Skip to main content
Log in

Diagnose der Multiplen Sklerose: Revision der McDonald-Kriterien 2017

Diagnosis of multiple sclerosis: revision of the McDonald criteria 2017

  • Übersichten
  • Published:
Der Nervenarzt Aims and scope Submit manuscript

Zusammenfassung

Die Diagnose der Multiplen Sklerose (MS) stützt sich auf zwei Pfeiler: 1) den Nachweis einer örtlichen und zeitlichen Dissemination der fokal-neurologischen Defizite, 2) den Ausschluss wichtiger Differenzialdiagnosen. Auch die aktuelle Revision der Diagnosekriterien – McDonald 2017 – folgt diesen Prinzipien, berücksichtigt neue Daten zur MRT-Bildgebung und stärkt die (zuletzt eingeschränkte) Rolle der Liquordiagnostik bei der schubförmigen Verlaufsform. Übergeordnetes Ziel bleibt die möglichst frühe zuverlässige Diagnosestellung zwecks zeitnahem Start einer verlaufsmodifizierenden Therapie. Zu den konkreten Neuerungen gehören die Berücksichtigung kortikaler MRT-Läsionen (äquivalent zu juxtakortikalen Herden), die aufgehobene Differenzierung zwischen asymptomatischen und symptomatischen MRT-Läsionen und die Berücksichtigung charakteristischer Liquorbefunde für das Kriterium der zeitlichen Dissemination. So lässt sich bereits bei einem ersten Schub mit der Detektion liquorspezifischer oligoklonaler Bande sowie dem MRT-Nachweis einer MS-typischen örtlichen Läsionsverteilung (auch ohne Schrankenstörung) eine MS diagnostizieren. Für die primär-progrediente Verlaufsform, für die mittlerweile auch eine erste Therapieoption existiert, bleibt die bekannte Definition bestehen. Hinsichtlich der Differenzialdiagnostik erfolgt eine klare Abgrenzung gegenüber den mittlerweile als NMO-Spektrum-Erkrankungen (NMOSD) bezeichneten, meist durch Anti-Aquaporin-4-Antikörper charakterisierten Devic-Syndrom. Die Zuordnung des sog. radiologisch isolierten Syndroms (RIS, inzidentell gefundene MS-typische MRT-Läsionen ohne klinisches Korrelat), der Stellenwert von Erkrankungen mit Nachweis von Myelin-Oligodendrozyten-Glykoprotein(MOG)-Antikörpern wie auch eine einheitliche Definition für den sekundär chronisch-progredienten Verlauf bleiben offen. Zusammengefasst steht damit McDonald 2017 im konzeptuellen Gerüst der Vorgänger und vereinfacht die Frühdiagnose.

Abstract

Multiple sclerosis (MS) is the most common chronic autoimmune disorder of the central nervous system (CNS) largely affecting young adults. The diagnosis of MS is based on two pillars: 1) detection of the spatial and temporal dissemination of focal neurological deficits and 2) exclusion of important differential diagnoses. The current revision of the diagnostic criteria (McDonald 2017) also follows these principles, takes new data on magnetic resonance imaging (MRI) into account and reintroduces the role of cerebrospinal fluid (CSF) diagnostics for relapsing-remitting forms. The main priority is a reliable diagnosis as early as possible with the aim of a timely initiation of course-adapted treatment. Some of the concrete innovations are the consideration of cortical MRI lesions (equivalent to juxtacortical foci), the elimination of a distinction between asymptomatic and symptomatic MRI lesions and consideration of characteristic CSF findings for the criterion of temporal dissemination. Relapsing MS can be diagnosed at the time of the first attack by the detection of CSF-specific oligoclonal bands and the MRI detection of a typical local lesion distribution (even without simultaneous detection of a contrast-enhancing lesion). For the primary progressive course, for which a first treatment option has recently been approved, the known definition remains unaltered. With respect to the differential diagnosis there is a clear demarcation from Devic’s syndrome, now known as neuromyelitis optica spectrum disorders (NMOSD), as recent insights indicate a separate disease entity caused by an autoimmune response against the astrocytic aquaporin 4 (AQP4) water channel. Finally, future studies will have to provide a definition for secondary progressive MS courses and clarify how to handle diseases characterized by antibodies against myelin oligodendrocyte glycoprotein (MOG) or patients with radiologically isolated syndrome (RIS), i. e. incidental MRI-based detection of CNS lesions in the absence of any clinical event. In summary, McDonald 2017 is within the conceptual structure of its predecessor and simplifies an early diagnosis, thus paving the way to early treatment of MS.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Abb. 1
Abb. 2
Abb. 3

