Non-invasive Mechanism Classification and Localization in Supraventricular Cardiac Arrhythmias

Abstract

[EN] In this study, we investigated the most relevant biomarkers for noninvasive classification and mechanism location in atrial tachycardia (AT), flutter (AFL) and fibrillation (AF). Biomarkers were calculated using noninvasive body surface (BSPM) dominant frequency and phase maps. We used 19 simulations of 567 to 64-lead BSPMs, from which were extracted 32 biomarkers. Biomarker ranking was performed with ANOVA, Kendall and Lasso techniques. The best four biomarkers were identified and used to classify the arrhythmias in all combinations, and the best two used for noninvasive driver localization. Arrhythmia classification accuracy was 94.74%. The feature combination which best distinguish AF from non-AF were mean filament displacement and mean OI, while those that best distinguish AFL from AT were mean and SD of SP distribution. There was good agreement across ranking techniques. Mechanism location accuracy was 78.95%, with the most important biomarkers being percentage SPs within each torso division, and SD of filament histogram cluster area. This study highlights that organization related features well identifies AF and spatial SP distribution discriminate AT from AFL and also it¿s localization.