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Title: An interactive platform to guide catheter ablation in human persistent atrial fibrillation using dominant frequency, organization and phase mapping
Authors: Li, Xin
Salinet, J. L.
Almeida, Tiago P.
Vanheusden, F. J.
Chu, Gavin S.
Ng, G André
Schlindwein, Fernando S.
First Published: 25-Jan-2017
Publisher: Elsevier
Citation: Computer Methods and Programs in Biomedicine, 2017, 141, pp. 83–92
Abstract: Background and Objective: Optimal targets for persistent atrial fibrillation (persAF) ablation are still debated. Atrial regions hosting high dominant frequency (HDF) are believed to participate in the initiation and maintenance of persAF and hence are potential targets for ablation, while rotor ablation has shown promising initial results. Currently, no commercially available system offers the capability to automatically identify both these phenomena. This paper describes an integrated 3D software platform combining the mapping of both frequency spectrum and phase from atrial electrograms (AEGs) to help guide persAF ablation in clinical cardiac electrophysiological studies. Methods: 30 s of 2048 non-contact AEGs (EnSite Array, St. Jude Medical) were collected and analyzed per patient. After QRST removal, the AEGs were divided into 4 s windows with a 50% overlap. Fast Fourier transform was used for DF identification. HDF areas were identified as the maximum DF to 0.25 Hz below that, and their centers of gravity (CGs) were used to track their spatiotemporal movement. Spectral organization measurements were estimated. Hilbert transform was used to calculate instantaneous phase. Results: The system was successfully used to guide catheter ablation for 10 persAF patients. The mean processing time was 10.4 ± 1.5 min, which is adequate comparing to the normal electrophysiological (EP) procedure time (120~180 min). Conclusions: A customized software platform capable of measuring different forms of spatiotemporal AEG analysis was implemented and used in clinical environment to guide persAF ablation. The modular nature of the platform will help electrophysiological studies in understanding of the underlying AF mechanisms
DOI Link: 10.1016/j.cmpb.2017.01.011.
ISSN: 0169-2607
eISSN: 1872-7565
Version: Post-print
Status: Peer-reviewed
Type: Journal Article
Rights: Creative Commons “Attribution Non-Commercial No Derivatives” licence CC BY-NC-ND, further details of which can be found via the following link: Archived with reference to SHERPA/RoMEO and publisher website.
Description: The file associated with this record is under embargo until 12 months after publication, in accordance with the publisher's self-archiving policy. The full text may be available through the publisher links provided above.
Appears in Collections:Published Articles, Dept. of Engineering

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