Generalized Anisotropic Inverse Mechanics for Structural Tissues

描述（由申请人提供）：我们建议测试一种新技术-广义各向异性逆力学（GAIM）方法-用于根据位移图像确定作为位置函数的组织各向异性。该方法利用位移数据和组织的一般线弹性力学模型，通过直接求解逆力学问题来确定不同位置处的力学参数。该方法将域划分为多个区域，并且假设一般线弹性张量的分量在每个分区上是恒定的。我们已经在模拟数据上测试了GAIM，但需要在真实的数据上进行研究，以评估其生成有关离体和体内组织的有用信息的能力。在这个探索性的项目中，我们将测试的假设，GAIM可以成功地提供分布式的机械信息的天然和工程组织，以及机械各向异性与结构各向异性，后者测量的其他方法的次要假设。如果成功，该项目将为GAIM技术的未来开发和实施奠定基础，从而为生物力学成像提供一种新的工具。组织的机械特性对于正常功能是必不可少的，并且可以指示损伤或疾病。非侵入性地研究健康与受损组织的工具的可用性，特别是在愈合期间，将是我们理解承重组织中的损伤和愈合的能力的主要帮助（例如，心脏瓣膜、心肌、腱、韧带），因此与公共健康高度相关。 公共卫生相关性：我们将探索一种新的生物力学图像分析技术-广义各向异性逆力学（GAIM）方法-测量分布，方向相关的组织特性的基础上产生的位移图像。与标准方法不同，GAIM计算组织的各向异性及其刚度，可能允许在体外和体内高度结构化组织中对损伤，疾病和愈合进行新水平的评估。

DESCRIPTION (provided by applicant): We propose to test a novel technique - the Generalized Anisotropic Inverse Mechanics (GAIM) method - for determination of tissue anisotropy as a function of position from a displacement image. The approach uses displacement data and a general linear elastic mechanical model for tissue to determine mechanical parameters at different positions by solving the inverse mechanics problem directly. The method partitions the domain into regions, and the components of the general linear elasticity tensor are assumed to be constant over each partition. We have tested GAIM on simulated data but need to perform studies on real data to assess its ability to generate useful information about ex vivo and in vivo tissues. In this exploratory project, we will test the hypothesis that GAIM can successfully provide distributed mechanical information about native and engineered tissue, as well as the secondary hypothesis that mechanical anisotropy correlates with structural anisotropy, the latter measured by other methods. If successful, the project will lay the groundwork for future development and implementation of the GAIM technique and thus lead to a new tool for biomechanical imaging. Mechanical properties of tissues are essential for proper function and may indicate injury or disease. The availability of a tool to study healthy vs. damaged tissue non-invasively, particularly during healing, would be a major aid to our ability to understand injury and healing in load-bearing tissues (e.g., heart valve, myocardium, tendon, ligament) and is thus highly relevant to public health. PUBLIC HEALTH RELEVANCE: We will explore a new biomechanical image analysis technique - the Generalized Anisotropic Inverse Mechanics (GAIM) method - to measure distributed, direction-dependent tissue properties based on displacement images generated. Unlike standard methods, GAIM calculates the anisotropy of the tissue as well as its stiffness, potentially allowing a new level of evaluation of injury, disease, and healing in highly structured tissues, in vitro and perhaps in vivo.