In this manuscript, a framework for the pre-clinical validation of LBM-EP, a fast cardiac electrophysiology model, is presented. The overarching objective is to assess whether the model is able to predict ventricular tachycardia (VT) induction given the lead location and the pacing frequency protocol. First, the random-walk algorithm is used to interactively segment the heart ventricles from delayed-enhancement magnetic resonance images (DE-MRI). Scar and border zone are delineated using image thresholding. Then, a detailed anatomical model is estimated, comprising fiber architecture and spatial distribution of action potential duration. That information is rasterized to a Cartesian grid, and the cardiac potentials are computed using a parallel implementation of LBM-EP. A preliminary evaluation of the framework was performed on one swine data, for which four diㄦent pacing protocols were tested. Each of the protocols were mimicked by computing seven seconds of heart beat. Model predictions in terms of VT induction were compared with what was observed in the animal. Moreover, our parallel implementation on graphics processing units enabled a total computation time of about two minutes at an isotropic grid resolution of 0.8mm, thus allowing, for the first time, interactive VT testing.     «

In this manuscript, a framework for the pre-clinical validation of LBM-EP, a fast cardiac electrophysiology model, is presented. The overarching objective is to assess whether the model is able to predict ventricular tachycardia (VT) induction given the lead location and the pacing frequency protocol. First, the random-walk algorithm is used to interactively segment the heart ventricles from delayed-enhancement magnetic resonance images (DE-MRI). Scar and border zone are delineated using...     »