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Towards Cardiac MRI based Risk Stratification in Idiopathic Dilated Cardiomyopathy. Dr Pamela Browna, Dr Chris Millera, Dr Andrea DiMarcob, Dr Matthias SchmittaCorresponding author: Pamela Brown, pamela.brown6@Cardiac MRI department, North West Heart Centre, Manchester University Foundation Trust-Wythenshawe Site, Southmoor Road, Manchester, M23 9LT. Arrhythmia Unit, Heart Disease Institute, Bellvitge University Hospital, Barcelona, SpainWord Count: 2669No conflicts of interestThe authors received no specific funding for this work.AbstractSudden cardiac death (SCD) secondary to arrhythmia remains a risk in those with dilated cardiomyopathy (DCM), an implantable cardiac defibrillator (ICD) is an effective strategy to prevent SCD. Current guidelines recommend selection for ICD based on ejection fraction (EF) less than 35%, however, most SCD occurs in those with EF >35%. Although meta-analysis has demonstrated a survival benefit for primary prevention ICD in DCM, no randomised trial has shown a significant reduction in overall mortality including the most recent ‘Danish Study to Assess the Efficacy of ICDs in Patients With Non-Ischemic Systolic Heat Failure on Mortality’ (DANISH study). Clearly, a more sophisticated selection strategy is required. CMR is an ideal non-invasive imaging technique which allows calculation of ejection fraction as well as tissue characterisation with gadolinium contrast, parametric mapping and feature tracking. Late gadolinium enhancement (LGE) detects mid-wall fibrosis in approximately 30% of those with DCM, three meta-analyses have demonstrated an association between fibrosis in DCM and SCD, and those without fibrosis are at low risk of SCD. T1 mapping and extra-cellular volume calculation (ECV) are methods of demonstrating diffuse fibrosis in the myocardium. Raised ECV and native T1 have been associated with worse outcomes but the relationship to SCD has not been well studied. Undoubtably, more research is required but CMR has several tools which offer incremental value above EF to improve risk stratification and consequent outcomes and resource utilisation in those with DCM. IntroductionDilated cardiomyopathy (DCM) is defined as ‘left ventricular or biventricular systolic dysfunction and dilatation that is not explained by abnormal loading conditions or coronary artery disease.’ (1) It is recognised to be a spectrum of clinical states rather than a single entity; the prevalence of DCM is 1 in 2500 with an incidence of 7 in 100,000. (2) (Image 1) Image 1. The DCM disease spectrum (Image adapted from Pinto et al 2016 (1))Sudden cardiac death (SCD) is an unexpected death occurring within one hour of symptom onset or within 24 hours from when the individual was last seen alive. (3) SCD accounts for 15-20% of all deaths worldwide with 1.4 deaths per 100,000 person years in women (95% CI 0.95-1.98) and 6.7 deaths per person years in men (95% CI 6.25-7.14). (4) Approximately 30% of those with DCM will suffer SCD. (5)The implantable defibrillator (ICD) is an effective strategy for the primary prevention of arrhythmic SCD. Currently, an ICD is recommended in symptomatic heart failure (NYHA II-III) and a left ventricular ejection fraction (LVEF) of less than 35%, regardless of aetiology. (6) However, the majority of SCD occurs in those without severe left ventricular systolic dysfunction (LVSD) (7,8) who have no primary prevention ICD indication and a significant proportion of patients implanted with an ICD will never receive appropriate therapy. (9)The broad issue of non-invasive imaging markers associated with SCD across the spectrum of cardiac disease has recently been reviewed. (10,11) This review will focus on the role of cardiac magnetic resonance (CMR) and it’s potential for improving risk stratification in DCM. Left Ventricular Ejection Fraction-the established risk stratification method. Mortality increases as EF deceases (12) and those with an EF <30% have the most adverse prognosis. (13, 14) Conversely, the absolute numbers of people who die from