Original article| Volume 45, 102388, October 2020

Measurements of the corpus callosum index and fractional anisotropy of the corpus callosum and their cutoff values are useful to assess global brain volume loss in multiple sclerosis


      • We studied the corpus callosum (CC) index (CCI) and fractional anisotropy (FA) of the CC.
      • CCI and FA were significantly correlated with whole brain volume (BV) in MS patients.
      • We identified optimal cutoff values for the CCI and FA of the CC to categorize MS patients.
      • The cutoff values categorized MS patients into mild, moderate, or severe BV loss groups.
      • The cutoff values classified MS patients with high sensitivity and specificity.



      Recent studies suggest that parameters of the corpus callosum (CC), such as the CC index (CCI) and fractional anisotropy (FA) of the CC, may be related to the degree of brain volume loss (BVL) in MS patients; however, cutoff values that determine the degree of BVL have not been set.


      Seventy-five MS patients and 21 healthy controls (HCs) underwent volumetric MRI examinations. MS patients were also evaluated for T2 lesion load, the CCI, and FA of the CC. Among the 75 MS patients, 20 had undergone cognitive assessments with the Symbol Digit Modalities Test (SDMT). After 75 MS patients were categorized into mild, moderate, or severe BVL subgroups according to our previous report, we performed receiver operating characteristic analysis to determine the cutoff values of CCI and FA, categorizing the MS patients into the three subgroups.


      The volume of the CC was significantly reduced in MS patients compared to that in HCs. The CCI and FA were significantly associated with EDSS, disease duration, clinical phenotype, T2-lesion load, and whole brain volume. The FA was significantly correlated with the SDMT score. We identified optimal cutoff values for the CCI and FA of 0.32 (85% sensitivity, 92% specificity) and 0.39 (100% sensitivity, 92% specificity), respectively, which discriminated the severe BVL group from others, and 0.385 (84% sensitivity, 74% specificity) and 0.45 (81% sensitivity, 89% specificity), respectively, which discriminated the mild BVL group from others.


      The CCI and FA cutoff values may be useful for evaluating the degree of MS brain atrophy in clinical practice.


