A New Algorithm to Diagnose Atrial Ectopic Origin from Multi Lead ECG Systems - Insights from 3D Virtual Human Atria and Torso

Abstract

Rapid atrial arrhythmias such as atrial fibrillation (AF) predispose to ventricular arrhythmias, sudden cardiac death and stroke. Identifying the origin of atrial ectopic activity from the electrocardiogram (ECG) can help to diagnose the early onset of AF in a cost-effective manner. The complex and rapid atrial electrical activity during AF makes it difficult to obtain detailed information on atrial activation using the standard 12-lead ECG alone. Compared to conventional 12-lead ECG, more detailed ECG lead configurations may provide further information about spatio-temporal dynamics of the body surface potential (BSP) during atrial excitation. We apply a recently developed 3D human atrial model to simulate electrical activity during normal sinus rhythm and ectopic pacing. The atrial model is placed into a newly developed torso model which considers the presence of the lungs, liver and spinal cord. A boundary element method is used to compute the BSP resulting from atrial excitation. Elements of the torso mesh corresponding to the locations of the placement of the electrodes in the standard 12-lead and a more detailed 64-lead ECG configuration were selected. The ectopic focal activity was simulated at various origins across all the different regions of the atria. Simulated BSP maps during normal atrial excitation (i.e. sinoatrial node excitation) were compared to those observed experimentally (obtained from the 64-lead ECG system), showing a strong agreement between the evolution in time of the simulated and experimental data in the P-wave morphology of the ECG and dipole evolution. An algorithm to obtain the location of the stimulus from a 64-lead ECG system was developed. The algorithm presented had a success rate of 93%, meaning that it correctly identified the origin of atrial focus in 75/80 simulations, and involved a general approach relevant to any multi-lead ECG system. This represents a significant improvement over previously developed algorithms.

Three-dimensional Multiscale Modelling and Simulation of Atria and Torso Electrophysiology

“…Both approaches pursue the same answers in regards the mechanisms and origin of atrial arrhythmias. During the present decade, there have been a number of works based on both, the analysis of the P-wave and torso surface potentials (Keller et al 2010;Weber, Luik, et al 2011;Krueger et al 2012;Lenkova et al 2012;Alday et al 2015;Perez Alday et al 2016) and on the electrocardiographic imaging ECGi (Rudy 2010;Wang et al 2012;Shah et al 2014;Figuera et al 2016).…”

“…Recent studies have focused on designing and validating algorithms based on P-wave polarity that used 12-lead (Kistler et al 2006;Colman et al 2011) or 64-lead recordings (Alday et al 2015) for identifying the origin of ectopic sites that were artificially induced from a pacing catheter in the atrium. Those procedures showed a general good accuracy for detecting the site of some ectopic foci.…”

“…Those procedures showed a general good accuracy for detecting the site of some ectopic foci. However, their accuracy decreases again when bi-phasic P-waves are present in many leads (Alday et al 2015).…”

“…Afterwards, the number of sites was increased to 34 divided into both atria (SippensGroenewegen et al 1998;Gerstenfeld et al 2000;SippensGroenewegen et al 2004) providing experimental patterns on the torso surface. However, the most recent studies (Kistler et al 2006;Cuculich et al 2010;Colman et al 2011;Alday et al 2015;Lim et al 2015) have not increased the number of the triggering sites and still stimulate in well-known locations (CT, BB, PM, AVR, SVC, IVC, CS os, RAA, PM, RPV, LPV, MV, LAA, CS, and RA and LA septum).…”

“…A more recent algorithm was developed (Alday et al 2015) to obtain the triggering site of the stimulus from a 64-lead ECG system with a success rate of 93%.The authors divided both the torso and the atria in 8 quadrants and used the P-wave polarity to quantify the differences in morphology. All these computational approaches assumed however, predefined areas what might lead to a bias when interpreting the results, and found the same problems associated with bi-phasic or irregular P-waves.…”