The H-scan approach to classifying ultrasound echoes

对超声回波进行分类的 H 扫描方法

• 批准号: 9598472
• 负责人: KEVIN J PARKER
• 金额: $ 19.01万
• 依托单位: UNIVERSITY OF ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-01 至 2020-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9598472
• 关键词: Acoustics; Address; Animal Model; Animals; Area; Biological; Biological Assay; Cell Size; Cellular Structures; Color; Data; Dependence; Diagnosis; Diagnostic Procedure; Disease; Ensure; Fatty Liver; Fatty acid glycerol esters; Fibrosis; Frequencies; Gaussian model; Gel; Glucose; Goals; Gray unit of radiation dose; Hepatectomy; High Fat Diet; Histology; Human; Image; Image Analysis; Inflammation; Inflammatory; Link; Liver; Liver diseases; Lobular; Malignant Neoplasms; Mathematics; Modeling; Nature; Organ; Output; Pathology; Performance; Placenta; Polynomial Models; Probability; Radiology Specialty; Rattus; Resolution; Scanning; Series; Serum; Shapes; Site; Steatohepatitis; Structure; Systems Analysis; Techniques; Testing; Time; Tissues; Transducers; Triglycerides; Ultrasonography; Vacuole; Variant; Vesicle; Weight; Wistar Rats; attenuation; clinical practice; clinically significant; electric impedance; experimental study; imaging platform; improved; in vivo; innovation; interest; statistics

Traditional ultrasound B-Scan images show the envelope of received echoes as a grey scale image. The echoes are produced from specular reflections and scattering sites where changes in acoustic impedance occur. A long- standing area of interest concerns the frequency dependence of backscattered ultrasound from within different tissues. Some advanced backscatter analyses estimate the frequency dependence and angular dependence of backscattered waves. However, most statistical averaging techniques require some region of interest over which to calculate the expected value of scattering parameters. Unfortunately, the unfavorable statistics of ultrasound echoes can limit the spatial resolution or accuracy of these estimators. Specific changes in pathology can cause changes in the underlying size, structure, and composition of tissue, and so the goal of somehow capturing these changes remains. We hypothesize that a new matched filter approach using matched Hermite functions can classify and visualize major scattering classes at high resolution. This enables clinicians to distinguish subtle cellular and parenchymal changes that would otherwise appear similar, thereby adding new and relevant information to diagnostic ultrasound. The recently derived H-scan is a fresh approach where the received echoes can be linked to three major classes of echoes from tissues. Echoes are linked to the mathematics of Gaussian Weighted Hermite Polynomials so that the overall identification task can be simplified. The resulting images are denoted as H-scans, where ‘H’ represents Hermite or hue, since the identification by hue is distinct from the traditional B-scan. The framework was given an initial test in biological tissues – liver and placenta – where changes in tissue H-scan images are plausibly linked to changes in the concentration of small scatterers. However, in order to establish H-Scan as a viable diagnostic technique, two issues must be proven. First, the H-scan must be shown to give consistent results within tissues over a range of depths and despite attenuation. Second, the H-scan must be shown to be sensitive to cellular and sub-cellular changes in tissue scatterers, relevant to a clinically significant condition. This project will address both these issues. The depth and attenuation dependence will be studied and corrected in a series of phantom and tissue experiments. The sensitivity and accuracy will be tested in a liver steatosis model in rats. The results should establish the key performance issues for H-scan, and thereby characterize its ability to advance diagnostic ultrasound imaging for assessing pathology in humans.

传统的超声B扫描图像以灰度图像显示了接收回声的信封。回声 是由特殊反射和散射部位产生的，在这些位点发生声阻抗的变化。沿着- 感兴趣的站立区涉及反向散射超声的频率依赖性 组织。一些高级反向散射分析估计了频率依赖性和角度依赖性 向后散射波。但是，大多数统计平均技术都需要某个感兴趣的地区 计算散射参数的预期值。不幸的是，超声的不利统计数据 回声可以限制这些估计器的空间分辨率或准确性。病理学的具体变化会导致 组织的基础大小，结构和组成的变化，因此以某种方式捕获这些目标的目标 变化仍然存在。我们假设使用匹配的HERMITE功能可以使用新的匹配的滤波器方法 在高分辨率下对主要散射类别进行分类和可视化。这使临床医生能够区分微妙 蜂窝和副群的变化，否则会看起来相似，从而增加了新的和相关的 信息以诊断超声。最近派生的H-Scan是一种新的方法，收到的回声 可以与组织中的三个主要的回声相关联。回声链接到高斯的数学 加权的HERMITE多项式，以便可以简化整体识别任务。由此产生的图像是 表示“ H”代表HERMITE或色相，因为色调的识别与 传统的B扫描。该框架在生物组织中进行了初步测试 - 肝脏和plapeta - 组织H扫描图像的变化与小散射器浓度的变化合可能相关。 但是，为了建立H-SCAN作为可行的诊断技术，必须证明两个问题。首先， 必须证明H扫描以在一系列深度和目的地衰减范围内在组织中产生一致的结果。 其次，必须证明H扫描对组织散射体的细胞和亚细胞变化敏感， 与临床上重要的状况有关。该项目将解决这两个问题。深度和 衰减依赖性将进行研究并在一系列幻影和组织实验中进行校正。这 敏感性和准确性将在大鼠的肝脏脂肪变性模型中进行测试。结果应建立关键 H-scan的性能问题，从而表征其推进诊断超声成像的能力 评估人类的病理。