TRD 2: Metabolic Markers

TRD 2：代谢标志物

基本信息

批准号：
10270099
负责人：
Richard Anthony Edward Edden
金额：
$ 17.5万
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/10270099
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 Detection Development Diagnosis Diffusion Magnetic Resonance Imaging Disease Fingerprint Functional Magnetic Resonance Imaging Glutamates Glutathione Image Label Lead Libraries Machine Learning Magnetic Resonance Imaging Magnetic Resonance Spectroscopy Magnetism Measurement Measures Metabolic Metabolic Marker Methods Modeling Molecular Monitor N-acetylaspartylglutamate Neurologic Neuromodulator Neurotransmitters 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 brain abnormalities brain metabolism deep learning design detection sensitivity gamma-Aminobutyric Acid improved innovation interest macromolecule metabolic imaging 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：代谢标记首席研究员：放射学教授理查德·埃登（Richard Edden）共同投资者：彼得·范·齐（Peter Van Zijl），彼得·巴克（Peter Barker），乔治·奥尔茨（Georg Oeltzschner），贾迪Xu，惠恩·霍恩（Hye-Young Heo）， Nirbhay Yadav。这种TRD将使用磁共振光谱发展脑代谢的生物标志物（MRS）和化学交换转移成像（CEST-MRI）。我们将开发新的多路复用编辑MRS的编辑时间表，允许同时解决几个包括神经递质在内的合作项目感兴趣的低浓度代谢物例如GABA，抗氧化剂，例如谷胱甘肽和神经调节剂，例如N- 乙酰基谷氨酸。我们将将这些方法与光谱成像读数相结合并开发用于定量的多光谱线性组合建模。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发Z光谱方法。深度学习工具为了对这些数据进行分析，还将特别关注集成基于MRSI的方法以及光谱分辨率的增强和代谢编辑培训CEST分析。在此TRD下开发的获取和分析工具将是传播到协作项目和服务项目，以在新的设置，并向更广泛的社区。