Computational modeling of hemodynamics for surgical planning and device development

Abstract

The mechanical coupling of blood flow and vascular tissue is an essential part of the cardiovascular system. Various mechanisms have been identified that enable cardiovascular remodeling in response to hemodynamic stressors acting on global and local levels. Furthermore, hemodynamic disturbances have been recognized as triggering factors in the pathogenesis of cardiovascular diseases. To study these stressors and disturbances, highly detailed hemodynamic analyses are needed. Computational fluid dynamics (CFD) modeling techniques offer the unique potential to provide these highly detailed analyses, as they can be used to compute hemodynamics with a higher spatial and temporal resolution than any clinical imaging test. In this thesis, patient-specific CFD modeling techniques were used to study the pathogenesis of cardiovascular diseases and guide surgical planning and device optimization. We found that patient-specific CFD modelling is capable of providing non-invasive high-resolution hemodynamic analyses that help understanding of hemodynamics in complex anatomies. Furthermore, it enables highly controllable testing of different geometries, which can be used for surgical planning and device development. Multidisciplinary collaboration between clinicians and biomedical engineers is essential to utilize the capabilities of computational modelling for surgical planning and device development. The challenge for the future is to perform prospective studies in larger patient populations to verify the computational results with postoperative clinical outcomes.