MR Diffusion Tensor Imaging for Detection and Characterization of Breast Lesions

描述(申请人提供)：乳腺癌非常常见，每8名美国女性中就有1人罹患乳腺癌，是美国女性癌症死亡的第二大原因。通过筛查及早发现是提高存活率的根本途径。乳腺动态增强磁共振成像(DCE-MRI)对乳腺癌的检测具有很高的敏感性，是筛查高危女性和检测新近诊断的乳腺癌患者对侧或多灶性病变的最敏感技术。然而，乳腺良恶性病变在DCE-MRI上的表现重叠会产生许多假阳性。特别是鉴于美国癌症协会最近的指南建议对高危女性进行年度MRI筛查，估计影响到美国多达180万女性，因此显然有必要提高乳腺MRI的特异性，以限制由于扩大使用这一高度敏感的筛查工具而导致的不必要活检的数量。此外，基于Gd的造影剂的高成本和安全性问题限制了许多女性进行乳腺MRI筛查的可及性，因此寻找一种非对比剂替代DCE-MRI来检测乳腺癌将具有强大的临床影响。扩散张量成像(DTI)是一种很有前途的辅助MRI技术，它可以间接评估组织的微结构，并能为DCE-MRI提供病变定性的补充信息。我们组和其他人在良性和恶性病变之间的表观扩散系数(ADC)值显示出显著的差异。此外，我们有很有希望的初步数据表明，表观扩散系数(ADC)测量可以提高传统乳腺MRI评估的阳性预测值，DTI分数各向异性(FA)在鉴别恶性肿瘤方面为ADC测量增加了补充信息。我们还观察到，许多乳房X光检查和临床上隐匿的癌症在扩散加权图像上是可见的，并且可以在不使用造影剂的情况下在MRI上被发现。这项工作的目的是：(1)验证DTI作为一种有价值的辅助手段来改善乳腺MRI上的病变特征，并确定将DTI测量方法结合到临床乳腺MRI评估中的最佳方法；(2)更好地了解肿瘤组织学对DTI测量的影响；(3)评估DTI作为一种替代非对比度乳腺筛查技术的潜在作用。这项研究的结果具有潜在的重要意义，因为DTI可以提供一种快速可翻译的解决方案来提高传统乳腺MRI的特异性并减少不必要的活检次数，或者，DTI可以提供比DCE-MRI更快、更便宜和更安全的筛查选择。

DESCRIPTION (provided by applicant): Breast cancer is extremely common, striking 1 in 8 American women, and is the second leading cause of cancer death among women in the U.S. Earlier detection through screening is a fundamental way to improve survival. Dynamic contrast enhanced MRI (DCE-MRI) of the breast has a high sensitivity for breast cancer detection and is the most sensitive technique for screening high risk women and detecting contralateral or multifocal disease in patients with recently diagnosed breast cancer. However, overlap in the appearance of benign and malignant breast lesions on DCE-MRI can produce many false positives. Particularly in light of recent American Cancer Society guidelines recommending annual MRI screening for high risk women, estimated to affect up to 1.8 million women in the US, there is a clear and quickly growing need to improve the specificity of breast MRI in order to limit the number of unnecessary biopsies that will result from expanded use of this highly sensitive screening tool. Furthermore, the high costs and safety concerns of gadolinium-based contrast agents limit the accessibility of breast MRI screening for many women, so identifying a non-contrast alternative to DCE-MRI for detecting breast cancer would have strong clinical impact. A promising adjunct MRI technique is Diffusion Tensor Imaging (DTI), which indirectly assesses tissue microstructure and can provide complementary information to DCE-MRI for lesion characterization. Our group and others have demonstrated notable differences in apparent diffusion coefficient (ADC) values between benign and malignant lesions. Moreover, we have promising preliminary data suggesting apparent diffusion coefficient (ADC) measures can increase the positive predictive value of conventional breast MRI assessment, and that DTI fractional anisotropy (FA) adds complementary information to ADC measures in discriminating malignancies. We have also observed that many mammographically and clinically-occult cancers are visible on diffusion-weighted images and can be detected on MRI without using a contrast agent. The aims of this work are: (1) to validate DTI as a valuable adjunct to improve lesion characterization on breast MRI and determine the optimal way to incorporate DTI measures into the clinical breast MRI assessment, (2) to better understand the effects of tumor histology on DTI measures, and (3) to evaluate the potential role of DTI as an alternative non-contrast breast screening technique. The outcomes of this study are potentially significant because DTI could provide a quickly translatable solution to improve the specificity of conventional breast MRI and reduce the number of unnecessary biopsies, and alternatively, DTI could provide a faster, less expensive, and safer screening option than DCE-MRI.