Surface unipolar electrogram characteristics to predict site of origin of outflow tract arrhythmias using noninvasive mapping. (6th January 2021)

• Record Type: Journal Article
• Authors: Coleman, Kristie M.; Saleh, Moussa; Makker, Parth; Vaishnav, Aditi S.; Atteya, Gourg; Shein, Jamie; Bhullar, Amarbir; Skipitaris, Nicholas T.; Mountantonakis, Stavros E.
• Is Part Of: Journal of cardiovascular electrophysiology. Volume 32:Number 2(2021)
• Page Start: 391
• Page End: 399
• Publication Date: 2021-01-06
• Subjects: body surface mapping -- catheter ablation -- noninvasive electroanatomic mapping -- premature ventricular contraction -- ventricular arrhythmia; Blood vessels -- Physiology -- Periodicals; Electrophysiology -- Periodicals; Heart -- Physiology -- Periodicals; 612.1
• DOI: 10.1111/jce.14857
• Languages: English
• ISSNs: 1045-3873

Abstract

Abstract: Background: Noninvasive electroanatomic mapping (NIEAM) demonstrate patterns of depolarization that are useful in identifying the chamber of origin (COO) in outflow tract ventricular arrhythmias (OTVA). However, its use in predicting exact site of origin (SOO) has not yet been validated. Methods: NIEAMs (CardioInsight, Medtronic) from 40 patients (age 62.5 ± 2.6) undergoing ablation for OTVA were reviewed for diagnostic accuracy in predicting the SOO. Earliest arrhythmia breakout and directionality of earliest instantaneous unipolar electrograms (uEGMs) on NIEAMs were evaluated subjectively by two observers for quality and amplitude. Sites with most negative earliest uEGMs on right and left ventricular outflow tracts, as well as epicardial surface were manually identified. Using NIEAM‐based activation timing of the lateral mitral annulus and basal septum COO was identified for each OTVA. Predictions of SOO using NIEAMs was compared with true SOO from invasive study. NIEAMs SOO predictions were compared with subjective 12 lead electrocardiogram (ECG) review by two observers. Results: Review of arrhythmia breakout and signal directionality had poor diagnostic value in predicting SOO in OTVA (50.6% and 49.4%, 56.6% and 43.4%, respectively) and underperformed compared with ECG interpretation (59.1% and 80.5%). After excluding uEGMs with poor characteristics, the uEGM with most negative amplitude at the COO was predictive of the true SOO with 96.4% sensitivity and specificity. Conclusion: We propose a stepwise approach when interpreting NIEAMs for OTVA where patterns of activation are evaluated first to determine the COO, followed by identification of the site with most negative amplitude instantaneous uEGM to determine SOO.