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Transformation Elastography

变换弹性成像

基本信息

批准号：
1852691
负责人：
Thomas Royston
金额：
$ 40.61万
依托单位：
University of Illinois at Chicago
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-06-01 至 2023-05-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1852691&HistoricalAwards=false
关键词：
Transformation Elastography

项目摘要

Elastography refers to mapping mechanical properties in a material based on measuring wave motion in it using noninvasive optical, acoustic or magnetic resonance imaging methods. For example, increased stiffness will increase wavelength. Stiffness and viscosity can depend on both location and direction. A material with aligned fibers or layers may have different stiffness and viscosity values along the fibers or layers versus across them. Converting wave measurements into a mechanical property map or image is known as reconstruction. Reconstruction in isotropic materials, with the same mechanical properties regardless of direction, is easier than in anisotropic materials, whose properties vary with direction. Transformation Elastography is based on the idea of distorting the material as part of the reconstruction algorithm to make the anisotropic problem become isotropic. This strategy, which has been shown to work in simple two-dimensional reconstruction problems, will be extended to more complex three-dimensional problems. Elastography is a potentially transformative measurement technology for basic research into material mechanics. Extending it to anisotropic materials is essential to advance its application in geophysical exploration, fiber composite analysis, and medical diagnosis of diseases of the brain, skeletal muscle, heart and other organs with aligned fibers for which changes in stiffness and viscosity have been proven to correlate with disease. This research supports NSF's mission to promote the progress of science and advance national health. Research developments will be integrated into courses and multimedia educational materials for a diverse group of students at multiple levels, from K-12 through graduate level engineering.Elastography relies on a constitutive model of mechanical wave motion in the viscoelastic material to interpret the noninvasive measurements. To make the modeling problem analytically tractable, isotropy and homogeneity are often assumed, and the effects of finite boundaries are ignored. But, infinite isotropic homogeneity is not the situation in most cases of interest, when there are pathological conditions, material faults or hidden anomalies that are not uniformly distributed in fibrous or layered structures of finite dimension. Introduction of anisotropy, inhomogeneity and finite boundaries complicates the analysis forcing the abandonment of analytically-driven strategies, in favor of numerical approximations that are computationally expensive and yield less physical insight. A new strategy, Transformation Elastography, is planned that involves spatial distortion in order to make an anisotropic problem become isotropic. Development and experimental validation of this new strategy requires inverting the algorithm and extending initial developments from two- to three-dimensional problems with inhomogeneity.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.

弹性成像是指利用非侵入性的光学、声学或磁共振成像方法，通过测量材料中的波动来绘制材料的力学特性。例如，刚度的增加会增加波长。刚度和粘度可以取决于位置和方向。具有排列纤维或层的材料沿纤维或层可能具有不同的刚度和粘度值。将波浪测量值转换成机械属性图或图像称为重建。各向异性材料的力学性能随方向而变化，而各向异性材料的力学性能随方向而变化，因此各向同性材料的重建更容易。转换弹性成像的思想是将材料变形作为重建算法的一部分，使各向异性问题变成各向同性问题。这一策略已被证明适用于简单的二维重建问题，将扩展到更复杂的三维问题。弹性成像对于材料力学的基础研究是一种潜在的变革性测量技术。将其扩展到各向异性材料，对于推进其在地球物理勘探、纤维复合分析以及对具有排列纤维的大脑、骨骼肌、心脏和其他器官疾病的医学诊断中的应用至关重要，这些疾病的刚度和粘度的变化已被证明与疾病有关。这项研究支持了NSF促进科学进步和促进国民健康的使命。研究进展将整合到课程和多媒体教育材料中，为不同层次的学生提供服务，从K-12到研究生水平的工程。弹性成像依赖于粘弹性材料中机械波动的本构模型来解释非侵入性测量。为了使建模问题易于解析处理，通常假设各向同性和均匀性，而忽略有限边界的影响。但是，在大多数感兴趣的情况下，当存在病理条件、材料缺陷或隐藏异常，而这些异常在有限维的纤维或层状结构中不均匀分布时，就不会出现无限各向同性的情况。引入各向异性、非均匀性和有限边界使分析变得复杂，迫使放弃分析驱动的策略，转而采用计算成本高且产生较少物理洞察力的数值近似。为了使各向异性问题变成各向同性问题，我们提出了一种新的策略，即转换弹性图。这种新策略的发展和实验验证需要反转算法并将初始发展从二维扩展到具有非均匀性的三维问题。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。