Multi-Scale Model of the Human Heart for Imaging Research

描述(由申请人提供)：为了更好地了解心脏的正常和病理功能，长期以来一直在开发心脏的综合计算模型。这些模型的一个关键组成部分是肌肉组织的肌纤维结构，它决定了心脏在健康和疾病中的电气和机械功能。由于计算方面的考虑和缺乏人体肌纤维结构的高分辨率成像数据，以前的计算模型基于动物数据，仅针对右和左心室进行定义。随着更有效的机电建模算法的发展，以及计算能力和成像技术的进步，如多层螺旋CT和扩散张量磁共振成像，现在为开发更复杂和详细的人体心脏模型提供了可能。该项目的长期目标是开发和验证一个四腔人体心脏的4D多尺度有限元(FE)计算模型，该模型能够基于最先进的人体成像数据真实地模拟正常和异常的心脏解剖和功能。这份提案概述了该项目的第一步，该项目将专注于对正常功能的人类心脏及其在人群中的变异进行建模。这种正常的心脏模型将为我们在未来的工作中模拟疾病过程提供必要的基础。提出的心脏模型在生物力学、生物物理学和生理学的教育和研究方面具有巨大的潜力，可以在多个层面上更深入地了解人类心脏的复杂性及其在健康和疾病中的功能基础。它将提供一个现实的框架，将细胞水平的结构和功能与完整的人类心脏和在普通人群中发现的一组解剖变异联系起来。心脏模型的驱动应用将作为成像研究和教育的模拟工具。当与人体的数字体模相结合时，该模型将提供现实的、预测性的多模式患者成像数据，这些数据来自健康和疾病的不同解剖对象。有了这一能力，该模型将提供一个独特而重要的工具，以定量评估和比较目前和新兴的4D成像技术在心血管疾病诊断中的应用。它还可以使用各种程序和扫描参数提供模拟数据，以培训医生。与公共卫生相关：这项提议的目标是开发一种人类心脏的计算模型，跨越从细胞到人群的生物物理尺度，能够真实地模拟正常和异常的心脏解剖和功能。拟议的心脏模型在教育和研究方面具有巨大的潜力，可以更深入地了解人类心脏的复杂性及其在健康和疾病中的功能基础。它将为了解心血管疾病的潜在机制及其对心脏功能的影响以及评估和改进用于诊断的现有和新兴的4D成像技术提供一个重要的模拟工具。

DESCRIPTION (provided by applicant): Integrated computational models of the heart have long been developed in order to gain a greater understanding of the normal and pathological function of the heart. A key component of these models is the myofiber architecture of the muscle tissue which dictates the heart's electrical and mechanical functions in health and disease. Due to computational concerns and the lack of high-resolution imaging data of the human myofiber architecture, previous computational models were based on animal data and were defined for just the right and left ventricles. With the development of more efficient algorithms for electromechanical modeling as well as advances in computational power and imaging technologies such as multi-slice CT and diffusion tensor MRI, it is now feasible to develop more complex and detailed models for the human heart. The long term goal of this project is to develop and validate a 4D multi-scale finite-element (FE) computational model of the 4-chamber human heart capable of realistically simulating normal and abnormal cardiac anatomy and function based on state-of-the-art human imaging data. This proposal outlines the first step of the project which will focus on modeling the normal functioning human heart and its variations in a population. This normal cardiac model will provide the necessary foundation from which we may simulate disease processes in future work. The proposed heart model has enormous potential in education and research in biomechanics, biophysics, and physiology, providing a deeper understanding of the complexity of the human heart at multiple levels and the basis of its function in health and disease. It will provide a realistic framework to link structure and function from the cellular level to that of the intact human heart and to a group of anatomical variations found in the general population. The driving application for the cardiac model will be as a simulation tool for imaging research and education. When combined with a digital phantom for the human body, the model will provide realistic, predictive multi-modality patient imaging data from anatomically diverse subjects in health and disease. With this ability, the model will provide a unique and vital tool to quantitatively evaluate and compare current and emerging 4D imaging techniques used in the diagnosis of cardiovascular disease. It may also provide simulated data using various procedures and scanning parameters to train physicians. PUBLIC HEALTH RELEVANCE: The goal of this proposal is to develop a computational model of the human heart, spanning biophysical scales from cell to population, capable of realistically simulating normal and abnormal cardiac anatomy and function. The proposed heart model has enormous potential in education and research, providing a deeper understanding of the complexity of the human heart and the basis of its function in health and disease. It will provide a vital simulation tool for understanding the underlying mechanisms of cardiovascular disease and its effect on cardiac function and for evaluating and improving existing and emerging 4D imaging techniques used in its diagnosis.