Unifying automated fractionated atrial electrogram classification using electroanatomical mapping systems in persistent atrial fibrillation studies

Almeida, TP, Chu, GS, Salinet, JL, Vanheusden, FJ ORCID: https://orcid.org/0000-0003-2369-6189, Li, X, Tuan, JH, Stafford, PJ, Ng, GA and Schlindwein, FS, 2015. Unifying automated fractionated atrial electrogram classification using electroanatomical mapping systems in persistent atrial fibrillation studies. In: Murray, A, ed., Computing in Cardiology Conference 2015. Computing in Cardiology, 42 . Piscataway, N.J.: IEEE, pp. 53-56. ISBN 9781509006854

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Abstract

Ablation targeting complex fractionated atrial electrograms (CFAE) for treating persistent atrial fibrillation (persAF) has shown conflicting results. Differences in automated algorithms embedded in NavX (St Jude Medical) and CARTO (Biosense Webster) could influence CF AE target identification for ablation, potentially affecting ablation outcomes. To evaluate this effect, automated CFAE classification performed by NavX and CARTO on the same bipolar electrograms from 18 persAF patients undergoing ablation was compared. Using the default thresholds, NavX classified 69±5% of the electrograms as CFAEs, while CARTO detected 35±5%% (Cohen's kappa κ≈0.3, P<0.0001). Both primary and complementary metrics for each system were optimized to balance CF AE detection for both systems. Using revised thresholds found from receiver operating characteristic curves, NavX classified 45±4%, while CARTO detected 42±5% (κ≈0.5, P<0.0001). Our work takes a first step towards the optimization of CFAE detection between NavX and CARTO by providing revised thresholds to reduce differences in CF AE classification. This would facilitate direct comparisons of persAF CFAE-guided ablation outcome guided by NavX or CARTO.

Item Type:	Chapter in book
Description:	Paper presented at 2015 Computing in Cardiology Conference (CinC), Nice, France, 6-9 September 2015.
Creators:	Almeida, T.P., Chu, G.S., Salinet, J.L., Vanheusden, F.J., Li, X., Tuan, J.H., Stafford, P.J., Ng, G.A. and Schlindwein, F.S.
Publisher:	IEEE
Place of Publication:	Piscataway, N.J.
Date:	2015
Volume:	42
ISBN:	9781509006854
ISSN:	2325-887X
Identifiers:	Number Type 10.1109/cic.2015.7408584 DOI
Rights:	Articles in this volume are copyright © 2015 by their respective authors, and are licensed by their authors under the Creative Commons Attribution License 2.5 (CCAL).
Divisions:	Schools > School of Science and Technology
Record created by:	Jonathan Gallacher
Date Added:	12 Dec 2018 11:52
Last Modified:	12 Dec 2018 17:10
URI:	https://irep.ntu.ac.uk/id/eprint/35302

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