Development of an Optimal MRI Platform for Prostate Investigations at 7 Tesla

描述（由申请人提供）：该提案的中心假设是，使用7特斯拉（7 T）的电磁场提高空间、光谱和时间分辨率的技术发展将允许开发定量和灵敏的MRI标记物，以更好地识别前列腺癌并区分病理惰性和侵袭性疾病。由于信噪比（SNR）的增益、并行成像性能以及新颖和/或改进的对比机制，双磁场MRI的优势已在人脑中得到充分证明。然而，与人体躯干相关的器官系统和疾病已经被排除在这些进展之外，因为当RF波长变得明显小于物体尺寸时会出现困难，就像在7 T的人体躯干中一样。最近的发展，主要来自我们的实验室，表明这些挑战是可以克服的。因此，我们建议进行开发，旨在利用MRI在更高磁场下的潜在增益，以研究人体躯干的临床问题。我们关注的临床问题是前列腺癌，这是美国男性最常见的非皮肤恶性肿瘤，其中六分之一的人在一生中会被诊断出患有这种疾病。尽管其流行，但很少有诊断工具，主要是活检和血清PSA，用于监测疾病进展和确定治疗成功。活检，虽然能够局部监测前列腺，是侵入性的，并受到固有的采样误差，导致低估肿瘤的等级和疾病的程度，而PSA缺乏特异性的恶性肿瘤。改进的监测疾病状态的方法将极大地有益于前列腺癌管理，其通过区分将受益于治疗的具有侵袭性疾病的患者与可能不需要治疗的具有小的、前列腺局限的、非侵袭性肿瘤的患者，从而避免具有非侵袭性肿瘤的男性中的治疗相关的发病率。此外，需要改进的方法来识别治疗后的早期疾病复发。我们的长期目标是确定定量和非侵入性的解剖和功能MRI标记物，用于识别前列腺癌和区分生物学侵袭性与惰性疾病，并使用这些标记物来评估个体化治疗的治疗反应。为了实现这些长期目标，本申请的主要目标是a）开发7特斯拉（7 T）前列腺平台，包括开发和评估几个相互依赖的组件（RF线圈、DCE-MRI方法、光谱成像方法和新的光谱定量技术），B）评估测量定量前列腺癌标志物的再现性以确定它们对变化的潜在敏感性，c）使用病理学作为金标准来评估成像方法和定量标志物检测癌症的能力，以及d）通过与3 T进行现场比较来确定7 T作为检测和监测前列腺癌的有力工具的真正优势。

DESCRIPTION (provided by applicant): 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.