964
Views
111
CrossRef citations to date
0
Altmetric
Review

Clinical relevance of brain atrophy assessment in multiple sclerosis. Implications for its use in a clinical routine

, , , , , , , , , & show all
Pages 777-793 | Received 18 Feb 2016, Accepted 19 Apr 2016, Published online: 13 May 2016

References

  • Frohman EM, Racke MK, Raine CS. Multiple sclerosis–the plaque and its pathogenesis. N Engl J Med. 2006;354(9):942–955.
  • Zivadinov R, Reder AT, Filippi M, et al. Mechanisms of action of disease-modifying agents and brain volume changes in multiple sclerosis. Neurology. 2008;71(2):136–144.
  • Bermel RA, Bakshi R. The measurement and clinical relevance of brain atrophy in multiple sclerosis. Lancet Neurol. 2006;5(2):158–170.
  • Jacobsen C, Hagemeier J, Myhr KM, et al. Brain atrophy and disability progression in multiple sclerosis patients: a 10-year follow-up study. J Neurol Neurosurg Psychiatry. 2014;85(10):1109–1115.
  • Miller DH, Barkhof F, Frank JA, et al. Measurement of atrophy in multiple sclerosis: pathological basis, methodological aspects and clinical relevance. Brain. 2002;125(Pt 8):1676–1695.
  • Minagar A, Barnett MH, Benedict RH, et al. The thalamus and multiple sclerosis: modern views on pathologic, imaging, and clinical aspects. Neurology. 2013;80(2):210–219.
  • De Stefano N, Airas L, Grigoriadis N, et al. Clinical relevance of brain volume measures in multiple sclerosis. CNS Drugs. 2014;28(2):147–156.
  • Fisher E, Lee JC, Nakamura K, et al. Gray matter atrophy in multiple sclerosis: a longitudinal study. Ann Neurol. 2008;64(3):255–265.
  • Popescu V, Agosta F, Hulst HE, et al. Brain atrophy and lesion load predict long term disability in multiple sclerosis. J Neurol Neurosurg Psychiatry. 2013;84(10):1082–1091.
  • Uher T, Blahova-Dusankova J, Horakova D, et al. Longitudinal MRI and neuropsychological assessment of patients with clinically isolated syndrome. J Neurol. 2014;261(9):1735–1744.
  • Fisniku LK, Chard DT, Jackson JS, et al. Gray matter atrophy is related to long-term disability in multiple sclerosis. Ann Neurol. 2008;64(3):247–254.
  • Horakova D, Cox JL, Havrdova E, et al. Evolution of different MRI measures in patients with active relapsing-remitting multiple sclerosis over 2 and 5 years: a case-control study. J Neurol Neurosurg Psychiatry. 2008;79(4):407–414.
  • Zivadinov R, Bergsland N, Dolezal O, et al. Evolution of cortical and thalamus atrophy and disability progression in early relapsing-remitting MS during 5 years. AJNR. 2013;34(10):1931–1939.
  • Calabrese M, Reynolds R, Magliozzi R, et al. Regional distribution and evolution of gray matter damage in different populations of multiple sclerosis patients. PloS One. 2015;10(8):e0135428.
  • Zivadinov R, Uher T, Hagemeier J, et al. A serial 10-year follow-up study of brain atrophy and disability progression in RRMS patients. Mult Scler. 2016. pii: 1352458516629769. [Epub ahead of print]
  • De Stefano N, Giorgio A, Battaglini M, et al. Assessing brain atrophy rates in a large population of untreated multiple sclerosis subtypes. Neurology. 2010;74(23):1868–1876.
  • Calabrese M, Rinaldi F, Mattisi I, et al. The predictive value of gray matter atrophy in clinically isolated syndromes. Neurology. 2011;77(3):257–263.
  • Zivadinov R, Havrdová E, Bergsland N, et al. Thalamic atrophy is associated with development of clinically definite multiple sclerosis. Radiology. 2013;268(3):831–841.
