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Neuroimaging in Multiple Sclerosis

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Neuropsychiatric Dysfunction in Multiple Sclerosis

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Abstract

Magnetic Resonance Imaging (MRI) is the principal neuroimaging technique applied to Multiple Sclerosis (MS). Since the early 1990s, conventional MRI (c-MRI) has become a fundamental tool for MS diagnosis, management and research (Miller DH, Grossman RI, Reingold SC, McFarland HF (1998) The role of magnetic resonance techniques in understanding and managing multiple sclerosis. Brain 1(121):3–24). The distinctive features of c-MRI are its high sensitivity to focal white matter (WM) lesions as well as to infraclinical disease activity which is characterized by the appearance of new lesions in the absence of signs and/or symptoms of clinical relapse. In acknowledging these properties, MS diagnostic criteria have implemented specific c-MRI criteria, so that this technique has been chosen as the main paraclinical tool for supporting and reaching MS diagnosis (McDonald WI, Compston A, Edan G, et al (2001) Recommended diagnostic criteria for multiple sclerosis: guidelines from the international panel on the diagnosis of multiple sclerosis. Ann Neurol 50:121–127; Polman CH, Reingold SC, Edan G, et al (2005) Diagnostic criteria for multiple sclerosis: 2005 revisions to the “McDonald Criteria”. Ann Neurol 58:840–846; Polman CH, Reingold SC, Banwell B, et al (2011) Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol 69(2):292–302). More recently, non-conventional MRI (nc-MRI) techniques have allowed researchers to investigate in vivo the pathophysiology of MS. These techniques have been able to confirm, or even anticipate, results of neuropathological studies showing the presence of diffuse microscopic damage outside focal WM lesions, including normal-appearing WM (NAWM) and gray matter (GM). nc-MRI-derived metrics have also prompted considerable interest since it has been shown that they correlate better with clinical disability scores than those deriving from c-MRI-derived. Finally, functional MRI (fMRI), the most recent and advanced nc-MRI technique, has made it possible to investigate mechanisms of cortical neuroplasticity in MS, reporting very promising results.

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References

  1. Miller DH, Grossman RI, Reingold SC, McFarland HF (1998) The role of magnetic resonance techniques in understanding and managing multiple sclerosis. Brain 1(121):3–24

    Article  Google Scholar 

  2. McDonald WI, Compston A, Edan G et al (2001) Recommended diagnostic criteria for multiple sclerosis: guidelines from the international panel on the diagnosis of multiple sclerosis. Ann Neurol 50:121–127

    Article  PubMed  CAS  Google Scholar 

  3. Polman CH, Reingold SC, Edan G et al (2005) Diagnostic criteria for multiple sclerosis: 2005 revisions to the “McDonald Criteria”. Ann Neurol 58:840–846

    Article  PubMed  Google Scholar 

  4. Polman CH, Reingold SC, Banwell B et al (2011) Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol 69(2):292–302

    Article  PubMed  Google Scholar 

  5. Ormerod IEC, Miller DH, McDonald WI et al (1987) The role of NMR imaging in the assessment of multiple sclerosis and isolated neurological lesions: a quantitative study. Brain 110:1579–1616

    Article  PubMed  Google Scholar 

  6. Thorpe JW, Kidd D, Moseley IF et al (1996) Spinal MRI in patients with suspected multiple sclerosis and negative brain MRI. Brain 119:709–714

    Article  PubMed  Google Scholar 

  7. Gass A, Filippi M, Rodegher ME et al (1998) Characteristics of chronic MS lesions in the cerebrum, brainstem, spinal cord, and optic nerve on T1-weighted MRI. Neurology 50:548–550

    Article  PubMed  CAS  Google Scholar 

  8. Rocca MA, Mastronardo G, Horsfield MA et al (1999) Comparison of three MR sequences for the detection of cervical cord lesions in patients with multiple sclerosis. AJNR Am J Neuroradiol 20(9):1710–1716

    PubMed  CAS  Google Scholar 

  9. Triulzi F, Scotti G (1998) Differential diagnosis of multiple sclerosis: contribution of magnetic resonance techniques. J Neurol Neurosurg Psychiatry 64(Suppl 1):S6–S14

    PubMed  Google Scholar 

  10. Pittock SJ, Lucchinetti CF (2007) The pathology of MS: new insights and potential clinical applications. Neurologist 13(2):45–56, Review

    Article  PubMed  Google Scholar 

  11. van Walderveen MA, Kamphorst W, Scheltens P et al (1998) Histopathologic correlate of hypointense lesions on T1-weighted spin-echo MRI in multiple sclerosis. Neurology 50:1282–1288

    Article  PubMed  Google Scholar 

  12. Filippi M, Paty DW, Kappos L et al (1995) Correlations between changes in disability and T2-weighted brain MRI activity in multiple sclerosis: A follow-up study. Neurology 45:255–260

    Article  PubMed  CAS  Google Scholar 

  13. Kappos L, Moeri D, Radue EW et al (1999) Predictive value of gadolinium-enhanced MRI for relapse rate and changes in disability/impairment in multiple sclerosis: a metaanalysis. Lancet 353:964–969

    Article  PubMed  CAS  Google Scholar 

  14. Barkhof F (2002) The clinico-radiological paradox in multiple sclerosis revisited. Curr Opin Neurol 15(3):239–245, Review

    Article  PubMed  Google Scholar 

  15. Kurtzke JF (1983) Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology 33(11):1444–1452

    Article  PubMed  CAS  Google Scholar 

  16. Bagnato F, Evangelou IE, Gallo A et al (2007) The effect of interferon-beta on black holes in patients with multiple sclerosis. Expert Opin Biol Ther 7(7):1079–1091, Review

    Article  PubMed  CAS  Google Scholar 

  17. Lucchinetti C, Bruck W, Parisi J et al (2000) Heterogeneity of multiple sclerosis lesions: implications for the pathogenesis of demyelination. Ann Neurol 47:707–717

