CAREER: Parallel Dynamic Meshing Techniques for Simulation-Assisted Medical Interventions

职业：用于模拟辅助医疗干预的并行动态网格技术

• 批准号: 1330056
• 负责人: Suzanne Shontz
• 金额: $ 35.08万
• 依托单位: Mississippi State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-10-01 至 2014-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1330056&HistoricalAwards=false
• 关键词: CAREER; Parallel; Dynamic; Meshing; Techniques

The investigators will research and develop parallel dynamic meshing algorithms, theory, and software for use in the patient-specific design of inferior vena cava (IVC) filters for improved treatment of deep vein thrombosis (DVT). This life-threatening disease results when blood clots form in a deep vein; DVT effects over 2,000,000 people in the U.S. each year. A mechanical filter is often placed in the IVC in order to trap a moving blood clot before it reaches the heart. A typical doctor uses only one or two types of filters when treating his patients rather than selecting the most appropriate IVC filter for his patient's condition. Current computational simulations of blood clot entrapment by IVC filters are of low accuracy. Hence, techniques to generate accurate meshes of the IVC and surrounding veins, IVC filter, and blood clots for use in such simulations will be developed. The investigators will develop novel, parallel dynamic meshing techniques to generate accurate meshes of the IVC and surrounding veins, IVC filter, and blood clots. The investigators will develop parallel mesh warping algorithms and muticore software for updating the meshes in response to patient-specific deformations. Parallel geometric and topological mesh optimization methods in order to improve the quality of the meshes will be developed. The algorithms will be encapsulated in the form of a parallel dynamic meshing toolkit for simulation-assisted medical interventions. In addition, the researchers will develop a theoretical framework for dynamic meshing for improved quantitative understanding of deformations. Educational activities at the college- and pre-college level will be designed to build pathways for women and underrepresented students to pursue computational science.

研究人员将研究和开发并行动态网格算法、理论和软件，用于下腔静脉（IVC）过滤器的患者特异性设计，以改善深静脉血栓（DVT）的治疗。这种危及生命的疾病是由于深静脉形成血块造成的；在美国，每年有超过200万人患有深静脉血栓。机械过滤器通常放置在下腔静脉，以便在移动的血块到达心脏之前将其捕获。一个典型的医生在治疗他的病人时只使用一种或两种类型的过滤器，而不是根据他的病人的情况选择最合适的下腔静脉过滤器。目前用IVC过滤器对血凝块捕获的计算模拟精度较低。因此，将开发用于此类模拟的精确生成下腔静脉和周围静脉，下腔静脉过滤器和血凝块网格的技术。研究人员将开发新的并行动态网格技术，以生成准确的下腔静脉和周围静脉、下腔静脉过滤器和血凝块网格。研究人员将开发并行网格翘曲算法和多核软件，用于更新网格以响应患者特定的变形。为了提高网格质量，将发展并行几何和拓扑网格优化方法。该算法将封装在一个并行的动态网格工具包的形式模拟辅助医疗干预。此外，研究人员将开发动态网格的理论框架，以提高对变形的定量理解。大学和大学预科阶段的教育活动将旨在为女性和代表性不足的学生开辟学习计算科学的途径。