Abbreviations

AQP4:

Aquaporin 4

CIS:

Klinisch isoliertes Syndrom

DIS:

Örtliche Dissemination

DIT:

Zeitliche Dissemination

FLAIR:

„fluid attenuated inversion recovery“

MOG:

Myelin-Oligodendrozyten-Glykoprotein

MRT:

Magnetresonanztomographie

MS:

Multiple Sklerose

NMO:

Neuromyelitis optica

NMOSD:

NMO-Spektrum-Erkrankung

VEP:

Visuell evozierte Potenziale

Literatur

  1. Aktas O (2015) Collateral benefit. The comeback of MOG antibodies as a biomarker in neurological practice. J Neurol Neurosurg Psychiatr 86(3):243

    Google Scholar 

  2. Aktas O, Hartung H‑P (2009) Neuromyelitis and more. The unfolding spectrum of aquaporin 4‑related neurological diseases. J Neurol 256(11):1906–1908

    PubMed  Google Scholar 

  3. Aliaga ES, Barkhof F (2014) MRI mimics of multiple sclerosis. Handb Clin Neurol 122:291–316

    PubMed  Google Scholar 

  4. Arrambide G, Tintore M (2016) CSF examination still has value in the diagnosis of MS – Commentary. Mult Scler 22(8):997–998

    CAS  PubMed  Google Scholar 

  5. Azevedo CJ, Overton E, Khadka S et al (2015) Early CNS neurodegeneration in radiologically isolated syndrome. Neurol Neuroimmunol Neuroinflamm 2(3):e102

    PubMed  PubMed Central  Google Scholar 

  6. Baumann M, Sahin K, Lechner C et al (2015) Clinical and neuroradiological differences of paediatric acute disseminating encephalomyelitis with and without antibodies to the myelin oligodendrocyte glycoprotein. J Neurol Neurosurg Psychiatr 86(3):265–272

    CAS  Google Scholar 

  7. Bellmann-Strobl J, Wuerfel J, Aktas O et al (2009) Poor PASAT performance correlates with MRI contrast enhancement in multiple sclerosis. Neurology 73(20):1624–1627

    CAS  PubMed  Google Scholar 

  8. Brownlee WJ, Miller DH (2014) Clinically isolated syndromes and the relationship to multiple sclerosis. J Clin Neurosci 21(12):2065–2071

    PubMed  Google Scholar 

  9. Brownlee WJ, Swanton JK, Miszkiel KA et al (2016) Should the symptomatic region be included in dissemination in space in MRI criteria for MS? Neurology 87(7):680–683

    PubMed  PubMed Central  Google Scholar 

  10. Brownlee WJ, Hardy TA, Fazekas F et al (2017) Diagnosis of multiple sclerosis. Progress and challenges. Lancet 389(10076):1336–1346

    PubMed  Google Scholar 

  11. Charil A, Yousry TA, Rovaris M et al (2006) MRI and the diagnosis of multiple sclerosis. Expanding the concept of “no better explanation”. Lancet Neurol 5(10):841–852

    PubMed  Google Scholar 

  12. D’Alessandro R, Vignatelli L, Lugaresi A et al (2013) Risk of multiple sclerosis following clinically isolated syndrome: a 4-year prospective study. J Neurol 260(6):1583–1593

    PubMed  Google Scholar 

  13. Dekker I, Wattjes MP (2017) Brain and spinal cord MR imaging features in multiple sclerosis and variants. Neuroimaging Clin N Am 27(2):205–227