    Article  PubMed  CAS  Google Scholar 

  18. Minneboo A, Uitdehaag BM, Ader HJ, Barkhof F, Polman CH, Castelijns JA (2005) Patterns of enhancing lesion evolution in multiple sclerosis are uniform within patients. Neurology 65(1):56–61

    Article  PubMed  CAS  Google Scholar 

  19. Li DK, Li MJ, Traboulsee A, Zhao G et al (2006) The use of MRI as an outcome measure in clinical trials. Adv Neurol 98:203–226, Review

    PubMed  Google Scholar 

  20. Paty DW, Li DK (1993) Interferon beta-1b is effective in relapsing-remitting multiple sclerosis. II. MRI analysis results of a multicenter, randomized, double-blind, placebo-controlled trial. UBC MS/MRI study group and the ifnb multiple sclerosis study group. Neurology 43(4):662–667

    Article  PubMed  CAS  Google Scholar 

  21. Simon JH, Jacobs LD, Campion M et al (1998) Magnetic resonance studies of intramuscular interferon beta-1a for relapsing multiple sclerosis. Ann Neurol 43:79–87

    Article  PubMed  CAS  Google Scholar 

  22. Li DKB, Paty DW, The UBC MS/MRI Analysis Research Group, PRISMS Study Group (1999) Magnetic resonance imaging results of the PRISMS trial: a randomized, double-blind, placebo-controlled study of Interferon beta-1a in relapsing-remitting multiple sclerosis. Ann Neurol 46:197–206

    Article  PubMed  CAS  Google Scholar 

  23. Comi G, Filippi M, Wolinsky JS, The European/Canadian Glatiramer Acetate Study Group (2001) European/Canadian multicenter, double blind, randomized, placebo-controlled study of the effects of glatiramer acetate on magnetic resonance imaging–measured disease activity and burden in patients with relapsing multiple sclerosis. Ann Neurol 49:290–297

    Article  PubMed  CAS  Google Scholar 

  24. Polman CH, O’Connor PW, Havrdova E et al (2006) A randomized, placebo-controlled trial of natalizumab for relapsing multiple sclerosis. N Engl J Med 354(9):899–910

    Article  PubMed  CAS  Google Scholar 

  25. Jacobs LD, Beck RW, Simon JH et al (2000) Intramuscular interferon beta-1a therapy initiated during a first demyelinating event in multiple sclerosis. N Engl J Med 343:898–904

    Article  PubMed  CAS  Google Scholar 

  26. Comi G, Filippi M, Barkhof F et al (2001) Early treatment of Multiple Sclerosis Study Group. Effect of early interferon treatment on conversion to definite multiple sclerosis: a randomised study. Lancet 357:1576–1582

    Article  PubMed  CAS  Google Scholar 

  27. Kappos L, Polman CH, Freedman MS et al (2006) Treatment with interferon beta-1b delays conversion to clinically definite and McDonald MS in patients with clinically isolated syndromes. Neurology 67:1242–1249

    Article  PubMed  CAS  Google Scholar 

  28. Comi G, Martinelli V, Rodegher M, et al (2009) PreCISe study group. Effect of glatiramer acetate on conversion to clinically definite multiple sclerosis in patients with clinically isolated syndrome (PreCISe study): A randomised, double-blind, placebo-controlled trial. Lancet 374(9700):1503–1511. Erratum. In: Lancet (2010), 375(9724):1436

    Google Scholar 

  29. Hauser SL, Waubant E, Arnold DL et al (2008) B-cell depletion with rituximab in relapsing-remitting multiple sclerosis. N Engl J Med 358(7):676–688

    Article  PubMed  CAS  Google Scholar 

  30. Bakshi R, Hutton GJ, Miller JR, Radue EW (2004) The use of magnetic resonance imaging in the diagnosis and long-term management of multiple sclerosis. Neurology 63(11 Suppl 5):S3–S11

    Article  PubMed  Google Scholar 

  31. Barkhof F, van Waesberghe JH, Filippi M et al (2001) European Study Group on Interferon beta-1b in secondary progressive multiple sclerosis. T(1) hypointense lesions in secondary progressive multiple sclerosis: effect of interferon beta-1b treatment. Brain 124(Pt 7):1396–1402

    Article  PubMed  CAS  Google Scholar 

  32. McGowan JC (1999) The physical basis of magnetization transfer imaging. Neurology 53(5 Suppl 3):S3–S7, Review

    PubMed  CAS  Google Scholar 

  33. van Buchem MA, McGowan JC, Grossman RI (1999) Magnetization transfer histogram methodology: its clinical and neuropsychological correlates. Neurology 53(5 Suppl 3):S23–S28

    PubMed  Google Scholar 

  34. Le Bihan D, Breton E, Lallemand D et al (1986) MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders. Radiology 161:401–407

    PubMed  Google Scholar 

  35. Basser PJ, Mattiello J, LeBihan D (1994) Estimation of the effective self-diffusion tensor from the NMR spin-echo. J Magn Reson B 103:247–254

    Article  PubMed  CAS  Google Scholar 

  36. Pierpaoli C, Jezzard P, Basser PJ, Barnett A et al (1996) Diffusion tensor MR imaging of the human brain. Radiology 201:637–648

    PubMed  CAS  Google Scholar 

  37. Cercignani M, Inglese M, Pagani E, Comi G et al (2001) Mean diffusivity and fractional anisotropy histograms in patients with multiple sclerosis. AJNR Am J Neuroradiol 22:952–958

    PubMed  CAS  Google Scholar 

  38. Ciccarelli O, Catani M, Johansen-Berg H, Clark C, Thompson A (2008) Diffusion-based tractography in neurological disorders: concepts, applications, and future developments. Lancet Neurol 7(8):715–727, Review

    Article  PubMed  Google Scholar 

  39. Sajja BR, Wolinsky JS, Narayana PA (2009) Proton magnetic resonance spectroscopy in multiple sclerosis. Neuroimaging Clin N Am 19:45–58, Review

