Multi-parametric structural magnetic resonance imaging in relation to cognitive dysfunction in long-standing multiple sclerosis. (April 2016)

• Record Type: Journal Article
• Authors: Daams, Marita; Steenwijk, Martijn D; Schoonheim, Menno M; Wattjes, Mike P; Balk, Lisanne J; Tewarie, Prejaas K; Killestein, Joep; Uitdehaag, Bernard MJ; Geurts, Jeroen JG; Barkhof, Frederik
• Is Part Of: Multiple sclerosis. Volume 22:Number 5(2016)
• Page Start: 608
• Page End: 619
• Publication Date: 2016-04
• Subjects: Multiple sclerosis -- magnetic resonance imaging -- cognition; Central nervous system -- Diseases -- Periodicals; Myelin sheath -- Diseases -- Periodicals; Inflammation -- Periodicals; Multiple sclerosis -- Periodicals; Central Nervous System Diseases -- Periodicals; Demyelinating Diseases -- Periodicals; Inflammation -- Periodicals; Multiple Sclerosis -- Periodicals; Système nerveux central -- Maladies -- Périodiques; Gaine de myéline -- Maladies -- Périodiques; Inflammation (Pathologie) -- Périodiques; Sclérose en plaques -- Périodiques; Electronic journals; 616.834005
• DOI: 10.1177/1352458515596598
• Languages: English
• ISSNs: 1352-4585

Abstract

Background: Cognitive deficits are common in multiple sclerosis. Most previous studies investigating the imaging substrate of cognitive deficits in multiple sclerosis included patients with relatively short disease durations and were limited to one modality/brain region. Objective: To identify the strongest neuroimaging predictors for cognitive dysfunction in a large cohort of patients with long-standing multiple sclerosis. Methods: Extensive neuropsychological testing and multimodal 3.0T MRI was performed in 202 patients with multiple sclerosis and 52 controls. Cognitive scores were compared between groups using Z -scores. Whole-brain, white matter, grey matter, deep grey matter and lesion volumes; cortical thickness, (juxta)cortical and cerebellar lesions; and extent and severity of diffuse white matter damage were measured. Stepwise linear regression was used to identify the strongest predictors for cognitive dysfunction. Results: All cognitive domains were affected in patients. Patients showed extensive atrophy, focal pathology and damage in up to 75% of the investigated white matter. Associations between imaging markers and average cognition were two times stronger in cognitively impaired patients than in cognitively preserved patients. The final model for average cognition consisted of deep grey matter DGMV volume and fractional anisotropy severity (adjusted R ²=0.490; p <0.001). Conclusion: From all imaging markers, deep grey matter atrophy and diffuse white matter damage emerged as the strongest predictors for cognitive dysfunction in long-standing multiple sclerosis.