Fibrosis entropy is associated with life-threatening arrhythmia in non-ischaemic cardiomyopathy

FUNDING ACKNOWLEDGEMENTS: Type of funding sources: Public Institution(s). Main funding source(s): This work was supported by the National Institute for Health Research Biomedical Research Centre at Guy’s and St. Thomas’ Trust and King’s College, the Centre of Excellence in Medical Engineering funded by the Wellcome Trust and Engineering and Physical Sciences Research Council (EPSRC; WT088641/Z/09/Z). M.J.B. is supported by a Medical Research Council New Investigator Grant (MR/N011007/1) and British Heart Foundation (Project grant PG/18/74/34077). This work was supported by EPSRC 2018/19 DTP - EP/R513064/1 grant. This work was supported by a National Heart and Lung Institute Foundation grant awarded to Professor Sanjay Prasad and Dr Richard Jones. BACKGROUND: Enhanced risk stratification for implanted defibrillator requirement represents an important area of research in patients with non-ischemic cardiomyopathy (NICM). Myocardial fibrosis represents the major underlying arrhythmic substrate in this population, and its identification on late-gadolinium enhancement cardiovascular magnetic resonance (LGE-CMR) is associated with life-threatening arrhythmia (LTA). Fibrosis entropy, a measure of scar texture heterogeneity, may confer important information regarding the underlying pro-arrhythmic mechanisms of both core scar and areas of intermediate signal intensity (Gray Zone [GZ]). PURPOSE: We sought to: 1) evaluate whether LGE-CMR assessment of left ventricular (LV) tissue entropy had incremental utility to fibrosis presence for arrhythmic risk stratification of patients with NICM; 2) quantify the added utility of GZ entropy in such analysis. METHODS: This study involved a prospective observational cohort of consecutive patients with NICM and myocardial fibrosis detected on LGE-CMR. Epicardial and endocardial contours obtained from LGE-CMR data were used with a FWHM method to delineate core fibrosis (≥50% maximum signal intensity) and GZ fibrosis (≥35%-<50% signal intensity). Fibrotic masks were subsequently used, along with native dicom LGE-CMR images to compute tissue entropy, defined by the standard Shannon Entropy for core fibrosis, GZ fibrosis, and combined core+GZ fibrosis. Patients underwent adjudicated long-term follow-up for LTA (composite of sudden cardiac death, aborted sudden cardiac death or sustained ventricular tachycardia). RESULTS: Of 291 patients with NICM and mid-wall/subepicardial fibrosis, 38 patients (13.1%) experienced LTA over median follow-up of 6.3 years (interquartile range 4.6-9.1 years). On Cox regression analysis, core fibrosis entropy (Hazard ratio [HR] 1.77, 95% CI 1.25-2.54, p=0.001), GZ fibrosis entropy (HR 1.74, 95% CI 1.20-2.54, p=0.004) and combined fibrosis entropy (HR 1.98, 95% CI 1.30-2.52, p=0.001) were associated LTA after adjustment for variables used to guide ICD implantation (LVEF <35% and NYHA class >1) and remained associated in multivariable models accounting separately for core and GZ fibrosis mass. The addition of core fibrosis entropy, GZ fibrosis entropy and combined fibrosis entropy to a baseline clinical model improved the C-statistic from 0.49 to 0.59, 0.62 and 0.62, respectively. LVEF <35% was not associated with LTA (HR 1.45, 95% CI 0.77-2.74, p=0.25) on multivariable analysis. CONCLUSIONS: Fibrosis entropy on LGE-CMR offers incremental utility to LVEF and fibrosis presence for arrhythmic risk prediction in patients with NICM. The combination of core and GZ fibrosis entropy offers the highest association with risk. [Figure: see text]