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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的其他部位来发挥作用。由于各种疾病，心脏的收缩能力在心腔壁的某些区域变得减弱，从而损害心脏的整体功能。为了确定和选择最佳的治疗方法，确定心壁收缩减少的区域是至关重要的。不幸的是，收缩不容易测量。这个项目将通过结合医学成像和心脏的机械建模来估计心肌内产生的应力(收缩能力)。这些压力将作为心脏收缩功能的定量测量，并有助于检测和定位疾病。因此，这项研究有可能演变为未来诊断心脏功能的工具。该项目还将以协同整合的教育和外联计划为特色。我们将为罗切斯特理工学院和堪萨斯大学计算机科学、生物医学工程、数学和成像科学的研究生和本科生培养研究机会。PIS将开发创新的动手工作坊，以启发和教育来自代表性不足群体的K-12学生生物医学计算和医学。该项目建议开发一种方法，能够对心肌中形成的主动应力进行非侵入性评估和可视化，作为评估心脏生物机械功能的直接手段。PIS将开发开源的网络基础设施，并将其集成到心脏生物力学的新计算框架中，该框架将重建心脏变形的主动应力。PI将通过开发和集成医学图像计算、高阶网格划分和反问题生物力学建模技术来实现这一目标。这项研究将解决目前心脏建模领域中一个尚未探索的领域，特别是心肌主动应力的重建和可视化，以实现对心功能的直接评估。这项研究将通过开发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格技术，并将它们与光纤体系结构相结合，以实现准确而高效的科学建模和计算。该项目将通过实现心脏生物力学逆问题的高效非线性最小二乘解，在数学建模和仿真方面贡献新的知识。最后，PIS将把由此产生的网络基础设施发布给科学计算社区用于研究和教育。这一奖励反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。