    Article  PubMed  Google Scholar 

  40. Arnold DL, De Stefano N, Narayanan S, Matthews PM (2001) Axonal injury and disability in multiple sclerosis: Magnetic resonance spectroscopy as a measure of dynamic pathological change in white matter. In: Magnetic resonance spectroscopy in multiple sclerosis, Milan, Springer, pp 61–67

    Google Scholar 

  41. Sarchielli P, Presciutti O, Pelliccioli GP et al (1999) Absolute quantification of brain metabolites by proton magnetic resonance spectroscopy in normal-appearing white matter of multiple sclerosis patients. Brain 122:513–521

    Article  PubMed  Google Scholar 

  42. Ogawa S, Menon RS, Kim SG, Ugurbil K (1998) On the characteristics of functional magnetic resonance imaging of the brain. Annu Rev Biophys Biomol Struct 27:447–474

    Article  PubMed  CAS  Google Scholar 

  43. Geurts JJ, Barkhof F (2008) Grey matter pathology in multiple sclerosis. Lancet Neurol 7(9):841–851, Review

    Article  PubMed  Google Scholar 

  44. Pirko I, Lucchinetti CF, Sriram S, Bakshi R (2007) Gray matter involvement in multiple sclerosis. Neurology 68(9):634–642, Review

    Article  PubMed  Google Scholar 

  45. Nakamura K, Fisher E (2009) Segmentation of brain magnetic resonance images for measurement of gray matter atrophy in multiple sclerosis patients. Neuroimage 44(3):769–776

    Article  PubMed  Google Scholar 

  46. Fischl B, Dale AM (2000) Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proc Natl Acad Sci 97(20):11050–11055

    Article  PubMed  CAS  Google Scholar 

  47. Ashburner J, Friston KJ (2000) Voxel-based morphometry – the methods. Neuroimage 11:805–821, Review

    Article  PubMed  CAS  Google Scholar 

  48. Wattjes MP, Lutterbey GG, Gieseke J et al (2007) Double inversion recovery brain imaging at 3 T: diagnostic value in the detection of multiple sclerosis lesions. AJNR Am J Neuroradiol 28(1):54–59

    PubMed  CAS  Google Scholar 

  49. Geurts JJ, Blezer EL, Vrenken H et al (2008) Does high-field MR imaging improve cortical lesion detection in multiple sclerosis? J Neurol 255(2):183–191

    Article  PubMed  Google Scholar 

  50. Mainero C, Benner T, Radding A et al (2009) In vivo imaging of cortical pathology in multiple sclerosis using ultra-high field MRI. Neurology 73(12):941–948

    Article  PubMed  Google Scholar 

  51. Schmierer K, Parkes HG, So PW et al (2010) High field (9.4 Tesla) magnetic resonance imaging of cortical grey matter lesions in multiple sclerosis. Brain 133(Pt 3):858–867

    Article  PubMed  Google Scholar 

  52. Nelson F, Poonawalla A, Hou P et al (2008) 3D MPRAGE improves classification of cortical lesions in multiple sclerosis. Mult Scler 14(9):1214–1219

    Article  PubMed  CAS  Google Scholar 

  53. Tubridy N, Barker GJ, Macmanus DG (1998) Three-dimensional fast fluid attenuated inversion recovery (3D fast FLAIR): a new MRI sequence which increases the detectable cerebral lesion load in multiple sclerosis. Br J Radiol 71(848):840–845

    PubMed  CAS  Google Scholar 

  54. Lazeron RH, Langdon DW, Filippi M et al (2000) Neuropsychological impairment in multiple sclerosis patients: the role of (juxta)cortical lesion on FLAIR. Mult Scler 6(4):280–285

    PubMed  CAS  Google Scholar 

  55. Bakshi R, Ariyaratana S, Benedict RH, Jacobs L (2001) Fluid-attenuated inversion recovery magnetic resonance imaging detects cortical and juxtacortical multiple sclerosis lesions. Arch Neurol 58(5):742–748

    Article  PubMed  CAS  Google Scholar 

  56. Geurts JJ, Pouwels PJ, Uitdehaag BM et al (2005) Intracortical lesions in multiple sclerosis: improved detection with 3D double inversion-recovery MR imaging. Radiology 236(1):254–260

    Article  PubMed  Google Scholar 

  57. Calabrese M, De Stefano N, Atzori M et al (2007) Detection of cortical inflammatory lesions by double inversion recovery magnetic resonance imaging in patients with multiple sclerosis. Arch Neurol 64(10):1416–1422

    Article  PubMed  Google Scholar 

  58. Bagnato F, Butman JA, Gupta S et al (2006) In vivo detection of cortical plaques by MR imaging in patients with multiple sclerosis. AJNR Am J Neuroradiol 27:2161–2167

    PubMed  CAS  Google Scholar 

  59. Dale AM, Fischl B, Sereno MI (1999) Cortical surface-based analysis. I. Segmentation and surface reconstruction. Neuroimage 9(2):179–194

    Article  PubMed  CAS  Google Scholar 

  60. Dale AM, Fischl B, Sereno MI (1999) Cortical surface-based analysis. II: Inflation, flattening, and a surface-based coordinate system. Neuroimage 9(2):195–207

    Article  PubMed  Google Scholar 

  61. Fischl B, van der Kouwe A, Destrieux C et al (2004) Automatically parcellating the human cerebral cortex. Cereb Cortex 14(1):11–22

    Article  PubMed  Google Scholar 

  62. Desikan RS, Ségonne F, Fischl B et al (2006) An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 31(3):968–980

    Article  PubMed  Google Scholar 

  63. Fischl B, Salat DH, Busa E et al (2002) Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron 33(3):341–355

    Article  PubMed  CAS  Google Scholar 

  64. Van Waesberghe JH, Kamphorst W, DeGroot CJ et al (1999) Axonal loss in multiple sclerosis lesions: magnetic resonance imaging insights into substrates of disability. Ann Neurol 46:747–754

