Abstract
Electrocardiographic imaging has been shown to provide useful information for pre-procedure planning of catheter-ablation procedures. The methodology involves reconstruction of unipolar electrograms (EGMs) and isochronal maps on the epicardial surface from non-invasively acquired body-surface potentials. We have developed an algorithm for evaluating global myocardial activation times. First, the cross-correlation method determines the delay in local activation times among pairs of neighboring nodes. Next, a sparse linear system is constructed from known activation delays of neighboring nodes. To solve this system, we use a sparse Bayesian learning method to calculate the global myocardial activation times. The aim of this study was to assess the proposed method in both structurally normal and scarred ventricular myocardium. Isochronal maps of calculated activation times were compared with local activation times (LATs) derived from directly-measured epicardial EGMs obtained by electroanatomic contact mapping, for pacing delivered by an implantable cardioverter defibrillator (ICD) at the endocardial right-ventricular (RV) apex, and for catheter pacing at RV epicardial site. We found that even in the presence of infarct scar, isochronal maps calculated by the proposed method correlated closely with known LATs exported from an electroanatomic mapping system.
Original language | English |
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Title of host publication | Computing in Cardiology Conference, CinC 2018 |
Publisher | IEEE Computer Society |
ISBN (Electronic) | 9781728109589 |
DOIs | |
Publication status | Published - Sept 2018 |
Event | 45th Computing in Cardiology Conference, CinC 2018 - Maastricht, Netherlands Duration: Sept 23 2018 → Sept 26 2018 |
Publication series
Name | Computing in Cardiology |
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Volume | 2018-September |
ISSN (Print) | 2325-8861 |
ISSN (Electronic) | 2325-887X |
Conference
Conference | 45th Computing in Cardiology Conference, CinC 2018 |
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Country/Territory | Netherlands |
City | Maastricht |
Period | 9/23/18 → 9/26/18 |
Bibliographical note
Funding Information:This work was supported in part by the Natural Sciences and Engineering Research Council of Canada, the Nova Scotia Health Research Foundation, the Nova Scotia Research and Innovation Graduate Scholarship, the Heart & Stroke Foundation of Nova Scotia, and the Cardiac Arrhythmia Network of Canada (CANet).
Publisher Copyright:
© 2018 Creative Commons Attribution.
ASJC Scopus Subject Areas
- General Computer Science
- Cardiology and Cardiovascular Medicine