  • Uher T, Horakova D, Kalincik T, et al. Early magnetic resonance imaging predictors of clinical progression after 48 months in clinically isolated syndrome patients treated with intramuscular interferon beta-1a. Eur J Neurol. 2015;22(7):1113–1123.
  • Kalincik T, Vaneckova M, Tyblova M, et al. Volumetric MRI markers and predictors of disease activity in early multiple sclerosis: a longitudinal cohort study. PloS One. 2012;7(11):e50101.
  • Kalkers NF, Ameziane N, Bot JC, et al. Longitudinal brain volume measurement in multiple sclerosis: rate of brain atrophy is independent of the disease subtype. Arch Neurol. 2002;59(10):1572–1576.
  • Pagani E, Rocca MA, Gallo A, et al. Regional brain atrophy evolves differently in patients with multiple sclerosis according to clinical phenotype. AJNR. 2005;26(2):341–346.
  • Amato MP, Hakiki B, Goretti B, et al. Association of MRI metrics and cognitive impairment in radiologically isolated syndromes. Neurology. 2012;78(5):309–314.
  • Amato MP, Portaccio E, Goretti B, et al. Relevance of cognitive deterioration in early relapsing-remitting MS: a 3-year follow-up study. Mult Scler. 2010;16(12):1474–1482.
  • Bergsland N, Zivadinov R, Dwyer MG, et al. Localized atrophy of the thalamus and slowed cognitive processing speed in MS patients. Mult Scler. 2015. pii: 1352458515616204. [Epub ahead of print]
  • Houtchens MK, Benedict RH, Killiany R, et al. Thalamic atrophy and cognition in multiple sclerosis. Neurology. 2007;69(12):1213–1223.
  • Rocca MA, Morelli ME, Amato MP, et al. Regional hippocampal involvement and cognitive impairment in pediatric multiple sclerosis. Mult Scler. 2016;22(5):628–640.
  • Zivadinov R, Sepcic J, Nasuelli D, et al. A longitudinal study of brain atrophy and cognitive disturbances in the early phase of relapsing-remitting multiple sclerosis. J Neurol Neurosurg Psychiatry. 2001;70(6):773–780.
  • Sormani MP, Arnold DL, De Stefano N. Treatment effect on brain atrophy correlates with treatment effect on disability in multiple sclerosis. Ann Neurol. 2014;75(1):43–49.
  • Tsivgoulis G, Katsanos AH, Grigoriadis N, et al. The effect of disease modifying therapies on brain atrophy in patients with relapsing-remitting multiple sclerosis: a systematic review and meta-analysis. PloS One. 2015;10(3):e0116511.
  • Tsivgoulis G, Katsanos AH, Grigoriadis N, et al. The effect of disease-modifying therapies on brain atrophy in patients with clinically isolated syndrome: a systematic review and meta-analysis. Ther Adv Neurol Disord. 2015;8(5):193–202.
  • Carlos R, Seifer G, Gaston K, et al. Brain atrophy in multiple sclerosis. Am J Psychaitry Neurosci. 2015;3(3):40–49.
  • Wattjes MP, Rovira A, Miller D, et al. Evidence-based guidelines: MAGNIMS consensus guidelines on the use of MRI in multiple sclerosis–establishing disease prognosis and monitoring patients. Nat Rev Neurol. 2015;11(10):597–606.
  • Rocca MA, Valsasina P, Damjanovic D, et al. Voxel-wise mapping of cervical cord damage in multiple sclerosis patients with different clinical phenotypes. J Neurol Neurosurg Psychiatry. 2013;84(1):35–41.
  • Schlaeger R, Papinutto N, Panara V, et al. Spinal cord gray matter atrophy correlates with multiple sclerosis disability. Ann Neurol. 2014;76(4):568–580.
  • Rovira A, Wattjes MP, Tintore M, et al. Evidence-based guidelines: MAGNIMS consensus guidelines on the use of MRI in multiple sclerosis-clinical implementation in the diagnostic process. Nat Rev Neurol. 2015;11(8):471–482.
  • Traboulsee A, Simon JH, Stone L, et al. Revised recommendations of the consortium of MS centers task force for a standardized MRI protocol and clinical guidelines for the diagnosis and follow-up of multiple sclerosis. AJNR. 2016;37(3):394–401.
