Establishing translational neuroimaging tools for quantitative assessment of energy metabolism and metabolic reprogramming in healthy and diseased human brain at 7T

建立转化神经影像工具,用于定量评估 7T 健康和患病人脑的能量代谢和代谢重编程

基本信息

  • 批准号:
    10714863
  • 负责人:
  • 金额:
    $ 63.02万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-06-01 至 2028-05-31
  • 项目状态:
    未结题

项目摘要

PROJECT SUMMARY Cellular energy metabolism is a fundamental process of life that produces biochemical energy in the form of adenosine triphosphate (ATP) to support neuronal activity and brain function. Glucose and oxygen are the main energy substrates of the brain and are metabolized through glycolysis, the tricarboxylic acid cycle and oxidative phosphorylation pathways, constituting a neuroenergetic network that effectively regulates ATP production and homeostasis. ATP production and homeostasis are affected when brain states change, as signs of altered cerebral glucose and oxidative metabolism are commonly seen in aging, neurodegenerative diseases, psychiatric disorders, stroke and cancer. Despite the important roles of brain energy metabolism, metabolic alteration and reprogramming in health and disease, noninvasive neuroimaging tools capable of mapping and quantifying key features of neuroenergetic network in the human brain are still lacking. Over the past two decades, we have developed three ultrahigh-field (UHF) metabolic imaging techniques based on deuterium-2 (2H), oxygen-17 (17O), and phosphorus-31 (31P) magnetic resonance spectroscopy (MRSI) imaging capable of noninvasive and quantitative assessment of brain energy metabolism along major metabolic pathways. However, X-nuclear MRSI-based methods face severe challenges in translational applications due to low detection sensitivity and metabolite content, and prolonged scanning time. This project aims to develop and integrate multiple cutting-edge technologies to build next generation high- resolution, high-performance and translatable neuroimaging tools on an FDA-approved 7 Tesla clinical scanner for quantitatively imaging key metabolic rates and other essential neurophysiological parameters related to energy metabolism in healthy and diseased human brains. Three pilot studies are proposed to test and demonstrate the utility and feasibility of the novel neuro-metabolic imaging tools to quantitatively study neuroenergetics and metabolic reprogramming in brain activation, aging processes and brain tumors, aiming to understand their critical roles in brain function and disease. This project leverages the interdisciplinary expertise of an outstanding team leading in the research field, excellent imaging facilities and resources, and close collaboration among team members. The advanced neuroimaging tools established by this project is expected to have significant impact on changing the paradigm of neurometabolic imaging and energy metabolism research, and enable translational studies of human brain bioenergetics and metabolic reprogramming under physiopathological conditions.
项目摘要 细胞能量代谢是生命的一个基本过程,它以生物化学的形式产生能量。 三磷酸腺苷(ATP),以支持神经元活动和大脑功能。葡萄糖和氧气是 脑的主要能量底物,并通过糖酵解、三羧酸循环和 氧化磷酸化途径,构成有效调节ATP的神经能量网络 生产和稳态。当大脑状态改变时,ATP的产生和体内平衡会受到影响, 改变的脑葡萄糖和氧化代谢的迹象通常见于衰老、神经退行性疾病、糖尿病和糖尿病。 疾病、精神障碍、中风和癌症。尽管大脑能量代谢的重要作用, 健康和疾病中的代谢改变和重编程,非侵入性神经成像工具能够 仍然缺乏对人脑中神经能量网络的关键特征的映射和量化。 在过去的二十年里,我们已经开发了三种超高场(UHF)代谢成像技术 基于氘-2(2 H)、氧-17(17 O)和磷-31(31 P)磁共振光谱 (MRSI)成像能够无创和定量评估脑能量代谢沿着主要 代谢途径然而,基于X-核MRSI的方法在翻译方面面临严峻的挑战。 由于检测灵敏度和代谢物含量低,以及扫描时间延长, 该项目旨在开发和整合多种尖端技术,以构建下一代高性能 高分辨率、高性能和可翻译的神经成像工具,用于FDA批准的7特斯拉临床扫描仪 用于定量成像关键代谢率和其他重要的神经生理学参数, 健康人和患病人大脑的能量代谢。建议进行三项试点研究, 展示了新的神经代谢成像工具的实用性和可行性,以定量研究 神经能量学和代谢重编程在大脑激活,衰老过程和脑肿瘤,旨在 了解它们在大脑功能和疾病中的关键作用。该项目利用跨学科的 在研究领域领先的优秀团队的专业知识,优秀的成像设施和资源,以及 团队成员之间的密切合作。该项目建立的先进神经成像工具是 预计将对改变神经代谢成像和能量的范式产生重大影响 代谢研究,并使人类大脑生物能量学和代谢的转化研究 在病理生理条件下重编程。

