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

ITR/AP：基于模拟的心血管疾病的医疗计划目前用于治疗先天性和获得性心血管疾病的介入和手术计划的范例完全依赖于诊断成像数据来定义患者的当前状态，经验数据来评估类似患者的先前治疗的疗效，以及外科医生的判断来决定优选的治疗。 人类生物系统的个体可变性和固有复杂性使得单独的诊断成像和经验数据不足以预测针对个体患者的给定治疗的结果。本提案中描述的具体目标是开发基于模拟的医疗计划的问题解决环境，结合（i）直接从医学成像数据构建人体血管系统的患者特定术前几何模型，（ii）修改这些模型以纳入多个潜在的介入和手术计划，（iii）生成治疗计划的有限元网格，（iv）模拟这些患者特定模型中的血流，以及（v）可视化和量化所得到的生理信息。将改进使用二维和三维水平集方法从计算机断层扫描（CT）和磁共振成像（MRI）数据中识别血管边界的技术，以提高准确性和效率。成功完成上述任务的最终结果将是开发一个集成的问题解决环境，用于基于模拟的医疗规划，包括图像分割、几何建模、网格生成、计算力学和科学可视化技术。

ITR/AP: Simulation-Based Medical Planning for Cardiovascular DiseaseThe 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.