M.Sc. Cristian Barrios

Nils Skupien

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 models, and can potentially be used in the clinics. Nonetheless, they fail to incorporate important physiological phenomena in their simulations. For example, one of the relevant effects is that changes on the curvature, bath loading and wall thickness of the heart can speed up or down the electrical propagation in the cardiac tissue. [1] The aim of this project, it to investigate how to incorporate these phenomena into the Eikonal models. This will contribute to better estimate the risk of arrhythmias in each patient using Eikonal models. [2]

References
1. Rossi, S., Gaeta, S., Griffith, B. E., & Henriquez, C. S. (2018). Muscle thickness and curvature influence atrial conduction velocities. Frontiers in physiology, 9, 1344.
2. Azzolin, L., Luongo, G., Ventura, S. R., Saiz, J., Dössel, O., & Loewe, A. Influence of Gradient and Smoothness of Atrial Wall Thickness on Initiation and Maintenance of Atrial Fibrillation.