TRD 2: Metabolic Markers

TRD 2：代谢标志物 首席研究员：Richard Edden，放射学教授 共同研究者：Peter货车Zijl，Peter Barker，Georg Oeltzschner，Jiadi Xu，Hye-Young Heo， 尼尔拜·亚达夫 该TRD将使用磁共振光谱学开发大脑代谢的生物标志物 (MRS)和化学交换饱和转移成像（CEST-MRI）。发展新型 多路编辑MRS的编辑时间表，允许同时解决几个 合作项目感兴趣的低浓度代谢物，包括神经递质 如GABA，抗氧化剂如谷胱甘肽，和神经调节剂如N- 乙酰基谷氨酸我们将联合收割机与光谱成像读数结合起来 并建立了多光谱线性组合模型定量方法。编辑 CEST方法，调整采集参数以提高检测特异性， 将开发指纹识别和单次激发z谱方法。深度学习工具 还将开发这些数据的分析，特别注重整合 的方法，并通过基于MRI的光谱分辨率增强和代谢编辑 CEST分析培训。在本技术建议文件下开发的采集和分析工具将 传播到合作项目和服务项目，以建立一个新的可重复性 #21453;，以及更广泛的社区。

TRD 2: Metabolic Markers Lead Principal investigator: Richard Edden, Professor of Radiology Co-investigators: Peter van Zijl, Peter Barker, Georg Oeltzschner, Jiadi Xu, Hye-Young Heo, Nirbhay Yadav. This TRD will develop biomarkers of brain metabolism, using magnetic resonance spectroscopy (MRS) and chemical exchange-saturation transfer imaging (CEST-MRI). We will develop new editing schedules for multiplexed editing MRS, allowing the simultaneous resolution of several low-concentration metabolites of interest to collaborative projects, including neurotransmitters such as GABA, antioxidants such as glutathione, and neuromodulators such as N- acetylaspartylglutamate. We will combine these methods with spectroscopic imaging readouts and develop multi-spectrum linear combination modeling approached for quantification. Edited CEST approaches, tuning acquisition parameters to improve specificity of detection, CEST fingerprinting, and single-shot z-spectrum approaches will be developed. Deep learning tools for the analysis of these data will also be developed, with a particular focus on the integration of methods, and spectral resolution enhancement and metabolic editing by MRSI-based training of CEST analyses. Acquisition and analysis tools developed under this TRD will be disseminated to collaborative projects and service projects, to establish reproducibility in a new setting, and to the broader community.