    PubMed  Google Scholar 

  14. Filippi M, Rocca MA, Ciccarelli O et al (2016) MRI criteria for the diagnosis of multiple sclerosis: MAGNIMS consensus guidelines. Lancet Neurol 15(3):292–303

    PubMed  PubMed Central  Google Scholar 

  15. Forslin Y, Granberg T, Jumah AA et al (2016) Incidence of radiologically isolated syndrome: a population-based study. AJNR Am J Neuroradiol 37(6):1017–1022

    CAS  PubMed  Google Scholar 

  16. Frohman EM, Stuve O, Miller DH (2007) W. Ian McDonald, MB, ChB, PhD (1933–2006). The Multiple Sclerosis Physician-Scientist of the 20th Century. Arch Neurol 64(3):452

    PubMed  Google Scholar 

  17. Gabelic T, Ramasamy DP, Weinstock-Guttman B et al (2014) Prevalence of radiologically isolated syndrome and white matter signal abnormalities in healthy relatives of patients with multiple sclerosis. AJNR Am J Neuroradiol 35(1):106–112

    CAS  PubMed  Google Scholar 

  18. Geurts JJG, Calabrese M, Fisher E et al (2012) Measurement and clinical effect of grey matter pathology in multiple sclerosis. Lancet Neurol 11(12):1082–1092

    PubMed  Google Scholar 

  19. Ghezzi A, Amato MP, Makhani N et al (2016) Pediatric multiple sclerosis. Conventional first-line treatment and general management. Neurology 87(9 Suppl 2):S97–S102

    CAS  PubMed  Google Scholar 

  20. Giovannoni G (2017) The neurodegenerative prodrome in multiple sclerosis. Lancet Neurol 16(6):413–414

    PubMed  Google Scholar 

  21. Granberg T, Martola J, Kristoffersen-Wiberg M et al (2013) Radiologically isolated syndrome—incidental magnetic resonance imaging findings suggestive of multiple sclerosis, a systematic review. Mult Scler 19(3):271–280

    PubMed  Google Scholar 

  22. Gómez-Moreno M, Díaz-Sánchez M, Ramos-González A (2012) Application of the 2010 McDonald criteria for the diagnosis of multiple sclerosis in a Spanish cohort of patients with clinically isolated syndromes. Mult Scler 18(1):39–44

    PubMed  Google Scholar 

  23. Hacohen Y, Absoud M, Deiva K et al (2015) Myelin oligodendrocyte glycoprotein antibodies are associated with a non-MS course in children. Neurol Neuroimmunol Neuroinflamm 2(2):e81

    PubMed  PubMed Central  Google Scholar 

  24. Halliday AM, McDonald WI, Mushin J (1972) Delayed visual evoked response in optic neuritis. Lancet 1(7758):982–985

    CAS  PubMed  Google Scholar 

  25. Hamill RW, Kurtzke JF (2009) George A. Schumacher, MD, FAAN (1912–2008). Neurology 72(11):954

    Google Scholar 

  26. Hardy TA, Reddel SW, Barnett MH et al (2016) Atypical inflammatory demyelinating syndromes of the CNS. Lancet Neurol 15(9):967–981

    CAS  PubMed  Google Scholar 

  27. Hartung H‑P, Aktas O (2009) Bleak prospects for primary progressive multiple sclerosis therapy. Downs and downs, but a glimmer of hope. Ann Neurol 66(4):429–432

    CAS  PubMed  Google Scholar 

  28. Hawker K, O’Connor P, Freedman MS et al (2009) Rituximab in patients with primary progressive multiple sclerosis. Results of a randomized double-blind placebo-controlled multicenter trial. Ann Neurol 66(4):460–471

    CAS  PubMed  Google Scholar 

  29. Hummel H‑M, Brück W, Dreha-Kulaczewski S et al (2013) Pediatric onset multiple sclerosis: McDonald criteria 2010 and the contribution of spinal cord MRI. Mult Scler 19(10):1330–1335

    PubMed  Google Scholar 

  30. Iaffaldano P, Simone M, Lucisano G et al (2017) Prognostic indicators in pediatric clinically isolated syndrome. Ann Neurol 81(5):729–739

