Abstract
Background: Perivascular spaces (PVSs) are important component of the brain glymphatic system. While visual rating has been widely used to assess PVS, computational measures may have higher sensitivity for capturing PVS characteristics under disease conditions. Purpose: To compute quantitative and morphological PVS features and to assess their associations with vascular risk factors and cerebral small vessel disease (CSVD). Study Type: Prospective. Population: One hundred sixty-one middle-aged/later middle-aged subjects (age = 60.4 ± 7.3). Sequence: 3D T1-weighted, T2-weighted and T2-FLAIR sequences, and susceptibility-weighted multiecho gradient-echo sequence on a 3 T scanner. Assessment: Automated PVS segmentation was performed on sub-millimeter T2-weighted images. Quantitative and morphological PVS features were calculated in white matter (WM) and basal ganglia (BG) regions, including volume, count, size, length (Lmaj), width (Lmin), and linearity. Visual PVS scores were also acquired for comparison. Statistical Tests: Simple and multiple linear regression analyses were used to explore the associations among variables. Results: WM-PVS visual score and count were associated with hypertension (β = 0.161, P < 0.05; β = 0.193, P < 0.05), as were BG-PVS rating score, volume, count and Lmin (β = 0.197, P < 0.05; β = 0.170, P < 0.05; β = 0.200, P < 0.05; β = 0.172, P < 0.05). WM-PVS size was associated with diabetes (β = 0.165, P < 0.05). WM-PVS and BG-PVS were associated with CSVD markers, especially white matter hyperintensities (WMHs) (P < 0.05). Multiple regression analysis showed that WM/BG-PVS quantitative measures were widely associated with vascular risk factors and CSVD markers (P < 0.05). Morphological measures were associated with WMH severity in WM region and also associated with lacunes and microbleeds (P < 0.05) in BG region. Data Conclusion: These novel PVS measures may capture mild PVS alterations driven by different pathologies. Evidence Level: 2. Technical Efficacy: Stage 2.
| Original language | English |
|---|---|
| Pages (from-to) | 1326-1336 |
| Number of pages | 11 |
| Journal | Journal of Magnetic Resonance Imaging |
| Volume | 54 |
| Issue number | 4 |
| DOIs | |
| State | Published - Oct 2021 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- aging
- cerebral small vessel disease
- isotropic magnetic resonance imaging
- morphology
- perivascular spaces segmentation
- vascular risk factors
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