Personalisation of Action Potentials Based on Activation Recovery Intervals in Post-Infarcted Pigs: A Simulation Study

Cardiac modeling is a powerful and robust tool in electrophysiology (EP), supporting non-invasive arrhythmia diagnosis and therapy planning.Some studies showed that in silico modeling can be used to predict scar-related arrhythmia risk and ablation targets.However, model personalisation still relies on "average" EP parameters derived from literature, largely due to a paucity of their identification from EP data.We posit that activation-recovery interval (ARI), a surrogate for action potential duration (APD), can be extracted from intracardiac electrograms (iEGMs) and used to parameterize models for more accurate AP wave simulations per individual case.In this work we personalised APDs using ARI values extracted from endocardial electro-anatomical maps recorded in sinus rhythm in post-infarcted swine (n=8).We sought to investigate the differences in model parameters needed to calibrate simulated APDs in healthy tissue and border zone, BZ (i.e., arrhythmia substrate) when using an "average" ARI computed from all cases versus those calibrated from ARIs extracted per case.Results showed that average ARIs in healthy tissue and BZ for all cases were 206.12 50.18 ms and 213.21 52.1 ms, respectively.This work underlines the importance of model personalisation by case, suggesting that is fundamentally needed to accurately reproduce in silico the experimental observations.