BACKGROUND AND PURPOSE: Potential differences between primary progressive and relapsing remitting multiple sclerosis are the subject of ongoing controversial discussions. The aim of this work was to determine whether and how primary-progressive and relapsing-remitting multiple sclerosis subtypes differ regarding conventional MR imaging parameters, cerebral iron deposits, and their association with clinical status. MATERIALS AND METHODS: We analyzed 24 patients with primary-progressive MS, 80 with relapsing-remitting MS, and 20 healthy controls with 1.5T MR imaging for assessment of the conventional quantitative parameters: T2 lesion load, T1 lesion load, brain parenchymal fraction, and corpus callosum volume. Quantitative susceptibility mapping was performed to estimate iron concentration in the deep gray matter. RESULTS: Decreased susceptibility within the thalamus in relapsing-remitting MS compared with primary-progressive MS was the only significant MR imaging difference between these MS subtypes. In the relapsing-remitting MS subgroup, the Expanded Disability Status Scale score was positively associated with conventional parameters reflecting white matter lesions and brain atrophy and with iron in the putamen and caudate nucleus. A positive association with putaminal iron and the Expanded Disability Status Scale score was found in primary-progressive MS. CONCLUSIONS: Susceptibility in the thalamus might provide additional support for the differentiation between primary-progressive and relapsing-remitting MS. That the Expanded Disability Status Scale score was associated with conventional MR imaging parameters and iron concentrations in several deep gray matter regions in relapsing-remitting MS, while only a weak association with putaminal iron was observed in primary-progressive MS suggests different driving forces of disability in these MS subtypes.

Department of Neurology Medical University of Graz Graz Austria

Department of Statistics and Probability University of Economics Prague Czech Republic

From the Departments of Radiology

Institute of Neuroradiology University Medicine Göttingen Göttingen Germany

Neurology Center of Clinical Neuroscience 1st Faculty of Medicine Charles University and General University Hospital Prague Prague Czech Republic

Zobrazit více v PubMed

Raz E, Branson B, Jensen JH, et al. . Relationship between iron accumulation and white matter injury in multiple sclerosis: a case-control study. J Neurol 2015;262:402–09 10.1007/s00415-014-7569-3 PubMed DOI PMC

Cobzas D, Sun H, Walsh AJ, et al. . Subcortical gray matter segmentation and voxel-based analysis using transverse relaxation and quantitative susceptibility mapping with application to multiple sclerosis. J Magn Reson Imaging 2015;42:1601–10 10.1002/jmri.24951 PubMed DOI

Stankiewicz JM, Neema M, Ceccarelli A. Iron and multiple sclerosis. Neurobiol Aging 2014;35(suppl 2):S51–58 10.1016/j.neurobiolaging.2014.03.039 PubMed DOI

Ropele S, Kilsdonk ID, Wattjes MP, et al. . Determinants of iron accumulation in deep grey matter of multiple sclerosis patients. Mult Scler 2014;20:1692–98 10.1177/1352458514531085 PubMed DOI

Ropele S, de Graaf W, Khalil M, et al. . MRI assessment of iron deposition in multiple sclerosis. J Magn Reson Imaging 2011;34:13–21 10.1002/jmri.22590 PubMed DOI

Khalil M, Langkammer C, Ropele S, et al. . Determinants of brain iron in multiple sclerosis: a quantitative 3T MRI study. Neurology 2011;77:1691–97 10.1212/WNL.0b013e318236ef0e PubMed DOI

Burgetova A, Seidl Z, Krasensky J, et al. . Multiple sclerosis and the accumulation of iron in the basal ganglia: quantitative assessment of brain iron using MRI t(2) relaxometry. Eur Neurol 2010;63:136–43 10.1159/000279305 PubMed DOI

Ge Y, Jensen JH, Lu H, et al. . Quantitative assessment of iron accumulation in the deep gray matter of multiple sclerosis by magnetic field correlation imaging. AJNR Am J Neuroradiol 2007;28:1639–44 10.3174/ajnr.A0646 PubMed DOI PMC

