Automatic Location of the Atrial Anatomy Under Cumulative Spatial Artifacts Based on ECG Imaging

Victor Gisbert1, Alejandro Liberos2, Ismael Hernandez-Romero2, Andreu M. Climent3, Felipe Atienza2, Maria S Guillem1, Miguel Rodrigo4
1ITACA Institute, Universitat Politècnica de València, Spain, 2Hospital GU Gregorio Marañón, IiSGM, CIBERCV, Spain, 3Hospital Gregorio Marañón, 4Universitat Politècnica de València


Electrocardiographic Imaging (ECGI) has become an increasingly used technique for non-invasive diagnosis of cardiac arrhythmias, although the need for medical imaging technology to determine the anatomy hinders its introduction in the clinical practice. This paper explores the ability of a new metric based on the inverse reconstruction quality and algorithm for determining the location and orientation of the atrial surface inside the torso. Synthetic EGM signals from 16 realistic mathematical models were used to estimate the correct position of the atria inside the torso, after solving the Forward Problem in a realistic torso geometry. The curvature of the L-curve when using Tikhonov’s regularization was measured after application of deviations in atrial position and orientation from the prop-er atrial location. Cumulative random displacements (±25 mm) and rotations (±30º) of the atria were automatically solved by finding the maximal L-curve curvature in 6 dimensions (3 axes of displacement + 3 axes of rotation) using optimization algorithms: Pattern Search for the 6 dimensions combined with a second iteration using Patter Search for the 3 rotation axes. Along the whole dataset, the location error in the displacements was 2.0±2.6 mm in the x axis, 2.6±2.8 mm in the y axis and 1.0±2.2 mm in the z axis, providing and absolute error of 3.4±4.5 mm. On the other hand, the error in the rotation was 4.0±2.5º in the x axis, 8.5±7.1º and 4.3±4.0º, consisting in an absolute error of 10.0±8.6º. The curvature of L-curve has been proven to be a useful marker for correcting the estimation of the atria inside the thorax, and can be used to guide a search algorithm to locate the atria inside the torso. These findings provide an insight to the use of combined image techniques for the ECGI solution and therefore extend the use of ECGI in clinical practice.