  • Anderson VM, Fox NC, Miller DH. Magnetic resonance imaging measures of brain atrophy in multiple sclerosis. JMRI. 2006;23(5):605–618.
  • Pirko I, Lucchinetti CF, Sriram S, et al. Gray matter involvement in multiple sclerosis. Neurology. 2007;68(9):634–642.
  • Van Munster CE, Jonkman LE, Weinstein HC, et al. Gray matter damage in multiple sclerosis: impact on clinical symptoms. Neuroscience. 2015;303:446–461.
  • Klaver R, De Vries HE, Schenk GJ, et al. Grey matter damage in multiple sclerosis: a pathology perspective. Prion. 2013;7(1):66–75.
  • Siffrin V, Vogt J, Radbruch H, et al. Multiple sclerosis - candidate mechanisms underlying CNS atrophy. Trends Neurosci. 2010;33(4):202–210.
  • Brownell B, Hughes JT. The distribution of plaques in the cerebrum in multiple sclerosis. J Neurol Neurosurg Psychiatry. 1962;25:315–320.
  • Geurts JJ, Pouwels PJ, Uitdehaag BM, et al. Intracortical lesions in multiple sclerosis: improved detection with 3D double inversion-recovery MR imaging. Radiology. 2005;236(1):254–260.
  • Kutzelnigg A, Lucchinetti CF, Stadelmann C, et al. Cortical demyelination and diffuse white matter injury in multiple sclerosis. Brain. 2005;128(Pt 11):2705–2712.
  • Bo L, Vedeler CA, Nyland H, et al. Intracortical multiple sclerosis lesions are not associated with increased lymphocyte infiltration. Mult Scler. 2003;9(4):323–331.
  • Peterson JW, Bö L, Mörk S, et al. Transected neurites, apoptotic neurons, and reduced inflammation in cortical multiple sclerosis lesions. Ann Neurol. 2001;50(3):389–400.
  • Gilmore CP, Donaldson I, Bö L, et al. Regional variations in the extent and pattern of grey matter demyelination in multiple sclerosis: a comparison between the cerebral cortex, cerebellar cortex, deep grey matter nuclei and the spinal cord. J Neurol Neurosurg Psychiatry. 2009;80(2):182–187.
  • Cifelli A, Arridge M, Jezzard P, et al. Thalamic neurodegeneration in multiple sclerosis. Ann Neurol. 2002;52(5):650–653.
  • Lucchinetti CF, Popescu BF, Bunyan RF, et al. Inflammatory cortical demyelination in early multiple sclerosis. N Engl J Med. 2011;365(23):2188–2197.
  • Vercellino M, Masera S, Lorenzatti M, et al. Demyelination, inflammation, and neurodegeneration in multiple sclerosis deep gray matter. J Neuropathol Exp Neurol. 2009;68(5):489–502.
  • Wegner C, Esiri MM, Chance SA, et al. Neocortical neuronal, synaptic, and glial loss in multiple sclerosis. Neurology. 2006;67(6):960–967.
  • Trapp BD, Peterson J, Ransohoff RM, et al. Axonal transection in the lesions of multiple sclerosis. N Engl J Med. 1998;338(5):278–285.
  • Mesaros S, Rocca MA, Absinta M, et al. Evidence of thalamic gray matter loss in pediatric multiple sclerosis. Neurology. 2008;70(13):1107–1112.
  • Lassmann H, Brück W, Lucchinetti C. Heterogeneity of multiple sclerosis pathogenesis: implications for diagnosis and therapy. Trends Mol Med. 2001;7(3):115–121.
  • Bergsland N, Laganà MM, Tavazzi E, et al. Corticospinal tract integrity is related to primary motor cortex thinning in relapsing-remitting multiple sclerosis. Mult Scler. 2015;21(14):1771–1780.
  • Molyneux PD, Kappos L, Polman C, et al. The effect of interferon beta-1b treatment on MRI measures of cerebral atrophy in secondary progressive multiple sclerosis. European Study Group on interferon beta-1b in secondary progressive multiple sclerosis. Brain. 2000;123(Pt 11):2256–2263.
