-urls><url> effective strategies are required to ensure optimal risk stratification of patients in order that appropriate treatment is both offered and developed. As an umbrella term, NAFLD encompasses two main clinico-pathological entities: simple steatosis and non-alcoholic steatohepatitis (NASH). These conditions have distinct clinical significance and prognosis. Simple steatosis indicates hepatic steatosis without inflammation and whilst simple steatosis has been shown to increase mortality from cardiovascular disease, natural history studies indicate that simple steatosis leads to little or no progression of fibrosis and no increase in liver related mortality.PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5EYW0tTGFyc2VuPC9BdXRob3I+PFllYXI+MjAwNDwvWWVh
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ADDIN EN.CITE.DATA 2, 3 In contrast, NASH is characterised histologically by hepatocyte ballooning and lobular inflammation, culminates in cirrhosis in up to 20% ADDIN EN.CITE <EndNote><Cite><Author>McCullough</Author><Year>2004</Year><RecNum>1255</RecNum><DisplayText><style face="superscript">4</style></DisplayText><record><rec-number>1255</rec-number><foreign-keys><key app="EN" db-id="afxe29afq2sd5deff94p5ttttxser00ffrr2" timestamp="1460468659">1255</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>McCullough, A. J.</author></authors></contributors><auth-address>Case Western Reserve University, 2500 Metro Health Drive, Cleveland, OH 44109, USA.</auth-address><titles><title>The clinical features, diagnosis and natural history of nonalcoholic fatty liver disease</title><secondary-title>Clin Liver Dis</secondary-title><alt-title>Clinics in liver disease</alt-title></titles><periodical><full-title>Clin Liver Dis</full-title><abbr-1>Clinics in liver disease</abbr-1></periodical><alt-periodical><full-title>Clin Liver Dis</full-title><abbr-1>Clinics in liver disease</abbr-1></alt-periodical><pages>521-33, viii</pages><volume>8</volume><number>3</number><edition>2004/08/28</edition><keywords><keyword>Adult</keyword><keyword>Diabetes Mellitus, Type 2/complications/pathology</keyword><keyword>Diagnosis, Differential</keyword><keyword>Disease Progression</keyword><keyword>Fatty Liver/complications/diagnosis/*pathology</keyword><keyword>Female</keyword><keyword>Humans</keyword><keyword>Male</keyword><keyword>Middle Aged</keyword><keyword>Obesity/complications/pathology</keyword></keywords><dates><year>2004</year><pub-dates><date>Aug</date></pub-dates></dates><isbn>1089-3261 (Print)
1089-3261</isbn><accession-num>15331061</accession-num><urls><related-urls><url> and carries a hepatocellular carcinoma risk of 5.29 cases per 1,000 person years. ADDIN EN.CITE <EndNote><Cite><Author>Younossi</Author><Year>2016</Year><RecNum>1422</RecNum><DisplayText><style face="superscript">1</style></DisplayText><record><rec-number>1422</rec-number><foreign-keys><key app="EN" db-id="afxe29afq2sd5deff94p5ttttxser00ffrr2" timestamp="1469451689">1422</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Younossi, Z. M.</author><author>Koenig, A. B.</author><author>Abdelatif, D.</author><author>Fazel, Y.</author><author>Henry, L.</author><author>Wymer, M.</author></authors></contributors><auth-address>Center For Liver Disease, Department of Medicine, Inova Fairfax Hospital, Falls Church, VA.
Betty and Guy Beatty Center for Integrated Research, Inova Health System, Falls Church, VA.
Center for Outcomes Research in Liver Disease, Washington, DC.</auth-address><titles><title>Global epidemiology of nonalcoholic fatty liver disease-Meta-analytic assessment of prevalence, incidence, and outcomes</title><secondary-title>Hepatology</secondary-title><alt-title>Hepatology (Baltimore, Md.)</alt-title></titles><periodical><full-title>Hepatology</full-title><abbr-1>Hepatology</abbr-1></periodical><alt-periodical><full-title>Hepatology (Baltimore, Md.)</full-title></alt-periodical><pages>73-84</pages><volume>64</volume><number>1</number><edition>2015/12/29</edition><dates><year>2016</year><pub-dates><date>Jul</date></pub-dates></dates><isbn>0270-9139</isbn><accession-num>26707365</accession-num><urls><related-urls><url> majority of liver related morbidity and mortality in NAFLD is secondary to the complications of advanced fibrosis and fibrosis stage predicts clinical outcome.PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5Bbmd1bG88L0F1dGhvcj48WWVhcj4yMDE1PC9ZZWFyPjxS
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ADDIN EN.CITE.DATA 5-7 This offers valuable prognostic information to patients and their clinicians. In addition to fibrosis staging, distinguishing between simple steatosis and NASH is highly relevant for risk stratification in clinical practice and the enrichment of interventional trial populations. Presently, the staging of NAFLD is largely dependent on interpretation of liver biopsy specimens, with the inherent challenges of procedural complications, cost, patient acceptability and sampling error.PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5OYWxiYW50b2dsdTwvQXV0aG9yPjxZZWFyPjIwMTQ8L1ll
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ADDIN EN.CITE.DATA 11 Many of these non-invasive techniques have acquired a role in routine clinical practice. To date for example, National Institute for Health and Clinical Excellence guidance for NAFLD recommends ELF as a risk stratification tool, and in the National Institute for Health and Clinical Excellence guidance on cirrhosis; transient elastography is recommended for staging of fibrosis. ADDIN EN.CITE <EndNote><Cite><Year>2016</Year><RecNum>1389</RecNum><DisplayText><style face="superscript">12, 13</style></DisplayText><record><rec-number>1389</rec-number><foreign-keys><key app="EN" db-id="afxe29afq2sd5deff94p5ttttxser00ffrr2" timestamp="1468851745">1389</key><key app="ENWeb" db-id="">0</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors></contributors><titles><title>National Institute for Health and Care Excellence. Nonalcoholic fatty liver disease (NAFLD): assessment and management</title><secondary-title>NICE guidelines (NG49)</secondary-title><short-title>NG49</short-title></titles><periodical><full-title>NICE guidelines (NG49)</full-title></periodical><dates><year>2016</year><pub-dates><date>6/7/16</date></pub-dates></dates><publisher>National Institute for Health and Care Excellence</publisher><work-type>NICE guideline</work-type><urls></urls></record></Cite><Cite><Year>2016</Year><RecNum>1450</RecNum><record><rec-number>1450</rec-number><foreign-keys><key app="EN" db-id="afxe29afq2sd5deff94p5ttttxser00ffrr2" timestamp="1474402167">1450</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors></contributors><titles><title>National Institute for Health and Care Excellence. Cirrhosis in over 16s: assessment and management</title><secondary-title>NICE guidelines (NG50)</secondary-title><short-title>NG50</short-title></titles><periodical><full-title>NICE guidelines (NG50)</full-title></periodical><dates><year>2016</year></dates><work-type>NICE Guideline</work-type><urls></urls></record></Cite></EndNote>12, 13 As diagnostic tests evolve and clinical and trial strategies change, comparative evaluation of novel technologies is critically important for users. We sought to determine how a novel quantitative liver MRI technology performed in terms of utility and comparative effectiveness, in the assessment of a prospective cohort of patients with NAFLD having routine liver biopsy as standard of care. We subsequently used the data to assess the potential cost effectiveness of this technique to understand whether this added investigation would reduce the cost burden of liver biopsy. Our study was an academic led, funded, and delivered evaluation of a proprietary algorithm - LiverMultiscan? (Perspectum Diagnostics Ltd. Oxford, UK), a multiparametric MRI technology used to quantify liver fat, iron and fibro-inflammatory injury by proton density fat fraction, T2* mapping and corrected T1 (cT1) ADDIN EN.CITE <EndNote><Cite><Author>Banerjee</Author><Year>2014</Year><RecNum>470</RecNum><DisplayText><style face="superscript">14</style></DisplayText><record><rec-number>470</rec-number><foreign-keys><key app="EN" db-id="afxe29afq2sd5deff94p5ttttxser00ffrr2" timestamp="1444924682">470</key></foreign-keys><ref-type name="Patent">25</ref-type><contributors><authors><author>Banerjee, R.</author><author>Piechnik, S.</author><author>Robson, M.</author><author>Rial, B.</author><author>Tunnicliffe, E.</author><author>Neubauer, S.</author></authors></contributors><titles><title>Multi-Parametric Magnetic Resonance Diagnosis & Staging of Liver Disease (US2014330106)</title></titles><num-vols>US2014330106</num-vols><section>WO2013088149 A1</section><dates><year>2014</year></dates><urls></urls></record></Cite></EndNote>14 mapping, respectively. T1 as a biomarker of hepatic fibrosis is confounded by hepatic siderosis. cT1 uses a measurement of iron content (T2*) and a patented algorithm to correct for this confounding.PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5CYW5lcmplZTwvQXV0aG9yPjxZZWFyPjIwMTQ8L1llYXI+
