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，心脏的心室壁某些区域的收缩能力减弱，从而损害心脏的整体功能。为了确定和选择最佳治疗方法，确定收缩减少的心壁区域至关重要。不幸的是，收缩不能轻易测量。该项目将通过结合医学成像和心脏机械建模来估计心肌内产生的压力（收缩力）。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，这项研究有可能发展成为未来诊断心脏功能的工具。该项目还将提供一个协同整合的教育和推广计划。我们将为罗彻斯特理工学院和堪萨斯大学的计算机科学、生物医学工程、数学和成像科学领域的研究生和本科生提供研究机会。 PI 将举办创新的实践研讨会，以激励和教育来自代表性不足群体的 K-12 学生有关生物医学计算和医学的知识。该项目建议开发一种方法，能够对心肌中产生的主动应力进行非侵入性评估和可视化，作为评估心脏生物力学功能的直接手段。 PI 将开发开源网络基础设施，并将其集成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产生的主动应力。 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。这项研究将解决心脏建模领域目前尚未探索的领域，特别是心肌活动应力的重建和可视化，以实现心脏功能的直接评估。这项研究将通过开发医学图像处理和可视化算法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划分技术，并将其与光纤架构集成，以实现准确、高效的科学建模和计算。该项目将通过为逆心脏生物力学实施高效的非线性最小二乘解决方案，贡献数学建模和模拟方面的新知识。最后，PI 将向科学计算界发布最终的网络基础设施，用于研究和教育用途。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。