Mesoscopic Biomarkers of Neurodegeneration with Diffusion MRI

弥散 MRI 神经退行性变的细观生物标志物

基本信息

  • 批准号:
    9134909
  • 负责人:
  • 金额:
    $ 37.08万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2014
  • 资助国家:
    美国
  • 起止时间:
    2014-09-01 至 2019-07-31
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): Diseases of the central nervous system (CNS) are a significant public health and economic problem, affecting nearly one in three Americans at some point in life, with a cost exceeding $500 billion per year. Pathologically, the axonal integrity in the brain white matter is compromised in most human neurological diseases or injuries, including multiple sclerosis, leukodystrophy, traumatic brain injury, as well as in normal aging and neurodegenerative diseases such as Parkinson's, Huntington's, amyotrophic lateral sclerosis, and Alzheimer's disease. Neurodegeneration occurs via a number of distinct processes, such as acute axonal injury, demyelination, inflammation, chronic axonal degeneration or axonal loss, and gliosis. Quantifying their degree, and distinguishing between these different underlying degenerative processes is particularly vital for adequate assessment of CNS disease progression and treatment, but currently not available. The main objective of this proposal is the development, validation and clinical translation of MesoMRI, a newly proposed framework that yields high specificity of diffusion MRI metrics to different degenerative processes by identifying how structural changes at the mesoscopic scale manifest themselves in the diffusion-weighted signal. The mesoscopic scale is the scale of cellular tissue architecture, intermediate between the molecular scale and the macroscopic MRI resolution. Our overall hypothesis is that our novel mesoscopic biomarkers of brain tissue integrity will be specific to different aspects of neurodegeneration in vivo, including demyelination and axonal loss. The development of the mesoscopic MRI framework involves qualitative understanding and quantitative modeling of the role of axonal geometry at the micrometer scale, and the response of water diffusion metrics to demyelination, axonal loss, injury, and other pathological changes. This involves bringing advanced analytical methods borrowed from modern transport theory and statistical physics into the context of diffusion MRI. In particular, we will first deveop and validate our white matter tract integrity metrics and the relation between them and the degree of demyelination and axonal loss in a single white matter fiber bundle. Subsequently, we will extend the mesoscopic modeling of a single fiber bundle onto the whole white matter, including regions of multiple fiber directions and crossings. This extension involves the development of MesoFT, a novel mesoscopic modeling and fiber tracking paradigm, able for the first time to produce self-consistent maps of both local mesoscopic parameters of fibers and their macroscopic connectivity maps. The potential of our technical developments for clinical translation will be evaluated by applying MesoFT to retrospectively acquired clinical cases of Alzheimer's disease and multiple sclerosis. Based on adequate interpretation of standard clinically feasible diffusion MRI metrics, our framework's translation into clinic will be straightforward, and will enable the quantitative assessment of disease progression and quality of treatment in neurological diseases.
中枢神经系统(CNS)疾病是一个重大的公共卫生和经济问题,在生命的某个阶段影响近三分之一的美国人,每年的成本超过5000亿美元。病理学上, 脑白色物质在大多数人类神经系统疾病或损伤(包括多发性硬化症、脑白质营养不良、创伤性脑损伤)以及正常衰老和神经变性疾病(例如帕金森氏病、亨廷顿氏病、肌萎缩侧索硬化症和阿尔茨海默氏病)中受损。神经变性通过许多不同的过程发生,例如急性轴突损伤、脱髓鞘、炎症、慢性轴突变性或轴突损失和神经胶质增生。量化它们的程度,并区分这些不同的潜在退行性过程对于充分评估CNS疾病进展和治疗特别重要,但目前尚不可用。该提案的主要目标是MesoMRI的开发,验证和临床翻译,这是一种新提出的框架,通过识别介观尺度的结构变化如何在扩散加权信号中表现出来,从而对不同的退行性过程产生高特异性的扩散MRI指标。介观尺度是细胞组织结构的尺度,介于分子尺度和宏观MRI分辨率之间。我们的总体假设是,我们的新的介观生物标志物的脑组织完整性将具体到不同方面的神经退行性疾病在体内,包括脱髓鞘和轴突损失。介观MRI框架的发展涉及在微米尺度上对轴突几何形状的作用的定性理解和定量建模,以及水扩散度量对脱髓鞘、轴突损失、损伤和其他病理变化的响应。这涉及到将从现代传输理论和统计物理学中借来的先进分析方法引入扩散MRI的背景下。特别是,我们将首先开发和验证我们的白色束完整性指标和它们之间的关系和脱髓鞘和轴突损失的程度在一个单一的白色纤维束。随后,我们将扩展到整个白色物质,包括多个纤维方向和交叉区域的单纤维束的介观建模。这种扩展涉及到MesoFT的发展,一种新的介观建模和纤维跟踪范例,能够第一次产生自洽的地图的本地介观参数的纤维和它们的宏观连接图。我们的临床翻译技术发展的潜力将通过将MesoFT应用于回顾性获得的阿尔茨海默病和多发性硬化症的临床病例进行评估。基于对标准临床可行的弥散MRI指标的充分解释,我们的框架将直接转化为临床,并将能够定量评估神经系统疾病的疾病进展和治疗质量。