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ADDIN EN.CITE.DATA 11 The proton density fat fraction measured using a modified Dixon sequence is a well-established and accurate technique for the assessment of hepatic fat content.PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5Ob3VyZWRkaW48L0F1dGhvcj48WWVhcj4yMDEzPC9ZZWFy
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ADDIN EN.CITE.DATA 15-17 Iron concentration was estimated from T2* according to a previously determined model. ADDIN EN.CITE <EndNote><Cite><Author>St Pierre</Author><Year>2005</Year><RecNum>0</RecNum><IDText>Noninvasive measurement and imaging of liver iron concentrations using proton magnetic resonance</IDText><DisplayText><style face="superscript">18</style></DisplayText><record><ref-type name="Journal Article">17</ref-type><contributors><authors><author>St Pierre, T G</author><author>Clark, P W</author><author>Chua-anusorn, W</author><author>Fleming, A J</author><author>Jeffrey, G P</author><author>Olynyk, J K</author><author>Pootrakul, P</author><author>Robins, E</author><author>Lindeman, R</author></authors></contributors><titles><title>Noninvasive measurement and imaging of liver iron concentrations using proton magnetic resonance</title><secondary-title>Blood</secondary-title></titles><dates><year>2005</year></dates><pages>855</pages><volume>105</volume><number>2</number></record></Cite></EndNote>18 We report our comparative evaluation of the ability of this quantitative MRI technology to identify patients with hepatic steatosis, differentiate those with simple steatosis from those with NASH, grade disease activity and stage hepatic fibrosis. We demonstrate maximal utility in the ability of multiparametric MRI to distinguish between patients at low risk and those at high risk of progressive disease.MethodsStudy ParticipantsOur prospective study was undertaken at the Queen Elizabeth Hospital Birmingham and Royal Infirmary of Edinburgh between February 2014 and September 2015. The study protocol conformed to the ethical guidelines of the 1975 Declaration of Helsinki, and was approved by the National Research Ethics Service (West Midlands – The Black Country; Ref: 14/WM/0010). The study was registered with the International Standard Randomised Controlled Trial Number registry (ISRCTN39463479) and the National Institute of Health Research portfolio (15912). The study sponsor was the University of Birmingham. Male and female adult (≥18 years of age) patients booked for non-targeted liver biopsy for any indication were prospectively recruited to a validation study of LiverMultiScan? ( currently being prepared for publication). Patients with a histologically confirmed diagnosis of NAFLD without secondary cause and without history of alcohol excess (men >21 UK units/week, women >14 UK units/week) were included in this sub-group analysis. Data on the indication for biopsy are included in the supplementary material. Exclusion criteria were: biopsy of a distinct focal lesion, inability to give fully informed consent and any contraindication to MRI.Healthy volunteers were recruited from staff and students at the University of Birmingham. Exclusion criteria were obesity (Body mass index (BMI) >30kg/m2), current or previous history of liver disease, significant medical co-morbidity, family history of liver disease, excess alcohol intake or any contraindication to MRI. All participants gave written, informed consent and attended for a single study visit during which they underwent multiparametric MRI, transient elastography with FibroScanTM (Echosens, Paris, France), blood sampling and collection of clinical and demographic data. All study investigations were performed after a 4 hour fast. Patients undertook their study visit in the 2 weeks prior to liver biopsy and healthy volunteers did not undergo liver biopsy.Study InvestigationsAll MRI scans were performed at 3.0 Tesla on Siemens Verio MRI scanners (Siemens Healthcare GMBH, Erlangen, Germany). The MRI protocol does not require intravenous contrast and has been previously described.PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5CYW5lcmplZTwvQXV0aG9yPjxZZWFyPjIwMTQ8L1llYXI+
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ADDIN EN.CITE.DATA 11 In brief, the participant lies supine with 3-lead ECG for cardiac gating. A combination of body matrix and spine matrix coil elements was used to acquire data. Following localisers and shimming, the sequences include: shortened modified Look Locker inversion (ShMOLLI) recovery sequence (T1 mapping), multi-gradient-echo sequence (T2* mapping), modified Dixon sequence and proton magnetic resonance spectroscopy with the Stimulated Echo Acquisition Mode sequence. All data were acquired during diastole with breath held in expiration to minimise movement artefact. Maps were acquired in a transverse plane through the liver hilum using the same slice position for each sequence. The voxel for magnetic resonance spectroscopy was placed in the right lobe of the liver avoiding biliary and vascular structures. Details of the MRI sequence parameters are contained in the supplementary material. Due to an error in the MRI acquisition protocol, proton density fat fraction as measured by the Dixon sequence (PDFF-Dixon) could not be calculated for the first 12 data sets. At this point the error was identified and corrected. PDFF-Dixon was calculated reliably for the remaining participants.Transient elastography was performed by trained operators (PJE and NM) in accordance with manufacturer’s guidelines and validated local clinical practice.PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5Bcm1zdHJvbmc8L0F1dGhvcj48WWVhcj4yMDEzPC9ZZWFy
