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The effect of morphological and microstructural integrity of the corpus callosum on cognition, fatigue and depression in mildly disabled MS patients

This publication appears in: Magnetic Resonance Imaging

Authors: J. Van Schependom, J. Gielen, J. Laton, G. Sotiropoulos, A. Vanbinst, J. De Mey, D. Smeets and G. Nagels

Volume: 40

Pages: 109-114

Publication Date: Jul. 2017


Abstract:

Aim To assess the value of callosal morphological and microstructural integrity in assessing different cognitive domains, fatigue and depression in mildly disabled multiple sclerosis (MS) patients.MATERIALS AND METHODS: We assessed 29 mildly disabled MS patients and 15 healthy controls using 3T magnetic resonance images (T1-weighted, FLAIR and DTI) and neuropsychological tests assessing different cognitive functions, depression and fatigue. We compared the added value of morphological measures (corpus callosum area corrected for total intracranial volume, index, circularity and the more detailed thickness profile) and diffusion features (fractional anisotropy and mean diffusivity) in multilinear models including standard clinical and whole-brain parameters in assessing neuropsychological scores.RESULTS: Even in mildly disabled MS patients, a significant reduction of the corpus callosum (p<0.001) was observed in comparison to healthy controls. Callosal area, index and circularity were significantly (p<0.002) related to whole-brain white matter volume, T2 lesion load and deep grey matter volume, but not with cortical grey matter. The combination of commonly used imaging and clinical parameters explained between 7% (Fatigue) and 50% (processing speed, verbal memory) of the adjusted variance. Inclusion of the mean diffusivity increased the adjusted R(2) significantly to 69% (p=0.004) and 71% (p=0.002) for visuospatial and verbal memory respectively.CONCLUSION: Our results show that callosal features may be used as an alternative to measuring whole-brain volumes. Furthermore, the microstructural integrity of the corpus callosum can help to predict an MS patient's memory performance.

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jvansche@etrovub.be

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