Abstract 10034: Novel Late-Gadolinium Enhanced Cardiac Magnetic Resonance (LGE-CMR)-Based Computational Heart Paradigm Predicts Optimal Ventricular Tachycardia (VT) Ablation Targets in Arrhythmogenic Right Ventricular (RV) Cardiomyopathy (ARVC)

Abstract

Introduction: ARVC is an inherited cardiac disease that increases risk of life-threatening VTs in young adults. Catheter ablation, a mainstay of VT treatment in ARVC, remains challenging due to difficulties in identifying optimal VT ablation targets. Hypothesis: Right Ventricular Cardiomyopathy Ablation Targeting (RVCAT) is a novel digital-heart paradigm that accurately predicts the optimal VT ablation targets of ARVC patients. Methods: We retrospectively enrolled 11 ARVC patients; 8 presented with clinical VTs and underwent VT ablation. In all patients, RV hyperenhancement on LGE-CMR was identified. For this study, we developed RVCAT, the first computational heart model integrating RV personalized diffuse and dense fibrosis as VT substrates. Each region was assigned ARVC-specific electrophysiologic properties. VT inducibility was assessed via rapid pacing in each model. If inducible, optimal ablation targets, which rendered the RV substrate non-inducible for each VT, were determined. Targets were compared to electroanatomic voltage maps (EAM), locations of clinical ablations, and clinical records. Results: Personalized model predictions correlated well with clinical observations. All 8 models of the patients with a history of clinical VT had inducible VTs (Fig A). Furthermore, model VT circuit locations matched the clinical description. Substrate distribution in models matched low-voltage zones in EAM. The predicted ablation targets coincided with clinical ablations (Fig B). Results showed that the volume of model ablation lesions was significantly smaller than that of clinical ablations (1.02±0.68 versus 1.45±0.91, p<0.05, Fig C). For the 3 patients who did not have VTs, their corresponding heart models correctly predicted that no VTs would be induced. Conclusions: RVCAT is a novel digital-heart technology for optimal ARVC VT ablation guidance that can be potentially integrated into clinical workflows for augmenting therapeutic precision.