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ADDIN EN.CITE.DATA 19 The decision on using the M probe or XL probe was made by the automated probe selection tool incorporated into the FibroScanTM machine. Examinations were regarded as ‘possible’ if at least 10 valid readings could be recorded and ‘reliable’ if they contained at least 10 valid readings and had interquartile range (IQR) to median ratio ≤30% (Boursier’s criteria). ADDIN EN.CITE <EndNote><Cite><Author>Boursier</Author><Year>2013</Year><RecNum>1212</RecNum><DisplayText><style face="superscript">20</style></DisplayText><record><rec-number>1212</rec-number><foreign-keys><key app="EN" db-id="afxe29afq2sd5deff94p5ttttxser00ffrr2" timestamp="1447932343">1212</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Boursier, Jér?me</author><author>Zarski, Jean-Pierre</author><author>de Ledinghen, Victor</author><author>Rousselet, Marie-Christine</author><author>Sturm, Nathalie</author><author>Lebail, Brigitte</author><author>Fouchard-Hubert, Isabelle</author><author>Gallois, Yves</author><author>Oberti, Frédéric</author><author>Bertrais, Sandrine</author><author>Calès, Paul</author><author>the Multicentric Group from, Anrs H. C. E. P. Fibrostar Studies</author></authors></contributors><titles><title>Determination of reliability criteria for liver stiffness evaluation by transient elastography</title><secondary-title>Hepatology</secondary-title></titles><periodical><full-title>Hepatology</full-title><abbr-1>Hepatology</abbr-1></periodical><pages>1182-1191</pages><volume>57</volume><number>3</number><dates><year>2013</year></dates><publisher>Wiley Subscription Services, Inc., A Wiley Company</publisher><isbn>1527-3350</isbn><urls><related-urls><url> At the start of the study the Controlled Attenuation Parameter was not available on the FibroScanTM XL probe. Controlled Attenuation Parameter on the XL probe was enabled during study recruitment so was recorded if available in addition to median liver stiffness.Blood samples were analysed routinely for markers of liver disease. Simple blood biomarker panels including aspartate aminotransferase/alanine aminotransferase (AST/ALT) ratio, Fibrosis-4 (FIB-4) and NAFLD fibrosis score were calculated according to published formulae.PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5TdGVybGluZzwvQXV0aG9yPjxZZWFyPjIwMDY8L1llYXI+
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ADDIN EN.CITE.DATA 21, 22 Serum was also analysed to determine the enhanced liver fibrosis (ELF) score.MRI data analysis and iron correctionT1, T2* and PDFF-Dixon maps were analysed using LiverMultiscanTM software by a single operator (AHH) blinded to the clinical findings and biopsy results. A user defined region of interest of approximately 1.4cm3 was placed in a representative area of the right lobe of the liver avoiding vascular and biliary structures on the T1, T2* and PDFF-Dixon maps. LiverMultiscanTM software then calculates a corrected T1 value (cT1). Magnetic resonance spectroscopy data were analysed by a single operator (RBF) blinded to the histology results. Proton density fat fraction measured with magnetic resonance spectroscopy (PDFF-MRS) was calculated from the non-water-suppressed Stimulated Echo Acquisition Mode acquisition (5 measurements of 1 signal average) using totally automatic robust quantitation in nuclear magnetic resonance (TARQUIN) software to perform automated preprocessing and fitting of the fat/liver spectrum. ADDIN EN.CITE <EndNote><Cite><Author>Wilson</Author><Year>2011</Year><RecNum>1447</RecNum><DisplayText><style face="superscript">23</style></DisplayText><record><rec-number>1447</rec-number><foreign-keys><key app="EN" db-id="afxe29afq2sd5deff94p5ttttxser00ffrr2" timestamp="1470316182">1447</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Wilson, Martin</author><author>Reynolds, Greg</author><author>Kauppinen, Risto A.</author><author>Arvanitis, Theodoros N.</author><author>Peet, Andrew C.</author></authors></contributors><titles><title>A constrained least-squares approach to the automated quantitation of in vivo 1H magnetic resonance spectroscopy data</title><secondary-title>Magnetic Resonance in Medicine</secondary-title></titles><periodical><full-title>Magnetic Resonance in Medicine</full-title></periodical><pages>1-12</pages><volume>65</volume><number>1</number><keywords><keyword>magnetic resonance spectroscopy</keyword><keyword>quantitation</keyword><keyword>brain</keyword><keyword>tumor</keyword></keywords><dates><year>2011</year></dates><publisher>Wiley Subscription Services, Inc., A Wiley Company</publisher><isbn>1522-2594</isbn><urls><related-urls><url> Visual quality control of fitted spectra was performed by a medical physicist with experience of in vivo Magnetic resonance spectroscopy. Poorly fitted spectra were excluded from the analysis. PDFF-MRS was defined by the equation:PDFF-MRS=area under methylene 1.3ppm peak area under methylene 1.3ppm peak + area under water peaksHistological assessmentLiver biopsy samples were taken with 16-gauge biopsy needles. Histology was assessed by experienced academic liver histopathologists blinded to the MRI, ELF and transient elastography findings. Biopsies that were less than 15 mm in length or that contained fewer than 11 portal tracts were regarded as inadequate for histological assessment and were therefore excluded.PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XeWF0dDwvQXV0aG9yPjxZZWFyPjIwMTQ8L1llYXI+PFJl
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ADDIN EN.CITE.DATA 26, 27 and siderosis according the Scheuer grading system. ADDIN EN.CITE <EndNote><Cite><Author>Scheuer</Author><Year>1962</Year><RecNum>197</RecNum><DisplayText><style face="superscript">28</style></DisplayText><record><rec-number>197</rec-number><foreign-keys><key app="EN" db-id="afxe29afq2sd5deff94p5ttttxser00ffrr2" timestamp="1379411673">197</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Scheuer, P. J.</author><author>Williams, R.</author><author>Muir, A. R.</author></authors></contributors><titles><title>Hepatic pathology in relatives of patients with haemochromatosis</title><secondary-title>J Pathol Bacteriol</secondary-title><alt-title>The Journal of pathology and bacteriology</alt-title></titles><periodical><full-title>J Pathol Bacteriol</full-title><abbr-1>The Journal of pathology and bacteriology</abbr-1></periodical><alt-periodical><full-title>J Pathol Bacteriol</full-title><abbr-1>The Journal of pathology and bacteriology</abbr-1></alt-periodical><pages>53-64</pages><volume>84</volume><edition>1962/07/01</edition><keywords><keyword>Liver/*pathology</keyword></keywords><dates><year>1962</year><pub-dates><date>Jul</date></pub-dates></dates><isbn>0368-3494 (Print)
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ADDIN EN.CITE.DATA 30Statistical analysisStatistical analysis was carried out using IBM SPSS Statistics for Windows version 22 (IBM Corp, Armonk, NY). Variables are summarised with mean ± standard deviation (SD) if normally distributed and with median and range if not normally distributed. Comparisons between patients and healthy volunteers were performed using independent samples t-tests, Mann-Whitney tests, or Fisher’s exact tests, as applicable. Correlation between continuous variables was determined with Spearman’s correlation coefficient (Rho). Comparisons across variables with multiple groups were performed using Kruskal-Wallis tests for nominal variables, or Jonckheere–Terpstra tests for ordinal variables. Post-hoc pairwise comparisons between groups were performed using Dunn’s test. Diagnostic performance was compared by calculation of the receiver operating characteristic and determination of the area under the curve (AUROC) with 95% confidence intervals (CI). For all tests, a p-value <0.05 was taken to indicate statistical significance. Decision analytic modelA recent study investigated the potential cost savings of adding multi-parametric MRI to the NAFLD risk stratification pathway. ADDIN EN.CITE <EndNote><Cite><Author>Blake</Author><Year>2016</Year><RecNum>1577</RecNum><DisplayText><style face="superscript">31</style></DisplayText><record><rec-number>1577</rec-number><foreign-keys><key app="EN" db-id="afxe29afq2sd5deff94p5ttttxser00ffrr2" timestamp="1492898561">1577</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Blake, Laurence</author><author>Duarte, Rui V</author><author>Cummins, Carole</author></authors></contributors><titles><title>Decision analytic model of the diagnostic pathways for patients with suspected non-alcoholic fatty liver disease using non-invasive transient elastography and multiparametric magnetic resonance imaging</title><secondary-title>BMJ Open</secondary-title></titles><periodical><full-title>BMJ Open</full-title></periodical><volume>6</volume><number>9</number><dates><year>2016</year></dates><urls><related-urls><url> A decision tree model was developed to compare the expected outcomes and costs associated with three potential risk stratification pathways for NAFLD: using transient