CMR—quantified epicardial adipose tissue heterogeneity and its predictive value for ventricular and atrial arrhythmias after myocardial infarction

BACKGROUND: Epicardial adipose tissue (EAT) contributes to arrhythmogenic substrate development through electrophysiological and structural remodeling. Pathological EAT exhibits significant heterogeneity. We investigated whether EAT heterogeneity, quantified by entropy analysis on cardiac magnetic resonance (CMR), predicts the occurrence of ventricular and atrial arrhythmias post-myocardial infarction (MI). MATERIALS AND METHODS: This cohort study enrolled 241 consecutive patients post-MI. CMR was performed to assess EAT volume, myocardial scar, biventricular function, and strain. EAT heterogeneity was quantified using an entropy algorithm. The primary endpoints were the occurrence of ventricular arrhythmias (VAs) or atrial tachyarrhythmias (AAs). RESULTS: Over a median follow-up of 31 months, 43 (17.8%) patients developed VAs and 30 (12.4%) developed AAs. EAT entropy was significantly higher in patients who developed either VAs or AAs. In multivariable Cox regression analysis, EAT entropy, LA reservoir strain (Es), and global longitudinal strain (GLS) were independent predictors of VAs. For AAs, EAT entropy, Es, and EAT thickness independently predicted the outcome. ROC analysis revealed that the model integrating these parameters have good efficacy for the prognosis evaluation of VAs (area under the curve [AUC] = 0.872) and AAs (AUC = 0.917). Myocardial fibrosis exhibited modest correlations with EAT entropy. CONCLUSION: EAT heterogeneity, quantified by entropy, is an independent predictor of both VAs and AAs in post-MI patients. This novel imaging biomarker may enhance risk stratification and guide therapeutic strategies in this high-risk population.