Next-generation in Silico Cardiac Electrophysiology through Immersed Grid Meshfree Modeling: Application to Simulation of Myocardial Infarction

Abstract

State-of-art simulators of cardiac tissue electrophysiology are commonly based on the Finite Element Method (FEM). FEM is known to be a robust and accurate numerical method, but its accuracy highly depends on the quality of the mesh. Generating a good-quality mesh may be cumbersome and time consuming for models with complex geometries, such as those representing the anatomy of human organs. This limitation restricts the clinical application of FEM. To overcome this challenge, we propose the use of a meshfree method, the Moving Kriging Mixed Collocation (MKMC) method for in silico cardiac electrophysiology. MKMC is a purely meshfree method requiring the definition of a point cloud rather than a mesh. We propose the construction of the point cloud as an immersed grid of points generated automatically from image data. In simulations on a swine biventricular model, both under baseline and myocardial infarction conditions, we demonstrate the capability of the MKMC method to generate results in very good agreement with FEM while alleviating the mesh requirement. Differences in local activation time and action potential duration between MKMC and FEM are in mean below 3%. The proposed MKMC method represents a promising alternative to FEM for cardiac in silico investigations with the potential to be integrated in the clinic.