Literature DB >> 27957121

Non-Invasive Estimation Of Left Atrial Dominant Frequency In Atrial Fibrillation From Different Electrode Sites: Insight From Body Surface Potential Mapping.

Marjan Bojarnejad1, James R Blake1, John Bourke1, Ewan Shepherd1, Alan Murray1, Philip Langley1.   

Abstract

The dominant driving sources of atrial fibrillation are often found in the left atrium, but the expression of left atrial activation on the body surface is poorly understood. Using body surface potential mapping and simultaneous invasive measurements of left atrial activation our aim was to describe the expression of the left atrial dominant fibrillation frequency across the body surface. 20 patients in atrial fibrillation were studied. The spatial distributions of the dominant atrial fibrillation frequency across anterior and posterior sites on the body surface were quantified. Their relationship with invasive left atrial dominant fibrillation frequency was assessed by linear regression analysis, and the coefficient of determination was calculated for each body surface site. The correlation between intracardiac and body surface dominant frequency was significantly higher with posterior compared with anterior sites (coefficient of determination 67±8% vs 48±2%, p<0.001). The site with largest coefficient of determination was 79.6% (p<0.001) and was a posterior site. In comparison with the site closest to lead V1 it had a coefficient of determination of 23.0% (p=0.033), and with the posterior body surface site closest to lead V9 had a coefficient of determination of 70.3% (p<0.001). Left atrial dominant fibrillation frequency was more closely represented at posterior body surface sites.

Entities:  

Keywords:  Atrial Arrhythmia; Atrial Fibrillation; Body Surface Potential Mapping; Intra-Atrial Electrograms; Signal Processing

Year:  2014        PMID: 27957121      PMCID: PMC4956290          DOI: 10.4022/jafib.1131

Source DB:  PubMed          Journal:  J Atr Fibrillation        ISSN: 1941-6911


  19 in total

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  2 in total

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Journal:  IEEE Trans Biomed Eng       Date:  2016-04-13       Impact factor: 4.538

2.  Novel non-invasive algorithm to identify the origins of re-entry and ectopic foci in the atria from 64-lead ECGs: A computational study.

Authors:  Erick A Perez Alday; Michael A Colman; Philip Langley; Henggui Zhang
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