ACOUSTIC NONLINEARITY FOR TISSUE CHARACTERIZATION

该提案是协会成员之间的一个合作项目 超声和磁共振成像实验室和 马约基金会病理学系。 总目标 本项目的目的是深入了解 相关声学非线性和声速参数 组织的内在属性，并利用这一点， 信息来构建显示内在 组织的性质，即，其组成。 我们以前已经做了大量的声学测量， 离体人的非线性参数（B/A）和声速（c 组织和许多模型液体。 根据这些 我们已经确定，这些大小的测量， 声学参数与体积分数定量相关 组织的组成部分。 此外，我们已经表明，这些 参数可以在数学建模的帮助下使用， 洗脱组织中水的物理状态。 言下之意 任何特定的疾病过程， 组织成分应该可以通过观察 这些声学参数的大小。 也就是说，B/A和 In是用于组织目的的合适候选物 表征和成像。 目前的建议包括三个具体目标：1） 验证了一个假设，即引起 声学非线性，或者说是有限声速的原因， 由于分子水平的扰动而发生， 2）制定、实施和评估三个 不同的方法（频率混合、幅度调制和脉冲调制 反转）以制作非线性参数的图像;以及3） 使用混合定律和声学数据来构建组织的图像 显示的二维分布的组成 组织中

This proposal is a collaborative project between the members of the Ultrasonic and Magnetic Resonance Imaging Laboratories and the Department of Pathology at the Mayo Foundation. The overall goal of this project is to obtain insight into the mechanisms that interrelate acoustic nonlinearity and sound speed parameters of tissues to their intrinsic properties, and to exploit this information to construct images that display the intrinsic properties of tissues, viz., its composition. We have previously made extensive measurements of acoustic nonlinearity parameter (B/A) and sound speed (c) in excised human tissues and numerous model liquids. On the basis of these measurements we have established that the magnitude of these acoustic parameters relate quantitatively to the volume fractions of the constituents of tissues. Also, we have shown that these parameters can be used with the aid of mathematieal modeling to elueidate the physical state of water in tissues. The implication of these results is that any specific disease process that changes tissue composition should be detectable by observing the changes in the magnitude of these acoustic parameters. That is, B/A and in are suitable candidates for the purpose of tissue characterization and imaging. The current proposal consists of three specifie aims: 1) to validate the hypothesis that the 1 phenomena that give rise to acoustic nonlinearity or, are responsible for finite sound speed, occur due to perturbations at molecular level and less likely at the cellular level; 2) to develop, implement and evaluate three different methods (frequency mixing, amplitude modulation and pulse reversal) to make images of the nonlinearity parameter; and 3) to use mixture laws and acoustic data to construct images of tissues displaying two-dimensional distributions of the composition of tissues.