Mean entropy predicts implantable cardioverter-defibrillator therapy using cardiac magnetic resonance texture analysis of scar heterogeneity

Background Risk stratification of ventricular arrhythmia remains complex in both ischemic and nonischemic populations. Objective The purpose of this study was to determine whether scar heterogeneity, quantified by mean entropy, predicts appropriate implantable cardioverter-defibrillator (ICD) therapy. We hypothesized that higher mean entropy calculated from cardiac magnetic resonance texture analysis (CMR-TA) will predict appropriate ICD therapy. Methods Consecutive patients underwent CMR imaging before ICD implantation. Short-axis left ventricular scar was manually segmented. CMR-TA was performed using a Laplacian filter to extract and augment image features to create a scar texture from which histogram analysis of pixel intensity was used to calculate mean entropy. The primary end point was appropriate ICD therapy. Results A total of 114 patients underwent CMR-TA (ischemic cardiomyopathy [ICM]: n=70; nonischemic cardiomyopathy [NICM]: n=44) with a median follow-up of 955 days (interquartile range 691–1185 days). Mean entropy was significantly higher in the ICM group (5.7 ± 0.7 vs 5.5 ± 0.7; P= .045). Overall, 33 patients received appropriate ICD therapy. Using optimized cutoff values from receiver operating characteristic curves, Kaplan-Meier survival analysis demonstrated time until first appropriate therapy was significantly shorter in the high mean entropy group ( P = .003). Multivariable analysis showed that mean entropy was the sole predictor of appropriate ICD therapy (hazard ratio 1.882; 95% confidence interval 1.083–3.271; P = .025). In the ICM group, mean entropy remained an independent predictor of appropriate ICD therapy, whereas in the NICM group, T1 -native was the sole predictor. Conclusion Scar heterogeneity, quantified by mean entropy using CMR-TA, was an independent predictor of appropriate ICD therapy in the mixed cardiomyopathy cohort and ICM-only group, suggesting a potential role for CMR-TA in predicting ventricular arrhythmia and risk-stratifying patients for ICD implantation.