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Features of the superficial white matter as biomarkers for the detection of Alzheimer's disease and mild cognitive impairment: A diffusion tensor imaging study.作为阿尔茨海默病和轻度认知障碍检测生物标志物的脑白质浅层特征:一项扩散张量成像研究
Heliyon. 2022 Jan 8;8(1):e08725. doi: 10.1016/j.heliyon.2022.e08725. eCollection 2022 Jan.
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Age and sex effects on advanced white matter microstructure measures in 15,628 older adults: A UK biobank study.年龄和性别对 15628 名老年人高级白质微观结构测量的影响:英国生物银行研究。
Brain Imaging Behav. 2021 Dec;15(6):2813-2823. doi: 10.1007/s11682-021-00548-y. Epub 2021 Sep 18.
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Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?束追踪解剖变异性:当 42 个组在同一数据集上解剖 14 个白质束时会发生什么?
Neuroimage. 2021 Nov;243:118502. doi: 10.1016/j.neuroimage.2021.118502. Epub 2021 Aug 22.
4
Fiber tractography bundle segmentation depends on scanner effects, vendor effects, acquisition resolution, diffusion sampling scheme, diffusion sensitization, and bundle segmentation workflow.束追踪纤维分割依赖于扫描仪的影响、供应商的影响、采集分辨率、扩散采样方案、扩散敏感和束分割工作流程。
Neuroimage. 2021 Nov 15;242:118451. doi: 10.1016/j.neuroimage.2021.118451. Epub 2021 Aug 4.
5
Tract-specific MRI measures explain learning and recall differences in multiple sclerosis.特定脑区的磁共振成像测量可解释多发性硬化症患者在学习和记忆方面的差异。
Brain Commun. 2021 Apr 1;3(2):fcab065. doi: 10.1093/braincomms/fcab065. eCollection 2021.
6
Investigating the Spatial Associations Between Amyloid-β Deposition, Grey Matter Volume, and Neuroinflammation in Alzheimer's Disease.探讨阿尔茨海默病中淀粉样蛋白-β沉积、灰质体积和神经炎症之间的空间关联。
J Alzheimers Dis. 2021;80(1):113-132. doi: 10.3233/JAD-200840.
7
Microstructural differences in white matter tracts across middle to late adulthood: a diffusion MRI study on 7167 UK Biobank participants.白质束在中年到晚年的微观结构差异:对 7167 名英国生物库参与者的扩散 MRI 研究。
Neurobiol Aging. 2021 Feb;98:160-172. doi: 10.1016/j.neurobiolaging.2020.10.006. Epub 2020 Nov 13.
8
Bundle analytics, a computational framework for investigating the shapes and profiles of brain pathways across populations.束分析,一种用于研究跨人群脑通路形状和特征的计算框架。
Sci Rep. 2020 Oct 13;10(1):17149. doi: 10.1038/s41598-020-74054-4.
9
White matter microstructure across the adult lifespan: A mixed longitudinal and cross-sectional study using advanced diffusion models and brain-age prediction.成人寿命期内的白质微观结构:采用先进扩散模型和大脑年龄预测的混合纵向和横断面研究。
Neuroimage. 2021 Jan 1;224:117441. doi: 10.1016/j.neuroimage.2020.117441. Epub 2020 Oct 9.
10
Changes Over Time of Diffusion MRI in the White Matter of Aging Brain, a Good Predictor of Verbal Recall.衰老大脑白质中扩散磁共振成像随时间的变化,言语回忆的良好预测指标。
Front Aging Neurosci. 2020 Aug 14;12:218. doi: 10.3389/fnagi.2020.00218. eCollection 2020.

衰老与脑白质微观结构和宏观结构:1218 名参与者的纵向多部位弥散磁共振成像研究。

Aging and white matter microstructure and macrostructure: a longitudinal multi-site diffusion MRI study of 1218 participants.

机构信息

Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA.

Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA.

出版信息

Brain Struct Funct. 2022 Jul;227(6):2111-2125. doi: 10.1007/s00429-022-02503-z. Epub 2022 May 23.

DOI:10.1007/s00429-022-02503-z
PMID:35604444
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9648053/
Abstract

Quantifying the microstructural and macrostructural geometrical features of the human brain's connections is necessary for understanding normal aging and disease. Here, we examine brain white matter diffusion magnetic resonance imaging data from one cross-sectional and two longitudinal data sets totaling in 1218 subjects and 2459 sessions of people aged 50-97 years. Data was drawn from well-established cohorts, including the Baltimore Longitudinal Study of Aging data set, Cambridge Centre for Ageing Neuroscience data set, and the Vanderbilt Memory & Aging Project. Quantifying 4 microstructural features and, for the first time, 11 macrostructure-based features of volume, area, and length across 120 white matter pathways, we apply linear mixed effect modeling to investigate changes in pathway-specific features over time, and document large age associations within white matter. Conventional diffusion tensor microstructure indices are the most age-sensitive measures, with positive age associations for diffusivities and negative age associations with anisotropies, with similar patterns observed across all pathways. Similarly, pathway shape measures also change with age, with negative age associations for most length, surface area, and volume-based features. A particularly novel finding of this study is that while trends were homogeneous throughout the brain for microstructure features, macrostructural features demonstrated heterogeneity across pathways, whereby several projection, thalamic, and commissural tracts exhibited more decline with age compared to association and limbic tracts. The findings from this large-scale study provide a comprehensive overview of the age-related decline in white matter and demonstrate that macrostructural features may be more sensitive to heterogeneous white matter decline. Therefore, leveraging macrostructural features may be useful for studying aging and could facilitate comparisons in a variety of diseases or abnormal conditions.

摘要

量化人类大脑连接的微观结构和宏观结构几何特征对于理解正常衰老和疾病是必要的。在这里,我们检查了来自一个横断面和两个纵向数据集的大脑白质扩散磁共振成像数据,这些数据共涉及 1218 名年龄在 50-97 岁的受试者和 2459 次检查。数据来自成熟的队列,包括巴尔的摩老龄化纵向研究数据集、剑桥认知老化神经科学数据集和范德比尔特记忆与衰老项目。我们量化了 4 种微观结构特征,以及首次量化了 120 条白质通路的体积、面积和长度的 11 种基于宏观结构的特征,我们应用线性混合效应模型来研究特定通路特征随时间的变化,并记录了白质内的大年龄关联。传统的扩散张量微观结构指数是最敏感的年龄测量指标,各向异性扩散度呈正相关,各向异性呈负相关,所有通路都观察到类似的模式。同样,通路形状测量值也随年龄变化而变化,大多数基于长度、表面积和体积的特征与年龄呈负相关。这项研究的一个特别新颖的发现是,尽管微观结构特征的趋势在整个大脑中是均匀的,但宏观结构特征在通路之间表现出异质性,几个投射、丘脑和连合束与联合和边缘束相比,随着年龄的增长表现出更多的衰退。这项大规模研究的结果提供了白质与年龄相关衰退的全面概述,并表明宏观结构特征可能对白质的异质性衰退更敏感。因此,利用宏观结构特征可能有助于研究衰老,并可以促进在各种疾病或异常情况下的比较。