项目成果

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Els Fieremans其他文献

Els Fieremans的其他文献

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{{ truncateString('Els Fieremans', 18)}}的其他基金

International Society for Magnetic Resonance in Medicine (ISMRM) workshop on WHATEVER: WHite Matter, Analysis, Translation, Experimental Validation, Evaluation, and Reproducibility
国际医学磁共振学会 (ISMRM) 研讨会主题为:白质、分析、翻译、实验验证、评估和再现性
  • 批准号:
    10757846
  • 财政年份:
    2023
  • 资助金额:
    $ 37.08万
  • 项目类别:
Random Matrix Theory-Based Noise Removal in MRI
MRI 中基于随机矩阵理论的噪声消除
  • 批准号:
    10456777
  • 财政年份:
    2019
  • 资助金额:
    $ 37.08万
  • 项目类别:
Random Matrix Theory-Based Noise Removal in MRI
MRI 中基于随机矩阵理论的噪声消除
  • 批准号:
    10229483
  • 财政年份:
    2019
  • 资助金额:
    $ 37.08万
  • 项目类别:
Random Matrix Theory-Based Noise Removal in MRI
MRI 中基于随机矩阵理论的噪声消除
  • 批准号:
    10018721
  • 财政年份:
    2019
  • 资助金额:
    $ 37.08万
  • 项目类别:
Mesoscopic Biomarkers of Neurodegeneration with Diffusion MRI
弥散 MRI 神经退行性变的细观生物标志物
  • 批准号:
    8744985
  • 财政年份:
    2014
  • 资助金额:
    $ 37.08万
  • 项目类别:
Mesoscopic Biomarkers of Neurodegeneration and Inflammation with Diffusion MRI
弥散 MRI 神经退行性变和炎症的细观生物标志物
  • 批准号:
    10673125
  • 财政年份:
    2014
  • 资助金额:
    $ 37.08万
  • 项目类别:
Mesoscopic Biomarkers of Neurodegeneration and Inflammation with Diffusion MRI
弥散 MRI 神经退行性变和炎症的细观生物标志物
  • 批准号:
    10022344
  • 财政年份:
    2014
  • 资助金额:
    $ 37.08万
  • 项目类别:
Mesoscopic Biomarkers of Neurodegeneration and Inflammation with Diffusion MRI
弥散 MRI 神经退行性变和炎症的细观生物标志物
  • 批准号:
    10457453
  • 财政年份:
    2014
  • 资助金额:
    $ 37.08万
  • 项目类别:
Mesoscopic Biomarkers of Neurodegeneration and Inflammation with Diffusion MRI
弥散 MRI 神经退行性变和炎症的细观生物标志物
  • 批准号:
    10251994
  • 财政年份:
    2014
  • 资助金额:
    $ 37.08万
  • 项目类别:
TR&D 4: Revealing Microstructure: Biophysical modeling and validation for discovery and clinical care
TR
  • 批准号:
    9804443
  • 财政年份:
    2014
  • 资助金额:
    $ 37.08万
  • 项目类别:

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