    Article  PubMed  Google Scholar 

  65. Kimura H, Grossman RI, Lenkinski RE et al (1996) Proton MR spectroscopy and magnetization transfer ratio in multiple sclerosis: correlative findings of active versus irreversible plaque disease. AJNR Am J Neuroradiol 17:1539–1547

    PubMed  CAS  Google Scholar 

  66. Loevner LA, Grossman RI, McGowan JC, Ramer KN et al (1995) Characterization of multiple sclerosis plaques with T1-weighted MR and quantitative magnetization transfer. AJNR Am J Neuroradiol 16:1473–1479

    PubMed  CAS  Google Scholar 

  67. Dousset V, Gayou A, Brochet B, Caille JM (1998) Early structural changes in acute MS lesions assessed by serial magnetization transfer studies. Neurology 51:1150–1155

    Article  PubMed  CAS  Google Scholar 

  68. Filippi M, Rocca MA, Martino G, Horsfield MA et al (1998) Magnetization transfer changes in the normal appearing white matter precede the appearance of enhancing lesions in patients with multiple sclerosis. Ann Neurol 43:809–814

    Article  PubMed  CAS  Google Scholar 

  69. Goodkin DE, Rooney WD, Sloan R, Bacchetti P et al (1998) A serial study of new MS lesions and the white matter from which they arise. Neurology 51:1689–1697

    Article  PubMed  CAS  Google Scholar 

  70. Rocca MA, Mastronardo G, Rodegher M et al (1999) Long-term changes of magnetization transfer-derived measures from patients with relapsing-remitting and secondary progressive multiple sclerosis. AJNR Am J Neuroradiol 20:821

    PubMed  CAS  Google Scholar 

  71. Werring DJ, Clark CA, Barker GJ, Thompson AJ et al (1999) Diffusion tensor imaging of lesions and normal-appearing white matter in multiple sclerosis. Neurology 52:1626–1632

    Article  PubMed  CAS  Google Scholar 

  72. Davie CA, Hawkins CP, Barker GJ, Brennan A et al (1994) Serial proton magnetic resonance spectroscopy in acute multiple sclerosis lesions. Brain 117:49–58

    Article  PubMed  Google Scholar 

  73. Narayana PA, Doyle TJ, Lai D, Wolinsky JS (1998) Serial proton resonance spectroscopic imaging, contrast-enhanced magnetic resonance imaging, and quantitative lesion volumetry in multiple sclerosis. Ann Neurol 43:56–71

    Article  PubMed  CAS  Google Scholar 

  74. De Stefano N, Matthews PM, Antel JP, Preul M, Francis G et al (1996) Chemical pathology of acute demyelinating lesions and its correlation with disability. Ann Neurol 38:901–909

    Article  Google Scholar 

  75. De Stefano N, Matthews PM, Arnold DL (1995) Reversible decreases in N-acetylaspartate after acute brain injury. Magn Reson Med 34:721–727

    Article  PubMed  Google Scholar 

  76. Fu L, Matthews PM, De Stefano N, Worsley KJ et al (1998) Imaging axonal damage of normal-appearing white matter in multiple sclerosis. Brain 121:159–166

    Article  Google Scholar 

  77. Arnold DL, Matthews PM, Francis GS, O’Connor J et al (1992) Proton magnetic resonance spectroscopic imaging for metabolic characterization of demyelinating plaques. Ann Neurol 31:235–241

    Article  PubMed  CAS  Google Scholar 

  78. Falini A, Calabrese G, Filippi M, Origgi D et al (1998) Benign versus secondary-progressive multiple sclerosis: the potential role of proton MR spectroscopy in defining the nature of disability. AJNR Am J Neuroradiol 19:223–229

    PubMed  CAS  Google Scholar 

  79. Trapp BD, Peterson J, Ransohoff RM, Rudick R et al (1998) Axonal transection in the lesions of multiple sclerosis. New Engl J Med 338:278–285

    Article  PubMed  CAS  Google Scholar 

  80. Allen IV, McKeown SR (1979) A histological, histochemical and biochemical study of the macroscopically normal white matter in multiple sclerosis. J Neurol Sci 41:81–91

    Article  PubMed  CAS  Google Scholar 

  81. Filippi M, Campi A, Dousset V et al (1995) A magnetization transfer imaging study of normal appearing white matter in multiple sclerosis. Neurology 45:478–482

    Article  PubMed  CAS  Google Scholar 

  82. Pike GB, De Stefano N, Narayanan S, Worsley KJ et al (2000) Multiple sclerosis: magnetization transfer MR imaging of white matter before lesion appearance on T2-weighted images. Radiology 215:824–830

    PubMed  CAS  Google Scholar 

  83. Filippi M, Iannucci G, Tortorella C, Minicucci L et al (1999) Comparison of MS clinical phenotypes using conventional and magnetization transfer MRI. Neurology 52:588–594

    Article  PubMed  CAS  Google Scholar 

  84. Rovaris M, Bozzali M, Santuccio G et al (2000) Relative contribution of brain and spine pathology to multiple sclerosis disability: a study with magnetisation transfer ratio analysis. J Neurol Neurosurg Psychiatry 69:723–727

    Article  PubMed  CAS  Google Scholar 

  85. Iannucci G, Tortorella C, Rovaris M et al (2000) Prognostic value of MR and MTI findings at presentation in patients with clinically isolated syndromes suggestive of MS. Am J NeuroRadiol 21:1034–1038

    PubMed  CAS  Google Scholar 

  86. Kaiser JS, Grossman RI, Polansky M et al (2000) Magnetization transfer histogram analysis of monosymptomatic episodes of neurologic dysfunction: Preliminary findings. Am J NeuroRadiol 21:1043–1047

