The central hypothesis of this proposal is that technological developments that enable increased spatial, spectral and temporal resolution using the ultrahigh magnetic field of 7 Tesla (7T) will allow the development of quantitative and sensitive MRI markers that better identify prostate cancer and differentiate pathologically indolent from aggressive disease. Advantages of ultrahigh magnetic field MRI, due to gains of signal-to-noise- ratio (SNR), parallel imaging performance and novel and/or improved contrast mechanism have been amply demonstrated in the human brain. However, the organ systems and diseases associated with the human torso have been excluded from these advances to date due to difficulties that arise when the RF wavelength becomes significantly smaller than the object size, as it does in the human torso at 7T. Recent developments, largely coming from our laboratory, demonstrate that these challenges can be overcome. Therefore, we propose to undertake developments aimed at exploiting the potential gains available at higher magnetic fields for MRI to investigate a clinical problem in the human torso. The clinical problem we focus on is prostate cancer, which is the most common non-cutaneous malignancy of American men, one in six of whom will be diagnosed with the disease in their lifetime. Despite its prevalence, few diagnostic tools, mainly biopsy and serum PSA, exist for monitoring disease progression and determining treatment success. Biopsies, while able to locally monitor the prostate, are both invasive and subject to inherent sampling error leading to underestimation of tumor grade and extent of disease, while PSA lacks specificity for malignancy. Improved methods to monitor the disease state would greatly benefit prostate cancer management by distinguishing between patients with aggressive disease who would benefit from treatment versus patients with small, prostate-confined, nonaggressive tumors that may not require treatment, and thus avoiding treatment- associated morbidities in men with nonaggressive tumors. Further, improved methods are needed to identify early disease recurrence after treatment. Our long term goals are to identify quantitative and non-invasive anatomic and functional MRI markers useful for the identification of prostate cancer and for distinguishing biologically aggressive versus indolent disease, and to use these markers to evaluate treatment responses to individualized therapies. To achieve these long term goals, the main objectives of this application are to a) develop a 7 Tesla (7T) prostate platform including the development and evaluation of several interdependent components (RF coils, DCE-MRI methods, spectroscopic imaging methods and new spectral quantification techniques), b) evaluate the reproducibility of measuring quantitative prostate cancer markers to determine their potential sensitivity to change, c) evaluate the ability of the imaging methods and quantitative markers to detect cancer using pathology as a gold standard and d) determine the true advantage of 7T as a powerful tool to detect and monitor prostate cancer by performing a field comparison with 3T.

Public Health Relevance

Upon successful completion of this proposal, an ultra high field magnetic resonance imaging (UHF MRI) platform will be developed taking advantage of the improved spatial, spectral and temporal resolution to quantitatively and sensitively measure several MRI markers to detect prostate cancer, determine the extent of disease, and assess pathological aggressiveness. The information provided by UHF MRI will improve our ability to characterize small volumes of disease and its progression, beyond what is currently possible at lower field strengths and with standard diagnostic tests. This technology is expected to be highly useful to monitor disease progression in patients under active surveillance, to determine the effectiveness of a therapy early in the therapeutic course to indicate if alternative treatment strategies are warranted, and to accurately target local therapies to reduce treatment morbidity and improve survival.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Project (R01)
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Biomedical Imaging Technology Study Section (BMIT)
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Zhang, Huiming
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University of Minnesota Twin Cities
Schools of Medicine
United States
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