ECG Imaging of Simulated Atrial Fibrillation: Imposing Epi-Endocardial Similarity Facilitates the Reconstruction of Transmembrane Voltages

Abstract

Electrocardiographic imaging (ECGI) could help in diagnosis and treatment of atrial fibrillation (AF), the most common life-threatening arrhythmia. Based on a previous work by Figuera et al. on the reconstruction of epicardial potentials (EP) during AF, we explore the performance of a Tikhonov regularization with two spatial constraints for transmembrane voltage (TMV) based ECGI. We develop a new method to impose epi-endocardial similarity and show its benefit for ECGI of atrial activity. Apart from TMVs, local activation times and dominant frequency are evaluated as target parameters. In the AF models studied, joint reconstruction of epi-and endocardial TMVs showed performance comparable to the previously reported EPs imaging.

Electrocardiographic Imaging Using a Spatio-Temporal Basis of Body Surface Potentials—Application to Atrial Ectopic Activity

“…Figure 2 shows the geometries used for forward and inverse calculations. They are the same as in Schuler et al ( 2017 ), which in turn are based on Figuera et al ( 2016 ). The surface meshes of the atria and torso consist of 4,800 and 844 nodes and have an average edge length of 3.4 and 27.0 mm, respectively.…”

Forcing Transmembrane Voltages to Decrease Slowly: A Temporal Regularization for ECG Imaging

“…As Tikhonov regularization is applied to all time steps simultaneously, the regularization parameters λ and η are constant over time. For fibrillatory activity, it was found that constant parameters do not impair the solution quality compared to instantaneous ones [2]. In this work, the optimal Tikhonov parameters were obtained by maximizing the temporal mean of spatial TMV correlation with the ground truth using downhill simplex optimization.…”

“…A more realistic geometry of the torso and the atria is later used to demonstrate the new regularization method in an application to irregular atrial activity. The geometry is the same as in [2], but the number of atrial nodes has been reduced to 1696 in order to speed up computations. The "simple atrial fibrillation" simulation from [3] is chosen as activity to be reconstructed, which includes rotational activity on the right atrium repeating at 7.3 Hz, while the left atrium is activated at 4.7 Hz.…”

“…For solving the inverse problem, we assume perfect knowledge of A and thus neglect errors due to imperfect geometries and conductivities. The epi-endo projection from [2] is applied for both geometries to resolve ambiguities between sources on the epi-and endocardial surfaces by reducing the source space to effectively one layer.…”

“…To quantify similarity of high frequency components of spatial TMV distributions, we calculate the spatial CC for the gradient norm of TMVs as well. Local activation times (LAT) are extracted and compared as described in [2]. In short, the peaks of a spatio-temporal derivative signal [8] are detected and absolute errors between only true positive detections are calculated together with the false negative rate (FNR) and the false positive rate (FPR).…”