Computational models with ±10% variability in electrophysiological parameters predicted 76.2-100% of ventricular tachycardia ablation targets in the same locations as models using average parameters.
Does variability in electrophysiological parameters (action potential duration and conduction velocity) alter predicted ablation targets in patient-specific computational models of post-infarction ventricular tachycardia?
Personalized ventricular modeling with an average representation of infarct-remodeled electrophysiology can reliably identify most targets for VT ablation, as localization is primarily driven by structural substrate.
Ventricular tachycardia (VT), which could lead to sudden cardiac death, occurs frequently in patients with myocardial infarction. Computational modeling has emerged as a powerful platform for the non-invasive investigation of lethal heart rhythm disorders in post-infarction patients and for guiding patient VT ablation. However, it remains unclear how VT dynamics and predicted ablation targets are influenced by inter-patient variability in action potential duration (APD) and conduction velocity (CV). The goal of this study was to systematically assess the effect of changes in the electrophysiological parameters on the induced VTs and predicted ablation targets in personalized models of post-infarction hearts. Simulations were conducted in 5 patient-specific left ventricular models reconstructed from late gadolinium-enhanced magnetic resonance imaging scans. We comprehensively characterized all possible pre-ablation and post-ablation VTs in simulations conducted with either an "average human VT"-based electrophysiological representation (i.e., EPavg) or with ±10% APD or CV (i.e., EPvar); additional simulations were also executed in some models for an extended range of these paramaters. The results showed that: 1) a subset of reentries (76.2%–100%, depending on EP parameter set) conducted with ±10% APD/CV was observed in approximately the same locations as reentries observed in EPavg cases; 2) emergent VTs could be induced sometimes after ablation in EPavg models, and these emergent VTs often corresponded to the pre-ablation reentries in simulations with EPvar parameter sets. These findings demonstrate that the VT ablation target uncertainty in patient-specific ventricular models with an average representation of VT-remodeled electrophysiology is relatively low and the ablation targets stable, as the localization of the induced VTs was primarily driven by the remodeled structural substrate. Thus, personalized ventricular modeling with an average representation of infarct-remodeled electrophysiology may uncover most targets for VT ablation.
Deng et al. (2019) studied Ventricular tachycardia (post-infarction) (n=5). Computational modeling with variable electrophysiological parameters (±10% APD or CV) vs. Computational modeling with average human VT electrophysiology (EPavg) was evaluated on Overlap of induced VT reentry locations (ablation targets) compared to EPavg models. Computational models with ±10% variability in electrophysiological parameters predicted 76.2-100% of ventricular tachycardia ablation targets in the same locations as models using average parameters.