ABSTRACT
Background and Purpose
Cognitive impairment is common and disabling in multiple sclerosis (MS), yet poorly explained by lesion burden. This study aimed to determine whether the indirect impact of lesions, quantified through disconnectomes, explains multidomain cognitive deficits more effectively than lesion load, and to identify specific white matter tracts underlying these deficits.
Methods
Thirty adults with MS completed the Brief International Cognitive Assessment for MS, covering processing speed (Symbol Digit Modalities Test; SDMT), verbal memory (California Verbal Learning Test-II; CVLT-II), and visuospatial memory (Brief Visuospatial Memory Test–Revised; BVMT-R). Lesions were segmented using 3 Tesla fluid-attenuated inversion recovery images and used to estimate tract-specific disconnections and generate voxel-wise disconnectome maps. Tract-specific and voxel-wise analyses were used to identify disconnection patterns associated with cognitive performance.
Results
Cognition was impaired across all domains (all p < 0.001). Disconnectome volume was a significant independent determinant of cognitive performance (β = –0.41, p = 0.004), whereas lesion volume was not. Tract-specific analyses revealed distinct disconnection patterns: slower SDMT was associated with left cingulum posterior (β = −0.310, 95% confidence interval [CI] [−0.599, −0.021]); poorer CVLT-II with left arcuate fasciculus (β = −0.232, 95% CI [−0.435, −0.030]); and lower BVMT-R with right cingulum posterior (β = −0.218, 95% CI [−0.383, −0.054]). Voxel-wise analyses identified where the strongest associations between disconnectomes and cognitive performance were located.
Conclusion
Lesion-driven disconnection is a more robust determinant of cognitive impairment in MS than lesion burden alone, and disconnectome mapping may help understand the indirect network-level mechanisms underlying cognitive deficits in MS.
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Background and Purpose
Cognitive impairment is common and disabling in multiple sclerosis (MS), yet poorly explained by lesion burden. This study aimed to determine whether the indirect impact of lesions, quantified through disconnectomes, explains multidomain cognitive deficits more effectively than lesion load, and to identify specific white matter tracts underlying these deficits.
Methods
Thirty adults with MS completed the Brief International Cognitive Assessment for MS, covering processing speed (Symbol Digit Modalities Test; SDMT), verbal memory (California Verbal Learning Test-II; CVLT-II), and visuospatial memory (Brief Visuospatial Memory Test–Revised; BVMT-R). Lesions were segmented using 3 Tesla fluid-attenuated inversion recovery images and used to estimate tract-specific disconnections and generate voxel-wise disconnectome maps. Tract-specific and voxel-wise analyses were used to identify disconnection patterns associated with cognitive performance.
Results
Cognition was impaired across all domains (all p < 0.001). Disconnectome volume was a significant independent determinant of cognitive performance (β = –0.41, p = 0.004), whereas lesion volume was not. Tract-specific analyses revealed distinct disconnection patterns: slower SDMT was associated with left cingulum posterior (β = −0.310, 95% confidence interval [CI] [−0.599, −0.021]); poorer CVLT-II with left arcuate fasciculus (β = −0.232, 95% CI [−0.435, −0.030]); and lower BVMT-R with right cingulum posterior (β = −0.218, 95% CI [−0.383, −0.054]). Voxel-wise analyses identified where the strongest associations between disconnectomes and cognitive performance were located.
Conclusion
Lesion-driven disconnection is a more robust determinant of cognitive impairment in MS than lesion burden alone, and disconnectome mapping may help understand the indirect network-level mechanisms underlying cognitive deficits in MS.
Only registered and activated users can see links., Click Here To Register...
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