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Association Between Diffusion Tensor Imaging Measurements and Cognitive Performances in People With Multiple Sclerosis: A Systematic Review and Meta-Analysis Publisher Pubmed



Mirmosayyeb O1 ; Yazdan Panah M2, 3 ; Vaheb S3 ; Ghoshouni H3 ; Mahmoudi F4 ; Kord R5 ; Kord A6 ; Zabeti A5 ; Shaygannejad V3, 7
Authors
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Authors Affiliations
  1. 1. Department of Neurology, Jacobs Comprehensive MS Treatment and Research Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, United States
  2. 2. Student Research Committee, Shahrekord University of Medical Sciences, Shahrekord, Iran
  3. 3. Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
  4. 4. Department of Neurology, University of Miami, Miami, 33136, FL, United States
  5. 5. Department of Neurology, University of Cincinnati, Cincinnati, OH, United States
  6. 6. Division of Interventional Radiology, Department of Radiology, University of Cincinnati, Cincinnati, OH, United States
  7. 7. Department of Neurology, Isfahan University of Medical Sciences, Isfahan, Iran

Source: Multiple Sclerosis and Related Disorders Published:2025


Abstract

Background: Alterations in structural connectivity of brain networks have been linked to complex cognitive functions in people with multiple sclerosis (PwMS). However, a definitive consensus on the optimal diffusion tensor imaging (DTI) markers as indicators of cognitive performance remains incomplete and inconclusive. This systematic review and meta-analysis aimed to explore the evidence on the correlation between DTI metrics and cognitive functions in PwMS. Methods: A comprehensive literature search was conducted across PubMed/MEDLINE, Embase, Scopus, and the Web of Science up to March 2024 to identify studies reporting the correlation between DTI metrics and cognitive functions. Cognitive function was assessed using the Symbol Digit Modalities Test (SDMT), California Verbal Learning Test (CVLT), and Brief Visuospatial Memory Test-Revised (BVMT-R). The pooled correlation coefficients were estimated using R software version 4.4.0 with the random effect model. Results: Out of 1952 studies, 38 studies on 2055 PwMS fulfilled the inclusion criteria. The meta-analysis indicated that the SDMT exhibited the greatest correlation with corpus callosum fractional anisotropy (FA) (r = 0.54, 95 % CI: 0.4 to 0.66, p-value < 0.001, I2 = 34.1 %, p-heterogeneity = 0.19) and mean diffusivity (MD) (r = -0.48, 95 % CI: 0.61 to -0.33, p-value < 0.001, I2 = 0 %, p-heterogeneity = 0.77), white matter FA (r = 0.39, 95 % CI: 0.24 to 0.52, p-value < 0.001, I2 = 0 %, p-heterogeneity = 0.1), and fornix FA (r = 0.35, 95 % CI: 0.12 to 0.54, p-value = 0.003, I2 = 50.7 %, p-heterogeneity = 0.18) and MD (r = -0.35, 95 % CI: 0.49 to -0.19, p-value < 0.001, I2 = 0 %, p-heterogeneity = 0.5). Conclusion: DTI measurements, including corpus callosum FA and MD, white matter FA, and fornix FA and MD, represent the indicators of cognitive performance in PwMS. Nonetheless, these findings warrant cautious interpretation due to the restricted kinds of cognitive tests and methodological variability across studies. © 2025 Elsevier B.V.
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