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        • Akaishi T.
        • Nakashima I.
        • Mugikura S.
        • Aoki M.
        • Fujihara K.
        Whole brain and grey matter volume of Japanese patients with multiple sclerosis.
        J. Neuroimmunol. 2017; 306: 68-75
        • Andersen O.
        • Hildeman A.
        • Longfils M.
        • Tedeholm H.
        • Skoog B.
        • Tian W.
        • et al.
        Diffusion tensor imaging in multiple sclerosis at different final outcomes.
        Acta Neurologica Scandinavica. 2018; 137: 165-173
        • Audoin B.
        • Ibarrola D.
        • Malikova I.
        • Soulier E.
        • Confort-Gouny S.
        • Duong M.V.
        • et al.
        Onset and underpinnings of white matter atrophy at the very early stage of multiple sclerosis–a two-year longitudinal MRI/MRSI study of corpus callosum.
        Mult. Scler. (Houndmills, Basingstoke, England). 2007; 13: 41-51
        • Azevedo C.J.
        • Cen S.Y.
        • Jaberzadeh A.
        • Zheng L.
        • Hauser S.L.
        • Pelletier D.
        Contribution of normal aging to brain atrophy in MS.
        Neurol.(R) Neuroimmunol. Neuroinflamm. 2019; 6
        • Azevedo C.J.
        • Overton E.
        • Khadka S.
        • Buckley J.
        • Liu S.
        • Sampat M.
        • et al.
        Early CNS neurodegeneration in radiologically isolated syndrome.
        Neurol.(R) Neuroimmunol. Neuroinflamm. 2015; 2: e102
        • Barone S.
        • Caligiuri M.E.
        • Valentino P.
        • Cherubini A.
        • Chiriaco C.
        • Granata A.
        • et al.
        Multimodal assessment of normal-appearing corpus callosum is a useful marker of disability in relapsing-remitting multiple sclerosis: an MRI cluster analysis study.
        J. Neurol. 2018; 265: 2243-2250
        • Branzoli F.
        • Ercan E.
        • Valabregue R.
        • Wood E.T.
        • Buijs M.
        • Webb A.
        • et al.
        Differentiating between axonal damage and demyelination in healthy aging by combining diffusion-tensor imaging and diffusion-weighted spectroscopy in the human corpus callosum at 7 T.
        Neurobiol. Aging. 2016; 47: 210-217
        • Caligiuri M.E.
        • Barone S.
        • Cherubini A.
        • Augimeri A.
        • Chiriaco C.
        • Trotta M.
        • et al.
        The relationship between regional microstructural abnormalities of the corpus callosum and physical and cognitive disability in relapsing-remitting multiple sclerosis.
        NeuroImage Clin. 2015; 7: 28-33
        • Chiang G.C.
        • Pinto S.
        • Comunale J.P.
        • Gauthier S.A.
        Gadolinium-enhancing lesions lead to decreases in white matter tract fractional anisotropy in multiple sclerosis.
        J. Neuroimaging. 2016; 26: 289-295
        • De Stefano N.
        • Airas L.
        • Grigoriadis N.
        • Mattle H.P.
        • O’Riordan J.
        • Oreja-Guevara C.
        • et al.
        Clinical relevance of brain volume measures in multiple sclerosis.
        CNS Drugs. 2014; 28: 147-156
        • Figueira F.F.
        • Santos V.S.
        • Figueira G.M.
        • Silva A.C.
        Corpus callosum index: a practical method for long-term follow-up in multiple sclerosis.
        Arquivos de neuro-psiquiatria. 2007; 65: 931-935
        • Fink F.
        • Klein J.
        • Lanz M.
        • Mitrovics T.
        • Lentschig M.
        • Hahn H.K.
        • et al.
        Comparison of diffusion tensor-based tractography and quantified brain atrophy for analyzing demyelination and axonal loss in MS.
        J. Neuroimaging. 2010; 20: 334-344
        • Fujimori J.
        • Fujihara K.
        • Ogawa R.
        • Baba T.
        • Wattjes M.
        • Nakashima I.
        Patterns of regional brain volume loss in multiple sclerosis: a cluster analysis.
        J. Neurol. 2019;
        • Goncalves L.I.
        • Dos Passos G.R.
        • Conzatti L.P.
        • Burger J.L.P.
        • Tomasi G.H.
        • Zandona M.E.
        • et al.
        Correlation between the corpus callosum index and brain atrophy, lesion load, and cognitive dysfunction in multiple sclerosis.
        Mult. Scler. Related Disord. 2018; 20: 154-158
        • Granberg T.
        • Bergendal G.
        • Shams S.
        • Aspelin P.
        • Kristoffersen-Wiberg M.
        • Fredrikson S.
        • et al.
        MRI-defined corpus callosal atrophy in multiple sclerosis: a comparison of volumetric measurements, corpus callosum area and index.
        J. Neuroimaging. 2015; 25: 996-1001
        • Granberg T.
        • Martola J.
        • Bergendal G.
        • Shams S.
        • Damangir S.
        • Aspelin P.
        • et al.
        Corpus callosum atrophy is strongly associated with cognitive impairment in multiple sclerosis: results of a 17-year longitudinal study.
        Mult. Scler. (Houndmills, Basingstoke, England). 2015; 21: 1151-1158
        • 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
        • Jain S.
        • Sima D.M.
        • Ribbens A.
        • Cambron M.
        • Maertens A.
        • Van Hecke W.
        • et al.
        Automatic segmentation and volumetry of multiple sclerosis brain lesions from MR images.
        NeuroImage. 2015; 8: 367-375
        • Kale N.
        • Agaoglu J.
        • Tanik O.
        Electrophysiological and clinical correlates of corpus callosum atrophy in patients with multiple sclerosis.
        Neurol. Res. 2010; 32: 886-890
      1. Kolasa, M., Hakulinen, U., Brander, A., Hagman, S., Dastidar, P., Elovaara, I., et al. Diffusion tensor imaging and disability progression in multiple sclerosis: a 4-year follow-up study. 2019;9(1):e01194.

