ITR/AP: Simulation-Based Medical Planning for Cardiovascular Disease

Stanford University, Stanford CA

Investigators

Abstract

ITR/AP: Simulation-Based Medical Planning for Cardiovascular Disease The current paradigm for interventional and surgery planning for the treatment of congenital and acquired cardiovascular disease relies exclusively on diagnostic imaging data to define the present state of the patient, empirical data to evaluate the efficacy of prior treatments for similar patients, and the judgement of the surgeon to decide on a preferred treatment. The individual variability and inherent complexity of human biological systems is such that diagnostic imaging and empirical data alone are insufficient to predict the outcome of a given treatment for an individual patient. The specific objectives described in the present proposal are to develop a Problem Solving Environment for Simulation-Based Medical Planning combining (i) the construction of patient-specific preoperative geometric models of the human vascular system directly from medical imaging data, (ii) the modification of these models to incorporate multiple potential interventional and surgical plans, (iii) the generation of finite element meshes of the treatment plans, (iv) the simulation of blood flow in these patient-specific models, and (v) the visualization and quantification of resulting physiologic information. Techniques for identifying vessel boundaries from computed tomography (CT) and magnetic resonance imaging (MRI) data using two- and three-dimensional level set methods will be improved to enhance accuracy and efficiency. The ultimate result of the successful completion of the outlined tasks will be the development of an integrated Problem Solving Environment for Simulation-Based Medical Planning incorporating image segmentation, geometric modeling, mesh generation, computational mechanics, and scientific visualization techniques.