ArticleJournal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing2026
Automated analysis of electrogram characteristics in baseline rhythm can distinguish isthmus regions and segments in reentrant ventricular tachycardia.
Article in Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
introductionBecause ventricular tachycardia (VT) is often hemodynamically unstable, ablation is typically performed in the baseline rhythm. While prior studies have assessed the electrogram (EGM) features of VT isthmuses mapped in baseline rhythm, they have largely relied on proprietary or manual analysis. We hypothesized that EGM morphologic features could be automatically calculated using the information typically obtained during mapping, and could aid in detecting VT isthmus areas and their components during substrate mapping.
methodsPatients undergoing ischemic VT ablation with detailed electroanatomic maps in both VT and a baseline rhythm were studied. Entrance, middle, exit, and adjacent bystander isthmus segments were determined in VT and registered to baseline rhythm maps. EGM features (voltage, velocity, signal duration, median vector angle difference (MVAD), number of deflections, and the maximum duration between electrogram segments) were assessed in both rhythms and compared between isthmus and non-isthmus regions and between isthmus segments.
resultsThere were 25,284 points in baseline rhythm and 10,923 in VT among 10 patients (all men, median age 67.0 (8.5) years). Significant differences between isthmus and non-isthmus regions were present in all features for both rhythms except for MVAD, which was only significant in VT. Baseline rhythm conduction was progressively more directionally uniform from isthmus entrance to exit. A multivariable regression model of points in baseline rhythm demonstrated an AUC of 0.810 for predicting VT isthmus regions.
conclusionAutomated EGM analysis can help identify isthmus in scar-related VT, different isthmus segments from each other, and may aid in targeting substrate for ablation.
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