Tumor Detection and Classification using QUS Technology's Structure Function

使用QUS技术的结构功能进行肿瘤检测和分类

• 批准号: 10592340
• 负责人: William D. O'Brien
• 金额: $ 44.26万
• 依托单位: UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-04-10 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10592340
• 关键词: Adult; Animal Model; Animals; Apoptotic; Architecture; Basic Science; Biological; Biopsy; Blood; Breast; Breast Cancer Treatment; Cancerous; Cell Nucleus; Cells; Cirrhosis; Classification; Clinical; Clinical Sciences; Collection; Contrast Media; Data; Detection; Development; Diagnostic; Diagnostic tests; Disease; Event; Eye; Fatty Liver; Fatty acid glycerol esters; Frequencies; General Population; Goals; Heart; Hepatic; Hepatocyte; Histology; Human; Image; Individual; Investigation; Kidney; Literature; Liver; Modeling; Monitor; Mus; Non-Invasive Detection; Organ; Outcome; Parameter Estimation; Participant; Patients; Pattern; Positioning Attribute; Premature Birth; Primary carcinoma of the liver cells; Process; Property; Prostate; Rattus; Research; Signal Transduction; Solid Neoplasm; Spatial Distribution; Statistical Mechanics; Structure; Techniques; Technology; Testing; Theoretical model; Tissues; Ultrasonics; Validation; clinically significant; design; diagnostic value; disease diagnosis; human subject; imaging biomarker; improved; in vivo; in vivo Model; innovation; lymph nodes; model development; non-alcoholic fatty liver disease; programs; quantitative ultrasound; success; three dimensional structure; translational study; tumor; tumor diagnosis; ultrasound

Project Summary Our collaborative basic science and clinical team will elucidate the mechanism(s) of ultrasound scattering in biological tissues by systematically studying a significant component of ultrasonic scattering, the structure function (SF), using solid tumors from animal models and hepatocellular carcinoma (HCC) in adult human subjects, and thereby improve the accuracy of Quantitative Ultrasound (QUS, the quantification of tissue microstructure) techniques in noninvasive tumor detection and classification. The SF concept arises in the context of wave scattering: the scattered power of a collection of scatterers depends not only on the properties of the individual scatterers (modeled by the form factor), but also on the spatial correlation among the scatterers (modeled by the SF). Structure function is new: The SF has largely been overlooked wherein the scatterer positions are assumed to be uncorrelated (i.e., SF is unity). The unity SF assumption is not appropriate for dense scattering media (e.g., solid tumors and most parenchymal tissues) or sparse media showing special patterns of scatterer distribution. Non-unity SF has mostly been studied on simple scattering media such as physical phantoms and blood. This investigation is new, and numerous basic science and technical innovations will be pursued. Our goal is to systematically study the SF using animal solid tumors and human liver and HCC data to improve ultrasonic scattering models and ultimately the diagnostic value of QUS outcomes. The research makes contributions at the basic science level to elucidate the scattering mechanisms by SF model development and validate using animal tumor models in vivo, and at the translational level to improve the accuracy of tumor detection/classification using human liver and HCC data. Central hypotheses and aims: 1) The SF is critical to elucidate ultrasonic scattering mechanism(s) in biological tissues. 2) The SF is sensitive to certain disease types and stages. 3) The accuracy of QUS to noninvasively detect/classify tissues/tumors in vivo will be significantly improved when the SF is utilized compared to when it is not utilized. To test these hypotheses, we have designed a research program with the following aims: Aim 1. Develop theoretical SF models that match scatterer spatial distributions of tumor/tissue types under investigation. Aim 2. Validate SF models using solid tumors in mice/rats. Aim 3. Test the diagnostic value of SF using clinical human liver data from 100 nonalcoholic fatty liver disease (NAFLD) participants, 150 cirrhotic participants, 50 HCC participants, and 150 normal participants. Summary/Impact: The SF is an ultrasound echo component that is determined by and sensitive to the architectural pattern of tissue microstructure (e.g., liver cell nuclei). The SF will be a clinically valuable imaging biomarker for disease diagnosis because many disease processes (e.g., HCC) remarkably change to a unique architectural pattern and consequently change the SF derived from the ultrasound signal.

项目摘要 我们的协作基础科学和临床团队将阐明超声散射的机制 生物组织通过系统地研究超声散射的重要组成部分 功能（SF），使用来自动物模型的实体瘤和成人人类的肝细胞癌（HCC） 受试者，从而提高了定量超声的准确性（QUS，组织的定量 微观结构）技术在非侵入性肿瘤检测和分类中。 SF概念出现在 波浪散射的背景：散射器集合的散射力不仅取决于 单个散射器的特性（由外形模型），但也与空间相关性 散点子（由SF建模）。 结构功能是新的：SF在很大程度上被忽略了 假定是不相关的（即SF是统一）。统一SF假设不适合致密 散射介质（例如实体瘤和大多数实质组织）或稀疏培养基显示特殊 散射器分布的模式。非统一的SF主要是在简单散射媒体上研究的 物理幻影和血液。这项调查是新的，而且许多基础科学和技术 将追求创新。我们的目标是使用动物实体瘤和人类系统地研究SF 肝脏和HCC数据以改善超声波散射模型，并最终的QUS诊断值 结果。该研究在基础科学层面做出了贡献，以阐明散射 SF模型开发的机制并使用体内动物肿瘤模型验证 翻译水平，以人肝和HCC数据提高肿瘤检测/分类的准确性。 中央假设和目的：1）SF对于阐明超声散射机制至关重要 在生物组织中。 2）SF对某些疾病类型和阶段敏感。 3）Q的准确性 使用SF时，非侵入性检测/分类体内的组织/肿瘤将显着改善 与未使用的情况相比。为了检验这些假设，我们设计了一个研究计划 以下目的：目标1。开发理论SF模型，以匹配散射器空间分布 正在研究的肿瘤/组织类型。 AIM 2。使用小鼠/大鼠实体瘤验证SF模型。目标3。 使用来自100种非酒精脂肪肝病的临床人肝数据测试SF的诊断值 （NAFLD）参与者，150名Cirrhotic参与者，50位HCC参与者和150名正常参与者。 摘要/影响：SF是一个超声回波组件，由并敏感 组织微观结构的结构模式（例如肝细胞核）。 SF将是临床上有价值的 成像疾病诊断的生物标志物，因为许多疾病过程（例如HCC）发生了明显变化 取得独特的架构模式，因此改变了从超声信号中得出的SF。