        • Kuchling J.
        • Backner Y.
        • Oertel F.C.
        • Raz N.
        • Bellmann-Strobl J.
        • Ruprecht K.
        • et al.
        Comparison of probabilistic tractography and tract-based spatial statistics for assessing optic radiation damage in patients with autoimmune inflammatory disorders of the central nervous system.
        NeuroImage Clin. 2018; 19: 538-550
        • Lin X.
        • Tench C.R.
        • Morgan P.S.
        • Constantinescu C.S.
        Use of combined conventional and quantitative MRI to quantify pathology related to cognitive impairment in multiple sclerosis.
        J. Neurol. Neurosurg. Psychiatry. 2008; 79: 437-441
        • Llufriu S.
        • Blanco Y.
        • Martinez-Heras E.
        • Casanova-Molla J.
        • Gabilondo I.
        • Sepulveda M.
        • et al.
        Influence of corpus callosum damage on cognition and physical disability in multiple sclerosis: a multimodal study.
        PloS One. 2012; 7: e37167
        • Martola J.
        • Stawiarz L.
        • Fredrikson S.
        • Hillert J.
        • Bergstrom J.
        • Flodmark O.
        • et al.
        Progression of non-age-related callosal brain atrophy in multiple sclerosis: a 9-year longitudinal MRI study representing four decades of disease development.
        J. Neurol. Neurosurg. Psychiatry. 2007; 78: 375-380
        • Mesaros S.
        • Rocca M.A.
        • Riccitelli G.
        • Pagani E.
        • Rovaris M.
        • Caputo D.
        • et al.
        Corpus callosum damage and cognitive dysfunction in benign MS.
        Hum. Brain Mapping. 2009; 30: 2656-2666
        • Miller D.
        • McDonald I.
        • Smith K.
        • et al.
        Chapter 7 - The diagnosis of multiple sclerosis.
        in: Compston A Confavreux C Lassmann H McDonald I Miller D Noseworthy J McAlpine's Multiple Sclerosis. Fourth Edition. Churchill Livingstone, Edinburgh2006: 347-388
        • Ozturk A.
        • Smith S.A.
        • Gordon-Lipkin E.M.
        • Harrison D.M.
        • Shiee N.
        • Pham D.L.
        • et al.
        MRI of the corpus callosum in multiple sclerosis: association with disability.
        Mult. Scler. (Houndmills, Basingstoke, England). 2010; 16: 166-177
        • Pawlitzki M.
        • Neumann J.
        • Kaufmann J.
        • Heidel J.
        • Stadler E.
        • Sweeney-Reed C.
        • et al.
        Loss of corticospinal tract integrity in early MS disease stages.
        Neurol.(R) Neuroimmunol. Neuroinflamm. 2017; 4: e399
        • Pelletier J.
        • Suchet L.
        • Witjas T.
        • Habib M.
        • Guttmann C.R.
        • Salamon G.
        • et al.
        A longitudinal study of callosal atrophy and interhemispheric dysfunction in relapsing-remitting multiple sclerosis.
        Arch. Neurol. 2001; 58: 105-111
        • Perez-Alvarez A.I.
        • Garcia-Rua A.
        • Suarez-Santos P.
        • Castanon-Apilanez M.
        • Ameijide-Sanluis E.
        • Saiz-Ayala A.
        • et al.
        [Appraisal of cerebral atrophy in multiple sclerosis by means of the corpus callosum index].
        Revista de neurologia. 2018; 67: 417-424
        • Piccolo L.
        • Kumar G.
        • Nakashima I.
        • Misu T.
        • Kong Y.
        • Wakerley B.
        • et al.
        Multiple sclerosis in Japan appears to be a milder disease compared to the UK.
        J. Neurol. 2015; 262: 831-836
        • Pokryszko-Dragan A.
        • Banaszek A.
        • Nowakowska-Kotas M.
        • Jezowska-Jurczyk K.
        • Dziadkowiak E.
        • Gruszka E.
        • et al.
        Diffusion tensor imaging findings in the multiple sclerosis patients and their relationships to various aspects of disability.
        J. Neurol. Sci. 2018; 391: 127-133
        • Polman C.H.
        • Reingold S.C.
        • Banwell B.
        • Clanet M.
