Tumor Diagnosis through Enhanced Ultrasound Imaging

描述（由申请人提供）：。拟议的长期目标 研究计划是开发和完善一种全新的超声 通过量化组织微观结构增强的成像方法 通过声波反向散射然后，增强成像技术将 适用于实体瘤的原位临床诊断， 期望准确检测和诊断癌症。 使用增强的超声成像在医学上是重要的，因为它 提供了一种快速和非侵入性的检测和分类肿瘤类型的方法。 为了实现这一长期目标的开始阶段， 提出了具体目标： 1.组织微结构的大小、形状和声学特性的假设 将使用不同的形状对当前的相关模型进行测试 具有非线性频率依赖性的因素。 2.新的算法，占频率相关的衰减损失， 将对组织进行测试，并将其纳入反向散射测量， 改进对组织微观结构的估计。 3.将介绍用于将组织结构与模型参数相关联的技术。 为快速估算而优化。 4.将建立一个接种肿瘤的对照组大鼠， 组织散射样本数据库。 5.将组织学数据与散射样本的定量相关联， 研究并用于测试超声散射模型的有效性。 6.将典型超声图像与 将评价组织微观结构的量化，以促进 疾病的临床检测和诊断。

Description (provided by applicant): .The long term goal of the proposed research program is to develop and refine a fundamentally new ultrasound imaging approach enhanced by the quantification of tissue microstructure through acoustic backscatter. The enhanced imaging technique will then be adapted for use in an in situ clinical diagnosis of solid tumors with the expectation of accurate detection and diagnosis of cancer. Use of the enhanced ultrasound imaging is medically significant because it offers a quick and noninvasive means of detecting and classifying tumor types. To accomplish the beginning stages of this long-term goal, the following specific aims are proposed: 1. Assumptions of size, shape and acoustic properties of tissue microstructures are to be tested against current correlation models using different shape factors with nonlinear frequency dependence. 2. New algorithms that account for frequency-dependent attenuation losses in tissues will be tested and incorporated into backscatter measurements for improved estimation of tissue microstructures. 3. Techniques for relating tissue structures to model parameters will be optimized for rapid estimation. 4. A control group of rats seeded with tumors will be created to build a database of tissue scattering samples. 5. Relating histological data to quantification of scattering samples will be investigated and used to test the validity of the ultrasound scattering models. 6. Several techniques for combining typical ultrasound images with the quantification of tissue microstructures will be evaluated for facilitation of clinical detection and diagnosis of disease.