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

该奖项将支持研究，这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。肌腱和血管等软组织依靠其复杂的机械特性来承受重量、力或压力等载荷。与人造材料不同，软组织可以对负荷的变化做出反应。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，疾病和损伤可能导致重塑，不足以承受持续的负荷，使组织处于撕裂和破裂的风险。该奖项支持开发，测试和验证量化空间变化和预测组织失效的方法所需的基础研究。量化材料特性的空间变化是必不可少的，因为组织在其最薄弱的位置失败。如果没有这种能力，修复或替换受伤组织的策略，预测破裂风险的工具，以及减少破裂倾向的治疗方法都将受到阻碍。这项研究的结果将有利于美国的健康和社会，影响组织力学，材料科学，外科手术和组织工程领域。在软组织内，损伤或疾病通常导致细胞以不均匀的方式重塑其周围的细胞外基质，这决定了机械响应。例如，心脏病发作引发复杂的炎症反应，涉及基质蛋白的降解和合成，改变局部硬度，强度和各向异性。虽然均匀性是一个常见的假设，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于失效预测是必不可少的。在该奖项下进行的工作将开发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，测试力学性质的转变在后期再灌注治疗后空间上更加扩散的假设。 这项工作还将开发一种算法来预测故障的位置，并测试假设，即再灌注和非再灌注心室组织的行为在子故障水平是相同的，但在撕裂开始后不同。该奖项反映了NSF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。

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.