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平行的动态网格序列算法，理论和软件，用于在患者特定的下腔静脉（IVC）滤波器的特定设计中，以改善对深静脉血栓形成（DVT）的处理。 当血凝块形成深静脉时，这种威胁生命的疾病会产生。 DVT每年在美国影响超过200万人。 通常将机械过滤器放置在IVC中，以便在移动的血凝块到达心脏之前将其捕获。 典型的医生在治疗患者时仅使用一种或两种过滤器，而不是为患者的病情选择最合适的IVC过滤器。 IVC过滤器对血凝块夹带的当前计算模拟的精度低。 因此，将开发出生成IVC及周围静脉，IVC过滤器和血凝块的精确网格的技术。研究人员将开发新型的平行动态网格划分技术，以生成IVC和周围静脉，IVC滤波器和血液凝块的精确网格。 研究人员将开发平行的网格翘曲算法和MUTICORE软件，以根据患者特异性变形来更新网格。 将开发平行的几何和拓扑网格优化方法，以提高网格的质量。 该算法将以平行的动态网格划分工具包的形式封装，用于模拟辅助医疗干预措施。 此外，研究人员将开发一个理论框架，用于动态网络，以改善对变形的定量理解。 大学和大学前一级的教育活动将旨在为女性和代表性不足的学生建立探索计算科学的途径。