Department of Bioengineering, University of Texas at Dallas, Richardson, Texas, USA.
Department of Bioengineering, University of Texas at Dallas, Richardson, Texas, USA.
Ultrasound Med Biol. 2023 Apr;49(4):951-960. doi: 10.1016/j.ultrasmedbio.2022.11.017. Epub 2023 Jan 19.
Ultrasound (US) has afforded an approach to tissue characterization for more than a decade. The challenge is to reveal hidden patterns in the US data that describe tissue function and pathology that cannot be seen in conventional US images. Our group has developed a high-resolution analysis technique for tissue characterization termed H-scan US, an imaging method used to interpret the relative size of acoustic scatterers. In the present study, the objective was to compare local H-scan US image intensity with registered histologic measurements made directly at the cellular level. Human breast cancer cells (MDA-MB 231, American Type Culture Collection, Manassas, VA, USA) were orthotopically implanted into female mice (N = 5). Tumors were allowed to grow for approximately 4 wk before the study started. In vivo imaging of tumor tissue was performed using a US system (Vantage 256, Verasonics Inc., Kirkland, WA, USA) equipped with a broadband capacitive micromachined ultrasonic linear array transducer (Kolo Medical, San Jose, CA, USA). A 15-MHz center frequency was used for plane wave imaging with five angles for spatial compounding. H-scan US image reconstruction involved use of parallel convolution filters to measure the relative strength of backscattered US signals. Color codes were applied to filter outputs to form the final H-scan US image display. For histologic processing, US imaging cross-sections were carefully marked on the tumor surface, and tumors were excised and sliced along the same plane. By use of optical microscopy, whole tumor tissue sections were scanned and digitized after nuclear staining. US images were interpolated to have the same number of pixels as the histology images and then spatially aligned. Each nucleus from the histologic sections was automatically segmented using custom MATLAB software (The MathWorks Inc., Natick, MA, USA). Nuclear size and spacing from the histology images were then compared with local H-scan US image features. Overall, local H-scan US image intensity exhibited a significant correlation with both cancer cell nuclear size (R > 0.27, p < 0.001) and the inverse relationship with nuclear spacing (R > 0.17, p < 0.001).
超声（US）已经提供了一种十多年来用于组织特征描述的方法。挑战在于揭示隐藏在 US 数据中的模式，这些模式描述了无法在常规 US 图像中看到的组织功能和病理学。我们小组开发了一种用于组织特征描述的高分辨率分析技术，称为 H-scan US，这是一种用于解释声散射体相对大小的成像方法。在本研究中，目的是比较局部 H-scan US 图像强度与直接在细胞水平进行的注册组织学测量。将人乳腺癌细胞（MDA-MB 231，美国模式培养物集存库，弗吉尼亚州马纳萨斯，美国）原位植入雌性小鼠（N=5）。在开始研究之前，大约让肿瘤生长 4 周。使用配备宽带电容式微机械超声线性阵列换能器（Kolo Medical，加利福尼亚州圣何塞，美国）的超声系统（Vantage 256，Verasonics Inc.，华盛顿州柯克兰，美国）对肿瘤组织进行体内成像。使用 15MHz 中心频率进行平面波成像，空间复合有五个角度。H-scan US 图像重建涉及使用平行卷积滤波器来测量反向散射 US 信号的相对强度。颜色代码应用于滤波器输出，以形成最终的 H-scan US 图像显示。对于组织学处理，小心地在肿瘤表面标记 US 成像横截面，然后沿着相同的平面切除和切片肿瘤。使用光学显微镜，在核染色后扫描并数字化整个肿瘤组织切片。对 US 图像进行插值，使其具有与组织学图像相同的像素数，然后进行空间对准。使用定制的 MATLAB 软件（马萨诸塞州纳蒂克的 MathWorks Inc.，美国）自动分割组织学切片中的每个细胞核。然后将组织学图像中的核大小和间隔与局部 H-scan US 图像特征进行比较。总体而言，局部 H-scan US 图像强度与癌细胞核大小（R > 0.27，p < 0.001）呈显著相关，与核间距呈负相关（R > 0.17，p < 0.001）。
