CDS&E: Collaborative Research: A Computational Framework for Reconstructing and Visualizing Myocardial Active Stresses

CDS

基本信息

批准号：
1808553
负责人：
Suzanne Shontz
金额：
$ 33.1万
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：
2018
资助国家：
美国
起止时间：
2018-10-01 至 2023-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1808553&HistoricalAwards=false
关键词：
CDS&amp Collaborative Research Computational Framework

项目摘要

The normal heart functions by contracting and pushing the blood from the left ventricle into the rest of the body. Due to various diseases, the contraction capabilities of the heart become diminished in certain regions of the heart chamber wall, compromising the overall function of the heart. In order to identify and select optimal treatment, it is critical to identify the regions of the heart wall that exhibit reduced contractions. Unfortunately, contractions cannot be easily measured. This project will estimate the stress (contraction power) developed within the heart muscle by combining medical imaging and mechanical modeling of the heart. These stresses will serve as a quantitative measure of the contractile function of the heart and help detect and localize disease. Therefore, this research has the potential to evolve into a future tool to diagnose cardiac function. This project will also feature a synergistically integrated education and outreach program. We will foster research opportunities for graduate and undergraduate students in computer science, biomedical engineering, mathematics, and imaging science at Rochester Institute of Technology and the University of Kansas. The PIs will develop innovative hands-on workshops to inspire and educate K-12 students from underrepresented groups on biomedical computing and medicine. This project proposes to develop a method that enables non-invasive appraisal and visualization of the active stresses developed in the myocardium to serve as a direct means to assess the bio-mechanical function of the heart. The PIs will develop open-source cyberinfrastructure and integrate it into a novel computational framework for cardiac biomechanics that will reconstruct the active stresses from cardiac deformations. The PIs will accomplish this goal by developing and integrating techniques for medical image computing, high-order meshing, and inverse-problem bio-mechanical modeling. This research will address a currently unexplored niche in the cardiac modeling field, specifically the reconstruction and visualization of myocardial active stresses, to enable direct appraisal of cardiac function. This research will contribute to medical image computing through the development of algorithms for medical image processing and visualization. The PIs will develop and implement novel high-order meshing techniques and integrate them with the fiber architecture to enable accurate and efficient scientific modeling and computing. The project will contribute new knowledge in mathematical modeling and simulation by implementing efficient nonlinear least-squares solutions for inverse cardiac biomechanics. Lastly, the PIs will release the resulting cyberinfrastructure to the scientific computing community for research and education use.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

正常的心脏通过收缩并将血液从左心室推入身体其余部分来发挥作用。由于各种疾病，心脏腔室壁的某些区域的心脏收缩能力会降低，从而损害了心脏的整体功能。为了识别和选择最佳治疗，至关重要的是确定表现出减少收缩的心脏壁的区域。不幸的是，宫缩不能轻易测量。该项目将通过结合心脏的医学成像和心脏的机械建模来估计心肌内发展的压力（收缩力）。这些应力将作为对心脏收缩功能的定量度量，并有助于检测和定位疾病。因此，这项研究有可能发展为诊断心脏功能的未来工具。该项目还将采用协同综合的教育和外展计划。我们将为罗切斯特理工学院和堪萨斯大学的计算机科学，生物医学工程，数学和成像科学的研究生和本科生提供研究机会。 PI将开展创新的动手研讨会，以激发和教育来自代表性不足的生物医学计算和医学团体的K-12学生。该项目建议开发一种方法，该方法能够对心肌中开发的活动应力进行非侵入性评估和可视化，以作为评估心脏生物力学功能的直接手段。 PI将开发开源网络基础结构，并将其整合到心脏生物力学的新型计算框架中，该框架将重建心脏变形中的主动应力。 PI将通过开发和集成用于医学图像计算，高阶网格序和逆问题生物力学建模的技术来实现这一目标。这项研究将解决心脏建模领域中当前未开发的利基市场，特别是心肌主动应力的重建和可视化，以直接评估心脏功能。这项研究将通过开发用于医学图像处理和可视化的算法来为医学图像计算做出贡献。 PI将开发和实施新颖的高阶网络介绍技术，并将它们与纤维结构集成在一起，以实现准确有效的科学建模和计算。该项目将通过实施有效的非线性最小二乘解决方案来为反向心脏生物力学实施有效的非线性最小二乘解决方案，从而为数学建模和仿真提供新知识。最后，PI将将所得的网络基础设施发布给科学计算社区，以供研究和教育使用。该奖项反映了NSF的法定使命，并使用基金会的知识分子优点和更广泛的影响审查标准，认为值得通过评估来获得支持。