    PubMed  CAS  Google Scholar 

  87. Traboulsee A, Dehmeshki J, Brex PA et al (2002) Normal-appearing brain tissue MTR histograms in clinically isolated syndromes suggestive of MS. Neurology 59:126–128

    Article  PubMed  CAS  Google Scholar 

  88. Gallo A, Rovaris M, Benedetti B et al (2007) A brain magnetization transfer MRI study with a clinical follow up of about four years in patients with clinically isolated syndromes suggestive of multiple sclerosis. J Neurol 254(1):78–83

    Article  PubMed  Google Scholar 

  89. Fernando KT, Tozer DJ, Miszkiel KA et al (2005) Magnetization transfer histograms in clinically isolated syndromes suggestive of multiple sclerosis. Brain 128:2911–2925

    Article  PubMed  CAS  Google Scholar 

  90. van Buchem MA, Grossman RI, Armstrong C, Polansky M et al (1998) Correlation of volumetric magnetization transfer imaging clinical data in MS. Neurology 50:1609–117

    Article  PubMed  Google Scholar 

  91. Iannucci G, Minicucci L, Rodegher M, Sormani MP et al (1999) Correlations between clinical and MRI involvement in multiple sclerosis: assessment using T(1), T(2) and MT histograms. J Neurol Sci 171(2):121–129

    Article  PubMed  CAS  Google Scholar 

  92. Cercignani M, Bozzali M, Iannucci G et al (2001) Magnetization transfer ratio and mean diffusivity of normal appearing white and grey matter from patients with multiple sclerosis. J Neurol Neurosurg Psychiatry 70:311–317

    Article  PubMed  CAS  Google Scholar 

  93. Ciccarelli O, Werring DJ, Wheeler-Kingshott CA et al (2001) Investigation of MS normal appearing brain using diffusion tensor MRI with clinical correlations. Neurology 56:926–933

    Article  PubMed  CAS  Google Scholar 

  94. Caramia F, Pantano P, Di legge S et al (2002) A longitudinal study of MR diffusion changes in normal appearing white matter of patients with early multiple sclerosis. Magn Reson Imaging 20:383–388

    Article  PubMed  Google Scholar 

  95. Gallo A, Rovaris M, Riva R, Ghezzi A et al (2005) Diffusion-tensor magnetic resonance imaging detects normal-appearing white matter damage unrelated to short-term disease activity in patients at the earliest clinical stage of multiple sclerosis. Arch Neurol 62(5):803–808

    Article  PubMed  Google Scholar 

  96. Arnold DL, Matthews PM, Francis G, Antel J (1990) Proton magnetic resonance spectroscopy of human brain in vivo in the evaluation of multiple sclerosis: assessment of the load of disease. Magn Reson Med 14:154–159

    Article  PubMed  CAS  Google Scholar 

  97. Fu L, Matthews PM, De Stefano N et al (1998) Imaging axonal damage of normal appearing white matter in multiple sclerosis. Brain 121:103–113

    Article  PubMed  Google Scholar 

  98. De Stefano N, Matthews PM, Fu L et al (1998) Axonal damage correlates with disability in patients with relapsing remitting multiple sclerosis: results of a longitudinal MR spectroscopy study. Brain 121:1469–1477

    Article  PubMed  Google Scholar 

  99. Rocca MA, Cercignani M, Iannucci G, Comi G et al (2000) Weekly diffusion-weighted imaging of normal-appearing white matter in MS. Neurology 55:882–884

    Article  PubMed  CAS  Google Scholar 

  100. Brenner RE, Munro PMG, Williams SCR, et al (1993) Abnormal neuronal mitochondria: a cause of reduction in NA in demyelinating disease. In: Proceedings of the SMRM, Amsterdam, p 281

    Google Scholar 

  101. Rovaris M, Gambini A, Gallo A et al (2005) Axonal injury in early multiple sclerosis is irreversible and independent of the short-term disease evolution. Neurology 65(10):1626–1630

    Article  PubMed  CAS  Google Scholar 

  102. De Stefano N, Narayanan S, Francis Gs et al (2001) Evidence of axonal damage in the early stages of MS and its relevance to disability. Arch Neurol 58:65–70

    Article  PubMed  Google Scholar 

  103. Fernando KT, McLean MA, Chard DT et al (2004) Elevated white matter myo-inositol in clinically isolated syndromes suggestive of multiple sclerosis. Brain 127:1361–1369

    Article  PubMed  CAS  Google Scholar 

  104. Wattjes MP, Harzheim M, Lutterbey GG et al (2008) Prognostic value of high-field proton magnetic resonance spectroscopy in patients presenting with clinically isolated syndromes suggestive of multiple sclerosis. Neuroradiology 50(2):123–129

    Article  PubMed  Google Scholar 

  105. Calabrese M, Filippi M, Rovaris M et al (2009) Evidence for relative cortical sparing in benign multiple sclerosis: a longitudinal magnetic resonance imaging study. Mult Scler 15(1):36–41

    Article  PubMed  CAS  Google Scholar 

  106. Roosendaal SD, Moraal B, Pouwels PJ et al (2009) Accumulation of cortical lesions in MS: relation with cognitive impairment. Mult Scler 15(6):708–714

    Article  PubMed  CAS  Google Scholar 

  107. Calabrese M, Agosta F, Rinaldi F et al (2009) Cortical lesions and atrophy associated with cognitive impairment in relapsing-remitting multiple sclerosis. Arch Neurol 66(9):1144–1150

    Article  PubMed  Google Scholar 

  108. Calabrese M, Rocca MA, Atzori M et al (2009) Cortical lesions in primary progressive multiple sclerosis: a 2-year longitudinal MR study. Neurology 72(15):1330–1336

    Article  PubMed  CAS  Google Scholar 

  109. Calabrese M, Rocca MA, Atzori M et al (2010) A 3-year magnetic resonance imaging study of cortical lesions in relapse-onset multiple sclerosis. Ann Neurol 67(3):376–383

