CAREER: A Parallel Computational Framework of Multiscale Geometric Modeling and Mesh Generation for Cardiac Biomechanics Application

职业：心脏生物力学应用的多尺度几何建模和网格生成的并行计算框架

• 批准号: 1149591
• 负责人: Yongjie Zhang
• 金额: $ 40万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-01 至 2019-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1149591&HistoricalAwards=false
• 关键词: CAREER; Parallel; Computational; Framework; Multiscale

The overall goal of this CAREER project is to establish a novel parallel computational framework of multiscale geometric modeling and mesh generation that can be applied to cardiac biomechanics applications. This capability will enable accurate, stable, efficient simulations of many biological processes such as calcium (Ca2+) mediated signaling, excitation-contraction coupling and energy metabolism in cardiac muscle cells, and lead to great advances in cardiac biomechanics. In cardiac muscle cells, Ca2+ is best known for its role in contraction activation. Alterations in Ca2+ distributions are now recognized to be the primary mechanisms of cardiac dysfunction in a diverse range of common pathologies including cardiac arrhythmias and hypertrophy. To predict and analyze how Ca2+ dynamics and cardiac excitation-contraction coupling are regulated, modeling of realistic geometries of large, complicated t-tubule network and associated protein complexes is needed. However, previous studies have been limited to simplified geometries. In this project, the PI focuses on 1) multiscale geometric modeling for protein complexes starting from atomic resolution data in the Protein Data Bank; 2) parallel mesh generation with topology ambiguity resolved and curvature-driven quality improvement; and 3) model validation in adaptive finite element analysis of Ca2+ signaling in ventricular myocytes with complicated realistic geometry. To handle such large, complicated systems, multicore parallel meshing toolkits will be developed and encapsulated with the simulation software. The proposed research will attain the highest degree of accuracy, efficiency and robustness in model development and simulation. It will significantly advance predictive capability in cardiac applications, and the understanding of anatomical and physiological properties at molecular and cellular scales. This parallel computational infrastructure can also be used for other complicated systems, providing engineers and scientists with novel technologies to construct accurate computer models. Furthermore, this interdisciplinary project will integrate research and education via novel educational tool and curriculum development as well as outreach activities. Students will interact with collaborative institutions to gain firsthand experience of real issues. Women, minority groups and high school students will be included in the proposed research and education activities through CMU's K-12 Programs. Education activities will be assessed in conjunction with CMU's Eberly Center for Teaching Excellence.

这个CAREER项目的总体目标是建立一个新的并行计算框架的多尺度几何建模和网格生成，可以应用到心脏生物力学的应用。 这种能力将能够准确，稳定，有效地模拟许多生物过程，如钙（Ca 2+）介导的信号传导，心肌细胞中的兴奋-收缩偶联和能量代谢，并导致心脏生物力学的巨大进步。 在心肌细胞中，Ca 2+最为人所知的是其在收缩激活中的作用。 Ca 2+分布的改变现在被认为是各种常见病理（包括心律失常和肥大）中心功能不全的主要机制。 为了预测和分析Ca 2+动力学和心脏兴奋-收缩耦合是如何调节的，需要对大型复杂的t-微管网络和相关蛋白质复合物的真实几何形状进行建模。 然而，以前的研究仅限于简化的几何形状。 在该项目中，PI专注于1）从蛋白质数据库中的原子分辨率数据开始的蛋白质复合物的多尺度几何建模; 2）并行网格生成，解决拓扑模糊性和曲率驱动的质量改进;以及3）具有复杂现实几何形状的心室肌细胞中Ca 2+信号的自适应有限元分析中的模型验证。 为了处理这样的大型，复杂的系统，多核并行网格工具包将开发和封装的仿真软件。建议的研究将达到最高程度的准确性，效率和鲁棒性的模型开发和仿真。 它将大大提高心脏应用的预测能力，以及在分子和细胞尺度上对解剖和生理特性的理解。 这种并行计算基础设施也可用于其他复杂系统，为工程师和科学家提供构建精确计算机模型的新技术。 此外，这个跨学科项目将通过新的教育工具和课程开发以及推广活动将研究和教育结合起来。 学生将与合作机构进行互动，以获得真实的问题的第一手经验。 妇女、少数群体和高中生将通过CMU的K-12方案被纳入拟议的研究和教育活动。 教育活动将与CMU的Eberly卓越教学中心一起进行评估。