• An Erratum to this article was published on 20 March 2018

This article has been updated


MRI red flags proposed over a decade ago by the European Magnetic Resonance Network in MS (MAGNIMS) have guided clinicians in the diagnosis of multiple sclerosis (MS). However, the past 10 years have seen increased recognition that vascular disease can coexist and possibly interact with MS, improvements in the reliability of ways to differentiate MS from novel antibody-mediated CNS disorders (such as anti-aquaporin-4 antibody and myelin-oligodendrocyte glycoprotein antibody-associated diseases) and advances in MRI techniques. In this Review, MAGNIMS updates the imaging features that differentiate the most common mimics of MS, particularly age-related cerebrovascular disease and neuromyelitis optica, from MS itself. We also provide a pragmatic summary of the clinically useful MRI features that distinguish MS from its mimics and discuss the future of nonconventional techniques that have identified promising disease-specific features.

Key points

  • MRI is crucial in the diagnosis of multiple sclerosis (MS), revealing the dissemination in space and time of white matter lesions (WMLs) and helping to rule out alternative diagnoses

  • WMLs with a distribution similar to that seen in MS can occur in many disorders, from common age-related vascular disease and migraine to neuromyelitis optica spectrum disorders and rarer conditions

  • The distribution of WMLs can help to differentiate MS from antibody-mediated CNS disorders

  • The proportion of lesions that exhibit the central vein sign and the presence of cortical lesions can be useful in differentiating MS from some of its mimics

  • Meningeal enhancement, indistinct (ill-defined) lesions that increase in size over time, macrobleeds and microbleeds, infarcts, cavities, symmetrical lesions that spare U-fibres, siderosis and extensive spinal cord lesions suggest diagnoses other than MS

  • We suggest the mnemonic iMIMICs to remember the atypical MRI features that indicate a diagnosis other than MS

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Change history

  • 27 March 2018

    In the version of this article originally published online, the heading of the third column in Table 1 was "Percentage of lesions that meet criteria". This heading should be "Percentage of patients that meet criteria". The error has been corrected in the print and online versions.


  1. 1.

    et al. Diagnostic criteria for multiple sclerosis: 2010 Revisions to the McDonald criteria. Ann. Neurol. 69, 292–302 (2011).

  2. 2.

    et al. MRI criteria for the diagnosis of multiple sclerosis: MAGNIMS consensus guidelines. Lancet Neurol. 15, 292–303 (2016).

  3. 3.

    et al. MRI mimics of multiple sclerosis. Handb. Clin. Neurol. 122, 291–316 (2014).

  4. 4.

    et al. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol. 17, 162–173 (2017). The most recent MS criteria in which the role of MRI in documenting dissemination in time and space are discussed.

  5. 5.

    , & A clinical approach to the differential diagnosis of multiple sclerosis. Curr. Neurol. Neurosci. Rep. 15, 57 (2015).

  6. 6.

    , , , & MRI differential diagnosis of suspected multiple sclerosis. Clin. Radiol. 71, 815–827 (2016).

  7. 7.

    et al. Comparison of MRI criteria at first presentation to predict conversion to clinically definite multiple sclerosis. Brain 120, 2059–2069 (1997).

  8. 8.

    et al. Prevalence of brain magnetic resonance imaging meeting Barkhof and McDonald criteria for dissemination in space among headache patients. Mult. Scler. J. 19, 1101–1105 (2013).

  9. 9.

    , & Brain white matter hyperintensities in migraine: Clinical and radiological correlates. Clin. Neurol. Neurosurg. 115, 1040–1043 (2013).

  10. 10.

    et al. Patients with migraine do not have MRI-visible cortical lesions. J. Neurol. 259, 2695–2698 (2012).

  11. 11.

    et al. Distinction of seropositive NMO spectrum disorder and MS brain lesion distribution. Neurology 80, 1330–1337 (2013). This paper describes the brain imaging criteria that were found to be useful in differentiating MS from NMOSD.

  12. 12.

    et al. The usefulness of brain MRI at onset in the differentiation of multiple sclerosis and seropositive neuromyelitis optica spectrum disorders. Mult. Scler. 20, 695–704 (2014).

  13. 13.

    et al. Brain lesion distribution criteria distinguish MS from AQP4-antibody NMOSD and MOG-antibody disease. J. Neurol. Neurosurg. Psychiatry 88, 132–136 (2017).

  14. 14.

    et al. 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. Neuroinflamm. 13, 280 (2016).

  15. 15.

    et al. Behçet's disease patients with multiple sclerosis-like features: discriminative value of Barkhof criteria. Clin. Exp. Rheumatol. 33, S80–84 (2015).

  16. 16.

    , , , & Limited utility of current MRI criteria for distinguishing multiple sclerosis from common mimickers: primary and secondary CNS vasculitis, lupus and Sjogren's syndrome. Mult. Scler. J. 20, 57–63 (2014).

  17. 17.

    et al. The contemporary spectrum of multiple sclerosis misdiagnosis. Neurology 87, 1393–1400 (2016). This article provides a good introduction to the problem of MS misdiagnosis.

  18. 18.

    et al. MRI and the diagnosis of multiple sclerosis: expanding the concept of 'no better explanation'. Lancet Neurol. 5, 841–852 (2006).

  19. 19.

