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ORIGINAL RESEARCH article

Front. Cardiovasc. Med.
Sec. Cardiac Rhythmology
Volume 11 - 2024 | doi: 10.3389/fcvm.2024.1408822
This article is part of the Research Topic The Role of Electrocardiogram in Prediction of Cardiovascular and non-Cardiovascular Health Outcomes View all 7 articles

ECG analysis of ventricular fibrillation dynamics reflects ischemic progression subject to variability in patient anatomy and electrode location

Provisionally accepted
Hector Martinez-Navarro Hector Martinez-Navarro 1*Ambre Bertrand Ambre Bertrand 1Ruben Doste Ruben Doste 1Hannah Smith Hannah Smith 1Jakub Tomek Jakub Tomek 2Giuseppe Ristagno Giuseppe Ristagno 3Rafael Sachetto Oliveira Rafael Sachetto Oliveira 4Rodrigo Weber dos Santos Rodrigo Weber dos Santos 5Sandeep V Pandit Sandeep V Pandit 6Blanca Rodriguez Blanca Rodriguez 1*
  • 1 Department of Computer Science, British Heart Foundation Centre of Research Excellence, University of Oxford, Oxford, England, United Kingdom
  • 2 Department of Physiology, Anatomy and Genetics, British Heart Foundation Centre of Research Excellence, University of Oxford, Oxford, United Kingdom
  • 3 Dipartimento di Fisiopatologia Medico-Chirurgica e dei Trapianti, Università degli Studi di Milano Statale, Milan, Italy
  • 4 Computer Science Department, Universidade Federal de São João del Rei, São João del Rei, Brazil
  • 5 Departamento de Ciência da Computação, Universidade Federal de Juiz de Fora, Juiz de Fora, Brazil
  • 6 ZOLL Medical Corporation, Chelmsford MA, United States

The final, formatted version of the article will be published soon.

    Background: Ventricular fibrillation (VF) is the deadliest arrhythmia, often caused by myocardial ischemia. VF patients require urgent intervention planned quickly and non-invasively. However, the accuracy with which ECG markers reflect the underlying arrhythmic substrate is unknown. Methods: We analysed how ECG metrics reflect the fibrillatory dynamics of electrical excitation and ischemic substrate. For this, we developed a human-based computational modelling and simulation framework for the quantification of ECG metrics, namely frequency, slope and amplitude spectrum analysis (AMSA) during VF in acute ischemia for several electrode configurations. Simulations reproduced experimental and clinical findings in 21 scenarios presenting variability in the location and transmural extent of regional ischemia, and severity of ischemia in the remote myocardium secondary to VF. Results: Regional acute myocardial ischemia facilitated reentries, potentially breaking up into VF. Ischemia in the remote myocardium modulated fibrillation dynamics. Cases presenting a mildly ischemic remote myocardium yielded sustained VF, enabled by the high proliferation of phase singularities (11-22 PS) causing remarkably disorganised activation patterns. Conversely, global acute ischemia, induced stable rotors instead (3-12 PS). Changes in frequency and morphology of the ECG during VF reproduced clinical findings but did not show a direct correlation with the underlying wave dynamics. The Amplitude Spectral Area (AMSA) allowed the precise stratification of VF according to ischemic severity in the remote myocardium (healthy: 23.62-24.45 mV-Hz; mild ischemia: 10.58-21.47 mV-Hz; moderate ischemia: 4.82-11.12 mV-Hz). Within the context of clinical reference values, apex-anterior and apex-posterior electrode configurations were the most discriminatory in stratifying VF based on the underlying ischemic substrate. Conclusion: This in silico study provides further insights into noninvasive patient-specific strategies for assessing acute ventricular arrhythmias. The use of reliable ECG markers to characterise VF is critical for developing tailored resuscitation strategies.

    Keywords: Cardiac Electrophysiology, Modelling and simulation, Ventricular Fibrillation, Myocardial Ischemia, arrhythmia, electrocardiogram. (Min.5-Max. 8)

    Received: 28 Mar 2024; Accepted: 04 Nov 2024.

    Copyright: © 2024 Martinez-Navarro, Bertrand, Doste, Smith, Tomek, Ristagno, Oliveira, Weber dos Santos, Pandit and Rodriguez. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Hector Martinez-Navarro, Department of Computer Science, British Heart Foundation Centre of Research Excellence, University of Oxford, Oxford, England, United Kingdom
    Blanca Rodriguez, Department of Computer Science, British Heart Foundation Centre of Research Excellence, University of Oxford, Oxford, England, United Kingdom

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.