A comprehensive framework for evaluation of high pacing frequency and arrhythmic optical mapping signals

Girish S Ramlugun; Kanchan Kulkarni; Nestor Pallares-Lupon; Bastiaan J Boukens; Igor R Efimov; Edward J Vigmond; Olivier Bernus; Richard D Walton

doi:10.3389/fphys.2023.734356

A comprehensive framework for evaluation of high pacing frequency and arrhythmic optical mapping signals

Front Physiol. 2023 Jan 23:14:734356. doi: 10.3389/fphys.2023.734356. eCollection 2023.

Authors

Girish S Ramlugun^{1

2}, Kanchan Kulkarni^{1

2}, Nestor Pallares-Lupon^{1

2}, Bastiaan J Boukens^{3

4}, Igor R Efimov^{5

6

7}, Edward J Vigmond^{1

8}, Olivier Bernus^{1

2}, Richard D Walton^{1

2}

Affiliations

¹ IHU-Liryc, Fondation Bordeaux Université, Pessac-Bordeaux, France.
² Univ. Bordeaux, Inserm, Centre de Recherche Cardio-Thoracique, Bordeaux, France.
³ Department of Physiology, Cardiovascular Research Institute Maastricht, University Maastricht, Maastricht, Netherlands.
⁴ Department of Medical Biology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, Netherlands.
⁵ Department of Biomedical Engineering, The George Washington University, Washington, DC, United States.
⁶ Department of Biomedical Engineering, Northwestern University, Chicago, IL, United States.
⁷ Department of Medicine, Northwestern University, Chicago, IL, United States.
⁸ Univ. Bordeaux, Centre National de la Recherche Scientifique (CNRS), Institut de Mathématiques de Bordeaux, UMR5251, Bordeaux, France.

Abstract

Introduction: High pacing frequency or irregular activity due to arrhythmia produces complex optical mapping signals and challenges for processing. The objective is to establish an automated activation time-based analytical framework applicable to optical mapping images of complex electrical behavior. Methods: Optical mapping signals with varying complexity from sheep (N = 7) ventricular preparations were examined. Windows of activation centered on each action potential upstroke were derived using Hilbert transform phase. Upstroke morphology was evaluated for potential multiple activation components and peaks of upstroke signal derivatives defined activation time. Spatially and temporally clustered activation time points were grouped in to wave fronts for individual processing. Each activation time point was evaluated for corresponding repolarization times. Each wave front was subsequently classified based on repetitive or non-repetitive events. Wave fronts were evaluated for activation time minima defining sites of wave front origin. A visualization tool was further developed to probe dynamically the ensemble activation sequence. Results: Our framework facilitated activation time mapping during complex dynamic events including transitions to rotor-like reentry and ventricular fibrillation. We showed that using fixed AT windows to extract AT maps can impair interpretation of the activation sequence. However, the phase windowing of action potential upstrokes enabled accurate recapitulation of repetitive behavior, providing spatially coherent activation patterns. We further demonstrate that grouping the spatio-temporal distribution of AT points in to coherent wave fronts, facilitated interpretation of isolated conduction events, such as conduction slowing, and to derive dynamic changes in repolarization properties. Focal origins precisely detected sites of stimulation origin and breakthrough for individual wave fronts. Furthermore, a visualization tool to dynamically probe activation time windows during reentry revealed a critical single static line of conduction slowing associated with the rotation core. Conclusion: This comprehensive analytical framework enables detailed quantitative assessment and visualization of complex electrical behavior.

Keywords: electrophysiology; fibrillation; image processing; optical mapping; pacing.

Grants and funding

This study received financial support from the French Government as part of the “Investments of the Future” program managed by the National Research Agency (ANR), Grant reference ANR-10-IAHU-04, funding from the European Research Area in Cardiovascular Diseases (ERA-CVD), grant reference H2020-HCO-2015_680969 (MultiFib), funding from the French Region Nouvelle Aquitaine, grant references 2016–1R 30113 0000 7550/2016-1R 30113 0000 7553, and ANR-19-ECVD-0006-01, and funding from the Leducq Foundation, grant reference 16CVD02 (RHYTHM).