SCD is substantially higher in those with EF >35%. (8) LVEF is clearly a marker of disease severity but is neither specific nor sensitive as a marker for SCD. When selecting according to LVEF, no randomised trial has shown a significant reduction in overall mortality with primary prevention ICD in DCM (9, 15-18), even though ICD implantation was effective in preventing SCD. (9, 18) A summary of the trials to date is seen in Table 1. Table 1. CATAMIOVIRTDEFINITE SCD-HeFTDANISHYear 20022003200420052016DesignICD vs OMTICD vs. amiodaroneICD vs OMTICD vs amiodarone vs OMTICD vs OMTInclusion criteriaLVEF <30%NYHA II–IIILVEF ≤35%NYHA I–IIINSVTLVEF <36%NYHA I–IIINSVT or PVCsLVEF <35%NYHA II–IIILVEF <35%NYHA II–III (IV if CRT)NT-proBNP >200pg/mLNo. randomised1041034582521 (total) 1211 (DCM group) 398 receiving ICD1116Aetiology (% with DCM)10010010047100Mean age 5259586064Mean EF %24 ± 723 ± 921 ± 1425 ± 525Median follow up period (months)2324294667All-Cause Mortality(DCM group only)Terminated earlyTerminated earlyICD, 12.2%; OMT, 17.4%HR, 0.65; 95% CI, 0.40–1.06;P=0.08ICD 21.4%; OMT 27.9% (5 y)HR, 0.73; 95% CI, 0.50–1.07;P=0.06ICD, 21.6%; OMT, 23.4%;HR, 0.87; 95% CI, 0.68–1.12;P=0.28Sudden Cardiac DeathNANAICD 1.3%; OMT 6.1%HR, 0.20; 95% CI, 0.06–0.71;P=0.006NAICD 4.3%; OMT 8.2%HR, 0.50; 95% CI, 0.31–0.82;P=0.005OMT=optimal medical therapyCurrent guidelines based on meta-analysis of these trials managed to demonstrate a significant survival benefit for primary prevention ICD in patients with DCM and severe LV impairment. (19) A recent meta-analysis, (20) including the DANISH trial data, confirmed previous results. The fact that survival benefits can be observed only by pooling data of several studies indicates that we need to improve patient selection by increasing our ability to discriminate between risk of SCD and risk of death from heart failure or non-cardiovascular causes. Sub-group analysis in the DANISH trial showed that ICDs provided a significant survival benefit only to patients younger than 70 years old, not because they had a higher risk of SCD without the ICD but because they had a lower risk of non-sudden death therefore their sudden vs non-sudden death ratio was higher. Clearly, a more sophisticated approach is required. The emerging risk stratification method-late gadolinium enhancement. CMR with administration of gadolinium based contrast agent allows non-invasive evaluation of localised cardiac replacement fibrosis, seen when a collagen matrix is laid down in response to myocyte damage, necrosis and/or apoptosis, leading to a distinct myocardial scar. Gadolinium shortens the T1 relaxation of the scarred tissue which consequently appears bright when the inversion recovery sequence is set to null normal myocardium (21). The presence of myocardial replacement fibrosis seen on late gadolinium enhanced CMR has been shown to correlate with histological areas of plexiform fibrosis. (22-25) A midwall pattern of fibrosis (MWF) is the most typical pattern seen in patients with DCM, with 30-40% having LGE, other patterns are seen, and several studies have classified hyperenhancement as simply ischaemic or non-ischaemic. (Wu 2008, 26,27) Beyond diagnosis, studies have demonstrated that fibrosis in DCM can be used to predict prognosis. Importantly, replacement fibrosis seems to be related to ventricular arrhythmias and SCD. Image 1 demonstrates MWF on LGE imaging, T1 and post-contrast T1 maps. Image 1Assomull et al (28) conducted the first study demonstrating the association of fibrosis with an adverse prognosis in DCM. 35% of 101 patients studied had MWF and LGE presence was found to be associated with all-cause mortality and hospital admission for cardiovascular causes (HR 3.4 95% CI 1.4-8.7 p=0.01). Those with LGE were more likely to have SCD/VT although overall event rates were low (7 in total). Subsequently, Iles (29), evaluated whether LGE presence predicted appropriate ICD shock in 103 patients who fitted primary prevention ICD criteria, 51% of those with DCM had LGE present. No ICD discharges were seen in those without LGE