Modeling Axonal Density and Inflammation-Associated Cellularity in Alzheimer’s Disease Using Hybrid Diffusion Imaging

使用混合扩散成像模拟阿尔茨海默病的轴突密度和炎症相关细胞结构

• 批准号: 9977066
• 负责人: Yu-Chien Wu
• 金额: $ 38.92万
• 依托单位: INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-15 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9977066
• 关键词: Affect; Alzheimer' s Disease; Alzheimer' s disease brain; Alzheimer' s disease patient; Alzheimer' s disease risk; Amyloid deposition; Area; Axon; Biological; Biological Markers; Brain; Cellularity; Cerebrospinal Fluid; Complex; Data; Development; Diagnostic; Diffuse; Diffusion; Diffusion Magnetic Resonance Imaging; Discrimination; Disease; Disease Progression; Early Diagnosis; Early Intervention; Elderly; Fiber; Fibrinogen; Future; Gaussian model; Goals; Human; Hybrids; Image; Individual; Inflammation; Inflammatory; Link; Magnetic Resonance; Magnetic Resonance Imaging; Measurement; Measures; Methods; Minor; Modeling; Monitor; Neurites; Neurodegenerative Disorders; Neuroglia; Pathologic; Patients; Phase; Prevalence; Prevention; Process; Property; Research; Risk; Risk Factors; Signal Transduction; Specificity; Structure; Symptoms; The Sun; Tissues; United States; Weight; aging population; apolipoprotein E-4; base; cohort; density; extracellular; follow-up; gray matter; human imaging; human old age (65+); imaging biomarker; in vivo; indexing; insight; interest; mild cognitive impairment; morphometry; novel; pre-clinical; public health relevance; screening; spectrograph; success; theories; tool; water diffusion; white matter

Project Abstract Alzheimer's disease (AD) affects as many as 5 million individuals over the age of 65 in the United States (US) and 35 million worldwide. Because of the aging population, the prevalence of AD will disproportionately increase in future years if no effective early interventions are developed. Converging evidence suggests that the pathophysiologic processes in the brains of AD patients begin decades before symptoms occur. The long preclinical phase of AD provides a valuable window for early intervention with disease-modifying therapy, if we are able to understand the underlying mechanisms of AD by identifying reliable biomarkers. Diffusion MRI (dMRI) probes microstructures of the human brain by measuring water diffusion properties at the cellular level in vivo and non-invasively, which is especially suitable for preclinical screening and monitoring disease progression for AD. Microstructural features with links to specific biologic targets, e.g., axons, glia, or extracellular substrates may provide direct insight into the pathophysiologic changes underlying neurodegenerative disorders. In theory, diffusion MRI provides significant advances for objectively detecting and characterizing the mechanisms of brain changes in AD. Current approaches using diffusion tensor imaging (DTI), however, have not achieved this potential. A very recent advance in the use of dMRI to image the human brain is the development of a method to reflect axonal density and volume fraction of glial cells (cellularity) among other microstructural features. These biologic specific diffusion metrics can be obtained by parametric analysis of the diffusion data via diffusion compartment modeling. We will use the hybrid diffusion imaging (HYDI) developed by the PI to acquire diffusion data with at least five diffusion-weighting b-value shells to sensitize diffusion compartments (e.g., axons, glia, and extracellular substrates) with different diffusivities. A novel feature of HYDI is its versatility for various diffusion model analyses and computational approaches. In the proposed research, we will use two diffusion modeling approaches: (1) neurite orientation dispersion and density imaging (NODDI) to extract the diffusion metric for axonal density, and (2) diffusion basis spectrum imaging (DBSI) to extract the cellularity of glial cells reflecting inflammatory processes. The goals of the proposed research are to determine the sensitivity (Aim 1), discrimination (Aim 2), and predictive power (Aim 3) of the diffusion metrics of axonal density and inflammation-associated cellularity cross-sectionally (Aims 1 and 2) and longitudinally (Aim 3) in a cohort of healthy control and preclinical (at-risk) older adults, and patients with early mild cognitive impairment (MCI), late MCI, and AD. The success of the proposed research will lead to the development of non-invasive differential diagnostic tools and reveal the micromechanisms of the pathophysiologic changes that occur in the early stages of AD.