elastography alone, using multiparametric MRI as an adjunct to transient elastography, and using multiparametric MRI alone. We repeated this analysis, using the data collected from our study, based on the risk stratification pathways detailed in supplementary figure 1. For each risk stratification pathway, failure rates of transient elastography and MRI were used as reported in the previous study ADDIN EN.CITE <EndNote><Cite><Author>Blake</Author><Year>2016</Year><RecNum>1577</RecNum><DisplayText><style face="superscript">31</style></DisplayText><record><rec-number>1577</rec-number><foreign-keys><key app="EN" db-id="afxe29afq2sd5deff94p5ttttxser00ffrr2" timestamp="1492898561">1577</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Blake, Laurence</author><author>Duarte, Rui V</author><author>Cummins, Carole</author></authors></contributors><titles><title>Decision analytic model of the diagnostic pathways for patients with suspected non-alcoholic fatty liver disease using non-invasive transient elastography and multiparametric magnetic resonance imaging</title><secondary-title>BMJ Open</secondary-title></titles><periodical><full-title>BMJ Open</full-title></periodical><volume>6</volume><number>9</number><dates><year>2016</year></dates><urls><related-urls><url> and we presumed the failure rate of ELF to be negligible at 0%. Using the prevalence of NAFLD in the previous study cohort (58.8%) and the sensitivities and specificities of each test derived in this study ( REF _Ref494747961 Table 8), the proportions of patients that would have been correctly and incorrectly stratified were then calculated for each pathway. The expected test results were used to estimate the number of biopsies that would have been performed for a cohort of 1,000 patients. The total cost of each pathway was then evaluated, by adding together the costs of the tests and biopsies (based on NHS tariff data contained in the recent National Institute for Health and Clinical Excellence guidelines ADDIN EN.CITE <EndNote><Cite><Year>2016</Year><RecNum>1389</RecNum><DisplayText><style face="superscript">12</style></DisplayText><record><rec-number>1389</rec-number><foreign-keys><key app="EN" db-id="afxe29afq2sd5deff94p5ttttxser00ffrr2" timestamp="1468851745">1389</key><key app="ENWeb" db-id="">0</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors></contributors><titles><title>National Institute for Health and Care Excellence. Nonalcoholic fatty liver disease (NAFLD): assessment and management</title><secondary-title>NICE guidelines (NG49)</secondary-title><short-title>NG49</short-title></titles><periodical><full-title>NICE guidelines (NG49)</full-title></periodical><dates><year>2016</year><pub-dates><date>6/7/16</date></pub-dates></dates><publisher>National Institute for Health and Care Excellence</publisher><work-type>NICE guideline</work-type><urls></urls></record></Cite></EndNote>12) that would have been required per 1,000 patients. This was then subtracted from the total cost that would result from performing biopsies on all patients, in order to estimate the cost savings of each pathway. The resulting value was divided by the number of correct diagnoses, in order to estimate the cost per correct diagnosis, which could then be compared to the cost of a biopsy.ResultsPatient demographicsOf 54 patients with NAFLD recruited into the study (whole study included 162 unselected liver biopsies) 50 had sufficient data for analysis. Three MRI data sets were unusable and 1 biopsy was judged too small for reliable fibrosis assessment and so these 4 patients were excluded. Seven healthy volunteers were recruited. One healthy volunteer was subsequently excluded from analysis due to the discovery of abnormal liver biochemistry. The study flow chart is shown in supplementary figure 2. The characteristics of the 50 patients and 6 healthy volunteers are outlined in REF _Ref494748003 Table 1. Comparisons between these groups found that the healthy volunteers were significantly younger (median 32 vs. 54 years, p=0.011), had significantly lower BMI and lower waist to hip ratio. 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ADDIN EN.CITE.DATA 20 Non-reliable transient elastography examinations were excluded from further analysis. In 16/47 (34%) patients, transient elastography was measured with the M probe and the remainder with the XL probe. For all healthy volunteers, transient elastography was measured with the M probe and was reliable by Boursier’s criteria. Median (range) length of liver biopsy samples was 25 (15-50) mm. Median (range) collagen proportionate area was 5.3 (0.6-34.2) %. Collagen proportionate area correlated strongly with Kleiner fibrosis stage (p<0.001) (supplementary figure 3). The characteristics of the histology and distribution of fibrosis stages in the cohort are shown in REF _Ref494748023 Table 2. Twelve (24%) of the patients had simple steatosis and 38 (76%) had NASH. Grading of steatosis by multiparametric MRIPDFF-Dixon data was available for 38/50 (76%) patients and all healthy volunteers. Median PDFF-Dixon for healthy volunteers, grade 1, grade 2 and grade 3 steatosis were 1.8, 6.6, 15.3 and 21.4% respectively (p<0.001) ( REF _Ref494748555 Figure 1A). PDFF-MRS was available for 43/50 (86%) patients and 5/6 (83%) healthy volunteers. Median PDFF-MRS for volunteers, grade 1, grade 2 and grade 3 steatosis were 0.3, 11.3, 23.7, and 31.5% respectively (p<0.001) ( REF _Ref494748555 Figure 1B). AUROC (95% CI) for the identification of steatosis (Brunt grade ≥1) for both PDFF-Dixon and PDFF-MRS was 1.00 (1.00-1.00).Controlled Attenuation Parameter was available in 24/50 (48%) patients and all healthy volunteers. Median Controlled Attenuation Parameter for healthy volunteers, grade 1, grade 2 and grade 3 steatosis were 246, 331, 361, 344 dB/m respectively (p=0.002) ( REF _Ref494748555 Figure 1C). AUROC (95% CI) for Controlled Attenuation Parameter for the identification of steatosis (Brunt grade ≥1) was 0.95 (0.87-1.00).Differentiation between NASH and simple steatosis by cT1 measurementDemographic characteristics and blood results presented in REF _Ref494748043 Table 3 showed no significant difference between patients with NASH and those with simple steatosis. cT1 showed a significant difference between simple steatosis and NASH and, although not validated for this purpose, liver stiffness and ELF also showed significant differences between patients with simple steatosis and those with NASH ( REF _Ref494748070 Table 4). Whilst multiparametric MRI did differentiate between NASH and simple steatosis, the AUROC (95% CI) for cT1 0.69 (0.50-0.88) was inferior to ELF 0.87 (0.77-0.79) and liver stiffness 0.82 (0.70-0.94) ( REF _Ref494748646 Figure 2).Grading of disease activity by cT1 measurement In patients with NAFLD, semi-quantitative assessment of hepatocyte ballooning showed a statistically significant correlation with cT1, liver stiffness, and ELF. Lobular inflammation was significantly correlated with liver stiffness and ELF but not cT1. Overall assessment of disease activity (as defined by the total NAFLD activity score) showed significant correlation with cT1, liver stiffness and ELF . The strength of these correlations can be seen in REF _Ref494750387 Table 5 and graphically in REF _Ref494748662 Figure 3 with p-values from the Jonckheere–Terpstra test. AUROC (95% CI) to differentiate those with NAFLD activity score <5 and NAFLD activity score ≥5 was statistically significant for cT1, liver stiffness, ELF and FIB-4, 0.74 (0.59-0.88), 0.74 (0.59-0.89), 0.74 (0.59-0.89) and 0.73 (0.58-0.88) respectively. Statistical significance was not reached by AST:ALT ratio and NAFLD fibrosis score 0.60 (0.43-0.77) and 0.63 (0.47-0.77), respectively.Staging of liver fibrosis by cT1 measurementMean (±SD) cT1 for healthy volunteers was 791 (±42) ms. For patients with NAFLD with F0, F1, F2, F3 and F4 fibrosis mean (±SD) cT1 was 882 (±141), 969 (±115), 985(±93), 1016 (±97) and 997 (±86) ms respectively as can be seen in REF _Ref494748672 Figure 4. Statistically significant differences were demonstrated between healthy volunteers and F2 fibrosis (p=0.048) and F3 fibrosis (p=0.003). However, cT1 showed no significant trend across the fibrosis stages (p=0.068), with pairwise comparisons finding no evidence of significant differences between individual fibrosis stages in patients with NAFLD. As shown in REF _Ref494748687 Figure 5, there was no evidence of significant correlation between cT1 and collagen proportionate area in patients with NAFLD (Rho=0.142, p=0.324). In NAFLD patients there was a significant association between Kleiner fibrosis stage and ELF (p<0.001), Liver stiffness (n=47) (p<0.001), NAFLD fibrosis score (p=0.003), AST/ALT ratio (p=0.002) and FIB-4 (p=0.013) ( REF _Ref494748672 Figure 4). Collagen proportionate area showed significant correlation with: ELF (Rho=0.404, p=0.004), liver stiffness (n=47) (Rho=0.511, p<0.001), NAFLD fibrosis score (Rho=0.306, p=0.030), AST/ALT ratio (Rho=0.453, p=0.001) and FIB-4 (Rho=0.292, p=0.039) ( REF _Ref494748687 Figure 5). To diagnose clinically significant (defined as ≥F2) fibrosis in patients with NAFLD, the AUROC (95% CI) for ELF, liver stiffness, AST:ALT ratio, NAFLD fibrosis score and FIB-4 were statistically significant; 0.90 (0.82-0.99), 0.90 (0.81-0.99), 0.78 (0.64-0.93), 0.72 (0.54-0.89) and 0.69 (0.52-0.86) respectively. cT1 did not reach statistical significance with AUROC (95% CI) of 0.63 (0.45-0.81). To diagnose advanced (defined as ≥F3) fibrosis in patients with NAFLD, liver stiffness, ELF and NAFLD fibrosis score were statistical significant with AUROC (95% CI) of 0.88 (0.76-0.99), 0.80 (0.68-0.93) and 0.66 (0.50-0.82), respectively. AST:ALT ratio, cT1 and FIB-4 did not reach statistical significance with AUROC (95%CI) of 0.63 (0.47-0.79), 0.62 (0.46-0.78) and 0.61 (0.45-0.78), respectively. Comparative utility of multiparametric MRI to exclude significant liver disease10/50 (20%) of patients in the cohort were classified as being at low risk for progressive liver disease. This was defined as simple steatosis without clinically significant (>F1) fibrosis. cT1, liver stiffness, ELF, AST:ALT ratio and NAFLD fibrosis score showed statistically significant differences between healthy volunteers, low risk patients and high risk patients as shown in REF _Ref494748096 Table 6. The AUROC (95% CI) to differentiate the different groups is shown in REF _Ref494748103 Table 7, and confirmed effective utility of multiparametric MRI as well as liver stiffness and ELF to exclude liver disease, with cT1 having the highest AUROC for differentiation of NAFLD and healthy volunteers (0.93). Taking common cut-off values for the three best performing tests, sensitivity, specificity, negative predictive value and positive predictive value for the diagnosis of high risk patients were calculated and are shown in REF _Ref494747961 Table 8. Importantly, negative predictive values, suggesting those patients for whom biopsy could potentially be avoided, were substantially higher for cT1 (80.0-83.3%) compared to liver stiffness (39.1-42.9%) and ELF (26.3-57.1%).Cost analysis of non-invasive tests for the staging of NAFLDThe results of applying the sensitivity and specificity described in this study to the previously published decision tree model using our cohort of patients with NAFLD are provided in REF _Ref494748149 Table 9. The risk stratification pathways considered the use of each test individually and also the combination of transient elastography followed by multiparametric MRI. For example, the use of the “cT1 only” risk stratification pathway using a 875ms cutoff was estimated to reduce the number of biopsies required by almost half (reduction of 458 per 1,000 patients). As a result, the estimated saving was ?150,218 per 1,000 patients, relative to the pathway in which biopsies are performed on all patients. All of the pathways considered were found to be potentially cost saving, relative to biopsy alone, with the exception of ELF at the lower cut-off of 7.7. In addition, those pathways that combined transient elastography and multiparametric MRI provided additional cost savings over multiparametric MRI alone. For example, the estimated cost per correct diagnosis was ?554.26 using cT1 with a cutoff of 875ms, which reduced to ?307.92 in the pathway where this was preceded by liver stiffness (7.0kPa cutoff).DiscussionThe global burden of NAFLD is increasing inexorably and validated non-invasive diagnostic tests are important for patients, clinicians and industry. This is not only the first independent validation study to assess the diagnostic accuracy of multiparametric MRI with LiverMultiscanTM in NAFLD, but also the first study to compare the performance and potential cost-effectiveness of this emerging methodology against more established non-invasive biomarkers of liver disease. In our prospectively recruited population we demonstrated the ability of multiparametric MRI to grade hepatic steatosis with a high degree of accuracy. Moreover, multiparametric MRI demonstrated accurate differentiation of patients with simple steatosis from those with NASH and also correlated in a highly significant manner with overall disease activity as defined by NAFLD activity score. However, in this cohort, multiparametric MRI did not predict the severity of histological liver fibrosis. Multiparametric MRI demonstrated the greatest negative predictive value for excluding significant liver disease in those with NAFLD. Identifying those patients with NAFLD requires accurate detection of steatosis. 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ADDIN EN.CITE.DATA 33, 34 PDFF-Dixon has been shown in this study to have excellent accuracy in differentiating patients with steatosis on liver biopsy from healthy volunteers with AUROC of 1.0. PDFF-Dixon also correlated strongly with PDFF-MRS (Rho=0.975, p<0.001), which is widely regarded at the most accurate method for non-invasive quantification of liver fat.PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5IYW1pbHRvbjwvQXV0aG9yPjxZZWFyPjIwMDk8L1llYXI+
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ADDIN EN.CITE.DATA 17, 35 Comparison of the accuracy of PDFF-Dixon and Controlled Attenuation Parameter for the detection of steatosis must be made with caution due to the small numbers of patients in this study with both a PDFF-Dixon and Controlled Attenuation Parameter reading. Both techniques had very high accuracy for the detection of any steatosis.PDFF-Dixon demonstrated a clear, stepwise increase with advancing Brunt steatosis grade in patients with NAFLD suggesting that multiparametric MRI could be used as an accurate method of monitoring steatosis progression and regression and assessing the therapeutic response to lifestyle or drug interventions in the context of clinical trials. In this study, Controlled Attenuation Parameter did not demonstrate the same stepwise increase with Brunt grade observed with PDFF-Dixon measurement. A single test to reliably exclude NAFLD would be of considerable value in clinical practice. In this study multiparametric MRI showed a high degree of accuracy for differentiating between healthy volunteers and those with NAFLD with AUROC (95% CI) of 0.93 (0.86-1.00). It should be recognised however, that the healthy volunteers and patients enrolled in this study were not well matched in terms of age, waist to hip ratio or BMI. Accepting this limitation, using a cT1 cut-off value of 875ms gave multiparametric MRI a sensitivity of 88.0% with specificity of 100% for the detection of any liver disease. This was superior to all other non-invasive tests. In addition, the negative predictive value for excluding any liver disease was substantially higher than those for the other non-invasive techniques. This indicates an opportunity to consider further work to establish the ability of multiparametric MRI to be used as a single one-stop comprehensive MRI examination to rule out significant liver disease. When used in a risk stratification pathway for people with NAFLD in whom biopsy is clinically indicated, these non-invasive tests could be cost-saving if applied as first line tests. Furthermore, the combination of transient elastography with multiparametric MRI would provide the lowest total cost and, because diagnostic accuracy is maintained, would result in a lower total cost per correct diagnosis.The differentiation of those with NASH from those with simple steatosis is also an important distinction in clinical practice as our current understanding of NAFLD recognises NASH as the harbinger of progressive fibrosis and hepatocellular carcinoma.PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5BZGFtczwvQXV0aG9yPjxZZWFyPjIwMDU8L1llYXI+PFJl
