A novel diagnostic tool to identify atrial endo-epicardial asynchrony using signal fingerprinting

Journal Article (2023)
Author(s)

Lu Zhang (Erasmus MC)

Mathijs S. van Schie (Erasmus MC)

Paul Knops (Erasmus MC)

Yannick J.H.J. Taverne (Erasmus MC)

Natasja M.S. de Groot (Erasmus MC, TU Delft - Signal Processing Systems)

Research Group
Signal Processing Systems
Copyright
© 2023 Lu Zhang, Mathijs S. van Schie, Paul Knops, Yannick J.H.J. Taverne, N.M.S. de Groot
DOI related publication
https://doi.org/10.1016/j.hjc.2023.07.006
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 Lu Zhang, Mathijs S. van Schie, Paul Knops, Yannick J.H.J. Taverne, N.M.S. de Groot
Research Group
Signal Processing Systems
Volume number
75
Pages (from-to)
9-20
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Abstract

Objective: Patients with persistent atrial fibrillation (AF) have more electrical endo-epicardial asynchrony (EEA) during sinus rhythm (SR) than patients without AF. Prior mapping studies indicated that particularly unipolar, endo- and/or epicardial electrogram (EGM) morphology may be indicators of EEA. This study aim to develop a novel method for estimating the degree of EEA by using unipolar EGM characteristics recorded from either the endo- and/or epicardium. Methods: Simultaneous endo-epicardial mapping during sinus rhythm was performed in 86 patients. EGM characteristics, including unipolar voltages, low-voltage areas (LVAs), potential types (single, short/long double and fractionated potentials: SP, SDP, LDP and FP) and fractionation duration (FD) of double potentials (DP) and FP were compared between EEA and non-EEA areas. Asynchrony Fingerprinting Scores (AFS) containing quantified EGM characteristics were constructed to estimate the degree of EEA. Results: Endo- and epicardial sites of EEA areas are characterized by lower unipolar voltages, a higher number of LDPs and FPs and longer DP and FP durations. Patients with AF have lower potential voltages in EEA areas, along with alterations in the potential types. The EE-AFS, containing the proportion of endocardial LVAs and FD of epicardial DPs, had the highest predictive value for determining the degree of EEA (AUC: 0.913). Endo- and epi-AFS separately also showed good predictive values (AUC: 0.901 and 0.830 respectively). Conclusions: EGM characteristics can be used to identify EEA areas. AFS can be utilized as a novel diagnostic tool for accurately estimating the degree of EEA. These characteristics potentially indicate AF related arrhythmogenic substrates.