Literature DB >> 34878119

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 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.
© The Author(s) 2021. For permissions, please email: journals.permissions@oup.com.

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


  6 in total

Review 1.  Clinical Relevance of Sinus Rhythm Mapping to Quantify Electropathology Related to Atrial Fibrillation.

Authors:  Mathijs S van Schie; Natasja Ms de Groot
Journal:  Arrhythm Electrophysiol Rev       Date:  2022-04

2.  The Relevance of Heart Rate Fluctuation When Evaluating Atrial Substrate Electrical Features in Catheter Ablation of Paroxysmal Atrial Fibrillation.

Authors:  Aikaterini Vraka; José Moreno-Arribas; Juan M Gracia-Baena; Fernando Hornero; Raúl Alcaraz; José J Rieta
Journal:  J Cardiovasc Dev Dis       Date:  2022-06-01

Review 3.  Atrial conduction velocity mapping: clinical tools, algorithms and approaches for understanding the arrhythmogenic substrate.

Authors:  Sam Coveney; Chris Cantwell; Caroline Roney
Journal:  Med Biol Eng Comput       Date:  2022-07-22       Impact factor: 3.079

4.  An Efficient Hybrid Methodology for Local Activation Waves Detection under Complex Fractionated Atrial Electrograms of Atrial Fibrillation.

Authors:  Diego Osorio; Aikaterini Vraka; Aurelio Quesada; Fernando Hornero; Raúl Alcaraz; José J Rieta
Journal:  Sensors (Basel)       Date:  2022-07-18       Impact factor: 3.847

Review 5.  Machine learning in the detection and management of atrial fibrillation.

Authors:  Felix K Wegner; Lucas Plagwitz; Florian Doldi; Christian Ellermann; Kevin Willy; Julian Wolfes; Sarah Sandmann; Julian Varghese; Lars Eckardt
Journal:  Clin Res Cardiol       Date:  2022-03-30       Impact factor: 6.138

6.  Omnipolar activation EGM to identify the earliest breakout site of atrial tachycardia.

Authors:  Colin Yeo; Vern Hsen Tan; Yue Wang
Journal:  J Arrhythm       Date:  2022-07-12
  6 in total

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