An Efficient Hemodynamic Workflow in Computational Surgery

For few decades, it has been shown that atherosclerosis is the cause of the majority of clinical cardiovascular diseases including peripheral arterial diseases. The diagnosis and treatment for vascular disease has evolved significantly over the past years considering the rapid advances in imaging technologies. In recent years, computational fluid dynamics has been increasingly used as a simulation tool for blood flows. Numerous researches connect wall shear stress quantities to endovascular diseases such as stenosis, aneurism, and atherosclerosis. A thorough knowledge of vascular anatomy and hemodynamic would be beneficial for understanding the development and progression of the disease, the therapeutic decision process and follow up. The objective of this dissertation is to propose a computational fluid dynamic framework that includes: Understanding how streamline efficiently hemodynamic simulation for main arteries to produce database for clinical study/Providing some confidence estimate on numerical results/Extending the state of the art of clinical study by including motion and particles analysis.