Identifying Spatial Variation in Soft Tissue Mechanics and Predicting Failure: Application to Cardiac Rupture

识别软组织力学的空间变化并预测失败：在心脏破裂中的应用

• 批准号: 2030173
• 负责人: Colleen Witzenburg
• 金额: $ 43.95万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2030173&HistoricalAwards=false
• 关键词: Identifying; Spatial; Variation; Soft; Tissue

This award will support research that will increase our understanding of load-bearing soft tissues, promoting both the progress of science and advancing national health. Soft tissues such as tendons and blood vessels rely on their complex mechanical properties to withstand loads such as weight, force, or pressure. Unlike manmade materials, soft tissues can respond to changes in loading. Cells can remodel their surroundings, altering the regional strength and stiffness of the tissue. Unfortunately, disease and injury can lead to remodeling that is insufficient to withstand continued loading, putting the tissue at risk of tearing and rupture. This award supports fundamental research needed to develop, test, and validate methods to quantify spatial variation and to predict tissue failure. Quantifying spatial variation in material properties is essential since tissues fail at their weakest location. Without this capability, strategies to repair or replace injured tissue, tools to predict rupture risk, and therapies to reduce rupture propensity have all been stymied. Results from this research will benefit the U.S. health and society, impacting the fields of tissue mechanics, material science, surgery, and tissue engineering. Within a soft tissue, damage or disease often causes cells to remodel their surrounding extracellular matrix, which dictates mechanical response, in a non-uniform manner. For example, a heart attack initiates a complex inflammatory response involving both the degradation and synthesis of matrix proteins, altering regional stiffness, strength, and anisotropy. Though homogeneity is a common assumption, both local geometry and local material properties affect tissue failure. Therefore, measuring the spatial variation in material properties is essential for failure prediction. The work performed under this award will develop a nonlinear generalized inverse mechanics method to determine the heterogeneous properties of soft tissues and apply it to ventricular tissue after myocardial infarction, testing the hypothesis that the transition in mechanical properties is spatially more diffuse following late reperfusion therapy. This work will also develop an algorithm to predict the location of failure and test the hypothesis that the behavior of reperfused and non-reperfused ventricular tissue are the same at sub-failure levels, but differ following tear initiation. The experimental techniques and analysis tools developed will be broadly applicable to many different tissue types and disease states.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该奖项将支持将增加我们对承重软组织的理解，促进科学进步和促进国民健康的研究。肌腱和血管等软组织依靠其复杂的机械特性来承受诸如重量、力或压力等负荷。与人造材料不同，软组织可以对载荷的变化做出反应。细胞可以重塑周围环境，改变组织的局部强度和硬度。不幸的是，疾病和损伤会导致重塑不足以承受持续的负荷，使组织处于撕裂和破裂的危险之中。该奖项支持开发、测试和验证量化空间变异和预测组织衰竭方法所需的基础研究。量化材料属性的空间变化是必不可少的，因为组织在最薄弱的位置失效。如果没有这种能力，修复或替换受损组织的策略、预测破裂风险的工具以及降低破裂倾向的治疗方法都将受到阻碍。这项研究的结果将有益于美国的健康和社会，影响组织力学、材料科学、外科和组织工程等领域。在软组织中，损伤或疾病通常会导致细胞重塑周围的细胞外基质，从而以不均匀的方式决定机械反应。例如，心脏病发作会引发复杂的炎症反应，包括基质蛋白的降解和合成，改变区域的僵硬度、强度和各向异性。虽然均匀性是常见的假设，但局部几何形状和局部材料特性都会影响组织失效。因此，测量材料性能的空间变化对失效预测至关重要。在该奖项下进行的工作将发展一种非线性广义逆力学方法，以确定软组织的异质性，并将其应用于心肌梗死后的心室组织，验证力学性质的转变在空间上更弥漫性的假设。这项工作还将开发一种算法来预测衰竭的位置，并验证再灌注和非再灌注心室组织的行为在亚衰竭水平是相同的，但在撕裂开始后不同的假设。开发的实验技术和分析工具将广泛适用于许多不同的组织类型和疾病状态。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。