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ADDIN EN.CITE.DATA 2, 3, 36 Identifying individuals with NASH stratifies patients at risk of significant disease and may do so at an earlier stage than tests that reflect fibrosis alone. ADDIN EN.CITE <EndNote><Cite><Author>Byrne</Author><RecNum>1218</RecNum><DisplayText><style face="superscript">37</style></DisplayText><record><rec-number>1218</rec-number><foreign-keys><key app="EN" db-id="afxe29afq2sd5deff94p5ttttxser00ffrr2" timestamp="1452073977">1218</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Byrne, Christopher D.</author><author>Targher, Giovanni</author></authors></contributors><titles><title>Time to Replace Assessment of Liver Histology With MR-Based Imaging Tests to Assess Efficacy of Interventions for Nonalcoholic Fatty Liver Disease</title><secondary-title>Gastroenterology</secondary-title></titles><periodical><full-title>Gastroenterology</full-title><abbr-1>Gastroenterology</abbr-1></periodical><pages>7-10</pages><volume>150</volume><number>1</number><dates><year>2016</year></dates><publisher>Elsevier</publisher><isbn>0016-5085</isbn><urls><related-urls><url> Detection of NASH guides decision making about clinical management and follow-up intensity and identifies patients who may be eligible for recruitment to clinical studies. ADDIN EN.CITE <EndNote><Cite><Author>Machado</Author><Year>2013</Year><RecNum>1252</RecNum><DisplayText><style face="superscript">38</style></DisplayText><record><rec-number>1252</rec-number><foreign-keys><key app="EN" db-id="afxe29afq2sd5deff94p5ttttxser00ffrr2" timestamp="1459776025">1252</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Machado, Mariana V.</author><author>Cortez-Pinto, Helena</author></authors></contributors><titles><title>Non-invasive diagnosis of non-alcoholic fatty liver disease. A critical appraisal</title><secondary-title>J Hepatol</secondary-title></titles><periodical><full-title>J Hepatol</full-title><abbr-1>Journal of hepatology</abbr-1></periodical><pages>1007-1019</pages><volume>58</volume><number>5</number><keywords><keyword>Non-alcoholic fatty liver disease</keyword><keyword>Non-alcoholic steatohepatitis</keyword><keyword>Fibrosis</keyword><keyword>Non-invasive diagnosis</keyword></keywords><dates><year>2013</year><pub-dates><date>5//</date></pub-dates></dates><isbn>0168-8278</isbn><urls><related-urls><url>(12)00890-2/pdf</url><url> To date, the differentiation of simple steatosis and NASH has been reliant on liver biopsy. Liver biopsy has low patient acceptability due to its invasiveness and associated risk. Liver biopsy is also prone to sampling error and interobserver variation of histological assessment. These factors reduce the suitability and reliability of liver biopsy for disease stratification in NAFLD. Currently available methods to non-invasively differentiate NASH and simple steatosis are suboptimal. Conventional blood tests and imaging techniques have low accuracy for the differentiation of simple steatosis and NASH. ADDIN EN.CITE <EndNote><Cite><Author>Machado</Author><Year>2013</Year><RecNum>1252</RecNum><DisplayText><style face="superscript">38</style></DisplayText><record><rec-number>1252</rec-number><foreign-keys><key app="EN" db-id="afxe29afq2sd5deff94p5ttttxser00ffrr2" timestamp="1459776025">1252</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Machado, Mariana V.</author><author>Cortez-Pinto, Helena</author></authors></contributors><titles><title>Non-invasive diagnosis of non-alcoholic fatty liver disease. A critical appraisal</title><secondary-title>J Hepatol</secondary-title></titles><periodical><full-title>J Hepatol</full-title><abbr-1>Journal of hepatology</abbr-1></periodical><pages>1007-1019</pages><volume>58</volume><number>5</number><keywords><keyword>Non-alcoholic fatty liver disease</keyword><keyword>Non-alcoholic steatohepatitis</keyword><keyword>Fibrosis</keyword><keyword>Non-invasive diagnosis</keyword></keywords><dates><year>2013</year><pub-dates><date>5//</date></pub-dates></dates><isbn>0168-8278</isbn><urls><related-urls><url>(12)00890-2/pdf</url><url> To determine the severity of disease, cT1 showed a highly significant, positive correlation with NAFLD activity score. The correlation between NAFLD activity score and cT1 was stronger than between NAFLD activity score and any other evaluated test, althought the authors acknowledge that these tests are not designed to assess disease activity. 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ADDIN EN.CITE.DATA 43 has shown a clear correlation between cT1 and fibrosis stage. It may be that our study is underpowered to detect this correlation, however, in our study it appears that the influence of disease activity on cT1 has hampered the ability of cT1 to detect stage differences in fibrosis; larger studies are needed to explore this further. REF _Ref494748721 Figure 6 shows the heavy confounding of disease activity on fibrosis assessment in this cohort. When grouped by fibrosis stage, the only statistically significant difference in cT1 is between low and high NAFLD activity score in patients with early stage fibrosis. This identification of a group of patient with early stage fibrosis and less severe disease as graded by NAFLD activity score characterises a group of patients at low risk of progressive liver disease. As shown in REF _Ref494747961 Table 8, cT1 had comparable sensitivity, specificity and positive predictive value to ELF and liver stiffness for the exclusion of significant disease (NASH or fibrosis ≥F1) but notably greater negative predictive value suggesting that multiparametric MRI can identify patients without significant liver disease with confidence. These patients would potentially not need further investigations. Our study was prospective and enrolled unselected consecutive patients across two sites. The statistical power is limited by recruitment volume, which may have resulted in some of the more subtle associations between variables being missed. Despite this, our independently collected data confirms the opportunities for new non-invasive biomarkers in liver disease severity assessment. Although liver biopsy remains the gold standard, as a comparator it has known limitations of sampling error and interobserver variation.PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5HZXJtYW5pPC9BdXRob3I+PFllYXI+MjAxMTwvWWVhcj48