  • Smith SM, Zhang Y, Jenkinson M, et al. Accurate, robust, and automated longitudinal and cross-sectional brain change analysis. NeuroImage. 2002;17(1):479–489.
  • Dwyer MG, Silva D, Bergsland N, et al. Neurological Software Tool for Reliable Atrophy Measurement (NeuroSTREAM) in Multiple Sclerosis. 68th Annual meeting of American academy of neurology; 2016 Apr 21; Vancouver. S45.005.
  • Sanfilipo MP, Benedict RHB, Sharma J, et al. The relationship between whole brain volume and disability in multiple sclerosis: A comparison of normalized gray vs. white matter with misclassification correction. NeuroImage. 2005;26:1068–1077.
  • Dell’Oglio E, Ceccarelli A, Glanz BI, et al. Quantification of global cerebral atrophy in multiple sclerosis from 3T MRI using SPM: the role of misclassification errors. J Neuroimaging. 2015;25(2):191–199.
  • Guizard N, Nakamura K, Coupé P, et al. Non-local means inpainting of MS lesions in longitudinal image processing. Front Neurosci. 2015;9:456.
  • Sdika M, Pelletier D. Nonrigid registration of multiple sclerosis brain images using lesion inpainting for morphometry or lesion mapping. Hum Brain Mapp. 2009;30(4):1060–1067.
  • Scheltens P, Pasquier F, Weerts JG, et al. Qualitative assessment of cerebral atrophy on MRI: inter- and intra-observer reproducibility in dementia and normal aging. Eur Neurol. 1997;37(2):95–99.
  • Simon JH, Li D, Traboulsee A, et al. Standardized MR imaging protocol for multiple sclerosis: consortium of MS centers consensus guidelines. AJNR. 2006;27(2):455–461.
  • Benedict RH, Bakshi R, Simon JH, et al. Frontal cortex atrophy predicts cognitive impairment in multiple sclerosis. J Neuropsychiatry Clin Neurosci. 2002;14(1):44–51.
  • Butzkueven H, Kolbe SC, Jolley DJ, et al. Validation of linear cerebral atrophy markers in multiple sclerosis. J Clin Neurosci. 2008;15(2):130–137.
  • Benedict RH, Weinstock-Guttman B, Fishman I, et al. Prediction of neuropsychological impairment in multiple sclerosis: comparison of conventional magnetic resonance imaging measures of atrophy and lesion burden. Arch Neurol. 2004;61(2):226–230.
  • Bermel RA, Bakshi R, Tjoa C, et al. Bicaudate ratio as a magnetic resonance imaging marker of brain atrophy in multiple sclerosis. Arch Neurol. 2002;59(2):275–280.
  • Martola J, Bergstrom J, Fredrikson S, et al. A longitudinal observational study of brain atrophy rate reflecting four decades of multiple sclerosis: a comparison of serial 1D, 2D, and volumetric measurements from MRI images. Neuroradiology. 2010;52(2):109–117.
  • Zivadinov R, Bakshi R. Role of MRI in multiple sclerosis II: brain and spinal cord atrophy. Front Biosci. 2004;9:647–664.
  • Grassiot B, Desgranges B, Eustache F, et al. Quantification and clinical relevance of brain atrophy in multiple sclerosis: a review. J Neurol. 2009;256(9):1397–1412.
  • Brewer JB, Magda S, Airriess C, et al. Fully-automated quantification of regional brain volumes for improved detection of focal atrophy in Alzheimer disease. AJNR. 2009;30(3):578–580.
  • Jain S, Sima DM, Ribbens A, et al. Automatic segmentation and volumetry of multiple sclerosis brain lesions from MR images. Neuroimage Clin. 2015;8:367–375.
  • Patenaude B, Smith SM, Kennedy DN, et al. A Bayesian model of shape and appearance for subcortical brain segmentation. NeuroImage. 2011;56(3):907–922.
