Macrostructural and Microstructural Imaging Biomarkers of Traumatic Brain Injury

脑外伤的宏观结构和微观结构成像生物标志物

基本信息

批准号：
8282871
负责人：
Pratik Mukherjee
金额：
$ 42.53万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-07-15 至 2015-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8282871
关键词：
Accounting Acute Affect Age American Amnesia Anisotropy Anterior Apolipoprotein E Atrophic Attention Behavioral Biological Markers Brain Concussion Brain Injuries Brain Mapping Brain scan Cause of Death Clinical Clinical Management Cognitive Contusions DNA Data Diagnosis Diagnostic Diffusion Magnetic Resonance Imaging Doctor of Medicine Doctor of Philosophy Education Educational Status Fiber Functional Magnetic Resonance Imaging Gender Genetic Predisposition to Disease Genetic Variation Genotype Glasgow Coma Scale Image Imaging technology Individual Injury Intervention Trial Investigation Lesion Long-Term Effects Magnetic Resonance Magnetic Resonance Imaging Measures Memory Memory impairment Metabolic Monitor Nerve Degeneration Neurocognitive Outcome Patients Phenotype Play Post-Concussion Syndrome Prevalence Principal Investigator Protocols documentation Rehabilitation therapy Research Research Proposals Resolution Role Scanning Scientific Advances and Accomplishments Severities Shapes Surrogate Endpoint Susceptibility Gene TBI Patients Techniques Testing Therapeutic Intervention Time Traumatic Brain Injury Unconscious State Weight X-Ray Computed Tomography base brain volume cerebral atrophy cohort disability endophenotype follow-up functional disability functional outcomes gray matter improved magnetic resonance spectroscopic imaging memory process morphometry neurocognitive test neuroimaging processing speed prognostic programs spectroscopic imaging tool white matter white matter damage white matter injury

项目摘要

PROJECT SUMMARY Traumatic brain injury (TBI) is the leading cause of death and disability in Americans under age 45, and is increasing in prevalence worldwide. Neuroimaging techniques such as computed tomography (CT) or magnetic resonance imaging (MRI) are important diagnostic tools for the clinical management of acute TBI. However, the focal lesions detected by CT or MRI in acute TBI, such as contusions and axonal shearing injuries, are often not predictive of long-term functional disability after TBI, especially in mild cases. The objective of this research proposal is to establish quantitative macrostructural and microstructural imaging biomarkers for predicting patient outcome after mild TBI. The macrostructural biomarker measures post- traumatic focal atrophy using deformation-based morphometry (DBM) of serial high-resolution 3D MR scans of the brain. The microstructural biomarker measures post-traumatic decreases in white matter integrity using quantitative fiber tracking based on serial diffusion tensor imaging (DTI). One hundred mild TBI patients will undergo high-resolution 3D structural MRI and DTI on 3 Tesla MR scanners at 1 month after injury, at 6 months after injury, and then again at 1 year after injury. Comparison will be made to the same imaging protocol in 40 age-, gender-, and education-matched healthy control subjects. All subjects will undergo neurocognitive and functional outcome tests at the same time points as the MRI/DTI scans. The hypothesis will be tested that increasing spatial extent of progressive focal atrophy detected by DBM of serial MRI and/or progressive white matter microstructural injury on serial DTI is correlated with worse neurocognitive and functional outcomes at one year after injury, after controlling for clinical measures of injury severity including Glasgow Coma Scale, duration of unconsciousness, and duration of post-traumatic amnesia. These macrostructural and microstructural imaging biomarkers will also be correlated with functional and metabolic imaging data using fMRI and 3D MR spectroscopic imaging, respectively. If the proposed investigation is successful in establishing these quantitative macrostructural and microstructural imaging biomarkers of long-term outcome in TBI, then they could potentially serve as surrogate endpoints for clinical intervention trials. They might also yield endophenotypes for studies of genetic susceptibility factors that worsen outcome after TBI. Towards this purpose, DNA will be banked from patients in this study for genotype analysis. Specifically, we will examine whether ApoE genotype influences the degree of regional brain atrophy and microstructural white matter injury. The allelic variants of ApoE are already known to modulate clinical outcome after TBI, and this study will determine if DBM and DTI can provide "intermediate phenotypes" for the effect of ApoE genotype on TBI outcome.

