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.
Relevance to Public Health: (1) Improving the characterization of suspicious lesions on conventional breast MRI would significantly reduce the resulting number of unnecessary biopsies performed, and (2) Identifying a non-contrast technique for detecting cancer would reduce costs and toxicity of breast MRI screening and increase accessibility to more women.
|Amornsiripanitch, Nita; Nguyen, Vicky T; Rahbar, Habib et al. (2018) Diffusion-weighted MRI characteristics associated with prognostic pathological factors and recurrence risk in invasive ER+/HER2- breast cancers. J Magn Reson Imaging 48:226-236|
|Amornsiripanitch, Nita; Rahbar, Habib; Kitsch, Averi E et al. (2018) Visibility of mammographically occult breast cancer on diffusion-weighted MRI versus ultrasound. Clin Imaging 49:37-43|
|Sorace, Anna G; Partridge, Savannah C; Li, Xia et al. (2018) Distinguishing benign and malignant breast tumors: preliminary comparison of kinetic modeling approaches using multi-institutional dynamic contrast-enhanced MRI data from the International Breast MR Consortium 6883 trial. J Med Imaging (Bellingham) 5:011019|
|Partridge, Savannah C; Amornsiripanitch, Nita (2017) DWI in the Assessment of Breast Lesions. Top Magn Reson Imaging 26:201-209|
|Partridge, Savannah C; Nissan, Noam; Rahbar, Habib et al. (2017) Diffusion-weighted breast MRI: Clinical applications and emerging techniques. J Magn Reson Imaging 45:337-355|
|Cheeney, Safia; Rahbar, Habib; Dontchos, Brian N et al. (2017) Apparent diffusion coefficient values may help predict which MRI-detected high-risk breast lesions will upgrade at surgical excision. J Magn Reson Imaging 46:1028-1036|
|Rahbar, Habib; McDonald, Elizabeth S; Lee, Janie M et al. (2016) How Can Advanced Imaging Be Used to Mitigate Potential Breast Cancer Overdiagnosis? Acad Radiol 23:768-73|
|Lasi?, Samo; Oredsson, Stina; Partridge, Savannah C et al. (2016) Apparent exchange rate for breast cancer characterization. NMR Biomed 29:631-9|
|Rahbar, Habib; Partridge, Savannah C (2016) Multiparametric MR Imaging of Breast Cancer. Magn Reson Imaging Clin N Am 24:223-238|
|Rahbar, Habib; Parsian, Sana; Lam, Diana L et al. (2016) Can MRI biomarkers at 3 T identify low-risk ductal carcinoma in situ? Clin Imaging 40:125-9|
Showing the most recent 10 out of 26 publications