Song Joan Y, Fleysher Roman, Ye Kenny, Kim Mimi, Zimmerman Molly E, Lipton Richard B, Lipton Michael L
Dominick P Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, United States.
Department of Radiology, Columbia University Irving Medical Center, New York, NY, United States.
Neuroimage. 2025 Feb 1;306:121019. doi: 10.1016/j.neuroimage.2025.121019. Epub 2025 Jan 12.
The cortical gray matter-white matter interface (GWI) is a natural transition zone where the composition of brain tissue abruptly changes and is a location for pathologic change in brain disorders. While diffusion magnetic resonance imaging (dMRI) is a reliable and well-established technique to characterize brain microstructure, the GWI is difficult to assess with dMRI due to partial volume effects and is normally excluded from such studies.
In this study, we introduce an approach to characterize the dMRI microstructural profile across the GWI and to assess the sharpness of the microstructural transition from cortical gray matter (GM) to white matter (WM). This analysis includes cross-sectional data from a total of 146 participants (18-91 years; mean age: 52.4 (SD 21.4); 83 (57 %) female) enrolled in two normative lifespan cohorts at Albert Einstein College of Medicine from 2019 to 2023. We compute the aggregate GWI slope for each parameter, across each of 6 brain regions (cingulate, frontal, occipital, orbitofrontal, parietal, and temporal) for each participant. The association of GWI slope in each region with age was assessed using a linear model, with biological sex as a covariate.
We demonstrate this method captures an inherent change in fractional anisotropy (FA), axial diffusivity (AD), orientation dispersion index (ODI) and intracellular volume fraction (ICVF) across the GWI that is characterized by small variance. We identified statistically significant associations of FA slope with age in all regions (p < 0.002 for all analyses), with FA slope magnitude inversely associated with higher age. Similar statistically significant age-related associations were found for AD slope in cingulate, occipital, and temporal regions, for ODI slope in parietal and occipital regions, and for ICVF slope in frontal, orbitofrontal, parietal, and temporal regions.
The inverse association of slope magnitude with age indicates loss of the sharp GWI transition in aging, which is consistent with processes such as dendritic pruning, axonal degeneration, and inflammation. This method overcomes techniques issues related to interrogating the GWI. Beyond characterizing normal aging, it could be applied to explore pathological effects at this crucial, yet under-researched region.
皮质灰质 - 白质界面(GWI)是一个自然过渡区,脑组织成分在此处突然变化,也是脑部疾病病理变化的发生部位。虽然扩散磁共振成像(dMRI)是一种可靠且成熟的表征脑微观结构的技术,但由于部分容积效应,GWI难以通过dMRI进行评估,因此在这类研究中通常被排除在外。
在本研究中,我们引入一种方法来表征跨GWI的dMRI微观结构轮廓,并评估从皮质灰质(GM)到白质(WM)的微观结构转变的锐度。该分析包括来自2019年至2023年在阿尔伯特·爱因斯坦医学院参加两个正常寿命队列研究的总共146名参与者(年龄在18 - 91岁之间;平均年龄:52.4(标准差21.4);83名(57%)女性)的横断面数据。我们为每个参与者计算6个脑区(扣带回、额叶、枕叶、眶额叶、顶叶和颞叶)中每个参数的总体GWI斜率。使用线性模型评估每个区域的GWI斜率与年龄的关联,并将生物学性别作为协变量。
我们证明该方法捕获了跨GWI的分数各向异性(FA)、轴向扩散率(AD)、方向离散指数(ODI)和细胞内体积分数(ICVF)的固有变化,其特征是方差较小。我们在所有区域都确定了FA斜率与年龄之间具有统计学意义的关联(所有分析中p < 0.002),FA斜率大小与较高年龄呈负相关。在扣带回、枕叶和颞叶区域发现AD斜率与年龄有类似的统计学意义的关联,在顶叶和枕叶区域发现ODI斜率与年龄有类似的统计学意义的关联,在额叶、眶额叶、顶叶和颞叶区域发现ICVF斜率与年龄有类似的统计学意义的关联。
斜率大小与年龄的负相关表明衰老过程中GWI的锐利转变丧失,这与树突修剪、轴突退化和炎症等过程一致。该方法克服了与研究GWI相关的技术问题。除了表征正常衰老外,它还可用于探索这个关键但研究不足的区域的病理效应。