    PubMed  Google Scholar 

  31. Jarius S, Ruprecht K, Wildemann B et al (2012) Contrasting disease patterns in seropositive and seronegative neuromyelitis optica. A multicentre study of 175 patients. J Neuroinflammation 9:14

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Jarius S, Paul F, Fechner K et al (2014) Aquaporin-4 antibody testing. Direct comparison of M1-AQP4-DNA-transfected cells with leaky scanning versus M23-AQP4-DNA-transfected cells as antigenic substrate. J Neuroinflammation 11:129

    PubMed  PubMed Central  Google Scholar 

  33. Jarius S, Ruprecht K, Kleiter I et al (2016) MOG-IgG in NMO and related disorders. A multicenter study of 50 patients. Part 2: epidemiology, clinical presentation, radiological and laboratory features, treatment responses, and long-term outcome. J Neuroinflammation 13(1):280

    PubMed  PubMed Central  Google Scholar 

  34. Jarius S, Ruprecht K, Kleiter I et al (2016) MOG-IgG in NMO and related disorders: a multicenter study of 50 patients. Part 1: Frequency, syndrome specificity, influence of disease activity, long-term course, association with AQP4-IgG, and origin. J Neuroinflammation 13(1):279

    PubMed  PubMed Central  Google Scholar 

  35. Jokubaitis VG, Spelman T, Kalincik T et al (2016) Predictors of long-term disability accrual in relapse-onset multiple sclerosis. Ann Neurol 80(1):89–100

    PubMed  Google Scholar 

  36. Kang H, Metz LM, Traboulsee AL et al (2014) Application and a proposed modification of the 2010 McDonald criteria for the diagnosis of multiple sclerosis in a Canadian cohort of patients with clinically isolated syndromes. Mult Scler 20(4):458–463

    CAS  PubMed  Google Scholar 

  37. Keegan BM, Kaufmann TJ, Weinshenker BG et al (2016) Progressive solitary sclerosis: gradual motor impairment from a single CNS demyelinating lesion. Neurology 87(16):1713–1719

    PubMed  PubMed Central  Google Scholar 

  38. Kim S‑M, Kim S‑J, Lee HJ et al (2017) Differential diagnosis of neuromyelitis optica spectrum disorders. Ther Adv Neurol Disord 10(7):265–289

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Kornek B, Schmitl B, Vass K et al (2012) Evaluation of the 2010 McDonald multiple sclerosis criteria in children with a clinically isolated syndrome. Mult Scler 18(12):1768–1774

    PubMed  Google Scholar 

  40. Korteweg T, Tintoré M, Uitdehaag B et al (2006) MRI criteria for dissemination in space in patients with clinically isolated syndromes. A multicentre follow-up study. Lancet Neurol 5(3):221–227

    PubMed  Google Scholar 

  41. Krupp LB, Banwell B, Tenembaum S (2007) Consensus definitions proposed for pediatric multiple sclerosis and related disorders. Neurology 68(16 Suppl 2):S7–S12

    PubMed  Google Scholar 

  42. Krupp LB, Tardieu M, Amato MP et al (2013) International pediatric multiple sclerosis study group criteria for pediatric multiple sclerosis and immune-mediated central nervous system demyelinating disorders. Revisions to the 2007 definitions. Mult Scler 19(10):1261–1267

    PubMed  Google Scholar 

  43. Kurth T, Mohamed S, Maillard P et al (2011) Headache, migraine, and structural brain lesions and function. Population based Epidemiology of Vascular Ageing-MRI study. BMJ 342:c7357

    PubMed  PubMed Central  Google Scholar 

  44. Lee JY, Chitnis T (2016) Pediatric multiple sclerosis. Semin Neurol 36(2):148–153

    PubMed  Google Scholar 

  45. Lennon VA, Kryzer TJ, Pittock SJ et al (2005) IgG marker of optic-spinal multiple sclerosis binds to the aquaporin-4 water channel. J Exp Med 202(4):473–477

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Makhani N, Lebrun C, Siva A et al (2017) Radiologically isolated syndrome in children. Clinical and radiologic outcomes. Neurol Neuroimmunol Neuroinflamm 4(6):e395