项目成果

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Wei Chen其他文献

Wei Chen的其他文献

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{{ truncateString('Wei Chen', 18)}}的其他基金

An ensemble deep learning model for tumor bud detection and risk stratification in colorectal carcinoma.
用于结直肠癌肿瘤芽检测和风险分层的集成深度学习模型。
  • 批准号:
    10564824
  • 财政年份:
    2023
  • 资助金额:
    $ 63.02万
  • 项目类别:
SCH: New Advanced Machine Learning Framework for Mining Heterogeneous Ocular Data to Accelerate
SCH:新的先进机器学习框架,用于挖掘异构眼部数据以加速
  • 批准号:
    10601180
  • 财政年份:
    2022
  • 资助金额:
    $ 63.02万
  • 项目类别:
SCH: New Advanced Machine Learning Framework for Mining Heterogeneous Ocular Data to Accelerate
SCH:新的先进机器学习框架,用于挖掘异构眼部数据以加速
  • 批准号:
    10665804
  • 财政年份:
    2022
  • 资助金额:
    $ 63.02万
  • 项目类别:
Cellular Interactions in Vascular Calcification of Chronic Kidney Disease
慢性肾病血管钙化中的细胞相互作用
  • 批准号:
    10525401
  • 财政年份:
    2022
  • 资助金额:
    $ 63.02万
  • 项目类别:
Console Replacement and Upgrade of 9.4 Tesla Animal Instrument
9.4特斯拉动物仪控制台更换升级
  • 批准号:
    10414184
  • 财政年份:
    2022
  • 资助金额:
    $ 63.02万
  • 项目类别:
Deep-learning-based prediction of AMD and its progression with GWAS and fundus image data
基于 GWAS 和眼底图像数据的 AMD 及其进展的深度学习预测
  • 批准号:
    10226322
  • 财政年份:
    2020
  • 资助金额:
    $ 63.02万
  • 项目类别:
Advancing simultaneous fMRI-multiphoton imaging technique to study brain function and connectivity across different scales at ultrahigh field
推进同步功能磁共振成像多光子成像技术,研究超高场下不同尺度的大脑功能和连接性
  • 批准号:
    10043972
  • 财政年份:
    2020
  • 资助金额:
    $ 63.02万
  • 项目类别:
Advancing simultaneous fMRI-multiphoton imaging technique to study brain function and connectivity across different scales at ultrahigh field
推进同步功能磁共振成像多光子成像技术,研究超高场下不同尺度的大脑功能和连接性
  • 批准号:
    10268184
  • 财政年份:
    2020
  • 资助金额:
    $ 63.02万
  • 项目类别:
Advancing simultaneous fMRI-multiphoton imaging technique to study brain function and connectivity across different scales at ultrahigh field
推进同步功能磁共振成像多光子成像技术,研究超高场下不同尺度的大脑功能和连接性
  • 批准号:
    10463737
  • 财政年份:
    2020
  • 资助金额:
    $ 63.02万
  • 项目类别:
Deep-learning-based prediction of AMD and its progression with GWAS and fundus image data
基于 GWAS 和眼底图像数据的 AMD 及其进展的深度学习预测
  • 批准号:
    10056062
  • 财政年份:
    2020
  • 资助金额:
    $ 63.02万
  • 项目类别:

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三磷酸腺苷作为海洋学背景下生物量的主变量
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