Electrocardiographic imaging for atrial fibrillation: a perspective from computer models and animal experiments to clinical value

Salinet, J, Molero, R, Schlindwein, FS, Karel, J, Rodrigo, M, Luis Rojo-Álvarez, J, Berenfeld, O, Climent, A, Zenger, B, Vanheusden, FJ ORCID: https://orcid.org/0000-0003-2369-6189, Paredes, JG, Macleod, R, Atienza, F, Guillem, MS, Cluitmans, M and Bonizzi, P, 2021. Electrocardiographic imaging for atrial fibrillation: a perspective from computer models and animal experiments to clinical value. Frontiers in Physiology, 12: 653013. ISSN 1664-042X

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Abstract

Electrocardiographic imaging (ECGI) is a technique to reconstruct noninvasively the electrical activity on the heart surface from body-surface potential recordings and geometric information of the torso and the heart. ECGI has shown scientific and clinical value when used to characterize and treat both atrial and ventricular arrhythmias. Regarding atrial fibrillation (AF), the characterization of the electrical propagation and the underlying substrate favouring AF is inherently more challenging than for ventricular arrhythmias, due to the progressive and heterogeneous nature of the disease and its manifestation, the small volume and wall thickness of the atria, and the relatively large role of microstructural abnormalities in AF. At the same time, ECGI has the advantage over other mapping technologies of allowing a global characterization of atrial electrical activity at every atrial beat and noninvasively. However, since ECGI is time-consuming and costly and the use of electrical mapping to guide AF ablation is still not fully established, the clinical value of ECGI for AF is still under assessment. Nonetheless, AF is known to be the manifestation of a complex interaction between electrical and structural abnormalities and therefore, true electro-anatomical-structural imaging may elucidate important key factors of AF development, progression, and treatment. Therefore, it is paramount to identify which clinical questions could be successfully addressed by ECGI when it comes to AF characterization and treatment, and which questions may be beyond its technical limitations. In this manuscript we review the questions that researchers have tried to address on the use of ECGI for AF characterization and treatment guidance (for example, localization of AF triggers and sustaining mechanisms), and we discuss the technological requirements and validation. We address experimental and clinical results, limitations, and future challenges for fruitful application of ECGI for AF understanding and management. We pay attention to existing techniques and clinical application, to computer models and (animal or human) experiments, to challenges of methodological and clinical validation. The overall objective of the study is to provide a consensus on valuable directions that ECGI research may take to provide future improvements in AF characterization and treatment guidance.

Item Type:	Journal article
Publication Title:	Frontiers in Physiology
Creators:	Salinet, J., Molero, R., Schlindwein, F.S., Karel, J., Rodrigo, M., Luis Rojo-Álvarez, J., Berenfeld, O., Climent, A., Zenger, B., Vanheusden, F.J., Paredes, J.G., Macleod, R., Atienza, F., Guillem, M.S., Cluitmans, M. and Bonizzi, P.
Publisher:	Frontiers Media
Date:	30 April 2021
Volume:	12
ISSN:	1664-042X
Identifiers:	Number Type 10.3389/fphys.2021.653013 DOI 1427158 Other
Rights:	Copyright © 2021 Salinet, Molero, Schlindwein, Karel, Rodrigo, Rojo-Álvarez, Berenfeld, Climent, Zenger, Vanheusden, Paredes, MacLeod, Atienza, Guillem, Cluitmans and Bonizzi. 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) and the copyright owner(s) 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.
Divisions:	Schools > School of Science and Technology
Record created by:	Jeremy Silvester
Date Added:	01 Apr 2021 11:54
Last Modified:	31 May 2021 15:03
URI:	https://irep.ntu.ac.uk/id/eprint/42650

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