Diffusion tensor imaging and cognitive speed in children with multiple sclerosis

Published:August 08, 2011DOI:



      To compare white matter (WM) integrity in children with MS and healthy children using diffusion tensor imaging (DTI), and correlate DTI findings with disease activity, lesion burden, and cognitive processing speed.


      Fractional anisotropy (FA) and mean diffusivity (MD) in normal-appearing white matter (NAWM) were measured in four corpus callosum (CC), eight hemispheric regions, and the normal-appearing thalamus of 33 children and adolescents with MS and 30 age-matched healthy controls. Images were acquired on a GE LX 1.5 T scanner. DTI parameters used were 25 directions, b=1000 s/mm2, and 5 mm slice thickness. MS patients had T2 lesion volumes and Expanded Disability Status Scale (EDSS) scores were measured; all participants underwent two speeded cognitive tasks (Visual Matching and Symbol Digit Modalities Test (SDMT)).


      MS participants displayed lower FA values in the genu (p<0.005), splenium (p<0.001) and in NAWM of bilateral parietal, temporal, and occipital lobes (p<0.001) versus controls. FA and MD in the thalamus did not differ between groups. Higher lesion volumes correlated with reduced FA in CC and hemispheric NAWM. DTI metrics did not correlate with EDSS. FA values in CC regions correlated with Visual Matching (p<0.001) and SDMT (p<0.005) in MS participants only.


      DTI analyses indicate widespread NAWM disruption in children with MS—with the degree of abnormality correlating with impaired cognitive processing speed. These findings support an early onset tissue pathology in MS and illustrate its functional consequence.


