This project will develop and test new MRI technology for detecting breast cancer one year earlier than standard breast MRI. This will be achieved through fourteen-fold higher spatio-temporal resolution dynamic contrast- enhanced imaging compared to current protocols, as well as improved spatial resolution of established quantitative imaging biomarkers of breast cancer. The diagnostic utility of all methods will be tested in studies of patients with breast cancer. Relevance: Breast cancer remains the second most lethal cancer amongst women, despite real reductions in mortality due to screening with mammography and better systemic therapy. While MRI screening detects twice as many tumors as mammography, the cost of MRI screening limits its use to women with a high risk of breast cancer. By significantly improving the diagnostic performance of MRI for small lesions, the technology in this proposal will enable breast MRI to reliably detect breast cancers much earlier. This could enable high-risk patients to undergo MRI screening less frequently while still ensuring detection of breast cancers when they are stage I and treatable with a high likelihood of long term survival, saving up to $1 billion and eliminating up to 50,000 costly, painful biopsie each year. It may also enable customized screening intervals depending on risk. The high spatial resolution quantitative imaging that we will develop will boost specificity among small lesions to minimize false positives. It will also improve the quality and reliability of existing M imaging biomarkers that are being used for prognosis, treatment selection and monitoring of treatment response. Approach: Our approach builds on our successful track record in high-resolution breast MRI established during our previous period of funding that generated numerous papers, patents and conference proceedings. In this work, we aim to offer (1) a fourteen-fold increase in spatio-temporal resolution that can be flexibly traded off between high spatial resolution static (0.35?0.35?0.7 mm3) and high spatio-temporal resolution (0.5?0.5?1.0 mm3 in 15 s) dynamic imaging, (2) high-spatial-resolution quantitative volumetric 3T MRI-based biomarkers including T2, apparent diffusion coefficient, and pharmacokinetic perfusion metrics with corrections for motion, B+1 inhomogeneity, and T1 effects, and (3) patient studies to demonstrate increased detection of small cancers, enabled by high-resolution imaging, while keeping the overall biopsy rate low. Summary: By offering multi-parametric quantitative information at higher spatial resolution using advanced breast coils, new optimized 3D pulse sequences, advanced data sampling and image reconstruction techniques using compressed sensing and parallel imaging, this work will make MRI a more practical and powerful screening method that reliably detects smaller breast tumors at earlier stages, further reducing mortality from breast cancer.

Public Health Relevance

Earlier diagnosis of breast cancer, when lesions are smaller, can both increase survival rates for patients and decrease costs associated with the disease. This work will develop technological methods to dramatically improve the spatial resolution of magnetic resonance imaging (MRI) detection methods, and to provide several quantitative measures of breast cancer, also at much higher resolution than previously attained. These methods will be tested in studies of breast cancer patients to demonstrate their ability to detect smaller tumors, at an earlier disease stage.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
2R01EB009055-05
Application #
8446215
Study Section
Biomedical Imaging Technology Study Section (BMIT)
Program Officer
Liu, Guoying
Project Start
2008-09-15
Project End
2016-12-31
Budget Start
2013-01-01
Budget End
2013-12-31
Support Year
5
Fiscal Year
2013
Total Cost
$491,262
Indirect Cost
$170,514
Name
Stanford University
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305
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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
Zhang, Tao; Chen, Yuxin; Bao, Shanshan et al. (2016) Resolving phase ambiguity in dual-echo dixon imaging using a projected power method. Magn Reson Med :
Levine, Evan; Daniel, Bruce; Vasanawala, Shreyas et al. (2016) 3D Cartesian MRI with compressed sensing and variable view sharing using complementary poisson-disc sampling. Magn Reson Med :
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
Clarke, Sharon E; Saranathan, Manojkumar; Rettmann, Dan W et al. (2015) High resolution multi-arterial phase MRI improves lesion contrast in chronic liver disease. Clin Invest Med 38:E90-9
Barentsz, Maarten W; Taviani, Valentina; Chang, Jung M et al. (2015) Assessment of tumor morphology on diffusion-weighted (DWI) breast MRI: Diagnostic value of reduced field of view DWI. J Magn Reson Imaging 42:1656-65
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
Saranathan, Manojkumar; Rettmann, Dan W; Hargreaves, Brian A et al. (2014) Variable spatiotemporal resolution three-dimensional Dixon sequence for rapid dynamic contrast-enhanced breast MRI. J Magn Reson Imaging 40:1392-9
Han, Misung; Cunningham, Charles H; Pauly, John M et al. (2014) Homogenous fat suppression for bilateral breast imaging using independent shims. Magn Reson Med 71:1511-7

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