compared to 9 of 31 (29%) discharges in those with LGE (p<0.01). The largest study to date consisted of 472 patients, (25), 30% had MWF. There was a significant association between MWF and all-cause mortality (p<0.001) even after adjustment for EF; 29.6% of those with fibrosis reached the arrhythmic end points of SCD or aborted SCD vs 7% those without fibrosis (p<0.001). Recently, the question of whether LGE signifies risk in those with DCM and EF >40% was studied. (30) 399 patients were enrolled 25% had MWF, mean EF was 49% and median follow up was 4.6 years. The composite primary end point of SCD or aborted SCD occurred in 18 (17.8%) patients with LGE and 7 (2.3%) patients without LGE (p=<0.0001). This significance continued even after adjustment for potential confounders such as age, NYHA class and LVEF (HR 9.3). MWF had just a borderline association with the secondary end point of all-cause mortality (p=0.056), suggesting that LGE might be a specific marker of ventricular arrhythmia and therefore, could identify patients with a higher risk of SCD rather than death from other causes. Several other smaller, often single centre studies with diverse end points have been studied and synthesised into three meta-analyses delivering a consistent message (27, 31, 32). (Table 2)Table 2. AuthorKuruvilla et al Disertori et alDiMarco et alYear201420162017Number of studies (DCM only)9829Number of patients (DCM only)1,4881,4432948Mean Age (Years)525356Mean EF %373320-43Mean Follow up (Months)303136% with LGE present384044Composite arrhythmic end pointAER 6.0% LGE present vs 1.2%, LGE absent p<0.001 Pooled OR 5.32, 95% CI 3.45 to 8.20, p<0.00001AER 7.6% LGE present vs 1.3% LGE absent. LGE pooled OR 6.27, 95% CI: 4.15 to 9.47AER 6.9% LGE present vs 1.6% absent. LGE pooled OR 4.3, 95% CI: 3.3 to 5.8 p=0.001The largest and most recent meta-analysis by Di Marco et al (27) confirmed LGE was significantly and strongly associated with the arrhythmic end point of SCD, sustained ventricular tachycardia or appropriate ICD therapy (pooled OR 4.3, 95% CI: 3.3 to 5.8 p=0.001). In contrast to LGE, LVEF was not found to correlate with the arrhythmic end-point. Moreover, the association between LGE and ventricular arrhythmias was observed both in studies with mean LVEF < 35% (OR 4.2 95% CI: 2.4 to 7.2 p=<0.001) and in studies with mean LVEF >35% (OR 5.2, 95% CI: 3.4 to 7.9 p=<0.001). All these results were obtained considering the simple dichotomous variable LGE presence vs LGE absence. It is unclear whether LGE quantification can further improve risk stratification. Studies analysing this have come to conflicting conclusions (29, 30) There are a variety of signal thresholding which can be used to quantify LGE, there is no consensus on the best method to use. In the case of hypertrophic cardiomyopathy LGE >15% myocardial mass was found to be the greatest risk for sudden cardiac death. (Chan 2014) One study using the 2 standard deviation and full width half max (FWHM) methods found that in those with DCM the greatest risk was in those with >6.1% of myocardium affected by LGE. (Neilan 2013) A further study by the same group (Neilan 2015) of cardiac arrest survivors (of both ischaemic and non-ischaemic aetiology) found that presence of LGE had the strongest association with both death and appropriate ICD therapy but that percentage of LGE to myocardium >8.1% was the most specific and sensitive amount. However, another study in those with DCM (Halliday 2017) concluded that there is no linear increase in SCD risk as extent of LGE increases; the greatest increase in risk of SCD occurs between no LGE and those with 2.5% LGE. LGE presence vs absence is a simple, reproducible parameter and the important message is that DCM patients without LGE have low risk of ventricular arrhythmia or SCD. T1 mapping and ECV quantification. LGE relies on local differences in tissue composition and cannot distinguish those who have diffuse interstitial fibrosis. Endomyocardial biopsy is currently the gold standard for detection of diffuse fibrosis but carries inherent risk and has