室性心动过速
医学
烧蚀
心动过速
心脏病学
算法
内科学
计算机科学
作者
Joshua Payne,Christopher E. Woods,Mohamed B. Elshazly,Aaron Matthews,Anne Kroman,Zekun Feng,Anna Rabinkova,Rugheed Ghadban,Bishnu P. Dhakal,Jeffery Winterfield
出处
期刊:Heart Rhythm
[Elsevier]
日期:2023-10-16
卷期号:21 (1): 27-33
被引量:17
标识
DOI:10.1016/j.hrthm.2023.10.014
摘要
Background Current annotation of local fractionated signals during ventricular electroanatomical mapping (EAM) requires manual input subject to variability and error. Objectives To evaluate a novel peak frequency (PF) annotation software for its ability to automatically detect late potentials (LP) and local abnormal ventricular activity (LAVA), determine an optimal range for display, and assess its impact on isochronal late activation mapping (ILAM). Methods EAM data from 25 patients who underwent ventricular tachycardia (VT) ablation were retrospectively analyzed. Samplings of electrogram peak frequencies from areas of normal bipolar voltage, areas of low voltage, and areas of low voltage with fractioned signals were performed. An optimal range of frequency display was identified from these patients and applied to a validation cohort of 10 prospective patients to assess high PF within scar as a predictor of VT ablation target sites, in particular deceleration zones (DZs) identified by ILAM, LP, and LAVA. Results Voltage and PF ranges of normal endocardial tissue varied widely. Using 220 Hz as a frequency cut-off value in areas of low bipolar voltage, areas of high fractionation were identified with a sensitivity of 91% and a specificity of 85% There was no significant reduction in targeted DZ surface areas and colocalization with DZs was observed in all cases. Applied to the prospective cohort, PF predicted fractionated areas and DZ in 9/10 patients. Conclusions A PF annotation algorithm with a cut off of 220 Hz accurately identifies areas of fractioned signals and accurately predicts DZs during ILAM.
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