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        • Trapp B.D.
        • Peterson J.
        • Ransohoff R.M.
        • Rudick R.
        • Mork S.
        • Bo L.
        Axonal transection in the lesions of multiple sclerosis [see comments].
        N Engl J Med. 1998; 338: 278-285
        • Roosendaal S.D.
        • Geurts J.J.
        • Vrenken H.
        • Hulst H.E.
        • Cover K.S.
        • Castelijns J.A.
        • et al.
        Regional DTI differences in multiple sclerosis patients.
        Neuroimage. 2009; 44: 1397-1403
        • Hasan K.M.
        • Gupta R.K.
        • Santos R.M.
        • Wolinsky J.S.
        • Narayana P.A.
        Diffusion tensor fractional anisotropy of the normal-appearing seven segments of the corpus callosum in healthy adults and relapsing–remitting multiple sclerosis patients.
        J Magn Reson Imaging. 2005; 21: 735-743
        • Sigal T.
        • Shmuel M.
        • Mark D.
        • Gil H.
        • Anat A.
        Diffusion tensor imaging of corpus callosum integrity in multiple sclerosis: correlation with disease variables.
        J Neuroimaging. 2010; (Dec 1 [Electronic publication ahead of print])
        • Vishwas M.S.
        • Chitnis T.
        • Pienaar R.
        • Healy B.C.
        • Grant P.E.
        Tract-based analysis of callosal, projection, and association pathways in pediatric patients with multiple sclerosis: a preliminary study.
        AJNR Am J Neuroradiol. 2010; 31: 121-128
        • Absinta M.
        • Rocca M.A.
        • Moiola L.
        • Ghezzi A.
        • Milani N.
        • Veggiotti P.
        • et al.
        Brain macro- and microscopic damage in patients with paediatric MS.
        J Neurol Neurosurg Psychiatry. 2010;
        • Tortorella P.
        • Rocca M.A.
        • Mezzapesa D.M.
        • Ghezzi A.
        • Lamantia L.
        • Comi G.
        • et al.
        MRI quantification of gray and white matter damage in patients with early-onset multiple sclerosis.
        J Neurol. 2006; 253: 903-907
        • Beaulieu C.
        The basis of anisotropic water diffusion in the nervous system—a technical review.
        NMR Biomed. 2002; 15: 435-455
        • Budde M.D.
        • Kim J.H.
        • Liang H.F.
        • Russell J.H.
        • Cross A.H.
        • Song S.K.
        Axonal injury detected by in vivo diffusion tensor imaging correlates with neurological disability in a mouse model of multiple sclerosis.
        NMR Biomed. 2008; 21: 589-597
        • Basser P.J.
        • Pierpaoli C.
        Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI.
        J Magn Reson B. 1996; 111: 209-219
        • Song S.K.
        • Yoshino J.
        • Le T.Q.
        • Lin S.J.
        • Sun S.W.
        • Cross A.H.
        • et al.
        Demyelination increases radial diffusivity in corpus callosum of mouse brain.
        Neuroimage. 2005; 26: 132-140
        • Werring D.J.
        • Clark C.A.
        • Barker G.J.
        • Thompson A.J.
        • Miller D.H.
        Diffusion tensor imaging of lesions and normal-appearing white matter in multiple sclerosis.
        Neurology. 1999; 52: 1626-1632
        • Lin X.
        • Tench C.R.
        • Morgan P.S.
        • Niepel G.
        • Constantinescu C.S.
        ‘Importance sampling’ in MS: use of diffusion tensor tractography to quantify pathology related to specific impairment.
        J Neurol Sci. 2005; 237: 13-19
        • Rovaris M.
        • Iannucci G.
        • Falautano M.
        • Possa F.
        • Martinelli V.
        • Comi G.
        • et al.
        Cognitive dysfunction in patients with mildly disabling relapsing–remitting multiple sclerosis: an exploratory study with diffusion tensor MR imaging.
        J Neurol Sci. 2002; 195: 103-109
        • Benedict R.H.
        • Bruce J.
        • Dwyer M.G.
        • Weinstock-Guttman B.
        • Tjoa C.
        • Tavazzi E.
        • et al.
        Diffusion-weighted imaging predicts cognitive impairment in multiple sclerosis.
        Mult Scler. 2007; 13: 722-730
        • Amato M.P.
        • Goretti B.
        • Ghezzi A.
        • Lori S.
        • Zipoli V.
        • Portaccio E.
        • et al.
        Cognitive and psychosocial features of childhood and juvenile MS.
        Neurology. 2008; 70: 1891-1897
        • Banwell B.L.
        • Anderson P.E.
        The cognitive burden of multiple sclerosis in children.
        Neurology. 2005; 64: 891-894
        • Till C.
        • Ghassemi R.
        • Aubert-Broche B.
        • Kerbrat A.
        • Collins D.L.
        • Narayanan S.
        • et al.
        MRI correlates of cognitive impairment in childhood-onset multiple sclerosis.
        Neuropsychology. 2011; 25: 319-332
        • Polman C.H.
        • Reingold S.C.
        • Edan G.
        • Filippi M.
        • Hartung H.P.
        • Kappos L.
        • et al.
        Diagnostic criteria for multiple sclerosis: 2005 revisions to the “McDonald Criteria”.
        Ann Neurol. 2005; 58: 840-846
        • Smith S.M.
        • Jenkinson M.
