MR Diffusion Tensor Imaging for Detection and Characterization of Breast Lesions

描述（由申请人提供）：乳腺癌非常常见，每8名美国妇女中就有1人患乳腺癌，是美国妇女癌症死亡的第二大原因。通过筛查进行早期检测是提高生存率的根本途径。乳腺动态对比增强MRI（DCE-MRI）对乳腺癌检测具有高灵敏度，是筛查高危女性和检测近期确诊乳腺癌患者对侧或多灶性疾病的最灵敏技术。然而，在DCE-MRI上良性和恶性乳腺病变的外观重叠可能会产生许多假阳性。特别是鉴于最近美国癌症协会指南建议每年对高风险女性进行MRI筛查，估计在美国影响多达180万女性，因此明确且快速增长的需要是提高乳腺MRI的特异性，以限制由于这种高度敏感的筛查工具的扩展使用而导致的不必要的活检的数量。此外，钆基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，因此确定DCE-MRI的非造影替代品用于检测乳腺癌将具有强大的临床影响。一种有前途的辅助MRI技术是扩散张量成像（DTI），它间接评估组织的微观结构，并可以为DCE-MRI提供补充信息，用于病变表征。我们的研究组和其他研究组已经证明了良性和恶性病变的表观扩散系数（ADC）值有显著差异。此外，我们有希望的初步数据表明，表观扩散系数（ADC）的措施，可以增加传统的乳腺MRI评估的阳性预测值，并DTI分数各向异性（FA）增加了互补的信息ADC措施，在区分恶性肿瘤。我们还观察到，许多乳腺摄影和临床隐匿性癌症在弥散加权图像上可见，并且可以在MRI上检测到，而无需使用造影剂。这项工作的目的是：（1）验证DTI作为改善乳腺MRI病变特征的有价值的辅助手段，并确定将DTI测量纳入临床乳腺MRI评估的最佳方法，（2）更好地了解肿瘤组织学对DTI测量的影响，（3）评价DTI作为替代非造影剂乳腺筛查技术的潜在作用。这项研究的结果可能是重要的，因为DTI可以提供一个快速翻译的解决方案，以提高传统乳腺MRI的特异性，减少不必要的活检数量，或者，DTI可以提供一个更快，更便宜，更安全的筛查选择比DCE-MRI。

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.