An Automata-Based Cardiac Electrophysiology Simulator to Assess Arrhythmia Inducibility

Dolors Serra, Pau Romero, Ignacio Garcia-Fernandez, Miguel Lozano, Alejandro Liberos, Miguel Rodrigo, Alfonso Bueno-Orovio, Antonio Berruezo and Rafael Sebastian
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Dolors Serra: CoMMLab, Universitat de València, 46100 Valencia, Spain
Pau Romero: CoMMLab, Universitat de València, 46100 Valencia, Spain
Ignacio Garcia-Fernandez: CoMMLab, Universitat de València, 46100 Valencia, Spain
Miguel Lozano: CoMMLab, Universitat de València, 46100 Valencia, Spain
Alejandro Liberos: CoMMLab, Universitat de València, 46100 Valencia, Spain
Miguel Rodrigo: CoMMLab, Universitat de València, 46100 Valencia, Spain
Alfonso Bueno-Orovio: Department of Computer Science, University of Oxford, Oxford OX1 3QD, UK
Antonio Berruezo: Cardiology Department, Heart Institute, Teknon Medical Center, 08022 Barcelona, Spain
Rafael Sebastian: CoMMLab, Universitat de València, 46100 Valencia, Spain

Mathematics, 2022, vol. 10, issue 8, 1-21

Abstract: Personalized cardiac electrophysiology simulations have demonstrated great potential to study cardiac arrhythmias and help in therapy planning of radio-frequency ablation. Its application to analyze vulnerability to ventricular tachycardia and sudden cardiac death in infarcted patients has been recently explored. However, the detailed multi-scale biophysical simulations used in these studies are very demanding in terms of memory and computational resources, which prevents their clinical translation. In this work, we present a fast phenomenological system based on cellular automata (CA) to simulate personalized cardiac electrophysiology. The system is trained on biophysical simulations to reproduce cellular and tissue dynamics in healthy and pathological conditions, including action potential restitution, conduction velocity restitution and cell safety factor. We show that a full ventricular simulation can be performed in the order of seconds, emulate the results of a biophysical simulation and reproduce a patient’s ventricular tachycardia in a model that includes a heterogeneous scar region. The system could be used to study the risk of arrhythmia in infarcted patients for a large number of scenarios.

Keywords: cellular automata; cardiac electrophysiology simulation; therapy planning; arrhythmia (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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