Constructing Virtual Patient Cohorts for Simulating Atrial Fibrillation Ablation

Caroline H. Roney*, Marianne Beach, Arihant Mehta, Iain Sim, Cesare Corrado, Rokas Bendikas, Jose A. Solis-Lemus, Orod Razeghi, John Whitaker, Louisa O. O'Neill, Gernot Plank, Edward Vigmond, Steven E. Williams, Mark D. O'Neill, Steven A. Niederer

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

3 Citations (Scopus)


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.

Original languageEnglish
Title of host publication2020 Computing in Cardiology, CinC 2020
PublisherIEEE Computer Society
ISBN (Electronic)9781728173825
Publication statusPublished - 13 Sept 2020
Event2020 Computing in Cardiology, CinC 2020 - Rimini, Italy
Duration: 13 Sept 202016 Sept 2020

Publication series

NameComputing in Cardiology
ISSN (Print)2325-8861
ISSN (Electronic)2325-887X


Conference2020 Computing in Cardiology, CinC 2020


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