    PubMed  PubMed Central  Google Scholar 

  47. McDonald WI, Sears TA (1970) The effects of experimental demyelination on conduction in the central nervous system. Brain 93(3):583–598

    CAS  PubMed  Google Scholar 

  48. 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(1):121–127

    CAS  PubMed  Google Scholar 

  49. Miller AE, Pelletier D (2016) Multiple sclerosis. Rapid diagnosis or right diagnosis? Neurology 87(7):652–653

    PubMed  Google Scholar 

  50. Miller DH, Weinshenker BG, Filippi M et al (2008) Differential diagnosis of suspected multiple sclerosis. A consensus approach. Mult Scler 14(9):1157–1174

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Montalban X, Hauser SL, Kappos L et al (2017) Ocrelizumab versus placebo in primary progressive multiple sclerosis. N Engl J Med 376(3):209–220

    CAS  PubMed  Google Scholar 

  52. Moore F, Okuda DT (2009) Incidental MRI anomalies suggestive of multiple sclerosis. The radiologically isolated syndrome. Neurology 73(20):1714

    PubMed  Google Scholar 

  53. Okuda DT, Mowry EM, Cree BAC et al (2011) Asymptomatic spinal cord lesions predict disease progression in radiologically isolated syndrome. Neurology 76(8):686–692

    CAS  PubMed  PubMed Central  Google Scholar 

  54. Okuda DT, Siva A, Kantarci O et al (2014) Radiologically isolated syndrome. 5‑year risk for an initial clinical event. PLoS ONE 9(3):e90509

    PubMed  PubMed Central  Google Scholar 

  55. Pardini M, Uccelli A, Grafman J et al (2014) Isolated cognitive relapses in multiple sclerosis. J Neurol Neurosurg Psychiatr 85(9):1035–1037

    Google Scholar 

  56. Paul F, Jarius S, Aktas O et al (2007) Antibody to aquaporin 4 in the diagnosis of neuromyelitis optica. Plos Med 4(4):e133

    PubMed  PubMed Central  Google Scholar 

  57. Peterson JW, Bö L, Mörk S et al (2001) Transected neurites, apoptotic neurons, and reduced inflammation in cortical multiple sclerosis lesions. Ann Neurol 50(3):389–400

    CAS  PubMed  Google Scholar 

  58. Planitzer J, Zschenderlein R (1983) Möglichkeiten und Grenzen computertomographischer Hirnstamm-Diagnostik (Possibilities and limitations of computer tomographic brain stem diagnosis). Psychiatr Neurol Med Psychol Beih 29:205–214

    CAS  PubMed  Google Scholar 

  59. Polman CH, Reingold SC, Edan G et al (2005) Diagnostic criteria for multiple sclerosis. 2005 revisions to the “McDonald Criteria”. Ann Neurol 58(6):840–846

    PubMed  Google Scholar 

  60. 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

    PubMed  PubMed Central  Google Scholar 

  61. Poser CM, Paty DW, Scheinberg L et al (1983) New diagnostic criteria for multiple sclerosis. Guidelines for research protocols. Ann Neurol 13(3):227–231

    CAS  PubMed  Google Scholar 

  62. Rose AS, Ellison GW, Myers LW et al (1976) Criteria for the clinical diagnosis of multiple sclerosis. Neurology 26(6 PT 2):20–22

    CAS  PubMed  Google Scholar 

  63. Rostasy K, Mader S, Schanda K et al (2012) Anti-myelin oligodendrocyte glycoprotein antibodies in pediatric patients with optic neuritis. Arch Neurol 69(6):752–756

    PubMed  Google Scholar 

  64. Rovira A, Auger C (2016) Spinal Cord in multiple sclerosis. Magnetic resonance imaging features and differential diagnosis. Semin Ultrasound Ct Mr 37(5):396–410

    PubMed  Google Scholar 

  65. Rovira À, Wattjes MP, Tintoré M et al (2015) Evidence-based guidelines. MAGNIMS consensus guidelines on the use of MRI in multiple sclerosis-clinical implementation in the diagnostic process. Nat Rev Neurol 11(8):471–482

