The study presents an image-based computational framework designed to perform controlled in silico trials comparing substrate-based ablation strategies for scar-related ventricular tachycardia (VT). The aim is to enable quantitative comparison of ablation efficacy, the amount of myocardium ablated (ablation burden), and the mechanisms underlying ablation success or failure in planning image-guided VT therapy.
Patient left ventricular electrophysiology models were generated from late gadolinium enhancement cardiac magnetic resonance (LGE-CMR) images. Image-derived components included delineation of dense scar and border-zone tissue. The pipeline incorporated structural fibrosis within border-zone regions as inferred from imaging to represent substrates relevant to scar-related VT.
Models integrated myocardial fiber orientation together with a physiologically plausible Purkinje-driven sinus activation to simulate native ventricular activation. These electrophysiological components were used to produce realistic baseline activation and to support reinducibility testing of ventricular arrhythmias in silico.
A dedicated standalone graphical user interface (GUI) was developed to permit interactive virtual ablation. The GUI accepts imaging-derived or simulated electrophysiological data as guidance for creating lesion sets. It provides an environment to apply lesion patterns, run post-ablation simulations, and record outcomes for standardized comparison across different strategies.
The framework implements standardized VT reinducibility testing to evaluate the effects of different lesion sets. Outcomes quantified include residual VT inducibility, the total number of sustained VT episodes, the number of unique reentrant circuits, and the volume of myocardium ablated (ablation burden). These standardized metrics enable head-to-head comparison of strategies within the same patient-specific substrate.
As a proof of concept, the authors applied the framework to a cohort of 20 patients with ischemic or non-ischemic cardiomyopathy who were undergoing VT ablation. At baseline (before virtual ablation), sustained VT was inducible in 17 of the 20 patients. Across those inducible patients the simulations yielded 127 sustained VT episodes and identified 88 unique reentrant circuits.
Four substrate-based ablation strategies were implemented and compared within the same modeling and testing pipeline:
Each strategy was applied virtually to each patient model and followed by standardized reinducibility testing to measure residual arrhythmia and ablated tissue volume.
All tested strategies produced a significant reduction in VT inducibility compared with baseline simulations. Key comparative findings reported in the source include:
Scar homogenization achieved the largest decrease in the number of residual unique sustained VTs, indicating high efficacy in eliminating reentrant circuits. However, it required the largest ablated myocardial volume, reflecting a high ablation burden.
CMR-guided scar dechanneling reduced VT inducibility while limiting the volume of viable myocardium ablated, demonstrating the most favorable efficiency profile among the strategies tested.
The primary and combined deceleration-zone approaches also reduced inducibility, but detailed numerical comparisons between those and other strategies beyond the categorical findings above were not reported in the abstract.
By combining image-derived structural detail with electrophysiological simulation and interactive lesion placement, the framework enables mechanistic analysis of how different lesion sets interrupt reentrant circuits or fail to do so. The results indicate a trade-off between efficacy (removing more circuits) and ablation burden (ablating more viable tissue): scar homogenization maximizes elimination of inducible VTs at the cost of larger lesions, while CMR-guided scar dechanneling preserves more myocardium while still lowering inducibility.
The proposed framework provides a tool to quantitatively compare ablation strategies in patient-specific substrates derived from LGE-CMR. It supports interactive planning and standardized post-ablation evaluation, offering measures of both procedural efficacy and tissue-sparing efficiency. As demonstrated in a 20-patient proof-of-concept application, the approach can identify strategy-specific profiles—such as high efficacy with high ablation burden for scar homogenization versus favorable efficiency for CMR-guided scar dechanneling—that may inform strategy selection in image-guided VT therapy planning.
Note on reported details and limitations
The content above summarizes findings and methods as reported in the source abstract and accompanying information. Additional numerical data, statistical testing details, full methodological parameters, and limitations beyond what is reported in the abstract and article metadata were not reported in the provided source text.