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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

基本信息

批准号：
1500487
负责人：
Suzanne Shontz
金额：
$ 26.55万
依托单位：
University of Kansas Center for Research Inc
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2014
资助国家：
美国
起止时间：
2014-10-01 至 2017-01-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1500487&HistoricalAwards=false
关键词：
CAREER Parallel Dynamic Meshing Techniques

项目摘要

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）滤器的患者特定设计，以改善深静脉血栓形成（DVT）的治疗。这种危及生命的疾病是在深静脉中形成血栓时引起的; DVT每年影响美国超过2，000，000人。机械过滤器通常放置在IVC中，以便在血液凝块到达心脏之前捕获移动的血液凝块。典型的医生在治疗患者时仅使用一种或两种类型的过滤器，而不是根据患者的病情选择最合适的IVC过滤器。目前IVC过滤器截留血凝块的计算模拟精度较低。因此，将开发用于生成IVC和周围静脉、IVC过滤器和血凝块的精确网格的技术以用于这种模拟。研究者将开发新的并行动态网格技术，以生成IVC和周围静脉、IVC滤器和血凝块的精确网格。研究人员将开发并行网格扭曲算法和多核软件，用于更新网格以响应患者特定的变形。并行几何和拓扑网格优化方法，以提高网格的质量将被开发。该算法将被封装在一个并行动态网格工具包的形式模拟辅助医疗干预。此外，研究人员将开发一个动态网格的理论框架，以提高对变形的定量理解。大学和大学预科教育活动的目的是为妇女和代表性不足的学生建立追求计算科学的途径。