Characterizing the microstructural transition at the gray matter-white matter interface: Implementation and...

Area of Science:

• Neuroimaging
• Brain Microstructure Analysis
• Aging Research

Background:

• The gray matter-white matter interface (GWI) is critical for brain function and susceptible to pathology.
• Assessing the GWI with diffusion MRI (dMRI) is challenging due to partial volume effects, leading to its exclusion in many studies.

Purpose of the Study:

• To develop and validate a novel dMRI approach for characterizing microstructural profiles across the GWI.
• To assess the sharpness of the transition from gray matter (GM) to white matter (WM) at the GWI.

Main Methods:

• Utilized cross-sectional dMRI data from 146 participants (aged 18-91).
• Computed aggregate GWI slope for microstructural parameters (FA, AD, ODI, ICVF) across six brain regions.
• Assessed the association of GWI slope with age and biological sex using linear models.

Main Results:

• The method successfully captured inherent microstructural changes (FA, AD, ODI, ICVF) across the GWI with low variance.
• Found significant inverse associations between FA slope and age in all regions, indicating a less sharp GWI with aging.
• Identified age-related associations for AD, ODI, and ICVF slopes in specific brain regions.

Conclusions:

• The inverse association of slope magnitude with age suggests a loss of GWI sharpness during aging, potentially due to dendritic pruning, axonal degeneration, and inflammation.
• This new method overcomes previous technical limitations in GWI analysis.
• The approach has potential applications in studying normal aging and pathological conditions affecting the GWI.