King's College London

Research portal

Constructing Virtual Patient Cohorts for Simulating Atrial Fibrillation Ablation

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

Original languageEnglish
Title of host publication2020 Computing in Cardiology, CinC 2020
PublisherIEEE Computer Society
ISBN (Electronic)9781728173825
Published13 Sep 2020
Event2020 Computing in Cardiology, CinC 2020 - Rimini, Italy
Duration: 13 Sep 202016 Sep 2020

Publication series

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


Conference2020 Computing in Cardiology, CinC 2020

Bibliographical note

Publisher Copyright: © 2020 Creative Commons; the authors hold their copyright. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

King's Authors


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.

View graph of relations

© 2020 King's College London | Strand | London WC2R 2LS | England | United Kingdom | Tel +44 (0)20 7836 5454