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Post-Processing of Electrocardiographic Imaging Signals to Identify Atrial Fibrillation Drivers

Authors :
Maria S. Guillem
Ruben Molero
Andreu M. Climent
Source :
CinC
Publication Year :
2020
Publisher :
Computing in Cardiology, 2020.

Abstract

Phase mapping of inverse-computed electrograms (ECGI) is used for rotor activity identification to guide ablation procedures in atrial fibrillation (AF) patients. This study aims at identifying the post-processing settings that best allow tracking meaningful rotors. ECGI signals of 24 AF patients prior to pulmonary vein isolation (PVI) were recorded. Patients were divided according to their 6 months outcome (sinus vs. no sinus). Rotor metrics were compared using 3 types of processing: none, a narrow band-pass filtering centered at the highest dominant frequency (NB HDF), and sinusoidal recomposition filtering (SRC). Different thresholds for rotor duration were also compared (0.5, 1, and 1.5 turns). Differences in the absolute error of rotor metrics between sinus and no sinus patients were best identified with raw ECGI signals than filtered ECGI signals. In contrast, rotor duration threshold had little effect on the statistical differentiation between groups. Filtering of AF ECGI signals does not improve rotor identification to predict PVI outcome.

Details

ISSN :
2325887X
Database :
OpenAIRE
Journal :
2020 Computing in Cardiology Conference (CinC)
Accession number :
edsair.doi...........ffa44a229a76bf6ece050690af1e8ea7
Full Text :
https://doi.org/10.22489/cinc.2020.113