Introduction: Atrial fibrillation (AF) is sustained by a combination of structural and electrophysiological features, including atrial fibrosis and anatomical variability. Pulmonary vein (PV) ectopy is a major AF trigger, yet the interplay between ectopic timing, patient-specific fibrosis distribution, and atrial geometry in promoting re-entry remains poorly understood. Computational modelling enables systematic investigation of these mechanisms in patient-specific settings.
Objective: To evaluate how anatomical and fibrotic features influence AF inducibility and dynamics in response to PV ectopic pacing, and whether pacing protocols impact re-entrant driver patterns.
Methods: 20 biatrial models were generated from LGE-MRI scans, with fibrosis mapped using image intensity ratio (IIR) projections and corresponding tissue conductivities adjusted. Simulations were run on both non-fibrotic and fibrotic meshes using the Courtemanche model in openCARP. Pacing was applied at the right superior PV followed by the left at 160, 165, and 170 ms to assess inducibility, defined as the proportion of re-entry occurrences. Anatomical dimensions were measured using PyVista. Phase singularities were tracked over 10s to detect re-entrant activity.
Results: AF inducibility varied across patient-specific anatomical models and was consistently higher in fibrotic compared to non-fibrotic simulations (p= 0.088, not statistically significant). The roof dimension was the only anatomical parameter associated with inducibility; longer roof lengths corresponded to higher re-entry rates, though this trend is not statistically significant. An example is shown in Fig 1. where rotational activity was present in the case with the largest roof but absent in the smallest Fibrotic burden also influenced inducibility, with sustained re-entry observed in the model exhibiting he highest fibrosis distribution (53%).
Conclusion: These findings highlight the critical need to integrate anatomical structure and fibrotic burden in assessing AF susceptibility and optimizing ablation strategies.