Personalized Computational Modeling of Left Atrial Substrate in Persistent Atrial Fibrillation: Insights from the...

Atrial fibrillation (AF) is the most common sustained arrhythmia and is often treated with catheter ablation targeting pulmonary vein isolation. However, recurrence rates remains high, suggesting the involvement of additional arrhythmogenic mechanisms beyond the pulmonary veins. In this study, we present a patient-specific computational modeling pipeline for the left atrium, integrating electroanatomical CARTO mapping and CT imaging. A key aspect of our approach is the calibration of the model using clinical local activation times (LATs) recorded during a triple extrastimulation protocol, which enables the assessment of conduction dynamics under progressively increased electrical stress. Our findings suggest that incorporating fibrosis distribution improves LAT synchronization with clinical data; however, reproducing the conduction slowing observed with triple stimulation likely requires personalized electrophysiological models, as structural remodeling alone appears insufficient. This highlights the need for a more comprehensive approach that accounts for both anatomical and cellular electrophysiological variability to enhance patient-specific stratification and ablation planning.Clinical relevance- Personalized computational models integrating both structural and electrophysiological remodeling may improve patient stratification and guide ablation strategies by better predicting conduction abnormalities under different pacing protocols.