TISSUE STRAIN AND ELASTICITY THROUGH SPECKLE MOTION

通过散斑运动测量组织应变和弹性

• 批准号: 5209361
• 负责人: MICHEL BERTRAND
• 金额: --
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/5209361
• 关键词: elastic tissue; elasticity; imaging /visualization /scanning; mathematical model; phantom model; ultrasonography

The long term objective of this research is to develop a method to infer and image tissue hardness using ultrasounds. This method would bring new quantitative informations about the condition of a tissue, similar to what palpation does qualitatively when sensing "hard" tumor or a muscle under contraction. It consists essentially in measuring the tissue deformation induced through an external force, the deformation being large in a compliant (i.e. soft) material, and smaller in a rigid (hard) one. As proposed here, tissue deformation is assessed by tracking the spatio- temporal changes induced by the compression force on the ultrasound speckle patterns. Technically, this application is for developing a model-based approach to compute the elasticity distribution (also called the elastogram) using ultrasound speckle displacement data. First it is proposed to study a direct elasticity problem; here the aim is to provide an analytical framework and a computer model of image formation for speckle correlation and motion, assuming an elastic scattering medium subjected to deformations. From a theoretical point of view, this will serve to better understand the complex relationship between the spatio-temporal changes in ultrasound signals and the underlying tissue motion. From a practical standpoint, this will serve to develop and test tissue motion estimators based either on speckle correlation measurements or on optical flow. Tissue motion estimation is the first step in solving the inverse elasticity problem which can be stated as: determining the spatial distribution of elasticity that could best reproduce the estimated tissue motion under constraints provided by the elasticity equations and boundary conditions. It is proposed to develop an iterative procedure to seek the optimal elastogram, i.e. an optical flow algorithm adapted to this problem; this elastogram will be compared to the one which is currently studied by others, and which uses correlation-based one-dimensional tissue motion estimator. It is finally proposed to study the improvement on the estimation of elasticity distribution through use of 2D and 3D speckle motion.

这项研究的长期目标是开发一种方法来推断 并使用超声波对组织硬度进行成像。 这个方法会带来新的 有关组织状况的定量信息，类似于 当触诊感觉到“硬”肿瘤或下面的肌肉时，触诊可以定性 收缩。 它主要包括测量组织变形 由外力引起，变形较大 柔顺（即软）材料，而刚性（硬）材料则较小。 作为 这里提出，组织变形是通过跟踪空间来评估的 超声波上的压缩力引起的时间变化 散斑图案。 从技术上讲，该应用程序用于开发基于模型的方法 使用以下方法计算弹性分布（也称为弹性图） 超声散斑位移数据。 首先建议研究一个 直接弹性问题；这里的目的是提供分析 散斑相关图像形成的框架和计算机模型 和运动，假设弹性散射介质受到 变形。 从理论上讲，这将有助于更好地 了解时空变化之间的复杂关系 超声信号和底层组织运动。 从实际出发 从角度来看，这将有助于开发和测试组织运动估计器 基于散斑相关测量或光流。 组织运动估计是求解逆矩阵的第一步 弹性问题可以表述为：确定空间 可以最好地再现估计组织的弹性分布 由弹性方程和边界提供的约束下的运动 状况。 建议开发一个迭代程序来寻求 最佳弹性图，即适应于此的光流算法 问题;该弹性图将与当前的弹性图进行比较 由其他人研究，并且使用基于相关的一维组织 运动估计器。 最后提出研究改进 通过使用 2D 和 3D 散斑估计弹性分布 运动。