    PubMed  Google Scholar 

  110. Calabrese M, Rinaldi F, Seppi D et al (2011) Cortical diffusion-tensor imaging abnormalities in multiple sclerosis: a 3-year longitudinal study. Radiology 261(3):891–898

    Article  PubMed  Google Scholar 

  111. Fisniku LK, Altmann DR, Cercignani M et al (2009) Magnetization transfer ratio abnormalities reflect clinically relevant grey matter damage in multiple sclerosis. Mult Scler 15(6):668–677

    Article  PubMed  CAS  Google Scholar 

  112. Sharma J, Zivadinov R, Jaisani Z, Fabiano AJ, Singh B, Horsfield MA, Bakshi R (2006) A magnetization transfer MRI study of deep gray matter involvement in multiple sclerosis. J Neuroimaging 16(4):302–310

    Article  PubMed  Google Scholar 

  113. Amato MP, Portaccio E, Stromillo ML et al (2008) Cognitive assessment and quantitative magnetic resonance metrics can help to identify benign multiple sclerosis. Neurology 71(9):632–638

    Article  PubMed  CAS  Google Scholar 

  114. Penny S, Khaleeli Z, Cipolotti L et al (2010) Early imaging predicts later cognitive impairment in primary progressive multiple sclerosis. Neurology 74(7):545–552

    Article  PubMed  CAS  Google Scholar 

  115. Khaleeli Z, Altmann DR, Cercignani M et al (2008) Magnetization transfer ratio in gray matter: a potential surrogate marker for progression in early primary progressive multiple sclerosis. Arch Neurol 65(11):1454–1459

    Article  PubMed  Google Scholar 

  116. Penny S, Khaleeli Z, Cipolotti L, Thompson A, Ron M (2010) Early imaging predicts later cognitive impairment in primary progressive multiple sclerosis. Neurology 74(7):545–552

    Article  PubMed  CAS  Google Scholar 

  117. Agosta F, Rovaris M, Pagani E et al (2006) Magnetization transfer MRI metrics predict the accumulation of disability 8 years later in patients with multiple sclerosis. Brain 129:2620–2627

    Article  PubMed  Google Scholar 

  118. Bozzali M, Cercignani M, Sormani MP et al (2002) Quantification of brain gray matter damage in different MS phenotypes by use of diffusion tensor MR imaging. AJNR Am J Neuroradiol 23:985–988

    PubMed  Google Scholar 

  119. Rovaris M, Bozzali M, Iannucci G et al (2002) Assessment of normal-appearing white and gray matter in patients with primary progressive multiple sclerosis: a diffusion-tensor magnetic resonance imaging study. Arch Neurol 59:1406–1412

    Article  PubMed  Google Scholar 

  120. Fabiano AJ, Sharma J, Weinstock-Guttman B et al (2003) Thalamic involvement in multiple sclerosis: a diffusion-weighted magnetic resonance imaging study. J Neuroimag 13:307–314

    Google Scholar 

  121. Hasan KM, Halphen C, Kamali A et al (2009) Caudate nuclei volume, diffusion tensor metrics, and T(2) relaxation in healthy adults and relapsing-remitting multiple sclerosis patients: implications for understanding gray matter degeneration. J Magn Reson Imaging 29(1):70–77

    Article  PubMed  Google Scholar 

  122. Oreja-Guevara C, Rovaris M, Iannucci G et al (2005) Progressive grey matter damage in patients with relapsing-remitting MS: a longitudinal diffusion tensor MRI study. Arch Neurol 62:578–584

    Article  PubMed  Google Scholar 

  123. Rovaris M, Gallo A, Valsasina P et al (2005) Short-term accrual of gray matter pathology in patients with progressive multiple sclerosis: An in vivo study using diffusion tensor MRI. Neuroimage 24:1139–1146

    Article  PubMed  Google Scholar 

  124. Rovaris M, Judica E, Gallo A et al (2006) Grey matter damage predicts the evolution of primary progressive multiple sclerosis at 5 years. Brain 129(Pt 10):2628–2634

    Article  PubMed  CAS  Google Scholar 

  125. Rovaris M, Iannucci G, Falautano M et al (2002) Cognitive dysfunction in patients with mildly disabling relapsing-remitting multiple sclerosis: an exploratory study with diffusion tensor MR imaging. J Neurol Sci 195(2):103–109

    Article  PubMed  Google Scholar 

  126. Benedict RH, Bruce J, Dwyer MG et al (2007) Diffusion-weighted imaging predicts cognitive impairment in multiple sclerosis. Mult Scler 13(6):722–730

    Article  PubMed  Google Scholar 

  127. Kapeller P, McLean MA, Griffin CM et al (2001) Preliminary evidence for neuronal damage in cortical grey matter and normal appearing white matter in short duration relapsing-remitting multiple sclerosis: a quantitative MR spectroscopic imaging study. J Neurol 248:131–138

    Article  PubMed  CAS  Google Scholar 

  128. Sarchielli P, Presciutti O, Tarduci R, Gobbi G et al (2002) Localized 1H magnetic resonance spectroscopy in mainly cortical gray matter of patients with multiple sclerosis. J Neurol 249:902–910

    Article  PubMed  CAS  Google Scholar 

  129. Chard DT, Griffin CM, McLean MA et al (2002) Brain metabolite changes in cortical grey and normal-appearing white matter in clinically early relapsing-remitting multiple sclerosis. Brain 125:2342–2352

    Article  PubMed  CAS  Google Scholar 

  130. Sharma R, Narayana PA, Wolinsky JS (2001) Grey matter abnormalities in multiple sclerosis: proton magnetic resonance spectroscopic imaging. Mult Scler 7:221–226

    PubMed  CAS  Google Scholar 

  131. Cifelli A, Arridge M, Jezzard P, Esiri MM, Palace J, Matthews PM (2002) Thalamic neurodegeneration in multiple sclerosis. Ann Neurol 52:650–653

