Noninvasive Identification of Atrial Fibrillation Drivers: Simulation and Patient Data Evaluation

Maria de la Salud Guillem Sanchez, Andreu M Climent, Miguel Rodrigo, Ismael Hernandez-Romero, Alejandro Liberos, Francisco Fernandez-Aviles, Omer Berenfeld, Felipe Atienza
2016 2016 Computing in Cardiology Conference (CinC)   unpublished
Identification of atrial drivers as singularity points by using the inverse problem of electrocardiography is being used to guide atrial fibrillation (AF) ablation. However, the ability of the inverse problem to reconstruct fibrillation patterns and identify AF drivers has not been validated. Position of AF drivers was compared between recorded and inverse computed EGMs by making use of (1) realistic mathematical models and (2) simultaneous endocardial and body surface recordings during AF
more » ... ings during AF ablation procedures. Atrial drivers were defined as the areas with the highest dominant frequencies (HDF) or at the sites with a higher incidence of long-lasting phase singularities (PS). On simulation data, HDF analysis allowed the identification of the chamber that harboured the AF source in 30 out of 30 of the models evaluated vs. 26 out of 30 models for PS analysis. On patient data, solution of the inverse problem only allowed identifying atrial drivers on the correct atrial chamber by HDF analysis (2 out of 2 patients vs. 0 out of 2 patients for PS analysis). Identification of atrial sources by solving the inverse problem of the electrocardiography is more reliably accomplished based HDF than on PS detection. A realistic 3D model of the atrial anatomy composed by 284,578 nodes and 1,353,783 tetrahedrons (673.4±130.3 µm between nodes) was used to simulate the atrial electrical activity [6] . A gradient on the electrophysiological properties of the atrial myocardium, specifically on Ik,ACh, IK1, INa and ICaL was introduced into
doi:10.22489/cinc.2016.039-420 fatcat:eylhmbagkrbi3irzcmpo6z6g5a