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Volume and Permeability of White Matter Hyperintensity on Cognition: A DCE Imaging Study of an Older Cohort With and Without Cognitive Impairmentopen access

Authors
Lim, ChangmokLee, HunwooMoon, YeonsilHan, Seol-HeuiKim, Hee JinChung, Hyun WooMoon, Won-Jin
Issue Date
May-2025
Publisher
John Wiley & Sons Inc.
Keywords
blood–brain barrier; elderly; permeability; prospective; volume; white matter hyperintensity
Citation
Journal of Magnetic Resonance Imaging, v.61, no.5, pp 2260 - 2270
Pages
11
Indexed
SCIE
SCOPUS
Journal Title
Journal of Magnetic Resonance Imaging
Volume
61
Number
5
Start Page
2260
End Page
2270
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/212193
DOI
10.1002/jmri.29631
ISSN
1053-1807
1522-2586
Abstract
Background: The impact of blood–brain barrier (BBB) leakage on white matter hyperintensity (WMH) subtypes (location) and its association with clinical factors and cognition remains unclear. Purpose: To investigate the relationship between WMH volume, permeability, clinical factors, and cognition in older individuals across the cognitive spectrum. Study Type: Prospective, cross-sectional. Subjects: A total of 193 older adults with/without cognitive impairment; 128 females; mean age 70.1 years (standard deviation 6.8). Field Strength/Sequence: 3 T, GE Dynamic contrast-enhanced, three-dimensional (3D) Magnetization-prepared rapid gradient-echo (MPRAGE T1WI), 3D fluid-attenuated inversion recovery (FLAIR). Assessment: Periventricular WMH (PWMH), deep WMH (DWMH), and normal-appearing white matter (NAWM) were segmented using FMRIB automatic segmentation tool algorithms on 3D FLAIR. Hippocampal volume and cortex volume were segmented on 3D T1WI. BBB permeability (Ktrans) and blood plasma volume (Vp) were determined using the Patlak model. Vascular risk factors and cognition were assessed. Statistical Tests: Univariate and multivariate analyses were performed to identify factors associated with WMH permeability. Logistic regression analysis assessed the association between WMH imaging features and cognition, adjusting for age, sex, apolipoprotein E4 status, education, and brain volumes. A P-value <0.05 was considered significant. Results: PWMH exhibited higher Ktrans (0.598 ± 0.509 × 10−3 minute−1) compared to DWMH (0.496 ± 0.478 × 10−3 minute−1) and NAWM (0.476 ± 0.398 × 10−3 minute−1). Smaller PWMH volume and cardiovascular disease (CVD) history were significantly associated with higher Ktrans in PWMH. In DWMH, higher Ktrans were associated with CVD history and cortical volume. In NAWM, it was linked to CVD history and dyslipidemia. Larger PWMH volume (odds ratio [OR] 1.106, confidence interval [CI]: 1.021–1.197) and smaller hippocampal volume (OR 0.069; CI: 0.019–0.253) were independently linked to worse global cognition after covariate adjustment. Data Conclusion: Elevated BBB leakage in PWMH was associated with lower PWMH volume and prior CVD history. Notably, PWMH volume, rather than permeability, was correlated with cognitive decline, suggesting that BBB leakage in WMH may be a consequence of CVD rather than indicate disease progression. Level of Evidence: 2. Technical Efficacy: Stage 3.
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