  • Ashburner J, Friston KJ. Voxel-based morphometry–the methods. NeuroImage. 2000;11(6 Pt 1):805–821.
  • Fischl B, Dale AM. Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proc Natl Acad Sci U S A. 2000;97(20):11050–11055.
  • Zivadinov R, Cerza N, Hagemeier J, et al. Humoral response to EBV is associated with cortical atrophy and lesion burden in patients with MS. Neurology(R) Neuroimmunology & Neuroinflammation. 2016;3(1):e190.
  • Dalton CM, Chard DT, Davies GR, et al. Early development of multiple sclerosis is associated with progressive grey matter atrophy in patients presenting with clinically isolated syndromes. Brain. 2004;127(Pt 5):1101–1107.
  • Filippi M, Preziosa P, Copetti M, et al. Gray matter damage predicts the accumulation of disability 13 years later in MS. Neurology. 2013;81(20):1759–1767.
  • Schoonheim MM, Popescu V, Rueda Lopes FC, et al. Subcortical atrophy and cognition: sex effects in multiple sclerosis. Neurology. 2012;79(17):1754–1761.
  • Calabrese M, Mattisi I, Rinaldi F, et al. Magnetic resonance evidence of cerebellar cortical pathology in multiple sclerosis. J Neurol Neurosurg Psychiatry. 2010;81(4):401–404.
  • Vaneckova M, Kalincik T, Krasensky J, et al. Corpus callosum atrophy–a simple predictor of multiple sclerosis progression: a longitudinal 9-year study. Eur Neurol. 2012;68(1):23–27.
  • Anderson VM, Bartlett JW, Fox NC, et al. Detecting treatment effects on brain atrophy in relapsing remitting multiple sclerosis: sample size estimates. J Neurol. 2007;254(11):1588–1594.
  • Healy B, Valsasina P, Filippi M, et al. Sample size requirements for treatment effects using gray matter, white matter and whole brain volume in relapsing-remitting multiple sclerosis. J Neurol Neurosurg Psychiatry. 2009;80(11):1218–1223.
  • Freeborough PA, Fox NC. The boundary shift integral: an accurate and robust measure of cerebral volume changes from registered repeat MRI. IEEE Trans Med Imaging. 1997;16(5):623–629.
  • De Stefano N, Stromillo ML, Giorgio A, et al. Establishing pathological cut-offs of brain atrophy rates in multiple sclerosis. J Neurol Neurosurg Psychiatry. 2016;87(1):93–99.
  • Caramanos Z, Fonov VS, Francis SJ, et al. Gradient distortions in MRI: characterizing and correcting for their effects on SIENA-generated measures of brain volume change. NeuroImage. 2010;49(2):1601–1611.
  • Battaglini M, Smith SM, Brogi S, et al. Enhanced brain extraction improves the accuracy of brain atrophy estimation. NeuroImage. 2008;40(2):583–589.
  • Dwyer MG, Bergsland N, Zivadinov R. Improved longitudinal gray and white matter atrophy assessment via application of a 4-dimensional hidden Markov random field model. NeuroImage. 2014;90:207–217.
  • Nakamura K, Guizard N, Fonov VS, et al. Jacobian integration method increases the statistical power to measure gray matter atrophy in multiple sclerosis. Neuroimage Clin. 2014;4:10–17.
  • Vrenken H, Vos EK, Van Der Flier WM, et al. Validation of the automated method VIENA: an accurate, precise, and robust measure of ventricular enlargement. Hum Brain Mapp. 2014;35(4):1101–1110.
  • Reuter M, Schmansky N, Rosas H, et al. Within-subject template estimation for unbiased longitudinal image analysis. Neuroimage Clin. 2012;61(4):1402–1418.
  • Hagemeier J, Yeh EA, Brown MH, et al. Iron content of the pulvinar nucleus of the thalamus is increased in adolescent multiple sclerosis. Mult Scler. 2013;19(5):567–576.
  • Kerbrat A, Aubert-Broche B, Fonov V, et al. Reduced head and brain size for age and disproportionately smaller thalami in child-onset MS. Neurology. 2012;78(3):194–201.
