ArticleFrontiers in physiology2021
A Computational Study of the Electrophysiological Substrate in Patients Suffering From Atrial Fibrillation.
Article in Frontiers in physiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 17 citations in OpenAlex.
- An eikonal model with re-excitability for fast simulations in cardiac electrophysiology.The Journal of physiology · 2026Article
- The functional impact of myofiber macroscopic organization and disarray in computational models of the murine heart.PLoS computational biology · 2026Article
- A systematic review of explainable artificial intelligence and cardiac electrophysiological models addressing sports-related sudden cardiac death and arrest in adolescents and young adults.NPJ digital medicine · 2026Article
- Defining myocardial fiber bundle architecture in atrial digital twins.Computers in biology and medicine · 2025Article
- Article
- A possible path to persistent re-entry waves at the outlet of the left pulmonary vein.NPJ systems biology and applications · 2024Article
- [Developments of ex vivo cardiac electrical mapping and intelligent labeling of atrial fibrillation substrates].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2024Review
- Overcoming Uncertainties in Electrogram-Based Atrial Fibrillation Mapping: A Review.Cardiovascular engineering and technology · 2024Review
- The role of computational methods in cardiovascular medicine: a narrative review.Translational pediatrics · 2024Review
- A Review of Personalised Cardiac Computational Modelling Using Electroanatomical Mapping Data.Arrhythmia & electrophysiology review · 2024Review
- lifex-ep: a robust and efficient software for cardiac electrophysiology simulations.BMC bioinformatics · 2023Article
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Authors and funding
11 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the context of cardiac electrophysiology, we propose a novel computational approach to highlight and explain the long-debated mechanisms behind atrial fibrillation (AF) and to reliably numerically predict its induction and sustainment. A key role is played, in this respect, by a new way of setting a parametrization of electrophysiological mathematical models based on conduction velocities; these latter are estimated from high-density mapping data, which provide a detailed characterization of patients' electrophysiological substrate during sinus rhythm. We integrate numerically approximated conduction velocities into a mathematical model consisting of a coupled system of partial and ordinary differential equations, formed by the monodomain equation and the Courtemanche-Ramirez-Nattel model. Our new model parametrization is then adopted to predict the formation and self-sustainment of localized reentries characterizing atrial fibrillation, by numerically simulating the onset of ectopic beats from the pulmonary veins. We investigate the paroxysmal and the persistent form of AF starting from electro-anatomical maps of two patients. The model's response to stimulation shows how substrate characteristics play a key role in inducing and sustaining these arrhythmias. Localized reentries are less frequent and less stable in case of paroxysmal AF, while they tend to anchor themselves in areas affected by severe slow conduction in case of persistent AF.
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