Perivascular Spaces, Diffusivity Along Perivascular Spaces, and Free Water in Cerebral Small Vessel Disease.

Neurology

From the Department of Neurology (H.L., M.A.J., M.C., F.-E.D.L., A.M.T.), Radboud University Medical Center, Donders Center for Medical Neurosciences, Nijmegen, the Netherlands; Department of Neurology (M.C.), Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China; Donders Institute for Brain (R.P.C.K.), Cognition and Behaviour, Radboud University, Nijmegen; Vincent van Gogh Institute for Psychiatry (R.P.C.K.), Venray; Department of Medical Psychology and Radboudumc Alzheimer Center (R.P.C.K.), Radboud University Medical Center; Donders Institute for Brain (D.G.N.), Cognition and Behaviour, Center for Cognitive Neuroimaging, Radboud University, Nijmegen, the Netherlands; Medical Image Analysis Center (MIAC AG) and Department of Biomedical Engineering (M.D.), University of Basel, Switzerland; and Institute for Stroke and Dementia Research (ISD) (M.D.), University Hospital, LMU Munich, Germany.

Published: May 2024

Background And Objectives: Previous studies have linked the MRI measures of perivascular spaces (PVSs), diffusivity along the perivascular spaces (DTI-ALPS), and free water (FW) to cerebral small vessel disease (SVD) and SVD-related cognitive impairments. However, studies on the longitudinal associations between the three MRI measures, SVD progression, and cognitive decline are lacking. This study aimed to explore how PVS, DTI-ALPS, and FW contribute to SVD progression and cognitive decline.

Methods: This is a cohort study that included participants with SVD who underwent neuroimaging and cognitive assessment, specifically measuring Mini-Mental State Examination (MMSE), cognitive index, and processing speed, at 2 time points. Three MRI measures were quantified: PVS in basal ganglia (BG-PVS) volumes, FW fraction, and DTI-ALPS. We performed a latent change score model to test inter-relations between the 3 MRI measures and linear regression mixed models to test their longitudinal associations with the changes of other SVD MRI markers and cognitive performances.

Results: In baseline assessment, we included 289 participants with SVD, characterized by a median age of 67.0 years and 42.9% women. Of which, 220 participants underwent the follow-up assessment, with a median follow-up time of 3.4 years. Baseline DTI-ALPS was associated with changes in BG-PVS volumes (β = -0.09, = 0.030), but not vice versa (β = -0.08, = 0.110). Baseline BG-PVS volumes were associated with changes in white matter hyperintensity (WMH) volumes (β = 0.33, -corrected < 0.001) and lacune numbers (β = 0.28, -corrected < 0.001); FW fraction was associated with changes in WMH volumes (β = 0.30, -corrected < 0.001), lacune numbers (β = 0.28, -corrected < 0.001), and brain volumes (β = -0.45, -corrected < 0.001); DTI-ALPS was associated with changes in WMH volumes (β = -0.20, -corrected = 0.002) and brain volumes (β = 0.23, -corrected < 0.001). Furthermore, baseline FW fraction was associated with decline in MMSE score (β = -0.17, -corrected = 0.006); baseline FW fraction and DTI-ALPS were associated with changes in cognitive index (FW fraction: β = -0.25, -corrected < 0.001; DTI-ALPS: β = 0.20, -corrected = 0.001) and processing speed over time (FW fraction: β = -0.29, -corrected < 0.001; DTI-ALPS: β = 0.21, -corrected < 0.001).

Discussion: Our results showed that increased BG-PVS volumes, increased FW fraction, and decreased DTI-ALPS are related to progression of MRI markers of SVD, along with SVD-related cognitive decline over time. These findings may suggest that the glymphatic dysfunction is related to SVD progression, but further studies are needed.

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http://dx.doi.org/10.1212/WNL.0000000000209306DOI Listing

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