  • Steenwijk MD, Geurts JJ, Daams M, et al. Cortical atrophy patterns in multiple sclerosis are non-random and clinically relevant. Brain. 2016;139(Pt 1):115–126.
  • Duning T, Kloska S, Steinsträter O, et al. Dehydration confounds the assessment of brain atrophy. Neurology. 2005;64(3):548–550.
  • Nakamura K, Brown RA, Araujo D, et al. Correlation between brain volume change and T2 relaxation time induced by dehydration and rehydration: implications for monitoring atrophy in clinical studies. Neuroimage Clin. 2014;6:166–170.
  • Nakamura K, Brown RA, Narayanan S, et al. Alzheimer’s disease neuroimaging I. diurnal fluctuations in brain volume: statistical analyses of MRI from large populations. NeuroImage. 2015;118:126–132.
  • Hedman AM, Van Haren NE, Schnack HG, et al. Human brain changes across the life span: a review of 56 longitudinal magnetic resonance imaging studies. Hum Brain Mapp. 2012;33(8):1987–2002.
  • Aubert-Broche B, Fonov V, Narayanan S, et al. Onset of multiple sclerosis before adulthood leads to failure of age-expected brain growth. Neurology. 2014;83(23):2140–2146.
  • Yeh EA, Weinstock-Guttman B, Ramanathan M, et al. Magnetic resonance imaging characteristics of children and adults with paediatric-onset multiple sclerosis. Brain. 2009;132(Pt 12):3392–3400.
  • Weinstock-Guttman B, Ramanathan M, Hashmi K, et al. Increased tissue damage and lesion volumes in African Americans with multiple sclerosis. Neurology. 2010;74(7):538–544.
  • Hagemann G, Ugur T, Schleussner E, et al. Changes in brain size during the menstrual cycle. PloS One. 2011;6(2):e14655.
  • Sicotte NL, Giesser BS, Tandon V, et al. Testosterone treatment in multiple sclerosis: a pilot study. Arch Neurol. 2007;64(5):683–688.
  • Kappus N, Weinstock-Guttman B, Hagemeier J, et al. Cardiovascular risk factors are associated with increased lesion burden and brain atrophy in multiple sclerosis. J Neurol Neurosurg Psychiatry. 2016;87(2):181–187.
  • Zivadinov R, Weinstock-Guttman B, Hashmi K, et al. Smoking is associated with increased lesion volumes and brain atrophy in multiple sclerosis. Neurology. 2009;73(7):504–510.
  • Durhan G, Diker S, Has AC, et al. Assessment of the effect of cigarette smoking on regional brain volumes and lesion load in patients with clinically isolated syndrome. Int J Neurosci. 2015;1–7. [Epub ahead of print]
  • Horakova D, Zivadinov R, Weinstock-Guttman B, et al. Environmental factors associated with disease progression after the first demyelinating event: results from the multi-center SET study. PloS One. 2013;8(1):e53996.
  • Weinstock-Guttman B, Zivadinov R, Horakova D, et al. Lipid profiles are associated with lesion formation over 24 months in interferon-beta treated patients following the first demyelinating event. J Neurol Neurosurg Psychiatry. 2013;84(11):1186–1191.
  • Browne RW, Weinstock-Guttman B, Horakova D, et al. Apolipoproteins are associated with new MRI lesions and deep grey matter atrophy in clinically isolated syndromes. J Neurol Neurosurg Psychiatry. 2014;85(8):859–864.
  • Bobb JF, Schwartz BS, Davatzikos C, et al. Cross-sectional and longitudinal association of body mass index and brain volume. Hum Brain Mapp. 2014;35(1):75–88.
  • Weinstock-Guttman B, Zivadinov R, Qu J, et al. Vitamin D metabolites are associated with clinical and MRI outcomes in multiple sclerosis patients. J Neurol Neurosurg Psychiatry. 2011;82(2):189–195.
  • Zivadinov R, Treu CN, Weinstock-Guttman B, et al. Interdependence and contributions of sun exposure and vitamin D to MRI measures in multiple sclerosis. J Neurol Neurosurg Psychiatry. 2013;84(10):1075–1081.
