Joint Department of Biomedical Engineering, University of North Carolina, Chapel Hill and North Carolina State University, 304 Taylor Hall, 109 Mason Farm Rd, Chapel Hill, NC 27599-6136, USA.
Radiology. 2012 Sep;264(3):733-40. doi: 10.1148/radiol.12112000. Epub 2012 Jul 6.
To determine if the morphologies of microvessels could be extracted from contrast material-enhanced acoustic angiographic ultrasonographic (US) images and used as a quantitative basis for distinguishing healthy from diseased tissue.
All studies were institutional animal care and use committee approved. Three-dimensional contrast-enhanced acoustic angiographic images were acquired in both healthy (n = 7) and tumor-bearing (n = 10) rats. High-spatial-resolution and high signal-to-noise acquisition was enabled by using a prototype dual-frequency US transducer (transmit at 4 MHz, receive at 30 MHz). A segmentation algorithm was utilized to extract microvessel structure from image data, and the distance metric (DM) and the sum of angles metric (SOAM), designed to distinguish different types of tortuosity, were applied to image data. The vessel populations extracted from tumor-bearing tissue volumes were compared against vessels extracted from tissue volumes in the same anatomic location within healthy control animals by using the two-sided Student t test.
Metrics of microvascular tortuosity were significantly higher in the tumor population. The average DM of the tumor population (1.34 ± 0.40 [standard deviation]) was 23.76% higher than that of the control population (1.08 ± 0.08) (P < .0001), while the average SOAM (22.53 ± 7.82) was 50.73% higher than that of the control population (14.95 ± 4.83) (P < .0001). The DM and SOAM metrics for the control and tumor populations were significantly different when all vessels were pooled between the two animal populations. In addition, each animal in the tumor population had significantly different DM and SOAM metrics relative to the control population (P < .05 for all; P value ranges for DM, 3.89 × 10(-)(7) to 5.63 × 10(-)(3); and those for SOAM, 2.42 × 10(-)(12) to 1.57 × 10(-)(3)).
Vascular network quantification by using high-spatial-resolution acoustic angiographic images is feasible. Data suggest that the angiogenic processes associated with tumor development in the models studied result in higher instances of vessel tortuosity near the tumor site.
确定对比增强声振造影超声(US)图像中的微血管形态是否可以提取出来,并作为区分健康组织和病变组织的定量基础。
所有研究均经机构动物护理和使用委员会批准。在健康(n=7)和荷瘤(n=10)大鼠中采集三维对比增强声振造影图像。使用原型双频 US 换能器(发射 4 MHz,接收 30 MHz)实现高空间分辨率和高信噪比采集。利用分割算法从图像数据中提取微血管结构,并应用距离度量(DM)和角度总和度量(SOAM)来区分不同类型的迂曲度。从肿瘤组织体积中提取的血管群与来自健康对照动物同一解剖位置的组织体积中提取的血管群进行比较,采用双侧学生 t 检验。
肿瘤人群的微血管迂曲度指标明显较高。肿瘤人群的平均 DM(1.34 ± 0.40[标准差])比对照人群(1.08 ± 0.08)高 23.76%(P<0.0001),而平均 SOAM(22.53 ± 7.82)则高 50.73%(P<0.0001)。当将两个动物群体之间的所有血管合并时,DM 和 SOAM 指标在对照和肿瘤群体之间差异显著。此外,肿瘤群体中的每只动物的 DM 和 SOAM 指标与对照群体相比均有显著差异(所有 P 值均<0.05;DM 的 P 值范围为 3.89×10(-)(7)至 5.63×10(-)(3);SOAM 的 P 值范围为 2.42×10(-)(12)至 1.57×10(-)(3))。
使用高空间分辨率声振造影图像进行血管网络量化是可行的。数据表明,在研究模型中,与肿瘤发展相关的血管生成过程导致肿瘤部位附近血管迂曲度增加。