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扫描图像将接收到的回波的包络显示为灰度图像。回声 是由镜面反射和发生声阻抗变化的散射部位产生的。很长的- 感兴趣的站立区域涉及来自不同区域内的反向散射超声的频率依赖性 组织中一些先进的后向散射分析估计的频率依赖性和角度依赖性 反向散射波然而，大多数统计平均技术需要一些感兴趣的区域， 以计算散射参数的期望值。不幸的是，超声的不利统计数据 回波会限制这些估计器的空间分辨率或精度。病理学的特定变化可能导致 组织的潜在大小、结构和组成的变化，因此以某种方式捕捉这些变化的目标是， 变化依然存在。我们假设，一个新的匹配滤波器的方法，使用匹配厄米函数， 以高分辨率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细微的 细胞和实质的变化，否则会出现类似的，从而增加新的和相关的 诊断超声的信息。最近导出的H扫描是一种新的方法，其中接收到的回波 可以与来自组织的三个主要类别的回声相关联。回声与高斯数学有关 加权厄米多项式，使整个识别任务可以简化。产生的图像是 表示为H-扫描，其中“H”表示厄米特或色调，因为通过色调的识别不同于通过颜色的识别。 传统B超扫描。该框架在生物组织-肝脏和胎盘-中进行了初步测试， 组织H扫描图像的变化与小散射体浓度的变化有明显联系。 然而，为了建立H扫描作为一种可行的诊断技术，必须证明两个问题。一是 H扫描必须显示在一定深度范围内的组织内得到一致的结果，尽管衰减。 其次，H扫描必须显示出对组织散射体中的细胞和亚细胞变化敏感， 与临床上显著的病症相关。本项目将解决这两个问题。深度和 将在一系列的体模和组织实验中研究和校正衰减依赖性。的 将在大鼠的肝脂肪变性模型中测试灵敏度和准确度。结果应该建立关键 性能问题的H扫描，从而表征其能力，以推进诊断超声成像， 评估人类的病理学