    Article  PubMed  Google Scholar 

  132. Gonen O, Viswanathan AK, Catalaa I, Babb J et al (1998) Total brain N-acetylaspartate concentration in normal, age-grouped females: quantitation with non-echo proton NMR spectroscopy. Magn Reson Med 40:684–689

    Article  PubMed  CAS  Google Scholar 

  133. Gonen O, Catalaa I, Babb JS, Ge Y et al (2000) Total brain N-acetylaspartate: a new measure of disease load in MS. Neurology 54:15–19

    Article  PubMed  CAS  Google Scholar 

  134. Pulizzi A, Rovaris M, Judica E et al (2007) Determinants of disability in multiple sclerosis at various disease stages: a multiparametric magnetic resonance study. Arch Neurol 64(8):1163–1168

    Article  PubMed  Google Scholar 

  135. Benedetti B, Rovaris M, Rocca MA et al (2009) In-vivo evidence for stable neuroaxonal damage in the brain of patients with benign multiple sclerosis. Mult Scler 15(7):789–794

    Article  PubMed  CAS  Google Scholar 

  136. Rovaris M, Gallo A, Falini A et al (2005) Axonal injury and overall tissue loss are not related in primary progressive multiple sclerosis. Arch Neurol 62(6):898–902

    Article  PubMed  Google Scholar 

  137. De Stefano N, Matthews PM, Filippi M et al (2003) Evidence of early cortical atrophy in MS: relevance to white matter changes and disability. Neurology 60(7):1157–1162

    Article  PubMed  Google Scholar 

  138. Sanfilipo MP, Benedict RH, Sharma J et al (2005) The relationship between whole brain volume and disability in multiple sclerosis: a comparison of normalized gray vs. white matter with misclassification correction. Neuroimage 26(4):1068–1077

    Article  PubMed  Google Scholar 

  139. Zivadinov R, Leist TP (2005) Clinical-magnetic resonance imaging correlations in multiple sclerosis. J Neuroimaging 15(4 Supp):10 S–21S, Review

    Google Scholar 

  140. Tedeschi G, Lavorgna L, Russo P et al (2005) Brain atrophy and lesion load in a large population of patients with multiple sclerosis. Neurology 65(2):280–285

    Article  PubMed  CAS  Google Scholar 

  141. Valsasina P, Benedetti B, Rovaris M et al (2005) Evidence for progressive gray matter loss in patients with relapsing-remitting MS. Neurology 65(7):1126–1128

    Article  PubMed  CAS  Google Scholar 

  142. Sastre-Garriga J, Ingle GT, Chard DT et al (2005) Grey and white matter volume changes in early primary progressive multiple sclerosis: a longitudinal study. Brain 128:1454–1460

    Article  PubMed  Google Scholar 

  143. Amato MP, Bartolozzi ML, Zipoli V et al (2004) Neocortical volume decrease in relapsing-remitting MS patients with mild cognitive impairment. Neurology 63(1):89–93

    Article  PubMed  CAS  Google Scholar 

  144. Amato MP, Portaccio E, Goretti B et al (2007) Association of neocortical volume changes with cognitive deterioration in relapsing-remitting multiple sclerosis. Arch Neurol 64(8):1157–1161

    Article  PubMed  Google Scholar 

  145. Sanfilipo MP, Benedict RH, Weinstock-Guttman B et al (2006) Gray and white matter brain atrophy and neuropsychological impairment in multiple sclerosis. Neurology 66(5):685–692

    Article  PubMed  Google Scholar 

  146. Rao SM (1995) Neuropsychology of multiple sclerosis. Curr Opin Neurol 8(3):216–220

    Article  PubMed  CAS  Google Scholar 

  147. Calabrese M, Rinaldi F, Mattisi I et al (2010) Widespread cortical thinning characterizes patients with MS with mild cognitive impairment. Neurology 74(4):321–328

    Article  PubMed  CAS  Google Scholar 

  148. Bermel RA, Bakshi R, Tjoa C et al (2002) Bicaudate ratio as a magnetic resonance imaging marker of brain atrophy in multiple sclerosis. Arch Neurol 59(2):275–280

    Article  PubMed  Google Scholar 

  149. Houtchens MK, Benedict RH, Killiany R et al (2007) Thalamic atrophy and cognition in multiple sclerosis. Neurology 69(12):1213–1223

    Article  PubMed  CAS  Google Scholar 

  150. Sicotte NL, Kern KC, Giesser BS et al (2008) Regional hippocampal atrophy in multiple sclerosis. Brain 131(Pt 4):1134–1141

    Article  PubMed  CAS  Google Scholar 

  151. Krupp LB, Serafin DJ, Christodoulou C (2010) Multiple sclerosis-associated fatigue. Expert Rev Neurother 10(9):1437–1447, Review

    Article  PubMed  Google Scholar 

  152. Tedeschi G, Dinacci D, Lavorgna L et al (2007) Correlation between fatigue and brain atrophy and lesion load in multiple sclerosis patients independent of disability. J Neurol Sci 263(1–2):15–19

    Article  PubMed  Google Scholar 

  153. Bakshi R, Czarnecki D, Shaikh ZA et al (2000) Brain MRI lesions and atrophy are related to depression in multiple sclerosis. Neuroreport 11(6):1153–1158

    Article  PubMed  CAS  Google Scholar 

  154. Zorzon M, Zivadinov R, Nasuelli D et al (2002) Depressive symptoms and MRI changes in multiple sclerosis. Eur J Neurol 9(5):491–496

    Article  PubMed  CAS  Google Scholar 

  155. Feinstein A, Roy P, Lobaugh N et al (2004) Structural brain abnormalities in multiple sclerosis patients with major depression. Neurology 62(4):586–590

    Article  PubMed  CAS  Google Scholar 

  156. Ceccarelli A, Rocca MA, Pagani E et al (2008) A voxel-based morphometry study of grey matter loss in MS patients with different clinical phenotypes. Neuroimage 42(1):315–322

