Breast cancer (BCa) is the most commonly diagnosed cancer and second most common cause of cancer death among women in the U.S. Breast density (BD) is a radiologic (image based) measure of the proportion of fat to fibroglandular tissues in the breast. It has been suggested that BD is an independent and significant risk factor for BCa, and BD changes have been increasingly incorporated as an intermediate surrogate endpoint to evaluate efficacy of drugs such as tamoxifen and aromatase inhibitors used in the treatment and prevention of BCa. Currently, mammography is the most widely used method of BD determination (MG-BD), but the requirement for ionizing radiation prohibits its use in studies requiring frequent monitoring. The accuracy of MG-BD is also limited due to the breast compression and the x-ray exposure calibration. As such, the accurate measurement of BD has emerged as a priority for assessing BCa risk and for evaluating the effects of prevention strategies aimed at reducing BD. BD derived from fat-water decomposition MRI (FWMRI-BD) has been proposed as an alternative for BD quantification without ionizing radiation. This proposal establishes an optimized FWMRI-BD measure that is automated, more accurate and reliable than the existing methods. Our immediate goal is to apply this highly sensitive FWMRI-BD change as a biomarker in research studies aimed at assessing the action of candidate prevention compounds on BD at an earlier time point than what is currently achievable using conventional mammography. In a previous study, a ?10% decrease in MG-BD after 12?18 months of tamoxifen therapy was associated with clinical benefit. Thus, in the longer term, earlier detection of BD changes that ultimately correlate with reduced BCa or BCa relapse will offer a precision medicine strategy to encourage intervention adherence for responders and allow individualized dose modification for non-responders. In addition, it will also facilitate discovery of novel agents for potential BCa chemopreventives using smaller studies, shorter intervention periods and at considerably lower costs.

Public Health Relevance

Breast density is a radiologic (image based) measure of the proportion of fat to fibroglandular tissues in the breast. It has been suggested that breast density is an independent and significant risk factor for breast cancer and a surrogate marker for treatment response. The accuracy of conventional mammography based breast density is limited. This project aims at establish an optimized MRI based breast density measure that is automated, more accurate and reliable than the existing methods. And we will apply it as an imaging marker in research studies aimed at assessing the action of candidate prevention compounds on breast density at an earlier time point than what is currently achievable using conventional mammography.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Small Research Grants (R03)
Project #
5R03CA223052-02
Application #
9607580
Study Section
Special Emphasis Panel (ZCA1)
Program Officer
Tata, Darayash B
Project Start
2018-01-01
Project End
2020-12-31
Budget Start
2019-01-01
Budget End
2020-12-31
Support Year
2
Fiscal Year
2019
Total Cost
Indirect Cost
Name
State University New York Stony Brook
Department
Psychiatry
Type
Schools of Medicine
DUNS #
804878247
City
Stony Brook
State
NY
Country
United States
Zip Code
11794
Ding, Jie; Stopeck, Alison T; Gao, Yi et al. (2018) Reproducible automated breast density measure with no ionizing radiation using fat-water decomposition MRI. J Magn Reson Imaging 48:971-981