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Regional Dominant Frequency: A New Tool for Wave Break Identification During Atrial Fibrillation

Overview of attention for article published in Frontiers in Cardiovascular Medicine, June 2018
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Title
Regional Dominant Frequency: A New Tool for Wave Break Identification During Atrial Fibrillation
Published in
Frontiers in Cardiovascular Medicine, June 2018
DOI 10.3389/fcvm.2018.00079
Pubmed ID
Authors

Mohammad Hassan Shariat, Javad Hashemi, Saeed Gazor, Damian P. Redfearn

Abstract

Cardiac mapping systems are based on the time/frequency feature analyses of intracardiac electrograms recorded from individual bipolar/unipolar electrodes. Signals from each electrode are processed independently. Such approaches fail to investigate the interrelationship between simultaneously recorded channels of any given mapping catheter during atrial fibrillation (AF). We introduce a novel signal processing technique that reflects regional dominant frequency (RDF) components. We show that RDF can be used to identify and characterize variation and disorganization in wavefront propagation- wave breaks. The intracardiac electrograms from the left atrium of 15 patients were exported to MATLAB and custom software employed to estimate RDF and wave break rate (WBR). We observed a heterogeneous distribution of both RDF and WBR; the two measures were weakly correlated (0.3; p < 0.001). We identified locations of AF or atrial tachycardia (ATach) termination and later compared offline with RDF and WBR maps. We inspected our novel metrics for associations with AF termination sites. Areas associated with AF termination demonstrated high RDF and low WBR (↑RDF,↓WBR). These sites were present in 14 of 15 patients (mean 2.6 ± 1.2 sites per patient; range, 1-4 sites), 43% situated within the pulmonary veins. In nine patients where AF terminated to sinus rhythm (6) or ATach (3), post-hoc analysis demonstrated all ↑RDF,↓WBR sites were ablated and correlated with AF termination sites. The proposed RDF signal processing tools can be used to identify and quantify wave break, and the combined use of these two novel metrics can aid characterization of AF. Further prospective studies are warranted.

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Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 20%
Student > Ph. D. Student 4 20%
Student > Postgraduate 3 15%
Student > Bachelor 2 10%
Lecturer 1 5%
Other 2 10%
Unknown 4 20%
Readers by discipline Count As %
Engineering 7 35%
Medicine and Dentistry 5 25%
Nursing and Health Professions 1 5%
Mathematics 1 5%
Computer Science 1 5%
Other 0 0%
Unknown 5 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 June 2018.
All research outputs
#18,640,437
of 23,092,602 outputs
Outputs from Frontiers in Cardiovascular Medicine
#3,272
of 7,011 outputs
Outputs of similar age
#254,161
of 328,981 outputs
Outputs of similar age from Frontiers in Cardiovascular Medicine
#54
of 63 outputs
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