  • Romero JR, Vasan RS, Beiser AS, et al. Association of matrix metalloproteinases with MRI indices of brain ischemia and aging. Neurobiol Aging. 2010;31(12):2128–2135.
  • Enzinger C, Ropele S, Smith S, et al. Accelerated evolution of brain atrophy and “black holes” in MS patients with APOE-epsilon 4. Ann Neurol. 2004;55(4):563–569.
  • Okuda DT, Srinivasan R, Oksenberg JR, et al. Genotype-phenotype correlations in multiple sclerosis: HLA genes influence disease severity inferred by 1HMR spectroscopy and MRI measures. Brain. 2009;132(Pt 1):250–259.
  • Zivadinov R, Uxa L, Zacchi T, et al. HLA genotypes and disease severity assessed by magnetic resonance imaging findings in patients with multiple sclerosis. J Neurol. 2003;250(9):1099–1106. [Epub ahead of print].
  • Zivadinov R, Raj B, Ramanathan M, et al. Autoimmune comorbidities are associated with brain injury in multiple sclerosis. AJNR Am J Neuroradiol. 2016. [Epub ahead of print].
  • Till C, Ghassemi R, Aubert-Broche B, et al. MRI correlates of cognitive impairment in childhood-onset multiple sclerosis. Neuropsychology. 2011;25(3):319–332.
  • Zivadinov R. Steroids and brain atrophy in multiple sclerosis. J Neurol Sci. 2005;233(1–2):73–81.
  • Mellanby AR, Reveley MA. Effects of acute dehydration on computerised tomographic assessment of cerebral density and ventricular volume. Lancet. 1982;320(8303):874.
  • Badaut J, Fukuda AM, Jullienne A, et al. Aquaporin and brain diseases. Biochim Biophys Acta. 2014;1840(5):1554–1565.
  • Addolorato G, Taranto C, De Rossi G, et al. Neuroimaging of cerebral and cerebellar atrophy in anorexia nervosa. Psychiatry Res. 1997;76(2–3):139–141.
  • Dwyer MG, Zivadinov R, Tao Y, et al. Immunological and short-term brain volume changes in relapsing forms of multiple sclerosis treated with interferon beta-1a subcutaneously three times weekly: an open-label two-arm trial. BMC Neurol. 2015;15:232.
  • Wassel CL, Pankow JS, Peralta CA, et al. Genetic ancestry is associated with subclinical cardiovascular disease in African-Americans and Hispanics from the multi-ethnic study of atherosclerosis. Circ Cardiovasc Genet. 2009;2(6):629–636.
  • Chataway J, Schuerer N, Alsanousi A, et al. Effect of high-dose simvastatin on brain atrophy and disability in secondary progressive multiple sclerosis (MS-STAT): a randomised, placebo-controlled, phase 2 trial. Lancet. 2014;383(9936):2213–2221.
  • Chua AS, Egorova S, Anderson MC, et al. Handling changes in MRI acquisition parameters in modeling whole brain lesion volume and atrophy data in multiple sclerosis subjects: comparison of linear mixed-effect models. Neuroimage Clin. 2015;8:606–610.
  • Tiberio M, Chard DT, Altmann DR, et al. Gray and white matter volume changes in early RRMS: A 2-year longitudinal study. Neurology. 2005;64(6):1001–1007.
  • Vollmer T, Signorovitch J, Huynh L, et al. The natural history of brain volume loss among patients with multiple sclerosis: a systematic literature review and meta-analysis. J Neurol Sci. 2015;357(1–2):8–18.
  • Henry RG, Shieh M, Okuda DT, et al. Regional grey matter atrophy in clinically isolated syndromes at presentation. J Neurol Neurosurg Psychiatry. 2008;79(11):1236–1244.
  • Azevedo CJ, Overton E, Khadka S, et al. Early CNS neurodegeneration in radiologically isolated syndrome. Neurol Neuroimmunol Neuroinflamm. 2015;2(3):e102.
