An image-based framework for in silico trials of ablation strategies in scar-related ventricular tachycardia

Authors

Biasi, N., Parollo, M., Vultaggio, D. M., Zucchelli, G., Tognetti, A.

Abstract

Scar-related ventricular tachycardia (VT) is sustained by patient-specific structural and functional remodeling of the ventricular substrate, and the optimal substrate-based ablation strategy remains debated. We present an image-based computational framework for conducting controlled in silico trials of VT ablation strategies. Patient-specific left ventricular electrophysiology models were generated from late gadolinium enhancement cardiac magnetic resonance images by incorporating image-derived scar, border-zone tissue with structural fibrosis, fiber orientation, and physiologically plausible Purkinje-driven sinus activation. A dedicated standalone graphical user interface was developed to perform interactive virtual ablation based on imaging-derived or simulated electrophysiological data. We implemented standardized VT reinducibility testing to compare different lesion sets in terms of residual VT inducibility and ablation burden. As a proof of concept, the framework was applied to 20 patients with ischemic or non-ischemic cardiomyopathy undergoing VT ablation. Sustained VT was inducible in 17 patients, yielding 127 sustained VT episodes and 88 unique reentrant circuits at baseline. Four substrate-based ablation strategies were compared: scar homogenization, primary deceleration-zone ablation, primary plus secondary deceleration-zone ablation, and CMR-guided scar dechanneling. All strategies significantly reduced VT inducibility compared with baseline. Scar homogenization achieved the largest reduction in residual unique sustained VTs but required the largest ablated myocardial volume. Conversely, CMR-guided scar dechanneling showed the most favorable efficiency profile by reducing VT inducibility while limiting ablated viable myocardium. The proposed framework enables quantitative comparison of ablation efficacy, ablation burden, and mechanisms of ablation success or failure in image-guided VT therapy planning.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 07 Aug 2026.

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