Non-Invasive Computational Modeling of Heart from Vectorcardiography in Myocardial Infarction using Magnetocardiography

Computational imaging of the cardio-magnetic sources is an emerging field in the biomedical society that promises to evaluate many cardiac related diseases without noninvasive procedures. The functional waves generated in terms of bio-magnetic field due to cardiac impulses can be investigated using Magnetocardiogram. The challenging task in the research is to image/localize the cardiac dysfunctions from MCG not only at the body surface but also to reconstruct the activities on the myocardial level. In order to solve this, one has to model a generic structure of the heart enclosed within a thorax with MCG sensors called as Forward problem.We proposed a novel approach in the construction of the spatial matrix derived from the vectorcardiography signals. The forward matrix was then used to estimate the position, orientation and the cardiac activities. The forward and inverse methods were applied to normal and myocardial infarcted cases for single and distributed source models. The localization accuracies of the proposed model based on VCG lied in the range of 0.01mm to 1 mm.The cardiac activities were estimated and compared using L2 norm and L1 norm regularization techniques. According to this study, the proposed spatial matrix used in the inverse problem gave good localization and L1 norm regularization provided sharper solutions than L2 norm.