Skeletonized mean diffusivity and neuropsychological performance in relapsing‐remitting multiple sclerosis
Background
Peak width of Skeletonized Mean Diffusivity (PSMD), as a novel marker of white matter (WM) microstructure damage, is associated with cognitive decline in several WM pathologies (i.e., small vessel disorders). We hypothesized that markers combining alterations in whole WM could be associated with cognitive dysfunction in relapsing‐remitting multiple sclerosis (RRMS) patients.
Methods
We used PSMD based on tract‐based spatial statistics (TBSS) of diffusion tensor imaging (DTI) magnetic resonance (MR) scans. We investigated RRMS patients (
n
= 73) undergoing interferon beta (IFN‐β) therapy. In this cross‐sectional study, we investigated the association between neuropsychological data and clinical and MRI variables: PSMD, WM hypointensities, and normalized brain volume (NBV).
Results
In our cohort, 37 (50.7%) patients were recognized as cognitively impaired (CI) and 36 (49.3%) patients were cognitively normal (CN). In regression analysis, PSMD was a statistically significant contributor in the California Verbal Learning Test (CVLT) list A (
p
= 0.04) and semantic fluency (
p
= 0.036). PSMD (
p
< 0.001,
r
2
= 0.35), NBV (
p
= 0.002,
r
2
= 2.6) and WM hypointensities (
p
< 0.001,
r
2
= 0.40) were major contributors to upper extremity disability (9HPT) in the CN subgroup. A significant contributor in the majority of neuropsychological measures was education attainment.
Conclusion
We investigated PSMD as a new parameter of WM microstructure damage that is a contributor in complex cognitive tasks, CVLT performance, and semantic fluency. PSMD was a statistically significant contributor to upper extremity disability (9HPT) together with WM hypointensities and NBV. Education attainment proved to be relevant in the majority of cognitive domains. Further studies are needed to estimate PSMD relevance as a marker of CI in MS.
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Jun Yao, Yuting Xia · 2026
- Published
- May 13, 2022
- Vol/Issue
- 12(6)
- License
- View
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