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.
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.
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|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|
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|Sung, Kyunghyun; Saranathan, Manojkumar; Daniel, Bruce L et al. (2013) Simultaneous T(1) and B(1) (+) mapping using reference region variable flip angle imaging. Magn Reson Med 70:954-61|
|Jordan, Caroline D; Daniel, Bruce L; Koch, Kevin M et al. (2013) Subject-specific models of susceptibility-induced B0 field variations in breast MRI. J Magn Reson Imaging 37:227-32|
|Sung, Kyunghyun; Daniel, Bruce L; Hargreaves, Brian A (2013) Location constrained approximate message passing for compressed sensing MRI. Magn Reson Med 70:370-81|
|Sung, Kyunghyun; Daniel, Bruce L; Hargreaves, Brian A (2013) Transmit B1+ field inhomogeneity and T1 estimation errors in breast DCE-MRI at 3 tesla. J Magn Reson Imaging 38:454-9|
|Saranathan, Manojkumar; Bayram, Ersin; Worters, Pauline W et al. (2012) A 3D balanced-SSFP Dixon technique with group-encoded k-space segmentation for breath-held non-contrast-enhanced MR angiography. Magn Reson Imaging 30:158-64|
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