        • Woolrich M.W.
        • Beckmann C.F.
        • Behrens T.E.
        • Johansen-Berg H.
        • et al.
        Advances in functional and structural MR image analysis and implementation as FSL.
        Neuroimage. 2004; 23: S208-S219
        • Jenkinson M.
        • Smith S.
        A global optimisation method for robust affine registration of brain images.
        Med Image Anal. 2001; 5: 143-156
        • Smith S.M.
        • Zhang Y.
        • Jenkinson M.
        • Chen J.
        • Matthews P.M.
        • Federico A.
        • et al.
        Accurate, robust, and automated longitudinal and cross-sectional brain change analysis.
        Neuroimage. 2002; 17: 479-489
        • Cox R.W.
        • Hyde J.S.
        Software tools for analysis and visualization of fMRI data.
        NMR Biomed. 1997; 10: 171-178
        • Chang L.C.
        • Jones D.K.
        • Pierpaoli C.
        RESTORE: robust estimation of tensors by outlier rejection.
        Magn Reson Med. 2005; 53: 1088-1095
        • Fonov V.
        • Evans A.
        • McKinstry R.C.
        • Almli C.R.
        • Collins D.
        Unbiased nonlinear average age-appropriate brain templates from birth to adulthood.
        Neuroimage. 2009; 47: S102
        • Collins D.
        • Evans A.
        ANIMAL: validation and applications of non-linear registration-based segmentation.
        Int J Pattern Recognit Artif Intell. 1997; 8: 1271-1294
        • Mabbott D.J.
        • Noseworthy M.D.
        • Bouffet E.
        • Rockel C.
        • Laughlin S.
        Diffusion tensor imaging of white matter after cranial radiation in children for medulloblastoma: correlation with IQ.
        Neuro Oncol. 2006; 8: 244-252
        • Collins D.L.
        • Neelin P.
        • Peters T.M.
        • Evans A.C.
        Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space.
        J Comput Assist Tomogr. 1994; 18: 192-205
        • Avants B.B.
        • Epstein C.L.
        • Grossman M.
        • Gee J.C.
        Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain.
        Med Image Anal. 2008; 12: 26-41
        • Francis S.
        Automatic lesion identification in MRI of multiple sclerosis patients; division of neuroscience.
        Department of Neurology and Neurosurgery, McGill University2004
        • Smith A.
        Symbol digit modalities test (SDMT).
        in: Smith A. Western Psychological Services, Los Angeles1991
        • Portaccio E.
        • Goretti B.
        • Lori S.
        • Zipoli V.
        • Centorrino S.
        • Ghezzi A.
        • et al.
        The brief neuropsychological battery for children: a screening tool for cognitive impairment in childhood and juvenile multiple sclerosis.
        Mult Scler. 2009; 15: 620-626
        • Woodcock R.
        • McGrew K.
        • Mather N.
        Woodcock–Johnson III tests of achievement.
        Itasca, IL, Riverside Publishing2001
        • Kurtzke J.F.
        Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS).
        Neurology. 1983; 33: 1444-1452
        • Filippi M.
        • Cercignani M.
        • Inglese M.
        • Horsfield M.A.
        • Comi G.
        Diffusion tensor magnetic resonance imaging in multiple sclerosis.
        Neurology. 2001; 56: 304-311
        • Stikov N.
        • Perry L.M.
        • Mezer A.
        • Rykhlevskaia E.
        • Wandell B.A.
        • Pauly J.M.
        • et al.
        Bound pool fractions complement diffusion measures to describe white matter micro and macrostructure.
        Neuroimage. 2011; 54: 1112-1121
        • Paus T.
        • Collins D.L.
        • Evans A.C.
        • Leonard G.
        • Pike B.
        • Zijdenbos A.
        Maturation of white matter in the human brain: a review of magnetic resonance studies.
        Brain Res Bull. 2001; 54: 255-266
        • Klingberg T.
        • Vaidya C.J.
        • Gabrieli J.D.
        • Moseley M.E.
        • Hedehus M.
        Myelination and organization of the frontal white matter in children: a diffusion tensor MRI study.
        Neuroreport. 1999; 10: 2817-2821
        • Schmithorst V.J.
        • Wilke M.
        • Dardzinski B.J.
        • Holland S.K.
        Correlation of white matter diffusivity and anisotropy with age during childhood and adolescence: a cross-sectional diffusion-tensor MR imaging study.
        Radiology. 2002; 222: 212-218
        • Tovar-Moll F.
        • Evangelou I.E.
        • Chiu A.W.
        • Richert N.D.
        • Ostuni J.L.
        • Ohayon J.M.
        • et al.
        Thalamic involvement and its impact on clinical disability in patients with multiple sclerosis: a diffusion tensor imaging study at 3 T.
        AJNR Am J Neuroradiol. 2009; 30: 1380-1386
        • Giorgio A.
        • Palace J.
        • Johansen-Berg H.
        • Smith S.M.
        • Ropele S.
        • Fuchs S.
        • et al.
        Relationships of brain white matter microstructure with clinical and MR measures in relapsing–remitting multiple sclerosis.
        J Magn Reson Imaging. 2010; 31: 309-316