M.Sc. Cristian Barrios

Guillaume Kachel

Cardiovascular diseases are the leading causes of mortality and mobility in the world. Many of the mechanisms of pathophysiology of these diseases are unclear. Consequently, treatment strategies are far from optimal. Biophysical models of the electrical activity of heart are the gold standard for cardiac electrophysiology modelling and they have provided meaningful contributions in the field during the last years.  Unfortunately, they require supercomputers to simulate one heartbeat of the whole heart taking a plethora of CPU hours. Application of these kind of models on supporting tools to cardiologists in the hospitals is very challenging. Eikonal models are another alternative to investigate these cardiac diseases. They can be 1000 times faster than biophysical detailed models, and can potentially be used in the clinics. Nonetheless, they fail to incorporate important physiological phenomena in the simulations. One of these is the influence of the curvature and collisions between electrical wavefronts on the conduction velocity. In this project, the student will perform atrial tissue simulations using the bidomain model to assess this influence. Then, the student will create a regression model to calculate the conduction velocity based on the curvature of the wavefront and the excitable gap between two wavefronts. These results will be used in future projects to improve the accuracy of the eikonal model.