limited diagnostic yield. CMR with T1 mapping and ECV calculation allows one to demonstrate diffuse fibrosis in a non-invasive manner. T1 mapping therefore has diagnostic ability beyond presence of LGE in those with diffuse fibrosis, this is used clinically in the case of Anderson-Fabry Disease when T1 decreases due to fatty deposition. It also holds promise in distinguishing between athletic hearts when ECV decreases and hypertrophic cardiomyopathy when ECV increases. (Swoboda 2016) In a T1 map the T1 value is encoded in each pixel and corresponds to the T1 relaxation time of the corresponding myocardial voxel. T1 maps can be created both pre (native T1) and post gadolinium contrast. (33) In general, native T1 values increase in DCM and post-contrast T1 values get shorter. (21, 33) By comparing signal intensity changes (as a function of contrast concentration changes) in the extracellular compartment with those in the blood pool and integrating the available blood volume distribution (1-haematocrit (HCT)) one can calculate the partition coefficient lambda which in turn allows estimation of the myocardial extracellular volume space using the formula ECV= (1-HCT x lambda). Post-contrast T1 mapping has been shown to correlate with histological presence of fibrosis on endomyocardial biopsy and on histological whole heart examinations in patients with heart failure. (23, 24) Aus dem Siepen et al (34) demonstrated that calculated ECV was comparable with histological collagen volume fraction (CVF) in DCM and that increased ECV and native T1 was seen in those with DCM compared to controls. Puntmann et al (35) found that in those with cardiomyopathy native T1 was longer (p<0.01), post contrast T1 was shorter (p<0.01), and ECV was significantly higher (p<0.01). When the data underwent ROC analysis native T1 was found to be the best independent discriminator between healthy and diseased myocardium with a specificity of 97% and sensitivity of 100%. Routine clinical use has been limited, not least by the recommendation that each centre establishes their own reference ranges given the potential variation in vendor, field strength and acquisition parameters. Normal values have however been published for T1 and ECV at both 1.5T and 3T field strength. (Sado 2012, Dabir 2014, Ray 2017) There are ongoing large scale standardisation and validation studies including phantom exchange projects. Do T1 mapping techniques and ECV parallel findings seen in LGE literature?Wong et al (36) examined those with both ischaemic and non-ischaemic cardiomyopathy and found that ECV >28.5% was significantly associated with all-cause mortality (HR 1.55 95% CI 1.27-1.88 for every 3% increase in ECV). This was supported in a later study by the same group (37) which calculated ECV across a range of ejection fractions. Raised ECV was associated with hospitalisation for heart failure, death or both. Barison et al (38) studied 89 patients with non-ischaemic cardiomyopathy and found that an ECV >32% was a prognostic predictor of mortality beyond echo parameters and that ECV was raised compared to controls even in those without LGE. In those with dilated cardiomyopathy (39) native T1 was significantly associated with both all-cause mortality and the secondary end points independently of both LVEF<35% and LGE presence. Indeed, higher T1 values outperformed presence of LGE in predicting adverse outcomes. The association between diffuse fibrosis detected by CMR and SCD in DCM has not been widely analysed yet. One study (40) has scrutinised the link between T1 mapping and ventricular arrhythmia in patients with ICD implanted for primary or secondary prevention. Sub-group analysis showed that, in the 59 non-ischaemic patients (53 DCM, 5 HCM and 1 sarcoidosis), native septal T1 was the only independent predictor of appropriate ICD therapies (HR 1.12 every 10ms increase, p<0.01) and of the composite end-point of appropriate ICD therapies or death from any cause (HR 1,1 every 10ms increase, p<0.01). In contrast, ECV was not associated with the end-points analysed. Detection of fibrosis