Atrial location optimization by electrical measures for Electrocardiographic Imaging

Abstract

Background: The Electrocardiographic Imaging (ECGI) technique, used to non-invasively reconstruct the epicardial electrical activity, requires an accurate model of the atria and torso anatomy. Here we evaluate a new automatic methodology able to locate the atrial anatomy within the torso based on an intrinsic electrical parameter of the ECGI solution.Methods: In 28 realistic simulations of the atrial electrical activity, we randomly displaced the atrial anatomy for ±2.5 cm and ±30 degrees on each axis. An automatic optimization method based on the L-curve curvature was used to estimate the original position using exclusively non-invasive data.Results: The automatic optimization algorithm located the atrial anatomy with a deviation of 0.5 ± 0.5 cm in position and 16.0 ± 10.7° in orientation. With these approximate locations, the obtained electrophysiological maps reduced the average error in atrial rate measures from 1.1 ± 1.1 Hz to 0.5 ± 1.0 Hz and in the phase singularity position from 7.2 ± 4.0 cm to 1.6 ± 1.7 cm (p<0.01).Conclusions: This proposed automatic optimization may help to solve spatial inaccuracies provoked by cardiac motion or respiration, as well as to use ECGI on torso and atrial anatomies from different medical image systems.

Electrocardiographic Imaging for Atrial Fibrillation: A Perspective From Computer Models and Animal Experiments to Clinical Value

“…Recently, Rodrigo et al (2018) explored the ability of a new metric based on the inverse reconstruction quality for the location and orientation of the atrial surface inside the torso. This approach has also been proposed to solve spatial inaccuracies provoked by cardiac motion or respiration, as well as to use ECGI on torso and atrial anatomies from different medical image systems (Gisbert et al, 2020).…”

“…Reducing the need for incorporation of inhomogeneities may lead to the development of inverse solutions that are free from the need for patient-specific imaging. Recent simulation studies have shown the potential of detecting atrial location based on a Pattern Search algorithm on the L-curve curvature from the Tikhonov regularization method (Rodrigo et al, 2018;Gisbert et al, 2020).…”