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ADDIN EN.CITE.DATA 25, 44 However, in our study we demonstrated that semi-quantitative histology scores correlated strongly with collagen proportionate area and other biomarkers performed as per previous publications. In conclusion, multiparametric MRI with LiverMultiscanTM has the ability to identify patients with NAFLD and to quantify steatosis and overall disease activity (by NAFLD activity score). Additionally, it stratified between healthy volunteers and patients with NAFLD as well as between patients at low risk and those at high risk of progressive liver disease. When evaluated alongside existing biomarkers, we conclude that different non-invasive tests may provide complementary diagnostic information and prove cost-effective when incorporated into clinical pathways by avoiding unnecessary liver biopsies. Multiparametric MRI was superior for the grading of steatosis, grading of NASH severity, and for excluding disease, but in this cohort was inferior for the staging of fibrosis. The potential application of multiparametric MRI in clinical and research settings thus remains of great interest and further studies in appropriate clinical populations will facilitate improved understanding of the opportunities for applying MR imaging in evaluation of liver disease.References ADDIN EN.REFLIST 1.Younossi ZM, Koenig AB, Abdelatif D, et al. Global epidemiology of nonalcoholic fatty liver disease-Meta-analytic assessment of prevalence, incidence, and outcomes. Hepatology 2016;64:73-84.2.Dam-Larsen S, Franzmann M, Andersen IB, et al. Long term prognosis of fatty liver: risk of chronic liver disease and death. Gut 2004;53:750-5.3.Adams LA, Lymp JF, St Sauver J, et al. The natural history of nonalcoholic fatty liver disease: a population-based cohort study. 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Hepatology 2010;51:454-462.Figure LegendsFigure SEQ Figure \* ARABIC 1: Box plots showing the relationships between non-invasive and histological assessment of steatosis. A) PDFF-Dixon and Brunt steatosis grade (n=38), B) PDFF-MRS and Brunt steatosis grade (n=43), C) Controlled Attenuation Parameter and Brunt steatosis grade (n=24). Inter-group differences were assessed with post-hoc tests with values shown in the supplementary material. CAP: controlled attenuation parameter, HV: healthy volunteer, PDFF: proton density fat fraction.Figure SEQ Figure \* ARABIC 2: Receiver operating characteristic curve for the differentiation of patients with simple steatosis from those with NASH (n=47) for cT1, liver stiffness and enhanced liver fibrosis test. ELF: enhanced liver fibrosis test.Figure SEQ Figure \* ARABIC 3: Box plots showing the relationships between the individual components of the NAFLD activity score and non-invasive markers of liver disease. p-values are derived from the Jonckheere–Terpstra test. NAS: NAFLD activity score, ELF: enhanced liver fibrosis test. A. cT1 showed a significant association with hepatocyte ballooning and total NAFLD activity score but not with lobular inflammation (n=50). B. Liver stiffness showed a significant association with hepatocyte ballooning, lobular inflammation and total NAFLD activity score (n=47). C. ELF score showed a significant association with hepatocyte ballooning and lobular inflammation but not total NAFLD activity score (n=50).Figure SEQ Figure \* ARABIC 4: Box plots showing the relationships between non-invasive markers of liver disease and Kleiner fibrosis stage in the study cohort. cT1 did not have a statistically significant association with Kleiner fibrosis stage for patients with NAFLD. Liver stiffness (n=47), ELF, NAFLD fibrosis score, AST:ALT ratio and FIB-4 had a statistically significant association with Kleiner fibrosis stage. p-values shown were determined by the Jonckheere–Terpstra test across patients with NAFLD only and exclude healthy volunteers. HV: healthy volunteer, ELF: enhanced liver fibrosis test, NFS: NAFLD fibrosis score.Figure SEQ Figure \* ARABIC 5: Scatter plots showing the relationships between non-invasive markers of liver disease and collagen proportionate area in the study cohort. cT1 did not have a statistically significant correlation with collagen proportionate area, assessed by Spearman’s rank correlation. All other biomarkers had statistically significant correlations with collagen proportionate area as shown. Liver stiffness (n=47), enhanced liver fibrosis test, NAFLD fibrosis score, AST:ALT ratio, FIB-4. ELF: enhanced liver fibrosis test, NFS: NAFLD fibrosis score, CPA: collagen proportionate area.Figure SEQ Figure \* ARABIC 6: Box plot showing the influence of overall disease activity (as assessed by NAFLD activity score) on cT1. In patients with low stage fibrosis there was significant difference in cT1 between those with NAFLD activity score <5 compared to those with a NAFLD activity score ≥5. This distinction had a trend towards significance in higher stage fibrosis. NAS: NAFLD activity score.Table SEQ Table \* ARABIC 1: Baseline characteristics of patients with NAFLD and healthy volunteers.Patientsn=50Healthy Volunteersn=6p-ValueAge (years)54 (18-73)32 (23-55)0.011Male28 (56%)3 (50%)1.000Caucasian43 (86%)6 (100%)1.000BMI (kg/m2)33.6 ±5.124.0 ±2.50.001waist to hip ratioMale 0.98 ±0.070.81 ±0.050.001Female0.90 ±0.060.72 ±0.030.001Post-transplant5 (10%)n/a-Type 2 diabetes26 (52%)n/a-Hypertension25 (50%)n/a-Dyslipidaemia26 (52%)n/a-Smoking Status1.000Non-smoker26 (58%)4 (67%)-Ex-smoker15 (30%)2 (33%)-Current smoker6 (12%)0 (0%)-Consume alcohol13 (26%)6 (100%)0.001UK units/week*8 (1-20)13 (1-15)0.701Data reported as mean ±SD, with p-values from t-tests; median (range), with p-values from Mann-Whitney tests; or n (%), with p-values from Fisher’s exact tests, as applicable.Bold p-values are significant at p<0.05*In patients that consume alcoholTable SEQ Table \* ARABIC 2: Liver histology characteristics of study participantsCharacteristicn%Kleiner Fibrosis Stage0612%11020%2918%32040%4510%DiagnosisSimple steatosis1224%NASH3876%Brunt Steatosis Grade000%12346%21734%31020%Lobular Inflammation (NAFLD activity score)01122%12346%21530%312%Hepatocyte Ballooning (NAFLD activity score)01020%11530%22550%Total NAFLD activity score000%1-2918%3-41632%5-62244%7-836%Table SEQ Table \* ARABIC 3: Demographic, clinical and laboratory parameters showed no difference between patients with simple steatosis and NASH.NASH(n=38)Simple Steatosis(n=12)p-ValueAge (years)54 (18-73)46 (23-69)0.216Male19 (50%)9 (75%)0.186Caucasian34 (90%)9 (75%)0.337BMI (kg/m2)34.2 ±4.831.6 ±5.70.125Type 2 diabetes22 (58%)4 (33%)0.190Hypertension20 (53%)5 (42%)0.742Hyperlipidaemia21 (55%)5 (42%)0.514Consume alcohol8 (21%)5 (42%)0.256Alcohol intake (UK units/week)* 7 (1-20)12 (2-16)0.831Bilirubin (?mol/L)11 (4-45)15 (5-50)0.318Aspartate transaminase (AST) (U/L)38 (19-119)41 (16-112)0.526Alanine transaminase (ALT) (U/L)53 (18-153)74 (15-176)0.707Alkaline phosphatase (ALP) (U/L)94 (45-251)76 (50-149)0.114Gamma-glutamyl transferase (gGT) (U/L)78 (22-381)58 (21-547)0.071Albumin (g/L)45 ±446 ±40.477Fasting glucose (mmol/L)6.3 (2.8-17.3)5.6 (4.6-11.4)0.111Cholesterol (mmol/L)4.8 ±1.55.2 ±1.20.470Triglycerides (mmol/L)2.0 (0.7-5.8)1.4 (0.9-2.7)0.099Ferritin (?g/L)115 (10-689)177 (45-346)0.159Transferrin saturation (%)24.3 (7.5-49.6)30.5 (14.7-43.7)0.080Creatinine (?mol/L)73 (46-143)77 (52-97)0.225Platelet count (x109/L)219 ±71197 ±370.172Data reported as mean ±SD, with p-values from t-tests; median (range), with p-values from Mann-Whitney tests; or n (%), with p-values from Fisher’s exact tests, as applicable.