项目概要创伤性脑损伤 (TBI) 是 45 岁以下美国人死亡和残疾的主要原因，并且在世界范围内流行率不断增加。神经影像技术，例如计算机断层扫描 (CT) 或磁共振成像 (MRI) 是急性 TBI 临床治疗的重要诊断工具。然而，急性TBI时CT或MRI检测到的局灶性病变，如挫伤和轴突剪切损伤通常不能预测 TBI 后的长期功能障碍，特别是在轻度病例中。这本研究计划的目标是建立定量的宏观结构和微观结构成像用于预测轻度 TBI 后患者预后的生物标志物。宏观结构生物标志物测量后使用基于变形的形态测量（DBM）对连续高分辨率 3D MR 扫描进行创伤性局灶性萎缩大脑。微观结构生物标志物使用以下方法测量创伤后白质完整性的下降基于串行扩散张量成像（DTI）的定量纤维跟踪。 100 名轻度 TBI 患者将在 3 台 Tesla MR 扫描仪上接受高分辨率 3D 结构 MRI 和 DTI 受伤后 1 个月、受伤后 6 个月、受伤后 1 年再次进行。将进行比较对 40 名年龄、性别和教育程度匹配的健康对照受试者采用相同的成像方案。全部受试者将在 MRI/DTI 的同一时间点接受神经认知和功能结果测试扫描。该假设将得到检验，即通过检测到的渐进性局灶性萎缩的空间范围不断增加连续 MRI 的 DBM 和/或连续 DTI 上的进行性白质微结构损伤与较差相关控制损伤的临床测量后，损伤后一年的神经认知和功能结果严重程度，包括格拉斯哥昏迷量表、意识丧失持续时间和创伤后遗忘持续时间。这些宏观结构和微观结构成像生物标志物也将与功能和功能相关。分别使用 fMRI 和 3D MR 光谱成像的代谢成像数据。如果拟议的调查成功地建立了这些定量的宏观结构和 TBI 长期结果的微结构成像生物标志物，那么它们有可能作为替代品临床干预试验的终点。它们还可能产生用于遗传研究的内表型 TBI 后导致预后恶化的易感因素。为此，将从患者身上储存 DNA 在本研究中进行基因型分析。具体来说，我们将检查 ApoE 基因型是否影响区域脑萎缩和微结构白质损伤的程度。 ApoE 的等位基因变体是已知 DBM 和 DTI 可以调节 TBI 后的临床结果，本研究将确定 DBM 和 DTI 是否可以为 ApoE 基因型对 TBI 结果的影响提供“中间表型”。

项目成果

期刊论文数量（7）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Edge density imaging: mapping the anatomic embedding of the structural connectome within the white matter of the human brain.

DOI：
10.1016/j.neuroimage.2015.01.007
发表时间：
2015-04-01
期刊：
NeuroImage
影响因子：
5.7
作者：
Owen JP;Chang YS;Mukherjee P
通讯作者：
Mukherjee P

Microstructural correlations of white matter tracts in the human brain.

DOI：
10.1016/j.neuroimage.2010.02.072
发表时间：
2010-06
期刊：
NEUROIMAGE
影响因子：
5.7
作者：
Wahl, Michael;Li, Yi-Ou;Ng, Joshua;LaHue, Sara C.;Cooper, Shelly R.;Sherr, Elliott H.;Mukherjee, Pratik
通讯作者：
Mukherjee, Pratik

Stochastic geometric network models for groups of functional and structural connectomes.