Critical appraisal of technologies to assess electrical activity during atrial fibrillation: a position paper from the European Heart Rhythm Association and European Society of Cardiology Working Group on eCardiology in collaboration with the Heart Rhythm Society, Asia Pacific Heart Rhythm Society, Latin American Heart Rhythm Society and Computing in Cardiology

Natasja M.S. de Groot*, Dipen Shah, ESC Scientific Document Group, Patrick M. Boyle, Elad Anter, Gari D. Clifford, Isabel Deisenhofer, Thomas Deneke, Pascal van Dessel, Olaf Doessel, Polychronis Dilaveris, Frank R. Heinzel, Suraj Kapa, Pier D. Lambiase, Joost Lumens, Pyotr G. Platonov, Tachapong Ngarmukos, Juan Pablo Martinez, Alejandro Olaya Sanchez, Yoshihide TakahashiBruno P. Valdigem, Alle Jan van der Veen, Kevin Vernooy, Ruben Casado-Arroyo, Tom De Potter, Borislav Dinov, Jedrzej Kosiuk, Dominik Linz, Lis Neubeck, Emma Svennberg, Young Hoon Kim, Elaine Wan, Nestor Lopez-Cabanillas, Emanuela T. Locati, Peter Macfarlane

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

We aim to provide a critical appraisal of basic concepts underlying signal recording and processing technologies applied for (i) atrial fibrillation (AF) mapping to unravel AF mechanisms and/or identifying target sites for AF therapy and (ii) AF detection, to optimize usage of technologies, stimulate research aimed at closing knowledge gaps, and developing ideal AF recording and processing technologies. Recording and processing techniques for assessment of electrical activity during AF essential for diagnosis and guiding ablative therapy including body surface electrocardiograms (ECG) and endo- or epicardial electrograms (EGM) are evaluated. Discussion of (i) differences in uni-, bi-, and multi-polar (omnipolar/Laplacian) recording modes, (ii) impact of recording technologies on EGM morphology, (iii) global or local mapping using various types of EGM involving signal processing techniques including isochronal-, voltage- fractionation-, dipole density-, and rotor mapping, enabling derivation of parameters like atrial rate, entropy, conduction velocity/direction, (iv) value of epicardial and optical mapping, (v) AF detection by cardiac implantable electronic devices containing various detection algorithms applicable to stored EGMs, (vi) contribution of machine learning (ML) to further improvement of signals processing technologies. Recording and processing of EGM (or ECG) are the cornerstones of (body surface) mapping of AF. Currently available AF recording and processing technologies are mainly restricted to specific applications or have technological limitations. Improvements in AF mapping by obtaining highest fidelity source signals (e.g. catheter-electrode combinations) for signal processing (e.g. filtering, digitization, and noise elimination) is of utmost importance. Novel acquisition instruments (multi-polar catheters combined with improved physical modelling and ML techniques) will enable enhanced and automated interpretation of EGM recordings in the near future.

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