    Article  PubMed  Google Scholar 

  157. Morgen K, Sammer G, Courtney SM et al (2006) Evidence for a direct association between cortical atrophy and cognitive impairment in relapsing-remitting MS. Neuroimage 30(3):891–898

    Article  PubMed  Google Scholar 

  158. Sepulcre J, Masdeu JC, Goñi J et al (2009) Fatigue in multiple sclerosis is associated with the disruption of frontal and parietal pathways. Mult Scler 15(3):337–344

    Article  PubMed  CAS  Google Scholar 

  159. Andreasen AK, Jakobsen J, Soerensen L et al (2010) Regional brain atrophy in primary fatigued patients with multiple sclerosis. Neuroimage 50(2):608–615

    Article  PubMed  CAS  Google Scholar 

  160. Chen JT, Narayanan S, Collins DL et al (2004) Relating neocortical pathology to disability progression in multiple sclerosis using MRI. Neuroimage 23(3):1168–1175

    Article  PubMed  CAS  Google Scholar 

  161. Charil A, Dagher A, Lerch JP et al (2007) Focal cortical atrophy in multiple sclerosis: Relation to lesion load and disability. Neuroimage 34(2):509–517

    Article  PubMed  Google Scholar 

  162. Ramasamy DP, Benedict RH, Cox JL et al (2009) Extent of cerebellum, subcortical and cortical atrophy in patients with MS: A case–control study. J Neurol Sci 282(1–2):47–54

    Article  PubMed  Google Scholar 

  163. Calabrese M, Atzori M, Bernardi V et al (2007) Cortical atrophy is relevant in multiple sclerosis at clinical onset. J Neurol 254(9):1212–1220

    Article  PubMed  Google Scholar 

  164. Pellicano C, Gallo A, Li X et al (2010) Relationship of cortical atrophy to fatigue in patients with multiple sclerosis. Arch Neurol 67(4):447–453

    Article  PubMed  Google Scholar 

  165. Filippi M, Rocca MA (2009) Functional MR imaging in multiple sclerosis. Neuroimaging Clin N Am 19(1):59–70, Review

    Article  PubMed  Google Scholar 

  166. Genova HM, Sumowski JF, Chiaravalloti N et al (2009) Cognition in multiple sclerosis: a review of neuropsychological and fMRI research. Front Biosci 14:1730–1744, Review

    Article  PubMed  CAS  Google Scholar 

  167. Fox MD, Raichle ME (2007) Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat Rev Neurosci 8(9):700–711, Review

    Article  PubMed  CAS  Google Scholar 

  168. Damoiseaux JS, Rombouts SA, Barkhof F et al (2006) Consistent resting-state networks across healthy subjects. Proc Natl Acad Sci USA 103(37):13848–13853

    Article  PubMed  CAS  Google Scholar 

  169. Raichle ME, MacLeod AM, Snyder AZ et al (2001) A default mode of brain function. Proc Natl Acad Sci USA 98:676–682

    Article  PubMed  CAS  Google Scholar 

  170. Greicius MD, Krasnow B, Reiss AL et al (2003) Functional connectivity in the resting brain: A network analysis of the default mode hypothesis. Proc Natl Acad Sci USA 100(1):253–258

    Article  PubMed  CAS  Google Scholar 

  171. Vanhaudenhuyse A, Noirhomme Q, Tshibanda LJ et al (2010) Default network connectivity reflects the level of consciousness in non-communicative brain-damaged patients. Brain 133(Pt1):161–171

    Article  PubMed  Google Scholar 

  172. Rocca MA, Valsasina P, Absinta M et al (2010) Default-mode network dysfunction and cognitive impairment in progressive MS. Neurology 74(16):1252–1259

    Article  PubMed  CAS  Google Scholar 

  173. Bonavita S, Gallo A, Sacco R et al (2011) Distributed changes in default-mode resting-state connectivity in multiple sclerosis. Mult Scler 17(4):411–422

    Article  PubMed  Google Scholar 

  174. Roosendaal SD, Schoonheim MM, Hulst HE et al (2010) Resting state networks change in clinically isolated syndrome. Brain 133(Pt 6):1612–1621

    Article  PubMed  Google Scholar 

  175. Schoonheim MM, Geurts JJ, Barkhof F (2010) The limits of functional reorganization in multiple sclerosis. Neurology 74(16):1246–7

    Article  PubMed  Google Scholar 

  176. Prinster A, Quarantelli M, Orefice G et al (2006) Grey matter loss in relapsing-remitting multiple sclerosis: A voxel-based morphometry study. Neuroimage 29(3):859–867

    Article  PubMed  CAS  Google Scholar 

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Authors and Affiliations

  1. Istituto di Scienze Neurologiche, Seconda Università di Napoli, Naples, Italy

    Prof./Director Gioacchino Tedeschi, Dr. Renato Docimo, Dr. Alvino Bisecco & Dr. Antonio Gallo Ph.D.

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  1. Prof./Director Gioacchino Tedeschi
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  2. Dr. Renato Docimo
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  3. Dr. Alvino Bisecco
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  4. Dr. Antonio Gallo Ph.D.
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  1. IRCCS, Fondazione Santa Lucia, Via Ardeatina 306, Roma, 00179, Italy

    Ugo Nocentini

  2. IRCCS, Fondazione Santa Lucia, Via Ardeatina 306, Roma, 00179, Italy

    Carlo Caltagirone

  3. Istituto di Scienze, Neurologiche, Seconda Univ. di Napoli, Via Pansini 5, Napoli, 80131, Italy

    Gioacchino Tedeschi

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Tedeschi, G., Docimo, R., Bisecco, A., Gallo, A. (2013). Neuroimaging in Multiple Sclerosis. In: Nocentini, U., Caltagirone, C., Tedeschi, G. (eds) Neuropsychiatric Dysfunction in Multiple Sclerosis. Springer, Milano. https://doi.org/10.1007/978-88-470-2676-6_8

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