*In patients that consume alcoholTable SEQ Table \* ARABIC 4: cT1, liver stiffness and ELF showed significant differences between those with simple steatosis and those with NASH.NASH(n=38)simple steatosis(n=12)p-ValuecT1 (ms)1007 ±94907 ±1200.004Liver Stiffness (kPa)*10.2 (4.9-27.7)6.1 (3.6-9.1)<0.001ELF9.3 ±1.07.8 ±0.8<0.001AST:ALT ratio0.76 (0.27-1.56)0.62 (0.34-1.07)0.077NAFLD fibrosis score-0.95 ±1.64-1.78 ±1.990.150FIB-41.20 (0.40-5.80)1.12 (0.38-4.61)0.351Data reported as mean ±SD, with p-values from t-tests or median (range), with p-values from Mann-Whitney tests, as applicable.Bold p-values are significant at p<0.05*Based on reliable scans only (n=47)Table SEQ Table \* ARABIC 5: Correlations between non-invasive biomarkers and the components of the NAFLD activity scorecT1Liver stiffness*ELFHepatocyte ballooningRho=0.308 (p=0.030)Rho=0.450 (p=0.002)Rho=0.366 (p=0.009)Lobular inflammationRho=0.069 (p=0.635)Rho=0.433 (p=0.002)Rho=0.440 (p=0.001)Total NAFLD activity scoreRho=0.514 (p<0.001)Rho=0.419 (p=0.003)Rho=0.460 (p=0.001)Correlations assessed with Spearman’s RhoBold p-values are significant at p<0.05*Based on reliable scans only (n=47)Table SEQ Table \* ARABIC 6: cT1, liver stiffness and ELF show significant differences between high risk patients, low risk patients and healthy volunteers.High risk patients*(n=40)Low riskPatients**(n=10)Healthy volunteers(n=6)p-ValuecT1 (ms)1007 ±93890 ±122790 ±42<0.001Liver Stiffness (kPa)?9.9 (4.9-27.7)6.1 (3.6-9.1)4.5 (3.6-6.8)<0.001ELF9.2 ±1.07.7 ±0.87.9 ±0.3<0.001AST:ALT ratio0.76 (0.27-1.56)0.65 (0.34-1.07)1.02 (0.86-1.67)0.018NAFLD fibrosis score-1.05 ±1.66-1.54 ±2.09-2.90 ±0.620.047FIB-41.15 (0.38-5.80)1.23 (0.53-4.61)0.87 (0.55-0.98)0.158Data reported as mean ±SD, with p-values from one-way ANOVA or median (range), with p-values from Kruskal-Wallis tests, as applicable.Bold p-values are significant at p<0.05* Patients with either NASH or >F1 fibrosis** Patients with simple steatosis and ≤F1 fibrosis? Based on reliable scans only (n=53)Table SEQ Table \* ARABIC 7: cT1, liver stiffness and ELF and stratification of low and high risk patientsLow risk patients* (n=10)vsHigh risk patients** (n=37)Healthy volunteers (n=6)vsAll patients (n=47)Healthy volunteers and low risk patients (n=16)vsHigh risk patients (n=37)cT10.73 (0.53-0.93)0.93 (0.86-1.00)0.83 (0.69-0.96)liver stiffness?0.82 (0.69-0.94)0.89 (0.77-1.00)0.86 (0.76-0.96)ELF0.89 (0.80-0.99)0.81 (0.69-0.92)0.89 (0.81-0.98)AST:ALT ratio0.64 (0.45-0.84)0.82 (0.67-0.97)??0.52 (0.34-0.70)??NAFLD fibrosis score0.55 (0.32-0.77)0.79 (0.66-0.91)0.64 (0.47-0.81)FIB-40.51 (0.31-0.71)0.72 (0.59-0.85)0.59 (0.43-0.75)Data reported as AUROC (95% CI)Bold values were significant at p<0.05* Patients with simple steatosis and ≤F1 fibrosis** Patients with either NASH or >F1 fibrosis? 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ADDIN EN.CITE.DATA 930.0%100.0%100.0%26.3%cT1 0.93 (0.86-1.00)822 ms90.0%83.3%97.8%50.0%Differentiation healthy volunteers and patients875 ms88.0%100.0%100.0%50.0%LS0.89 (0.77-1.00)5.8 kPa85.1%66.7%95.2%36.4%7.0 kPa68.1%100.0%100.0%28.6%ELF0.81 (0.69-0.92)7.786.0%16.7%89.6%12.5%9.824.0%100.0%100.0%13.6%* Patients with simple steatosis and ≤F1 fibrosis** Patients with either NASH or >F1 fibrosisLS: liver stiffnes, PPV: positive predictive value, NPV: negative predictive valueTable SEQ Table \* ARABIC 9: Cost and effectiveness of diagnostic pathways for patients with suspected NAFLDOverall outcomePer 1000 patientsTotal costCut-offCorrectIncorrectFailBiopsies avoidedTotal cost (?)Cost Saving vs Biopsy (?)Per correct diagnosis (?)cT1822 ms82.9%12.1%5.0%381.9538,345101,265649.57875 ms88.3%6.7%5.0%458.4489,392150,218554.26liver stiffness5.8 kPa63.6%18.4%18.0%297.2517,530122,080814.167.0 kPa66.6%15.4%18.0%491.6393,146246,464590.14ELF7.757.4%42.6%0.0%151.1654,010-14,4001138.439.855.3%44.7%0.0%858.9201,322438,288363.97liver stiffness (5.8 kPa) + cT1822 ms81.4%15.0%3.5%734.6338,260301,350415.37875 ms83.4%13.1%3.5%722.7345,851293,759414.60liver stiffness (7.0 kPa) + cT1822 ms76.8%20.7%2.5%841.1242,309397,301315.60875 ms77.1%20.3%2.5%848.7237,488402,122307.92Assumed costs: Biopsy (?639.91), MRI (?143), liver stiffness (?68), ELF (?111.06). Overall outcome rates are derived from the data in REF _Ref494747961 Table 8, with the rate of correct and incorrect outcomes being the sum of the true positives and true negatives (correct), or the false positives and false negatives (incorrect), respectively, for the pathway. Costs for each diagnostic pathway include all predicted test and biopsy costs for a cohort of 1,000 patients.Section & TopicNoItemReported on page #TITLE OR ABSTRACT1Identification as a study of diagnostic accuracy using at least one measure of accuracy(such as sensitivity, specificity, predictive values, or AUC)1ABSTRACT2Structured summary of study design, methods, results, and conclusions (for specific guidance, see STARD for Abstracts)7INTRODUCTION3Scientific and clinical background, including the intended use and clinical role of the index test94Study objectives and hypotheses10METHODSStudy design5Whether data collection was planned before the index test and reference standard were performed (prospective study) or after (retrospective study)12Participants6Eligibility criteria 127On what basis potentially eligible participants were identified (such as symptoms, results from previous tests, inclusion in registry)128Where and when potentially eligible participants were identified (setting, location and dates)129Whether participants formed a consecutive, random or convenience series12Test methods10aIndex test, in sufficient detail to allow replication1310bReference standard, in sufficient detail to allow replication15/1611Rationale for choosing the reference standard (if alternatives exist)No alternatives12aDefinition of and rationale for test positivity cut-offs or result categories of the index test, distinguishing pre-specified from exploratory REF _Ref494747961 Table 812bDefinition of and rationale for test positivity cut-offs or result categories of the reference standard, distinguishing pre-specified from exploratory15/1613aWhether clinical information and reference standard results were available to the performers/readers of the index test1513bWhether clinical information and index test results were available to the assessors of the reference standard15Analysis14Methods for estimating or comparing measures of diagnostic accuracy1615How indeterminate index test or reference standard results were handledn/a16How missing data on the index test and reference standard were handled1817Any analyses of variability in diagnostic accuracy, distinguishing pre-specified from exploratoryn/a18Intended sample size and how it was determined18RESULTSParticipants19Flow of participants, using a diagramSupplementary material20Baseline demographic and clinical characteristics of participants18 / REF _Ref494748003 Table 121aDistribution of severity of disease in those with the target condition REF _Ref494748023 Table 221bDistribution of alternative diagnoses in those without the target conditionn/a22Time interval and any clinical interventions between index test and reference standard13Test results23Cross tabulation of the index test results (or their distribution) by the results of the reference standard REF _Ref494748070 Table 4 REF _Ref494748096 cT1Liver stiffness*ELFHepatocyte ballooningRho=0.308 (p=0.030)Rho=0.450 (p=0.002)Rho=0.366 (p=0.009)Lobular inflammationRho=0.069 (p=0.635)Rho=0.433 (p=0.002)Rho=0.440 (p=0.001)Total NAFLD activity scoreRho=0.514 (p<0.001)Rho=0.419 (p=0.003)Rho=0.460 (p=0.001)Correlations assessed with Spearman’s RhoBold p-values are significant at p<0.05*Based on reliable scans only (n=47)Table 6 REF _Ref494748103 Table 724Estimates of diagnostic accuracy and their precision (such as 95% confidence intervals) REF _Ref494747961 Table 825Any adverse events from performing the index test or the reference standardn/aDISCUSSION26Study limitations, including sources of potential bias, statistical uncertainty, and generalisability25-3027Implications for practice, including the intended use and clinical role of the index test25-30OTHER INFORMATION28Registration number and name of registry1229Where the full study protocol can be accessedSupplementary material30Sources of funding and other support; role of funders31. Authors' declaration of personal interests:?(i) Peter J Eddowes, Phillip N Newsome and Gideon M Hirschfield are supported by the National Institute of Health Research Birmingham Biomedical Research Centre. Jonathan A Fallowfield is supported by a NHS Research Scotland/Universities Senior (ii) Catherine J Kelly, Amy H Herlihy and Matthew D Kelly are employees of Perspectum Diagnostics ltd.?2. Declaration of funding interests:(i) This study was funded in full by Innovate-UK, grant number 101679.? ................
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