Noninvasive electrocardiographic imaging with low-rank and non-local total variation regularization

Abstract

Abstract The reconstruction of epicardial and endocardial extracellular potentials (EEP) by noninvasive methods has become a significant topic in cardiac electrophysiology over recent years. It is of great importance for the diagnosis of arrhythmia and for guidance of radiofrequency ablation, based on the difference in potentials between different locations on the heart's surface. In this study, we propose a non-local regularization of total variation (TV) in a low-rank (LR) and sparse decomposition framework, suitable for the rank-deficient problem of EEP reconstruction. LR and sparse decomposition can be utilized to extract the spatial-temporal information resulting from the sparse properties of EEP data, and the non-local similarities in the LR part can be a constraint for a non-local total variation regularization. The proposed method is implemented in simulated myocardial infarction (MI), interventional, and clinical premature ventricular contraction (PVC) experiments to verify its feasibility and reliability. Compared with the existing LR and TV methods, the proposed method performs better at potential reconstruction as well as PVC localization, particularly in the boundary of the MI region, while the results of this method are also consistent with those of invasive measurements using an EnSite 3000 system in the clinical experiment.