TRD 2: Metabolic Markers

TRD 2：代谢标志物

基本信息

批准号：
10614610
负责人：
Richard Anthony Edward Edden
金额：
$ 19.69万
依托单位：
HUGO W. MOSER RES INST KENNEDY KRIEGER
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-07-01 至 2026-04-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10614610
关键词：
Affect Anatomy Antioxidants Binding Biochemical Biochemistry Biological Markers Brain Brain Chemistry Brain imaging Chemicals Collaborations Communities Coupling Data Data Analyses Data Set Decision Making Detection Development Diagnosis Diffusion Magnetic Resonance Imaging Disease Fingerprint Functional Magnetic Resonance Imaging Glutamates Glutathione Image Immobilization Label Lead Libraries Machine Learning Magnetic Resonance Imaging Magnetic Resonance Spectroscopy Magnetism Measurement Measures Metabolic Metabolic Marker Methods Modeling Molecular Monitor N-acetylaspartylglutamate Neuromodulator Neurotransmitters Oncology Phosphocreatine Physiologic pulse Physiological Preparation Principal Investigator Property Proteins Protons Radiology Specialty Relaxation Reproducibility Research Personnel Resolution Resources Schedule Scheme Services Shapes Signal Transduction Specificity System Techniques Testing Training Validation Water amplification detection base editing brain abnormalities brain metabolism deep learning design detection sensitivity gamma-Aminobutyric Acid improved innovation interest macromolecule metabolic imaging nervous system disorder open source professor response small molecule spectroscopic imaging statistics synergism tool

项目摘要

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.

TRD 2：代谢标志物首席研究员：Richard Edden，放射学教授联合研究员：Peter van Zijl、Peter Barker、Georg Oeltzschner、Jiadi Xu、Hye-Young Heo、尼尔巴伊·亚达夫。该TRD将利用磁共振波谱法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)。我们将开发新的用于多路编辑 MRS 的编辑计划，允许同时解析多个合作项目感兴趣的低浓度代谢物，包括神经递质例如 GABA、抗氧化剂（例如谷胱甘肽）和神经调节剂（例如 N- 乙酰天冬氨酰谷氨酸。我们将把这些方法与光谱成像读数结合起来并开发用于量化的多谱线性组合模型。已编辑 CEST 方法，调整采集参数以提高检测的特异性，CEST 将开发指纹识别和单次 z 谱方法。深度学习工具还将开发对这些数据的分析，特别关注整合基于 MRSI 的方法、光谱分辨率增强和代谢编辑 CEST 分析培训。根据该 TRD 开发的采集和分析工具将传播到协作项目和服务项目，以在新的环境中建立可重复性环境，以及更广泛的社区。