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.

Public Health 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.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA151326-04
Application #
8468582
Study Section
Medical Imaging Study Section (MEDI)
Program Officer
Zhang, Huiming
Project Start
2010-07-16
Project End
2015-05-31
Budget Start
2013-06-01
Budget End
2014-05-31
Support Year
4
Fiscal Year
2013
Total Cost
$295,160
Indirect Cost
$55,988
Name
University of Washington
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195
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Partridge, Savannah C; Stone, Karen M; Strigel, Roberta M et al. (2014) Breast DCE-MRI: influence of postcontrast timing on automated lesion kinetics assessments and discrimination of benign and malignant lesions. Acad Radiol 21:1195-203
Partridge, Savannah C; McDonald, Elizabeth S (2013) Diffusion weighted magnetic resonance imaging of the breast: protocol optimization, interpretation, and clinical applications. Magn Reson Imaging Clin N Am 21:601-24
Rahbar, Habib; Partridge, Savannah C; Demartini, Wendy B et al. (2012) Improved B1 homogeneity of 3 Tesla breast MRI using dual-source parallel radiofrequency excitation. J Magn Reson Imaging 35:1222-6
Partridge, Savannah C; Singer, Lisa; Sun, Ryan et al. (2011) Diffusion-weighted MRI: influence of intravoxel fat signal and breast density on breast tumor conspicuity and apparent diffusion coefficient measurements. Magn Reson Imaging 29:1215-21