Microstructure of Strategic White Matter Tracts and Cognition in Memory Clinic Patients with Vascular Brain Injury

Abstract

Background: White matter injury is an important factor for cognitive impairment in memory clinic patients. We determined the added value of diffusion tensor imaging (DTI) of strategic white matter tracts in explaining variance in cognition in memory clinic patients with vascular brain injury.

Methods: We included 159 patients. Conventional MRI markers (white matter hyperintensity volume, lacunes, nonlacunar infarcts, brain atrophy, and microbleeds), and fractional anisotropy and mean diffusivity (MD) of the whole brain white matter and of 18 white matter tracts were related to cognition using linear regression and Bayesian network analysis.

Results: On top of all conventional MRI markers combined, MD of the whole brain white matter explained an additional 3.4% (p = 0.014), 7.8% (p < 0.001), and 1.2% (p = 0.119) variance in executive functioning, speed, and memory, respectively. The Bayesian analyses of regional DTI measures identified strategic tracts for executive functioning (right superior longitudinal fasciculus), speed (left corticospinal tract), and memory (left uncinate fasciculus). MD within these tracts explained an additional 3.4% (p = 0.012), 3.8% (p = 0.007), and 2.1% (p = 0.041) variance in executive functioning, speed, and memory, respectively, on top of all conventional MRI and global DTI markers combined.

Conclusion: In memory clinic patients with vascular brain injury, DTI of strategic white matter tracts has a significant added value in explaining variance in cognitive functioning.

Keywords: Alzheimer disease; Diffusion tensor imaging; Small vessel disease; Strategic white matter tract; Vascular dementia.

Fig. 1.

Illustration of the image processing procedure and integration of microstructural and macrostructural data for a single patient. a Left: color-coded fractional anisotropy (FA) map overlaying the corresponding T1 image after correcting for susceptibility-induced deformations. Right: results of whole brain tractography, which is used to extract the FA and mean diffusivity (MD) of the whole brain white matter. b Tractography results of 10 white matter fiber bundles (8 of which were bilaterally reconstructed), used to extract the FA and MD of each tract. c T2 FLAIR image projected onto the corresponding T1 image after rigid registration. The color bar applies to the intensity range of the T2 FLAIR image. d Sagittal T2 FLAIR slice before and after manual segmentation. White matter hyperintensities (WMHs) are green and lacunes are red. e Left: 3D reconstruction of WMHs and lacunes in relation to the right inferior fronto-occipital fasciculus. Right: integration of WMHs and lacunes with the inferior fronto-occipital fasciculus is used to extract the FA and MD of the normal-appearing white matter and the proportion of the tract that is affected by these lesions.

Fig. 2.

Bayesian networks for executive functioning (executive), psychomotor speed (speed), and verbal memory (memory). Bayesian network analyses were used to analyze the conditional dependencies between FA/MD in 18 white matter tracts, age, sex, and education as potential determinants, and executive functioning, psychomotor speed, and verbal memory as outcome variables. Variables that are directly connected to one of the cognitive domains are identified as direct determinants. Variables that are connected indirectly to the cognitive domains (via other variables) are conditionally independent. As such, this method separates determinants with a direct deterministic influence on the outcome variable from other determinants that, although showing a univariate correlation with the outcome variable, have only an indirect influence when taking the direct determinants into account. Percentages indicate the confidence level of the arcs towards cognitive domains determined by 100 bootstrap replications. L, left; R, right.