        • Cohen J.A.
        • Filippi M.
        • et al.
        Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria.
        Ann. Neurol. 2011; 69: 292-302
        • Rimkus Cde M.
        • Junqueira Tde F.
        • Lyra K.P.
        • Jackowski M.P.
        • Machado M.A.
        • Miotto E.C.
        • et al.
        Corpus callosum microstructural changes correlate with cognitive dysfunction in early stages of relapsing-remitting multiple sclerosis: axial and radial diffusivities approach.
        Mult. Scler. Int. 2011; 2011304875
        • Rocca M.A.
        • Battaglini M.
        • Benedict R.H.
        • De Stefano N.
        • Geurts J.J.
        • Henry R.G.
        • et al.
        Brain MRI atrophy quantification in MS: from methods to clinical application.
        Neurology. 2017; 88: 403-413
        • Rocca M.A.
        • Comi G.
        • Filippi M.
        The role of T1-weighted derived measures of neurodegeneration for assessing disability progression in multiple sclerosis.
        Front. Neurol. 2017; 8: 433
        • 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
        • Sampat M.P.
        • Berger A.M.
        • Healy B.C.
        • Hildenbrand P.
        • Vass J.
        • Meier D.S.
        • et al.
        Regional white matter atrophy–based classification of multiple sclerosis in cross-sectional and longitudinal data.
        AJNR Am. J. Neuroradiol. 2009; 30: 1731-1739
        • 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. 2012; 22: 33-37
        • Sormani M.P.
        • Kappos L.
        • Radue E.W.
        • Cohen J.
        • Barkhof F.
        • Sprenger T.
        • et al.
        Defining brain volume cutoffs to identify clinically relevant atrophy in RRMS.
        Mult. Scler. (Houndmills, Basingstoke, England). 2017; 23: 656-664
        • Sun P.
        • George A.
        • Perantie D.C.
        • Trinkaus K.
        • Ye Z.
        • Naismith R.T.
        • et al.
        Diffusion basis spectrum imaging provides insights into MS pathology.
        Neurol.(R) Neuroimmunol. Neuroinflamm. 2020; 7
        • Thompson A.J.
        • Banwell B.L.
        • Barkhof F.
        • Carroll W.M.
        • Coetzee T.
        • Comi G.
        • et al.
        Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria.
        Lancet Neurol. 2018; 17: 162-173
        • Van Hecke W.
        • Nagels G.
        • Leemans A.
        • Vandervliet E.
        • Sijbers J.
        • Parizel P.M.
        Correlation of cognitive dysfunction and diffusion tensor MRI measures in patients with mild and moderate multiple sclerosis.
        J. Magn. Reson. Imaging. 2010; 31: 1492-1498
        • Yaldizli O.
        • Atefy R.
        • Gass A.
        • Sturm D.
        • Glassl S.
        • Tettenborn B.
        • et al.
        Corpus callosum index and long-term disability in multiple sclerosis patients.
        J. Neurol. 2010; 257: 1256-1264
        • Yaldizli O.
        • Glassl S.
        • Sturm D.
        • Papadopoulou A.
        • Gass A.
        • Tettenborn B.
        • et al.
        Fatigue and progression of corpus callosum atrophy in multiple sclerosis.
        J. Neurol. 2011; 258: 2199-2205
        • Yaldizli O.
        • Penner I.K.
        • Frontzek K.
        • Naegelin Y.
        • Amann M.
        • Papadopoulou A.
        • et al.
        The relationship between total and regional corpus callosum atrophy, cognitive impairment and fatigue in multiple sclerosis patients.
        Mult. Sclerosis (Houndmills, Basingstoke, England). 2014; 20: 356-364
        • Zivadinov R.
        • Jakimovski D.
        • Gandhi S.
        • Ahmed R.
        • Dwyer M.G.
        • Horakova D.
        • et al.
        Clinical relevance of brain atrophy assessment in multiple sclerosis. Implications for its use in a clinical routine.
        Expert Rev. Neurotherapeut. 2016; 16: 777-793