Imagine the brain as a vast network of roads connecting different cities. Just like how we can measure the quality and condition of roads to understand the efficiency of transportation, scientists can use diffusion magnetic resonance imaging (MRI) to study the white matter tracts in the brain that connect different functional regions. In this research, they compared different MRI metrics to see which ones were most closely associated with age and cognitive performance in older adults. They found that multi-compartment metrics, such as Free Water Eliminated Fractional Anisotropy (FWE-FA) and Intracellular Volume Fraction (ICVF), were more sensitive to cognitive performance, specifically working memory, than single-compartment metrics. These multi-compartment metrics reveal more specific characteristics about the white matter tracts, providing insights into how these neural highways contribute to cognitive abilities. The findings suggest that maintaining healthy white matter tracts may be important for preserving cognitive function with age. To dive deeper into this intriguing research, check out the full article!

Multi-compartment diffusion MRI metrics [such as metrics from free water elimination diffusion tensor imaging (FWE-DTI) and neurite orientation dispersion and density imaging (NODDI)] may reflect more specific underlying white-matter tract characteristics than traditional, single-compartment metrics [i.e., metrics from Diffusion Tensor Imaging (DTI)]. However, it remains unclear if multi-compartment metrics are more closely associated with age and/or cognitive performance than single-compartment metrics. Here we compared the associations of single-compartment [Fractional Anisotropy (FA)] and multi-compartment diffusion MRI metrics [FWE-DTI metrics: Free Water Eliminated Fractional Anisotropy (FWE-FA) and Free Water (FW); NODDI metrics: Intracellular Volume Fraction (ICVF), Orientation Dispersion Index (ODI), and CSF-Fraction] with both age and working memory performance. A functional magnetic resonance imaging (fMRI) guided, white matter tractography approach was employed to compute diffusion metrics within a network of tracts connecting functional regions involved in working memory. Ninety-nine healthy older adults (aged 60–85) performed an in-scanner working memory task while fMRI was performed and also underwent multi-shell diffusion acquisition. The network of white matter tracts connecting functionally-activated regions was identified using probabilistic tractography. Diffusion metrics were extracted from skeletonized white matter tracts connecting fMRI activation peaks. Diffusion metrics derived from both single and multi-compartment models were associated with age (ps ≤ 0.011 for FA, FWE-FA, ICVF and ODI). However, only multi-compartment metrics, specifically FWE-FA (p = 0.045) and ICVF (p = 0.020), were associated with working memory performance. Our results suggest that while most current diffusion metrics are sensitive to age, several multi-compartment metrics (i.e., FWE-FA and ICVF) appear more sensitive to cognitive performance in healthy older adults.

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