Abstract
The inverse problem of electrocardiography aims at noninvasively reconstructing electrical activity of the heart from recorded body-surface electrocardiograms. A crucial step is regularization, which deals with ill-posedness of the problem by imposing constraints on the possible solutions. We developed a regularization method that includes electrophysiological input. Body-surface potentials are recorded and a computed tomography scan is performed to obtain the torso–heart geometry. Propagating waveforms originating from several positions at the heart are simulated and used to generate a set of basis vectors representing spatial distributions of potentials on the heart surface. The real heart-surface potentials are then reconstructed from the recorded body-surface potentials by finding a sparse representation in terms of this basis. This method, which we named ‘physiology-based regularization’ (PBR), was compared to traditional Tikhonov regularization and validated using in vivo recordings in dogs. PBR recovered details of heart-surface electrograms that were lost with traditional regularization, attained higher correlation coefficients and led to improved estimation of recovery times. The best results were obtained by including approximate knowledge about the beat origin in the PBR basis.
Highlights
Cardiac arrhythmias are among the leading causes of death worldwide
Electrograms were reconstructed with physiology-based regularization’ (PBR) using different action potentials (APs) models and with traditional zeroth-order Tikhonov regularization for comparison
These examples show that, regardless of the AP model, all PBR methods were able to recover some of the electrogram characteristics that were lost with Tikhonov regularization, for example the negative deflection in electrogram 1 and 2, and the positive deflection in electrogram 7
Summary
The 12-lead electrocardiogram (ECG) is a wellestablished, patient-friendly, quick, reproducible and cheap tool to determine normal cardiac activation and recovery, to diagnose cardiac arrhythmias, altered activation, ischemia, infarction, primary electrical abnormalities of the heart, structural disease, metabolic disorders, electrolyte imbalance and other conditions. It reflects the attenuated and dispersed result of propagated electrical activity and recovery in the heart on the body surface. Electrocardiographic imaging (ECGI) aims at noninvasively reconstructing the electrical activity of the heart, based on body-surface potential measurements and a patient-specific torso–heart geometry [5, 18, 21, 22, 28]. Much progress has been made in ECGI and clinical applications are published with increasing frequency, yet the accuracy of the reconstructed electrical heart activity is still
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