Generalized Anisotropic Inverse Mechanics for Structural Tissues

结构组织的广义各向异性逆力学

• 批准号: 8117688
• 负责人: VICTOR H BAROCAS
• 金额: $ 17.3万
• 依托单位: UNIVERSITY OF MINNESOTA
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-08-01 至 2013-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8117688
• 关键词: Algorithms; Anisotropy; Architecture; Area; Attention; Biological; Biomechanics; Biomedical Engineering; Blood Vessels; Cancer Detection; Cardiac; Collagen; Data; Data Analyses; Data Set; Detection; Development; Disease; Elasticity; Evaluation; Family suidae; Freezing; Future; Healed; Heart Valves; Image; Image Analysis; In Vitro; Injury; Lead; Ligaments; Measurement; Measures; Mechanics; Methods; Modeling; Myocardium; Output; Polarization Microscopy; Positioning Attribute; Property; Public Health; Relative (related person); Scheme; Simulate; Skin; Structure; Techniques; Tendon structure; Testing; Tissue Engineering; Tissue Model; Tissues; Variant; Weight-Bearing state; Work; base; capsular ligament; cost; femoral artery; healing; improved; in vivo; novel; polarized light; public health relevance; research study; response; supraspinatus muscle; tool; tumor

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.

描述(由申请人提供)：我们建议测试一种新的技术--广义各向异性逆力学(GAIM)方法--用于根据位移图像确定组织各向异性作为位置的函数。该方法利用位移数据和组织的一般线弹性力学模型，通过直接求解力学逆问题来确定不同位置的力学参数。该方法将区域划分为多个区域，并假定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，但需要在真实数据上进行研究，以评估其生成关于体外和体内组织的有用信息的能力。在这个探索性项目中，我们将测试GAIM可以成功提供有关天然组织和工程组织的分布式机械信息的假设，以及机械各向异性与结构各向异性相关的次要假设，后者可通过其他方法测量。如果成功，该项目将为未来GAIM技术的开发和实施奠定基础，从而产生一种新的生物力学成像工具。组织的机械性能对于正常的功能是必不可少的，可能预示着损伤或疾病。一种非侵入性研究健康和受损组织的工具的可用性，特别是在愈合过程中，将对我们了解承载组织(例如心脏瓣膜、心肌、肌腱、韧带)的损伤和愈合的能力有很大的帮助，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--基于生成的位移图像来测量分布的、方向相关的组织属性。与标准方法不同，GAIM计算组织的各向异性及其硬度，潜在地允许在体外或体内对高度结构的组织中的损伤、疾病和愈合进行新的水平的评估。