Sixteen channel carbon-13 phased array spectroscopy at 7 Tesla

描述(申请人提供)：核磁共振波谱(核磁共振或MRS)在当前国家个性化医学的努力中发挥着独特的作用，使研究完整的、功能正常的组织的新陈代谢成为可能。 结构和功能磁共振成像。虽然人们认识到MRS是代谢研究的一种独特/有利的检测技术，但公认的关键缺点是缺乏灵敏度。足够的信号和分解类似分子的能力是与患者相关的MRS实用和常规使用的两个关键因素。两者在高场下都有显著的改进，使最近可获得的全身商业7T系统成为生物化学家努力使MRS成为实用(即适当敏感的)活体检测工具的有力工具。增加的第二种技术 核磁共振实验的灵敏度是通过使用相控阵射频线圈来实现的。理想的情况是，相控阵将与高场MRS的好处结合使用。这一努力目前受到商业7T扫描仪多核接收器通道数量有限的事实的阻碍，相反，可能更直接地对多通道1H成像感兴趣。该建议旨在克服这一限制，方法是开发一种‘附加’频率转换器，为任何系统提供等于可用1H通道数量的宽带多通道能力，并开发用于7T下1H和13C谱学的表面和体积阵列线圈。该项目将利用和促进德克萨斯A&M大学磁共振系统实验室和德克萨斯大学西南医学中心高级成像研究中心之间现有合作的独特能力。要研究的特定代谢过程是UTSW正在进行的了解乳腺癌和乳腺癌易感因素的研究的一部分。这项工作将开发更灵敏地检测乳腺肿瘤中胆碱的技术，将其作为肿瘤恶性程度和侵袭性行为的高风险的指标。另一个公众非常感兴趣的问题是饮食在 乳腺癌的发病机制，普遍假设高饱和脂肪和单不饱和脂肪的饮食是乳腺癌的环境决定因素。用侵入性活组织检查研究乳房脂肪成分与癌症风险的关系已被证明是困难的，而这一点 这项工作将支持13C核磁共振波谱作为一种基本上未被探索的替代方案的作用。为完成这项工作有三个具体目标：1)建立一个附加的多通道移频接口盒，使UT西南医学中心飞利浦Achieva 7T扫描仪上现有的16通道1H接收器能够提供宽带多通道接收能力；2)设计和构建16通道RF线圈阵列，用于7T时的表面和体积1H和13C核磁共振研究；3)使用7特斯拉的多通道13C和1H磁共振波谱演示脂谱和可溶性代谢物的定量。

DESCRIPTION (provided by applicant): Nuclear magnetic resonance spectroscopy (NMR or MRS) plays a unique role in the current national effort towards personalized medicine, enabling the investigation of metabolism in intact, functioning tissues inherently integrated with the power of structural and functional MR imaging. While it is recognized that MRS is a unique/advantageous detection technique for metabolic studies, the universally acknowledged crucial drawback is a lack of sensitivity. Adequate signal and the ability to resolve similar molecules are two factors that are essential for practical, routine use of MRS relevant to patients. Both improve dramatically at high fields, making the recent availability of whole body commercial 7T systems a powerful tool added to the armament of biochemists striving to make MRS a practical (i.e. suitably sensitive) in vivo detection tool. A second technique for increasing the sensitivity of the NMR experiment is through the use of phased array RF coils. Ideally then, phased arrays would be used in combination with the benefits of high field MRS. This endeavor is currently hampered by the fact that commercial 7T scanners are limited in their number of multi-nuclear receiver channels, instead enabling the potentially more immediate interest in multi-channel 1H imaging. This proposal aims to overcome this limitation by developing an 'add-on' frequency converter to provide any system with broadband multi-channel capability equal to the number of available 1H channels and by developing surface and volume array coils for 1H and 13C spectroscopy at 7T. This project will leverage and promote distinctive capabilities in an existing collaboration between the Magnetic Resonance Systems Lab at Texas A&M University and the Advanced Imaging Research Center at UT Southwestern Medical Center. The specific metabolic processes to be investigated are part of ongoing studies at UTSW to understand breast cancer and the factors predisposing breast cancer. This work will develop technology to more sensitively detect choline in breast tumors as an indicator of malignancy and a high risk of aggressive behavior of tumors. Another issue of great interest to the public is the role of diet in the pathogenesis of breast cancer, with the general hypothesis that a diet high in saturated and monounsaturated fats is an environmental determinant of breast cancer. It has proven difficult to study the relation of breast fat composition to the risk of cancer with invasive biopsies, and this work will support the role of 13C NMR spectroscopy as a largely unexplored alternative. Three specific aims are outlined to accomplish this work: 1) Build an add-on multi-channel frequency shifting interface box to enable the existing 16-channel 1H receiver on the Philips Achieva 7T scanner at UT Southwestern Medical Center to provide broadband multi-channel receive capability 2) Design and construct 16-channel RF coil arrays for surface and volume 1H and 13C NMR studies at 7T and 3) Demonstrate quantification of the lipid profile and soluble metabolites using multi- channel 13C and 1H MR spectroscopy at 7 Tesla.