NDLI: Atrial fibrillation disorganization is reduced by catheter ablation: A standard ECG study

Content Provider	IEEE Xplore Digital Library
Author	Bonizzi, P. Meste, O. Zarzoso, V. Latcu, D.G. Popescu, I. Ricard, P. Saoudi, N.
Copyright Year	2010
Description	Author affiliation: Centre Hospitalier Princesse G., 1, Avenue Pasteur BP 489 - MC 98012 MONACO Cedex, France (Latcu, D.G.; Popescu, I.; Ricard, P.; Saoudi, N.) \|\| Laboratoire I3S, UNSA/CNRS, 2000 Route des Lucioles, Les Algorithmes Euclide B, B.P. 121, 06903 Sophia Antipolis Cedex, France (Bonizzi, P.; Meste, O.; Zarzoso, V.)
Abstract	Selection of candidates to catheter ablation (CA) of long-lasting persistent atrial fibrillation (AF) is challenging, since success is not guaranteed. In this study, we put forward an automated method for noninvasively evaluating the reduction of the complexity of the AF organization following CA. Complexity is meant as the amount of disorganization observed on the ECG, supposed to be directly correlated to the number and interactions of atrial wavefronts. By means of PCA, the complexity of the AF organization is evaluated quantitatively from a 12-lead ECG recording. Preliminary results show that CA is able to reduce the complexity of AF organization in the atrial wavefront pattern propagation, despite the persistence of AF in most cases. This can be viewed as a first clinical validation of this parameter. Whether AF complexity and its reduction by CA are predictive of long-term outcome is thus still to be determined.
Starting Page	5286
Ending Page	5289
File Size	311491
Page Count	4
File Format	PDF
ISBN	9781424441235
ISSN	1557170X
DOI	10.1109/IEMBS.2010.5626335
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-31
Publisher Place	Argentina
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Complexity theory Electrocardiography Organizations Correlation Principal component analysis Cardiology Standards organizations
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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