    PubMed  Google Scholar 

  66. Sadaka Y, Verhey LH, Shroff MM et al (2012) 2010 McDonald criteria for diagnosing pediatric multiple sclerosis. Ann Neurol 72(2):211–223

    PubMed  Google Scholar 

  67. Schmalstieg WF, Keegan BM, Weinshenker BG (2012) Solitary sclerosis. Progressive myelopathy from solitary demyelinating lesion. Neurology 78(8):540–544

    PubMed  Google Scholar 

  68. Schumacher GA, Beebe G, Kibler RF et al (1965) Problems of experimental trials of therapy in multiple sclerosis. Report by the panel on the evaluation of experimental trials of therapy in multiple sclerosis. Ann N Y Acad Sci 122:552–568

    CAS  PubMed  Google Scholar 

  69. de Seze J (2017) MOG-antibody neuromyelitis optica spectrum disorder. Is it a separate disease? Brain 140(12):3072–3075

    PubMed  Google Scholar 

  70. Simone M, Chitnis T (2016) Use of disease-modifying therapies in pediatric MS. Curr Treat Options Neurol 18(8):36

    PubMed  Google Scholar 

  71. Soelberg Sorensen P (2017) Safety concerns and risk management of multiple sclerosis therapies. Acta Neurol Scand 136(3):168–186

    CAS  PubMed  Google Scholar 

  72. Solomon AJ, Klein EP, Bourdette D (2012) “Undiagnosing” multiple sclerosis. The challenge of misdiagnosis in MS. Neurology 78(24):1986–1991

    PubMed  PubMed Central  Google Scholar 

  73. Solomon AJ, Bourdette DN, Cross AH et al (2016) The contemporary spectrum of multiple sclerosis misdiagnosis. A multicenter study. Neurology 87(13):1393–1399

    PubMed  PubMed Central  Google Scholar 

  74. Stangel M, Fredrikson S, Meinl E et al (2013) The utility of cerebrospinal fluid analysis in patients with multiple sclerosis. Nat Rev Neurol 9(5):267–276

    CAS  PubMed  Google Scholar 

  75. Tardieu M, Banwell B, Wolinsky JS et al (2016) Consensus definitions for pediatric MS and other demyelinating disorders in childhood. Neurology 87(9 Suppl 2):S8–S11

    PubMed  Google Scholar 

  76. Thompson A, Banwell BL, Barkhof F et al (2018) Diagnosis of multiple sclerosis: recommended 2017 revisions of the “McDonald” criteria. Lancet Neurol 17(2):162–173. https://doi.org/10.1016/S1474-4422(17)30470-2

    Article  PubMed  Google Scholar 

  77. Thompson AJ, Miller D, Youl B et al (1992) Serial gadolinium-enhanced MRI in relapsing/remitting multiple sclerosis of varying disease duration. Neurology 42(1):60–63

    CAS  PubMed  Google Scholar 

  78. Tintoré M, Rovira A, Brieva L et al (2001) Isolated demyelinating syndromes. Comparison of CSF oligoclonal bands and different MR imaging criteria to predict conversion to CDMS. Mult Scler 7(6):359–363

    PubMed  Google Scholar 

  79. Tintoré M, Rovira A, Río J et al (2003) New diagnostic criteria for multiple sclerosis. Application in first demyelinating episode. Neurology 60(1):27–30

    PubMed  Google Scholar 

  80. Tintoré M, Rovira A, Río J et al (2008) Do oligoclonal bands add information to MRI in first attacks of multiple sclerosis? Neurology 70(13 Pt 2):1079–1083

    PubMed  Google Scholar 

  81. Tintore M, Rovira À, Río J et al (2015) Defining high, medium and low impact prognostic factors for developing multiple sclerosis. Brain 138(Pt 7):1863–1874

    PubMed  Google Scholar 

  82. Tintore M, Otero-Romero S, Río J et al (2016) Contribution of the symptomatic lesion in establishing MS diagnosis and prognosis. Neurology 87(13):1368–1374