Haider L, Simeonidou C, Steinberger G, et al. . Multiple sclerosis deep grey matter: the relation between demyelination, neurodegeneration, inflammation and iron. J Neurol Neurosurg Psychiatry 2014;85:1386–95 10.1136/jnnp-2014-307712 PubMed DOI PMC

Hametner S, Wimmer I, Haider L, et al. . Iron and neurodegeneration in the multiple sclerosis brain. Ann Neurol 2013;74:848–61 10.1002/ana.23974 PubMed DOI PMC

Khalil M, Langkammer C, Pichler A, et al. . Dynamics of brain iron levels in multiple sclerosis: a longitudinal 3T MRI study. Neurology 2015;84:2396–402 10.1212/WNL.0000000000001679 PubMed DOI

Antel J, Antel S, Caramanos Z, et al. . Primary progressive multiple sclerosis: part of the MS disease spectrum or separate disease entity? Acta Neuropathol 2012;123:627–38 10.1007/s00401-012-0953-0 PubMed DOI

Dusek P, Dezortova M, Wuerfel J. Imaging of iron. Int Rev Neurobiol 2013;110:195–239 10.1016/B978-0-12-410502-7.00010-7 PubMed DOI

Langkammer C, Schweser F, Krebs N, et al. . Quantitative susceptibility mapping (QSM) as a means to measure brain iron? A post mortem validation study. Neuroimage 2012;62:1593–99 10.1016/j.neuroimage.2012.05.049 PubMed DOI PMC

Schmalbrock P, Prakash RS, Schirda B, et al. . Basal ganglia iron in patients with multiple sclerosis measured with 7T quantitative susceptibility mapping correlates with inhibitory control. AJNR Am J Neuroradiol 2016;37:439–46 10.3174/ajnr.A4599 PubMed DOI PMC

Al-Radaideh AM, Wharton SJ, Lim SY, et al. . Increased iron accumulation occurs in the earliest stages of demyelinating disease: an ultra-high field susceptibility mapping study in clinically isolated syndrome. Mult Scler 2013;19:896–903 10.1177/1352458512465135 PubMed DOI

Wang Y, Liu T. Quantitative susceptibility mapping (QSM): decoding MRI data for a tissue magnetic biomarker. Magn Reson Med 2015;73:82–101 10.1002/mrm.25358 PubMed DOI PMC

Schweser F, Deistung A, Lehr BW, et al. . Differentiation between diamagnetic and paramagnetic cerebral lesions based on magnetic susceptibility mapping. Med Phys 2010;37:5165–78 10.1118/1.3481505 PubMed DOI

Lublin FD, Reingold SC, Cohen JA, et al. . Defining the clinical course of multiple sclerosis: the 2013 revisions. Neurology 2014;83:278–86 10.1212/WNL.0000000000000560 PubMed DOI PMC

Ho DE, Imai K, King G, et al. . MatchIt: nonparametric preprocessing for parametric causal inference. J Stat Soft 2011;42:1–28

Horakova D, Kalincik T, Dolezal O, et al. . Early predictors of non-response to interferon in multiple sclerosis. Acta Neurol Scand 2012;126:390–97 10.1111/j.1600-0404.2012.01662.x PubMed DOI

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:e50101 10.1371/journal.pone.0050101 PubMed DOI PMC

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;68:23–27 10.1159/000337683 PubMed DOI

Langkammer C, Bredies K, Poser BA, et al. . Fast quantitative susceptibility mapping using 3D EPI and total generalized variation. Neuroimage 2015;111:622–30 10.1016/j.neuroimage.2015.02.041 PubMed DOI

Yushkevich PA, Piven J, Hazlett HC, et al. . User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. Neuroimage 2006;31:1116–28 10.1016/j.neuroimage.2006.01.015 PubMed DOI

Hallgren B, Sourander P. The effect of age on the non-haemin iron in the human brain. J Neurochem 1958;3:41–51 10.1111/j.1471-4159.1958.tb12607.x PubMed DOI

Kuchling J, Ramien C, Bozin I, et al. . Identical lesion morphology in primary progressive and relapsing-remitting MS: an ultrahigh field MRI study. Mult Scler 2014;20:1866–71 10.1177/1352458514531084 PubMed DOI

