Multiscale cardiac fluid-structure-growth model

多尺度心脏液体结构生长模型

• 批准号: 1702987
• 负责人: Tong Gao
• 金额: $ 30万
• 依托单位: Michigan State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1702987&HistoricalAwards=false
• 关键词: Multiscale; cardiac; fluid; structure; growth

Patient-specific computational models have tremendous potential in revolutionizing disease management and advancing heart failure treatments. Significant advances have been made in the last twenty years on the theoretical and computational developments of cardiac computational models. However, there is currently a lack of a complete computational model that is capable of taking into account all the principal physics occurring in a beating heart, specifically, electrical conduction in the heart, dynamics of blood flow, mechanics of the cardiac wall motion, and the long-term changes in heart function and geometry. The lack of such a modeling framework is a critical barrier to the development of in-depth knowledge about the heart function and diseases. This is especially so as the interactions of these physics are important aspects that need to be taken into account when designing heart disease treatments and understanding heart function. The proposed project aims to develop a strongly-coupled cardiac electromechanics-fluid-growth computational modeling framework that takes into account the key principal physics occurring in the beating heart. Both graduate and undergraduate students will be involved with the research project.The proposed bottom-up multiscale model will be versatile to allow for arbitrary 3D heart geometries as well as multiscale physics, including: (i) cellular excitation-contraction coupling processes, (ii) contribution of constituents found in the cardiac tissue to its anisotropic mechanical behavior, (iii) macroscale fluid-structure interactions between the heart wall and blood, and (iv) long term growth and remodeling processes. Specific goals that will be accomplished in this project are as follows. First, a strongly coupled cardiac electromechanics-fluid modeling framework will be developed based on a hybrid Fictitious-Domain Arbitrary-Lagrange-Eulerian formulation to describe the short-term bidirectional fluid-elastic-structure interactions between blood flow and ventricular wall deformation driven by the cellular excitation-contraction coupling processes. Second, a cardiac growth model will be integrated into the modeling framework based on the principle of timescale separation to describe long-term changes in the heart geometry and function driven by pathophysiological insults. Last, with clinical data obtained from collaborators, the PIs will apply the modeling framework to develop new understanding concerning normal and abnormal heart functions, such as the short- and long-term effects arising from flow obstruction due to abnormalities in the geometry and deformation of the ventricular wall in hypertrophic cardiomyopathy.

针对患者的计算模型在革新疾病管理和推进心力衰竭治疗方面具有巨大的潜力。在过去的二十年中，心脏计算模型的理论和计算发展取得了重大进展。然而，目前还缺乏一个完整的计算模型，能够考虑到心脏跳动中发生的所有主要物理现象，特别是心脏中的电传导、血流动力学、心壁运动力学以及心脏功能和几何形状的长期变化。缺乏这样一个建模框架是发展深入了解心脏功能和疾病的关键障碍。在设计心脏病治疗和了解心脏功能时，这些物理的相互作用是需要考虑的重要方面，因此尤其如此。拟议的项目旨在开发一个强耦合的心脏机电-流体生长计算建模框架，考虑到心脏跳动中发生的关键主要物理现象。研究生和本科生都将参与研究项目。提出的自下而上的多尺度模型将是多功能的，允许任意的3D心脏几何形状以及多尺度物理，包括：(i)细胞兴奋-收缩耦合过程，（ii）心脏组织中发现的成分对其各向异性力学行为的贡献，（iii）心脏壁和血液之间的宏观流体结构相互作用，以及（iv）长期生长和重塑过程。在这个项目中将完成的具体目标如下。首先，将基于混合虚拟域任意拉格朗日-欧拉公式建立一个强耦合的心脏力学-流体建模框架，以描述由细胞兴奋-收缩耦合过程驱动的血流和心室壁变形之间的短期双向流体-弹性-结构相互作用。其次，将基于时间尺度分离原理的心脏生长模型整合到建模框架中，以描述由病理生理损伤驱动的心脏几何形状和功能的长期变化。最后，根据合作者提供的临床数据，pi将应用建模框架对正常和异常心功能进行新的理解，例如肥厚性心肌病中由于心室壁几何形状异常和变形引起的血流阻塞所产生的短期和长期影响。

项目成果

Model of Anisotropic Reverse Cardiac Growth in Mechanical Dyssynchrony

• DOI: 10.1038/s41598-019-48670-8
• 发表时间: 2019-09-03
• 期刊: SCIENTIFIC REPORTS
• 影响因子: 4.6
• 作者: Arumugam, Jayayel;Mojumder, Joy;Lee, Lik Chuan
• 通讯作者: Lee, Lik Chuan

Control-oriented Modeling of Soft Robotic Swimmer with Koopman Operators

• DOI: 10.1109/aim43001.2020.9159033
• 发表时间: 2020-07
• 期刊: 2020 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)
• 作者: Maria L. Castaño;Andrew Hess;Giorgos Mamakoukas;Tong Gao;T. Murphey;Xiaobo Tan

CFD-based multi-objective controller optimization for soft robotic fish with muscle-like actuation

• DOI: 10.1088/1748-3190/ab6dbb
• 发表时间: 2020-05-01
• 期刊: BIOINSPIRATION & BIOMIMETICS
• 影响因子: 3.4
• 作者: Hess, Andrew;Tan, Xiaobo;Gao, Tong
• 通讯作者: Gao, Tong

Stability of Couette flow past a gel film

库埃特流过凝胶膜的稳定性

• DOI: 10.1016/j.taml.2017.09.006
• 发表时间: 2017
• 期刊: Theoretical and Applied Mechanics Letters
• 影响因子: 3.4
• 作者: Hess, Andrew;Cai, Shengqiang;Gao, Tong
• 通讯作者: Gao, Tong

Polydopamine-Coated Main-Chain Liquid Crystal Elastomer as Optically Driven Artificial Muscle

聚多巴胺涂层主链液晶弹性体作为光驱动人造肌肉

• DOI: 10.1021/acsami.8b00639
• 发表时间: 2018-03-07
• 期刊: ACS APPLIED MATERIALS & INTERFACES
• 影响因子: 9.5
• 作者: Tian, Hongmiao;Wang, Zhijian;Cai, Shengqiang
• 通讯作者: Cai, Shengqiang