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An interactive platform to guide catheter ablation in human persistent atrial fibrillation using dominant frequency, organization and phase mapping.

Authors :
Li, Xin
Salinet, João L
Almeida, Tiago P
Vanheusden, Frederique J
Chu, Gavin S
Ng, G André
Schlindwein, Fernando S
Source :
Computer Methods & Programs in Biomedicine. Apr2017, Vol. 141, p83-92. 10p.
Publication Year :
2017

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01692607
Volume :
141
Database :
Academic Search Index
Journal :
Computer Methods & Programs in Biomedicine
Publication Type :
Academic Journal
Accession number :
121452196
Full Text :
https://doi.org/10.1016/j.cmpb.2017.01.011