Probabilistic Dominant Frequency Estimation in AF From ECGI

Abstract

Non-invasive estimation of high frequency activation regions in atrial fibrillation (AF) may have an important role in patient stratification and ablation guidance. This work presents a methodology to robustly estimate DF maps in ECGI, where the uncertainty associated to the estimates is modelled making use of a set of ECGI solutions from a range of different lambda parameters (DF-LR) in Tikhonov O-order regularization. The proposed DF-LR method was compared to the $DFs$ obtained from the standard L-curve (DF-LC) optimization. Specifically, the highest dominant frequency (HDF) found with both methods was tested in 2 AF simulations. In addition, the reproducibility of the DF maps was studied in a clinical case using ECGI signals from a persistent AF patient. DF-LR method overcame the DF-LC in terms of HDF sensitivity. Furthermore, the mean absolute difference between consecutive DF maps was lower in DF-LR method $(0.64\pm 0.34Hz\quad vs \quad 1.38\pm 0.11 \quad Hz)$ showing higher reproducibility.