Constructing Virtual Patient Cohorts for Simulating Atrial Fibrillation Ablation

Determining the optimal treatment approach for patients with atrial fibrillation (AF) is challenging as patient-specific mechanisms underlying the arrhythmia are typically unknown. Virtual patient cohort simulations can be used to investigate these mechanisms and the effects of atrial anatomy, electrical and structural substrate on potential AF ablation treatment outcomes. It is important that virtual cohort models are constructed using a consistent and reproducible approach regardless of the large variability in atrial morphology between patients. This allows comparison of virtual ablation outcomes between cases. In this study we developed a standardised pipeline for constructing personalised biophysical left atrial models using segmented late-gadolinium enhancement magnetic resonance imaging (LGE-MRI) data. Fibrotic remodelling was incorporated according to the distribution of LGE intensity values as changes in conductivity and ionic cell model properties. We present a methodology for simulating AF: seeding four spiral wave re-entries at standard locations across the anatomies; and for testing different ablation approaches across a large virtual patient cohort of personalised left atrial models. We simulated pulmonary vein isolation (PVI) ablation across a cohort of 20 paroxysmal and 30 persistent AF patient models.