  • Okuda DT, Mowry EM, Beheshtian A, et al. Incidental MRI anomalies suggestive of multiple sclerosis: the radiologically isolated syndrome. Neurology. 2009;72(9):800–805.
  • Rocca MA, Mesaros S, Pagani E, et al. Thalamic damage and long-term progression of disability in multiple sclerosis. Radiology. 2010;257(2):463–469.
  • Rojas JI, Patrucco L, Míguez J, et al. Brain atrophy in radiologically isolated syndromes. J Neuroimaging. 2015;25(1):68–71.
  • Uher T, Horakova D, Bergsland N, et al. MRI correlates of disability progression in patients with CIS over 48 months. Neuroimage Clin. 2014;6:312–319.
  • Lukas C, Minneboo A, De Groot V, et al. Early central atrophy rate predicts 5 year clinical outcome in multiple sclerosis. J Neurol Neurosurg Psychiatry. 2010;81(12):1351–1356.
  • Rojas JI, Patrucco L, Besada C, et al. Brain atrophy at onset and physical disability in multiple sclerosis. Arq Neuropsiquiatr. 2012;70(10):765–768.
  • Horakova D, Kalincik T, Dusankova JB, et al. Clinical correlates of grey matter pathology in multiple sclerosis. BMC Neurol. 2012;12:10.
  • Geurts JJ, Calabrese M, Fisher E, et al. Measurement and clinical effect of grey matter pathology in multiple sclerosis. Lancet Neurol. 2012;11(12):1082–1092.
  • Mesaros S, Rocca MA, Sormani MP, et al. Clinical and conventional MRI predictors of disability and brain atrophy accumulation in RRMS. A large scale, short-term follow-up study. J Neurol. 2008;255(9):1378–1383.
  • Sastre-Garriga J, Ingle GT, Chard DT, et al. Grey and white matter volume changes in early primary progressive multiple sclerosis: a longitudinal study. Brain. 2005;128(Pt 6):1454–1460.
  • Banwell B, Giovannoni G, Hawkes C, et al. Editors’ welcome and a working definition for a multiple sclerosis cure. Mult Scler Relat Disord. 2013;2(2):65–67.
  • Kappos L, De Stefano N, Freedman MS, et al. Inclusion of brain volume loss in a revised measure of ‘no evidence of disease activity’ (NEDA-4) in relapsing-remitting multiple sclerosis. Mult Scler. 2015. pii: 1352458515616701. [Epub ahead of print]
  • Bakshi R, Neema M, Tauhid S, et al. An expanded composite scale of MRI-defined disease severity in multiple sclerosis: MRDSS2. Neuroreport. 2014;25(14):1156–1161.
  • Sumowski JF, Rocca MA, Leavitt VM, et al. Brain reserve and cognitive reserve protect against cognitive decline over 4.5 years in MS. Neurology. 2014;82(20):1776–1783.
  • Uher T, Benedict RH, Horakova D, et al. Relationship between gray matter volume and cognitive learning in CIS patients on disease-modifying treatment. J Neurol Sci. 2014;347(1–2):229–234.
  • Summers M, Fisniku L, Anderson V, et al. Cognitive impairment in relapsing-remitting multiple sclerosis can be predicted by imaging performed several years earlier. Mult Scler. 2008;14(2):197–204.
  • Sumowski JF, Rocca MA, Leavitt VM, et al. Brain reserve and cognitive reserve in multiple sclerosis: what you’ve got and how you use it. Neurology. 2013;80(24):2186–2193.
  • Bergendal G, Martola J, Stawiarz L, et al. Callosal atrophy in multiple sclerosis is related to cognitive speed. Acta Neurol Scand. 2013;127(4):281–289.
  • Branger P, Parienti -J-J, Sormani MP, et al. The effect of disease-modifying drugs on brain atrophy in relapsing-remitting multiple sclerosis: a meta-analysis. PloS One. 2016;11(3):e0149685.
  • Chen JT, Collins DL, Atkins HL, et al. Brain atrophy after immunoablation and stem cell transplantation in multiple sclerosis. Neurology. 2006;66(12):1935–1937.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.