Computational bioengineering for heart disease

Abstract

In silico clinical trials are a new paradigm for development of a new drug and medical device. SILICOFCM project is multiscale modeling of familial cardiomyopathy which considers a comprehensive list of patient specific features as genetic, biological, pharmacologic, clinical, imaging and cellular aspects. The 3D deformable-body represents the left and right ventricle of the heart. Blood flow is modeled during the filling phase by applying the fluid-solid interaction method. The ventricle wall is modeled by 3D brick 8-node solid elements, with fibers that have threedimensional direction. The Navier-Stokes equations are solved using the ALE formulation for fluid with large displacements of the boundary. The ventricle wall model is simulated by the muscle material model. Muscle fiber orientation is defined by direction vector in 3D prescribed through input data. The outlet blood pressure is used as the boundary condition. At the same time, the wall muscle fibers are activated according to the activation function taken from specific patient measurements. Computational Platform for Multiscale Modelling in biomedical engineering is results of SGABU project that is served as an educational tool for students and researchers. The platform integrates already developed solutions and various datasets related to cancer, cardiovascular, bone disorders and tissue engineering into one multiscale platform. This will enable further validation and parameterization of models, creation of environment for future trends, e.g. in silico clinical trials, virtual surgery, development of prediction models. InSilc project is devoted to in silico mechanical stent testing within ISO 25539 standards and in silico stent deployment for metallic and biodegradable material. In-silico projects will connect basic experimental research with clinical study and bioinformatics, data mining and image processing tools using very advanced computer models for drug, stent and patient database in order to reduce animal and clinical studies.