Jonkman LE, Rosenthal DM, Sormani MP, et al. . Gray matter correlates of cognitive performance differ between relapsing-remitting and primary-progressive multiple sclerosis. PLoS One 2015;10:e0129380 10.1371/journal.pone.0129380 PubMed DOI PMC

Galego O, Gouveia A, Batista S, et al. . Brain atrophy and physical disability in primary progressive multiple sclerosis: a volumetric study. Neuroradiol J 2015;28:354–58 10.1177/1971400915594984 PubMed DOI PMC

Nijeholt GJ, van Walderveen MA, Castelijns JA, et al. . Brain and spinal cord abnormalities in multiple sclerosis: correlation between MRI parameters, clinical subtypes and symptoms. Brain 1998;121(pt 4):687–97 10.1093/brain/121.4.687 PubMed DOI

Hagemeier J, Heininen-Brown M, Poloni GU, et al. . Iron deposition in multiple sclerosis lesions measured by susceptibility-weighted imaging filtered phase: a case control study. J Magn Reson Imaging 2012;36:73–83 10.1002/jmri.23603 PubMed DOI

Quinn MP, Gati JS, Klassen ML, et al. . Increased deep gray matter iron is present in clinically isolated syndromes. Mult Scler Relat Disord 2014;3:194–202 10.1016/j.msard.2013.06.017 PubMed DOI

Hammond KE, Metcalf M, Carvajal L, et al. . Quantitative in vivo magnetic resonance imaging of multiple sclerosis at 7 Tesla with sensitivity to iron. Ann Neurol 2008;64:707–13 10.1002/ana.21582 PubMed DOI

Khalil M, Enzinger C, Langkammer C, et al. . Quantitative assessment of brain iron by R(2)* relaxometry in patients with clinically isolated syndrome and relapsing-remitting multiple sclerosis. Mult Scler 2009;15:1048–54 10.1177/1352458509106609 PubMed DOI

Zivadinov R, Heininen-Brown M, Schirda CV, et al. . Abnormal subcortical deep-gray matter susceptibility-weighted imaging filtered phase measurements in patients with multiple sclerosis: a case-control study. Neuroimage 2012;59:331–39 10.1016/j.neuroimage.2011.07.045 PubMed DOI

Du S, Sah SK, Zeng C, et al. . Iron deposition in the gray matter in patients with relapse-remitting multiple sclerosis: a longitudinal study using three-dimensional (3D)-enhanced T2*-weighted angiography (ESWAN). Eur J Radiol 2015;84:1325–32 10.1016/j.ejrad.2015.04.013 PubMed DOI

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;19:567–76 10.1177/1352458512459289 PubMed DOI

Modica CM, Zivadinov R, Dwyer MG, et al. . Iron and volume in the deep gray matter: association with cognitive impairment in multiple sclerosis. AJNR Am J Neuroradiol 2015;36:57–62 10.3174/ajnr.A3998 PubMed DOI PMC

Morris CM, Candy JM, Oakley AE, et al. . Histochemical distribution of non-haem iron in the human brain. Acta Anat (Basel) 1992;144:235–57 10.1159/000147312 PubMed DOI

Acosta-Cabronero J, Betts MJ, Cardenas-Blanco A, et al. . In vivo MRI mapping of brain iron deposition across the adult lifespan. J Neurosci 2016;36:364–74 10.1523/JNEUROSCI.1907-15.2016 PubMed DOI PMC

Fukunaga M, Li TQ, van Gelderen P, et al. . Layer-specific variation of iron content in cerebral cortex as a source of MRI contrast. Proc Natl Acad Sci U S A 2010;107:3834–39 10.1073/pnas.0911177107 PubMed DOI PMC

Truyen L, van Waesberghe JH, van Walderveen MA, et al. . Accumulation of hypointense lesions (“black holes”) on T1 spin-echo MRI correlates with disease progression in multiple sclerosis. Neurology 1996;47:1469–76 10.1212/WNL.47.6.1469 PubMed DOI

