Physiology-based regularization recovered details of heart-surface electrograms lost with traditional Tikhonov regularization, attaining higher correlation coefficients and improved estimation of recovery times.
Does physiology-based regularization improve the reconstruction of heart-surface electrograms from body-surface recordings compared to traditional Tikhonov regularization in dog models?
A novel physiology-based regularization method improves the noninvasive reconstruction of cardiac electrical activity from body-surface ECGs in a preclinical model.
p-value: p=<0.05
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.
Cluitmans et al. (Mon,) conducted a other in Normal cardiac electrophysiology (n=3). Physiology-based regularization (PBR) vs. Traditional Tikhonov regularization was evaluated on Correlation coefficient between recorded and reconstructed epicardial electrograms (p=<0.05). Physiology-based regularization recovered details of heart-surface electrograms lost with traditional Tikhonov regularization, attaining higher correlation coefficients and improved estimation of recovery times.