[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.VGM is funded by the European Union's Horizon
2020 research and innovation programme under the Marie
Skodowska-Curie grant agreement No. 860974. IS, JAS
and JS are supported by grant #2018/25606-2, Sao Paulo Research Foundation (FAPESP).Sandoval, I.; Marques, VG.; Sims, JA.; Rodrigo, M.; Guillem Sánchez, MS.; Salinet, J. (2021). Non-invasive Mechanism Classification and Localization in Supraventricular Cardiac Arrhythmias. 1-4. https://doi.org/10.22489/CinC.2021.2261
