Background: Twelve-lead electrocardiogram (ECG) criteria for epicardial ventricular tachycardia (VT) origins have been described. In patients with structural heart disease, the ability to predict an epicardial origin based on QRS morphology is limited and has been investigated only for limited regions in the heart.

Objective: The purpose of this study was to determine whether a computerized algorithm is able to accurately differentiate epicardial vs endocardial origins of ventricular arrhythmias.

Methods: Endocardial and epicardial pace-mapping were performed in 43 patients at 3277 sites. The 12-lead ECGs were digitized and analyzed using a mixture of gaussian model (MoG) to assess whether the algorithm was able to identify an epicardial vs endocardial origin of the paced rhythm. The MoG computerized algorithm was compared to algorithms published in prior reports.

Results: The computerized algorithm correctly differentiated epicardial vs endocardial pacing sites for 80% of the sites compared to an accuracy of 42% to 66% of other described criteria. The accuracy was higher in patients without structural heart disease than in those with structural heart disease (94% vs 80%, P = .0004) and for right bundle branch block (82%) compared to left bundle branch block morphologies (79%, P = .001). Validation studies showed the accuracy for VT exit sites to be 84%.

Conclusion: A computerized algorithm was able to accurately differentiate the majority of epicardial vs endocardial pace-mapping sites. The algorithm is not region specific and performed best in patients without structural heart disease and with VTs having a right bundle branch block morphology.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.hrthm.2014.06.036DOI Listing

Publication Analysis

Top Keywords

structural heart
16
heart disease
16
computerized algorithm
16
epicardial endocardial
16
patients structural
12
bundle branch
12
branch block
12
epicardial
8
identify epicardial
8
epicardial ventricular
8

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!