by CMR is a useful non-invasive diagnostic and prognostic tool in dilated cardiomyopathy. Native T1 mapping in particular has the potential to negate the need for gadolinium based contrast examinations in selected patients. It seems unlikely that T1 mapping or ECV will be used as a single diagnostic or prognostic parameter and should be used in conjunction with LGE as a multiparametric approach. One particular T1 or ECV value can indicate a variety of cardiomyopathies and pseudonormalisation can occur for example in Anderson-Fabry disease when fibrosis replaces fat in the myocardium. Strain imaging. Whilst ejection fraction describes global myocardial function, it is an imprecise measure of regional myocardial dysfunction, strain imaging on the contrary characterises regional deformation of an area of myocardium. Strain imaging is less subjective than an eyeball estimate of LVEF and can be used to detect early regional myocardial dysfunction before ejection fraction decreases. Substantial echocardiography based data has accumulated highlighting the value of strain based data (specifically global longitudinal (peak) strain (GLS)) in predicting outcome. One multimodality study (Chimura 2016) found that GLS >-8.3% calculated by 2D echocardiography combined with positive LGE on CMR heralded the most adverse prognosis above LVEF. Regional assessment of myocardial deformation has been available via CMR since the 1980s. Traditionally, this required dedicated (time consuming) sequences combined with dedicated post-processing technologies. Various conceptual approaches based on myocardial tagging or displacement encoding with stimulated echos were developed but did not penetrate into daily clinical routine. This changed with the arrival of feature tracking technology which is analogous to echocardiographic speckle tracking but rather than tracking an intramyocardial point it tracks endocardial borders over time and can be easily applied as part of a standard CMR protocol (43) has been found to be reliable, reproducible and has been validated against existing techniques such as HARP and SPAMM. (44-46) Buss (47) conducted a study of 210 patients with dilated cardiomyopathy who had CMR feature tracking based strain calculated. They found that a GLS >-12.5% was predictive of a combined primary end point of, cardiac death, heart transplantation, and appropriate ICD shock due to ventricular tachycardia or fibrillation. This was significant regardless of LVEF. In univariate analysis GLS was predictive of the primary end point (HR 1.33 95% CI 1.21-1.47 p=< 0.0001). After multivariate analysis GLS was predictive of the primary end point above LVEF and BNP (HR 1.27 95% CI 1.05-1.52 p<0.02). The study also suggested that those with preserved GLS had a good outlook irrespective of EF and LGE presence. A further study (48) studied a mixed-aetiology cohort of 1012 patients and EF <50%. It was found that after adjustment for EF and LGE every 1% decrease in GLS conferred an 89.1% increased risk of death (HR 1.891 per % p<0.001). When limiting the analysis to those with non-ischaemic cardiomyopathy GLS was an independent risk factor for death beyond LGE and EF (HR 2.01 per % p<0.001). Preserved GLS also identified patients with lower risk amongst those with LGE. GLS calculation by CMR feature tracking has yet to be widely used in clinical practice. Although normal values have been studied (Taylor 2015) these have yet to be validated on a large scale and cut offs for specific disease states are yet to be established. CMR feature tracking is limited by it’s lower temporal resolution meaning that strain values may be underestimated. Certainly, more studies are needed using CMR based methods of calculating strain to determine the exact prognostic role of GLS in arrhythmia and SCD prediction in patients with DCM. ConclusionCurrent clinically applied risk stratification for ventricular arrhythmia and SCD death in dilated cardiomyopathy, purely based on EF as the single imaging parameter, remains inadequate. 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