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

正常的心脏通过收缩并将血液从左心室推到身体的其他部位来发挥功能。由于各种疾病，心脏的收缩能力在心室壁的某些区域减弱，损害心脏的整体功能。为了识别和选择最佳治疗，识别心脏壁收缩减少的区域至关重要。不幸的是，收缩不容易测量。该项目将通过结合心脏的医学成像和机械建模来估计心肌内产生的应力（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。该项目还将以协同整合的教育和推广计划为特色。我们将在罗切斯特理工学院和堪萨斯大学为计算机科学、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将开发创新的实践研讨会，以激励和教育来自生物医学计算和医学代表性不足的群体的K-12学生。本项目提出开发一种方法，能够对心肌中产生的主动应力进行无创评估和可视化，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设施，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的主动应力。PI将通过开发和集成医学图像计算、高阶网格和逆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利基，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。这项研究将有助于医学图像计算通过医学图像处理和可视化算法的发展。PI将开发和实施新型高阶网格技术，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。该项目将通过实现心脏生物力学逆问题的有效非线性最小二乘解，为数学建模和仿真提供新的知识。最后，PI将发布最终的网络基础设施给科学计算社区用于研究和教育。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.