Overview: Ductal carcinoma in situ (DCIS) comprises approximately 20% of breast cancers diagnosed annually in the US. DCIS is currently treated aggressively with surgery and radiation, or mastectomy. Yet the excellent long-term outcome for many DCIS patients indicates that there is substantial over-treatment of DCIS, and trials of active surveillance are starting. Relevance: The critical question is which cases of DCIS can be safely followed without being removed? One major unmet need is that 1/4 of DCIS cases diagnosed by core needle biopsy actually harbor occult invasive cancers that merit de?nitive treatment. Accurate identi?cation of DCIS cases to exclude these invasive cancers has been identi?ed as one of the major roadblocks to active surveillance. Currently, MRI is viewed as the most promising staging strategy. However, while MRI is twice as sensitive as mammography for breast cancer detection overall, it is not that accurate for selectively detecting invasive cancers in a background of DCIS. Approach: Over two prior funding cycles, we have made key developments in high spatiotemporal resolu- tion breast MRI that are industry standards, with numerous advances in other breast MRI sequences including diffusion-weighted imaging (DWI). Here, we propose to investigate and test two promising areas of MRI technol- ogy to improve discrimination of invasive cancer from DCIS.
In Aim 1, we will develop dynamic contrast enhanced MRI with high spatiotemporal resolution sampling, spatiotemporally-sparse compressed-sensing reconstruction, integrated fat-water separation and non-rigid motion correction. We will also incorporate novel pharmacokinetic mapping that includes modeling of arterial bolus dispersion for better lesion discrimination.
In Aim 2, we will develop diffusion-weighted MRI with multi-shot methods that use novel shot-to-shot motion correction, fast-spin- echo diffusion imaging for better performance around biopsy markers, and steady-state diffusion for 3D imaging. Finally in Aim 3, we will validate and test the accuracy of these new techniques in large patient studies, to show their bene?t for invasive tumor detection in DCIS patients compared to conventional ACR-standard breast MRI. Summary: The advanced MRI techniques that we propose to develop, validate and test in this proposal have tremendous potential to identify which DCIS patients can safely select active surveillance and which need de?ni- tive treatment. High accuracy for invasive cancer will provide this value with many fewer false-positive biopsies than conventional breast MRI.

Public Health Relevance

Every year, 50,000 American women undergo breast surgery for non-invasive breast cancer, also known as ductal carcinoma in situ (DCIS). Active surveillance (AS) has been proposed as a non-surgical management strategy for DCIS because 46-87% of the time DCIS does not progress to clinically relevant illness. We propose to develop and validate new high-resolution multi-contrast magnetic resonance imaging (MRI) technology that can accurately discriminate which patients with DCIS harbor occult invasive cancer, and therefore are not suit- able for AS, from patients without invasive cancer who are suitable for AS, to reduce over-treatment of breast cancer.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
2R01EB009055-09A1
Application #
9886796
Study Section
Emerging Imaging Technologies and Applications Study Section (EITA)
Program Officer
Liu, Guoying
Project Start
2020-03-01
Project End
2023-11-30
Budget Start
2020-03-01
Budget End
2020-11-30
Support Year
9
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Stanford University
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305
Srinivasan, Subashini; Hargreaves, Brian A; Daniel, Bruce L (2018) Fat-based registration of breast dynamic contrast enhanced water images. Magn Reson Med 79:2408-2414
Levine, Evan; Hargreaves, Brian (2018) On-the-Fly Adaptive ${k}$ -Space Sampling for Linear MRI Reconstruction Using Moment-Based Spectral Analysis. IEEE Trans Med Imaging 37:557-567
Perkins, Stephanie L; Daniel, Bruce L; Hargreaves, Brian A (2018) MR imaging of magnetic ink patterns via off-resonance sensitivity. Magn Reson Med 80:2017-2023
Taviani, Valentina; Alley, Marcus T; Banerjee, Suchandrima et al. (2017) High-resolution diffusion-weighted imaging of the breast with multiband 2D radiofrequency pulses and a generalized parallel imaging reconstruction. Magn Reson Med 77:209-220
Levine, Evan; Daniel, Bruce; Vasanawala, Shreyas et al. (2017) 3D Cartesian MRI with compressed sensing and variable view sharing using complementary poisson-disc sampling. Magn Reson Med 77:1774-1785
Zhang, Tao; Chen, Yuxin; Bao, Shanshan et al. (2017) Resolving phase ambiguity in dual-echo dixon imaging using a projected power method. Magn Reson Med 77:2066-2076
Horst, Kathleen C; Fero, Katherine E; Hancock, Steven L et al. (2016) Breast Imaging in Women Previously Irradiated for Hodgkin Lymphoma. Am J Clin Oncol 39:114-9
Yoruk, Umit; Saranathan, Manojkumar; Loening, Andreas M et al. (2016) High temporal resolution dynamic MRI and arterial input function for assessment of GFR in pediatric subjects. Magn Reson Med 75:1301-11
Quist, Brady; Hargreaves, Brian A; Daniel, Bruce L et al. (2015) Balanced SSFP Dixon imaging with banding-artifact reduction at 3 Tesla. Magn Reson Med 74:706-15
Kang, Bong Joo; Lipson, Jafi Alyssa; Planey, Katie RoseMary et al. (2015) Rim sign in breast lesions on diffusion-weighted magnetic resonance imaging: diagnostic accuracy and clinical usefulness. J Magn Reson Imaging 41:616-23

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