Nissan Noam, Furman-Haran Edna, Feinberg-Shapiro Myra, Grobgeld Dov, Eyal Erez, Zehavi Tania, Degani Hadassa
Department of Biological Regulation, Weizmann Institute of Science.
Unit of Biological Services, Weizmann Institute of Science.
J Vis Exp. 2014 Dec 15(94):52048. doi: 10.3791/52048.
Breast cancer is the most common cause of cancer among women worldwide. Early detection of breast cancer has a critical role in improving the quality of life and survival of breast cancer patients. In this paper a new approach for the detection of breast cancer is described, based on tracking the mammary architectural elements using diffusion tensor imaging (DTI). The paper focuses on the scanning protocols and image processing algorithms and software that were designed to fit the diffusion properties of the mammary fibroglandular tissue and its changes during malignant transformation. The final output yields pixel by pixel vector maps that track the architecture of the entire mammary ductal glandular trees and parametric maps of the diffusion tensor coefficients and anisotropy indices. The efficiency of the method to detect breast cancer was tested by scanning women volunteers including 68 patients with breast cancer confirmed by histopathology findings. Regions with cancer cells exhibited a marked reduction in the diffusion coefficients and in the maximal anisotropy index as compared to the normal breast tissue, providing an intrinsic contrast for delineating the boundaries of malignant growth. Overall, the sensitivity of the DTI parameters to detect breast cancer was found to be high, particularly in dense breasts, and comparable to the current standard breast MRI method that requires injection of a contrast agent. Thus, this method offers a completely non-invasive, safe and sensitive tool for breast cancer detection.
乳腺癌是全球女性中最常见的癌症病因。早期发现乳腺癌对提高乳腺癌患者的生活质量和生存率起着关键作用。本文描述了一种基于使用扩散张量成像（DTI）追踪乳腺结构元素来检测乳腺癌的新方法。本文重点介绍了为适应乳腺纤维腺组织的扩散特性及其在恶性转化过程中的变化而设计的扫描协议、图像处理算法和软件。最终输出产生逐像素的向量图，用于追踪整个乳腺导管腺树的结构以及扩散张量系数和各向异性指数的参数图。通过对包括68名经组织病理学检查确诊为乳腺癌的女性志愿者进行扫描，测试了该方法检测乳腺癌的效率。与正常乳腺组织相比，癌细胞区域的扩散系数和最大各向异性指数显著降低，为描绘恶性肿瘤生长边界提供了内在对比度。总体而言，发现DTI参数检测乳腺癌的敏感性很高，尤其是在致密型乳腺中，并且与目前需要注射造影剂的标准乳腺MRI方法相当。因此，该方法为乳腺癌检测提供了一种完全非侵入性、安全且敏感的工具。