Di Perri C, Battaglini M, Stromillo ML, et al. . Voxel-based assessment of differences in damage and distribution of white matter lesions between patients with primary progressive and relapsing-remitting multiple sclerosis. Arch Neurol 2008;65:236–43 PubMed

Miller DH, Leary SM. Primary-progressive multiple sclerosis. Lancet Neurol 2007;6:903–12 10.1016/S1474-4422(07)70243-0 PubMed DOI

Stevenson VL, Miller DH, Rovaris M, et al. . Primary and transitional progressive MS: a clinical and MRI cross-sectional study. Neurology 1999;52:839–45 10.1212/WNL.52.4.839 PubMed DOI

Thompson AJ, Montalban X, Barkhof F, et al. . Diagnostic criteria for primary progressive multiple sclerosis: a position paper. Ann Neurol 2000;47:831–35 PubMed

Zhang Y, Metz LM, Yong VW, et al. . 3T deep gray matter T2 hypointensity correlates with disability over time in stable relapsing-remitting multiple sclerosis: a 3-year pilot study. J Neurol Sci 2010;297:76–81 10.1016/j.jns.2010.07.014 PubMed DOI

Tjoa CW, Benedict RH, Weinstock-Guttman B, et al. . MRI T2 hypointensity of the dentate nucleus is related to ambulatory impairment in multiple sclerosis. J Neurol Sci 2005;234:17–24 10.1016/j.jns.2005.02.009 PubMed DOI

Ruggieri S, Petracca M, Miller A, et al. . Association of deep gray matter damage with cortical and spinal cord degeneration in primary progressive multiple sclerosis. JAMA Neurol 2015;72:1466–74 10.1001/jamaneurol.2015.1897 PubMed DOI

Bergsland N, Horakova D, Dwyer MG, et al. . Subcortical and cortical gray matter atrophy in a large sample of patients with clinically isolated syndrome and early relapsing-remitting multiple sclerosis. AJNR Am J Neuroradiol 2012;33:1573–78 10.3174/ajnr.A3086 PubMed DOI PMC

Bermel RA, Bakshi R. The measurement and clinical relevance of brain atrophy in multiple sclerosis. Lancet Neurol 2006;5:158–70 10.1016/S1474-4422(06)70349-0 PubMed DOI

Bodini B, Battaglini M, De Stefano N, et al. . T2 lesion location really matters: a 10-year follow-up study in primary progressive multiple sclerosis. J Neurol Neurosurg Psychiatry 2011;82:72–77 10.1136/jnnp.2009.201574 PubMed DOI PMC

Ciccarelli O, Brex PA, Thompson AJ, et al. . Disability and lesion load in MS: a reassessment with MS functional composite score and 3D fast FLAIR. J Neurol 2002;249:18–24 10.1007/PL00007843 PubMed DOI

Kearney H, Rocca MA, Valsasina P, et al. . Magnetic resonance imaging correlates of physical disability in relapse onset multiple sclerosis of long disease duration. Mult Scler 2014;20:72–80 10.1177/1352458513492245 PubMed DOI PMC

Zivadinov R, Stosic M, Cox JL, et al. . The place of conventional MRI and newly emerging MRI techniques in monitoring different aspects of treatment outcome. J Neurol 2008;255(suppl 1):61–74 10.1007/s00415-008-1009-1 PubMed DOI

CSF Markers of Oxidative Stress Are Associated with Brain Atrophy and Iron Accumulation in a 2-Year Longitudinal Cohort of Early MS

Sex bias in multiple sclerosis and neuromyelitis optica spectrum disorders: How it influences clinical course, MRI parameters and prognosis

Oxidative Stress Markers in Cerebrospinal Fluid of Newly Diagnosed Multiple Sclerosis Patients and Their Link to Iron Deposition and Atrophy

Cerebral Iron Deposition in Neurodegeneration

Age-related magnetic susceptibility changes in deep grey matter and cerebral cortex of normal young and middle-aged adults depicted by whole brain analysis

Deep Gray Matter Iron Content in Neuromyelitis Optica and Multiple Sclerosis