项目摘要 阿尔茨海默病（AD）在美国（US）影响多达500万65岁以上的个体 全球3500万人。由于人口老龄化，AD的患病率将不成比例地 如果没有制定有效的早期干预措施，未来几年的死亡率将上升。越来越多的证据表明， AD患者脑中的病理生理过程在症状出现前开始几十年就开始了。长 AD的临床前阶段为疾病改善治疗的早期干预提供了一个有价值的窗口，如果我们 能够通过识别可靠的生物标志物来了解AD的潜在机制。扩散MRI （dMRI）通过在细胞水平上测量水扩散特性来探测人脑的微观结构 体内无创，特别适合临床前筛查和疾病监测 AD的进展。与特定生物靶点相关的微观结构特征，例如，轴突，神经胶质，或 细胞外基质可以提供直接洞察的病理生理变化， 神经退行性疾病从理论上讲，扩散MRI为客观检测 并描述AD的脑变化机制。当前使用扩散张量的方法 然而，磁共振成像（DTI）还没有实现这一潜力。 使用dMRI对人脑成像的最新进展是开发了一种方法来反映 神经胶质细胞的轴突密度和体积分数（细胞性）以及其他显微结构特征。这些 通过扩散数据的参数分析可以获得生物特异性扩散度量 隔室建模我们将使用PI开发的混合扩散成像（HYDI）获取 具有至少五个扩散加权b值壳层的扩散数据以敏化扩散隔室（例如， 轴突、神经胶质和细胞外基质）具有不同的扩散率。HYDI的一个新特点是它的多功能性， 各种扩散模型分析和计算方法。在研究中，我们将使用两个 扩散建模方法：（1）神经突方向弥散和密度成像（NODDI），以提取 轴突密度的扩散度量，和（2）扩散基础光谱成像（DBSI）以提取轴突的细胞结构。 反映炎症过程的神经胶质细胞。拟议研究的目标是确定 轴突扩散度量的灵敏度（目标1）、区分度（目标2）和预测能力（目标3） 密度和炎症相关的细胞结构的横截面（目的1和2）和纵向（目的3），在一个 健康对照和临床前（风险）老年人队列以及早期轻度认知障碍患者 (MCI)晚期MCI和AD。这项研究的成功将导致非侵入性的发展。 鉴别诊断工具，并揭示发生在 早期AD。

项目成果

Rapid golden-angle diffusion-weighted propeller MRI for simultaneous assessment of ADC and IVIM.

• DOI: 10.1016/j.neuroimage.2020.117327
• 发表时间: 2020-12
• 期刊: NeuroImage
• 影响因子: 5.7
• 作者: Wen Q;Feng L;Zhou K;Wu YC
• 通讯作者: Wu YC

Effects of White-Matter Tract Length in Sport-Related Concussion: A Tractography Study from the NCAA-DoD CARE Consortium.

白质纤维束长度对运动相关脑震荡的影响：来自 NCAA-DoD CARE 联盟的纤维束描记术研究。

• DOI: 10.1089/neu.2021.0239
• 发表时间: 2022
• 期刊: Journal of neurotrauma
• 影响因子: 4.2
• 作者: Mustafi,SourajitM;Yang,Ho-Ching;Harezlak,Jaroslaw;Meier,TimothyB;Brett,BenjaminL;Giza,ChristopherC;Goldman,Joshua;Guskiewicz,KevinM;Mihalik,JasonP;LaConte,StephenM;Duma,StefanM;Broglio,StevenP;McCrea,MichaelA;McAllister
• 通讯作者: McAllister

Advanced Meditation Alters Resting-State Brain Network Connectivity Correlating With Improved Mindfulness.

• DOI: 10.3389/fpsyg.2021.745344
• 发表时间: 2021
• 期刊: Frontiers in psychology
• 影响因子: 3.8
• 作者: Vishnubhotla RV;Radhakrishnan R;Kveraga K;Deardorff R;Ram C;Pawale D;Wu YC;Renschler J;Subramaniam B;Sadhasivam S
• 通讯作者: Sadhasivam S

Comparison of multi-shot and single shot echo-planar diffusion tensor techniques for the optic pathway in patients with neurofibromatosis type 1.

多射和单射回波平面扩散张量技术对 1 型神经纤维瘤病患者视神经通路的比较。

• DOI: 10.1007/s00234-019-02164-6
• 发表时间: 2019
• 期刊: Neuroradiology
• 影响因子: 2.8
• 作者: Ho,ChangY;Deardorff,Rachael;Kralik,StephenF;West,JohnD;Wu,Yu-Chien;Shih,Chie-Schin
• 通讯作者: Shih,Chie-Schin

Bifurcated Topological Optimization for IVIM.

• DOI: 10.3389/fnins.2021.779025
• 发表时间: 2021
• 期刊: Frontiers in neuroscience
• 影响因子: 4.3
• 作者: Fadnavis S;Endres S;Wen Q;Wu YC;Cheng H;Koudoro S;Rane S;Rokem A;Garyfallidis E
• 通讯作者: Garyfallidis E