    PubMed  Google Scholar 

  83. Trebst C, Jarius S, Berthele A et al (2014) Update on the diagnosis and treatment of neuromyelitis optica. Recommendations of the Neuromyelitis Optica Study Group (NEMOS). J Neurol 261(1):1–16

    CAS  PubMed  Google Scholar 

  84. Tumani H, Deisenhammer F, Giovannoni G et al (2011) Revised McDonald criteria. The persisting importance of cerebrospinal fluid analysis. Ann Neurol 70(3):520 (author reply 521)

    PubMed  Google Scholar 

  85. Waters P, Reindl M, Saiz A et al (2016) Multicentre comparison of a diagnostic assay. Aquaporin-4 antibodies in neuromyelitis optica. J Neurol Neurosurg Psychiatr 87(9):1005–1015

    Google Scholar 

  86. Wattjes MP, Harzheim M, Lutterbey GG et al (2008) Does high field MRI allow an earlier diagnosis of multiple sclerosis? J Neurol 255(8):1159–1163

    PubMed  Google Scholar 

  87. Wattjes MP, Rovira À, Miller D et al (2015) Evidence-based guidelines. MAGNIMS consensus guidelines on the use of MRI in multiple sclerosis—establishing disease prognosis and monitoring patients. Nat Rev Neurol 11(10):597–606

    CAS  PubMed  Google Scholar 

  88. Wattjes MP, Steenwijk MD, Stangel M (2015) MRI in the Diagnosis and Monitoring of Multiple Sclerosis. An Update. Clin Neuroradiol 25(Suppl 2):157–165

    PubMed  Google Scholar 

  89. Wijnands JMA, Kingwell E, Zhu F et al (2017) Health-care use before a first demyelinating event suggestive of a multiple sclerosis prodrome. A matched cohort study. Lancet Neurol 16(6):445–451

    PubMed  Google Scholar 

  90. Wingerchuk DM, Banwell B, Bennett JL et al (2015) International Panel for NMO Diagnosis. Neurology. 85(2):177–189. https://doi.org/10.1212/WNL.0000000000001729

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to H.-P. Hartung.

Ethics declarations

Interessenkonflikt

O. Aktas erhielt Forschungsförderung durch Bayer Healthcare, Biogen, Novartis, Sanofi-Genzyme, und Teva, sowie Honorare und Reisekostenunterstützung durch Almirall, Bayer Healthcare, Biogen, Medimmune, Merck, Novartis, Roche, Sanofi-Genzyme und Teva, mit Genehmigung der Rektorin der Heinrich-Heine-Universität Düsseldorf. M.P. Wattjes erhielt Vortrags- und Beratungshonorare von Biogen, Novartis, IXICO, Janssen, Roche, Sanofi-Genzyme und Springer mit Genehmigung des Präsidiums der Medizinischen Hochschule Hannover. M. Stangel erhielt Referentenhonorare, Reisekostenzuschüsse und Beraterhonorare von Biogen, Baxalta/Shire, Bayer Vital, CSL Behring, Grifols, MedDay, Merck-Serono, Novartis, Roche, Sanofi-Genzyme und Teva. Seine Institution erhielt Forschungsunterstützung von Bayer Healthcare, Biogen, Merck-Serono, Novartis, Sanofi-Genzyme und Teva. H.-P. Hartung erhielt Honorare für Beratungs- und Vortragstätigkeiten und Mitarbeit in steering committees von Bayer Healthcare, Biogen, GeNeuro, MedImmune, Merck, Novartis, Receptos Celgene, Roche, Sanofi-Genzyme und Teva, mit Genehmigung der Rektorin der Heinrich-Heine-Universität Düsseldorf.

Dieser Beitrag beinhaltet keine von den Autoren durchgeführten Studien an Menschen oder Tieren.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Aktas, O., Wattjes, M.P., Stangel, M. et al. Diagnose der Multiplen Sklerose: Revision der McDonald-Kriterien 2017. Nervenarzt 89, 1344–1354 (2018). https://doi.org/10.1007/s00115-018-0550-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00115-018-0550-0

Schlüsselwörter

Keywords

Navigation