| Literature DB >> 34878119 |
Natasja M S de Groot1, Dipen Shah2, Patrick M Boyle3, Elad Anter4, Gari D Clifford5, Isabel Deisenhofer6, Thomas Deneke7, Pascal van Dessel8, Olaf Doessel9, Polychronis Dilaveris10, Frank R Heinzel11, Suraj Kapa12, Pier D Lambiase13, Joost Lumens14, Pyotr G Platonov15, Tachapong Ngarmukos16, Juan Pablo Martinez17, Alejandro Olaya Sanchez18, Yoshihide Takahashi19, Bruno P Valdigem20, Alle-Jan van der Veen21, Kevin Vernooy22, Ruben Casado-Arroyo23, Tom De Potter24, Borislav Dinov25, Jedrzej Kosiuk26, Dominik Linz27, Lis Neubeck28, Emma Svennberg29,30, Young-Hoon Kim31, Elaine Wan32, Nestor Lopez-Cabanillas33,34, Emanuela T Locati35, Peter Macfarlane36.
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. Published on behalf of the European Society of Cardiology. All rights reserved.Entities:
Keywords: Atrial fibrillation; Cardiac implantable electronic devices; EHRA position paper; Machine learning; Mapping; Signal processing; Signal recording
Mesh:
Year: 2022 PMID: 34878119 DOI: 10.1093/europace/euab254
Source DB: PubMed Journal: Europace ISSN: 1099-5129 Impact factor: 5.214