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An Automata-Based Cardiac Electrophysiology Simulator to Assess Arrhythmia Inducibility

Author

Listed:
  • 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
    Current address: Dto. Informática, ETSE-UV. Avda. de la Universidad s/n, 46100 Burjassot, Spain.)

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.

Suggested Citation

  • Dolors Serra & Pau Romero & Ignacio Garcia-Fernandez & Miguel Lozano & Alejandro Liberos & Miguel Rodrigo & Alfonso Bueno-Orovio & Antonio Berruezo & Rafael Sebastian, 2022. "An Automata-Based Cardiac Electrophysiology Simulator to Assess Arrhythmia Inducibility," Mathematics, MDPI, vol. 10(8), pages 1-21, April.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:8:p:1293-:d:792948
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    References listed on IDEAS

    as
    1. Hermenegild J. Arevalo & Fijoy Vadakkumpadan & Eliseo Guallar & Alexander Jebb & Peter Malamas & Katherine C. Wu & Natalia A. Trayanova, 2016. "Arrhythmia risk stratification of patients after myocardial infarction using personalized heart models," Nature Communications, Nature, vol. 7(1), pages 1-8, September.
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