Electrocardiographic Imaging for Atrial Fibrillation: A Perspective From Computer Models and Animal Experiments to Clinical Value

Frontiers in Physiology

Felipe Atienza¹  Matthijs Cluitmans²  Rob MacLeod³  Brian Zenger³  João Salinet⁴  Jimena Gabriela Siles Paredes⁴  Omer Berenfeld⁵  Pietro Bonizzi⁶  Joël Karel⁶  Frederique Vanheusden⁷  José Luis Rojo-Álvarez⁸  Miguel Rodrigo⁹  Andreu M. Climent^1,10  Rubén Molero^1,10  María S. Guillem^1,10  Fernando S. Schlindwein^1,11 

[1] 0Cardiology Department, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón, and Facultad de Medicina, Universidad Complutense de Madrid, Madrid, Spain;1Department of Cardiology, Cardiovascular Research Institute Maastricht, Maastricht University, Maastricht, Netherlands;Biomedical Engineering Department, Scientific Computing and Imaging Institute (SCI), and Cardiovascular Research and Training Institute (CVRTI), The University of Utah, Salt Lake City, UT, United States;Biomedical Engineering, Centre for Engineering, Modelling and Applied Social Sciences (CECS), Federal University of ABC, São Bernardo do Campo, Brazil;Center for Arrhythmia Research, University of Michigan, Ann Arbor, MI, United States;Department of Data Science and Knowledge Engineering, Maastricht University, Maastricht, Netherlands;Department of Engineering, School of Science and Technology, Nottingham Trent University, Nottingham, United Kingdom;Department of Signal Theory and Communications and Telematic Systems and Computation, University Rey Juan Carlos, Madrid, Spain;Electronic Engineering Department, Universitat de València, València, Spain;ITACA Institute, Universitat Politècnica de València, València, Spain;School of Engineering, University of Leicester, United Kingdom and National Institute for Health Research, Leicester Cardiovascular Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom;

关键词: electrocardiographic imaging;    cardiac arrhythmias;    atrial fibrillation;    inverse solution;    AF characterization;    catheter ablation;   

DOI  :  10.3389/fphys.2021.653013

来源: DOAJ

【 摘 要 】

Electrocardiographic imaging (ECGI) is a technique to reconstruct non-invasively 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 favoring 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 non-invasively. 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.

【 授权许可】

Unknown