    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. 11, 471–482 (2015). This paper presents key guidelines for the use of MRI in MS diagnosis, including details on MRI protocols.

  20. 20.

    & Conventional MRI in multiple sclerosis. J. Neuroimag. 17, 3S–9S (2007).

  21. 21.

    & Advanced structural and functional brain MRI in multiple sclerosis. Semin. Neurol. 36, 163–176 (2016).

  22. 22.

    , , , & Subcortical vascular cognitive impairment: Similarities and differences with multiple sclerosis. J. Neurol. Sci. 245, 3–7 (2006).

  23. 23.

    , , & Age-related small vessel disease: A potential contributor to neurodegeneration in multiple sclerosis. Brain Pathol. 27, 707–722 (2016).

  24. 24.

    & Misdiagnosis of multiple sclerosis: frequency, causes, effects, and prevention. Curr. Neurol. Neurosci. Rep. 13, 403 (2013).

  25. 25.

    Cerebral small vessel disease: from pathogenesis and clinical characteristics to therapeutic challenges. Lancet Neurol. 9, 689–701 (2010).

  26. 26.

    et al. Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration. Lancet Neurol. 12, 822–838 (2013). This article provides a clear outline of the key MRI features of SVD.

  27. 27.

    et al. Changes in white matter as determinant of global functional decline in older independent outpatients: three year follow-up of LADIS (leukoaraiosis and disability) study cohort. BMJ 339, b2477 (2009).

  28. 28.

    et al. Incident lacunes influence cognitive decline: The LADIS study. Neurology 76, 1872–1878 (2011).

  29. 29.

    et al. Heterogeneity in age-related white matter changes. Acta Neuropathol. 122, 171–185 (2011).

  30. 30.

    et al. Collagenosis of the deep medullary veins: an underrecognized pathologic correlate of white matter hyperintensities and periventricular infarction? J. Neuropathol. Exp. Neurol. 76, 299–312 (2017).

  31. 31.

    et al. The spatial distribution of age-related white matter changes as a function of vascular risk factors-Results from the LADIS study. Neuroimage 60, 1597–1607 (2012).

  32. 32.

    et al. Incident lacunes preferentially localize to the edge of white matter hyperintensities: insights into the pathophysiology of cerebral small vessel disease. Brain 136, 2717–2726 (2013).

  33. 33.

    et al. White matter lesion progression in LADIS: frequency, clinical effects, and sample size calculations. Stroke 43, 2643–2647 (2012).

  34. 34.

    et al. MRI-visible perivascular spaces in cerebral amyloid angiopathy and hypertensive arteriopathy. Neurology 88, 157–1164 (2017).

  35. 35.

    et al. Features of Virchow-Robin spaces in newly diagnosed multiple sclerosis patients. Eur. J. Radiol. 80, e104–108 (2011).

  36. 36.

    et al. Perivascular spaces — MRI marker of inflammatory activity in the brain? Brain 131, 2332–2340 (2008).

  37. 37.

    et al. Brain MRI atrophy quantification in MS: from methods to clinical application. Neurology 88, 403–413 (2017).

  38. 38.

    & The clinical course of multiple sclerosis. Handb. Clin. Neurol. 122, 343–369 (2014).

  39. 39.

    et al. Vascular comorbidity is associated with more rapid disability progression in multiple sclerosis. Neurology 74, 1041–1047 (2010).

  40. 40.

    et al. A systematic review of the incidence and prevalence of cardiac, cerebrovascular, and peripheral vascular disease in multiple sclerosis. Mult. Scler. 21, 318–331 (2014).

  41. 41.

    et al. Cardiovascular risk factors are associated with increased lesion burden and brain atrophy in multiple sclerosis. J. Neurol. Neurosurg. Psychiatry 87, 181–187 (2015).

  42. 42.

    et al. Three-dimensional shape and surface features distinguish multiple sclerosis lesions from nonspecific white matter disease. J. Neuroimag. 27, 613–619 (2017).

  43. 43.

    , & Mechanisms of sporadic cerebral small vessel disease: insights from neuroimaging. Lancet Neurol. 12, 483–497 (2013).

  44. 44.

    , , , & Cerebral microbleeds in patients with hypertensive stroke. Topographical distribution in the supratentorial area. J. Neurol. 251, 1183–1189 (2004).

  45. 45.

    et al. Spatial clustering of hemorrhages in probable cerebral amyloid angiopathy. Ann. Neurol. 58, 459–462 (2005).

  46. 46.

    et al. Cerebral microbleeds in multiple sclerosis evaluated on susceptibility-weighted images and quantitative susceptibility maps: a case-control study. Radiology 281, 884–895 (2016).

  47. 47.

    et al. Investigation of cerebral microbleeds in multiple sclerosis as a potential marker of blood-brain barrier dysfunction. Mult. Scler. Relat. Disord. 7, 61–64 (2016).

  48. 48.

    et al. Prevalence and mechanisms of cortical superficial siderosis in cerebral amyloid angiopathy. Neurology 81, 626–632 (2013).

  49. 49.

    et al. Imaging central veins in brain lesions with 3-T T2*-weighted magnetic resonance imaging differentiates multiple sclerosis from microangiopathic brain lesions. Mult. Scler. J. 22, 1289–1296 (2016).

  50. 50.

    et al. The central vein sign in multiple sclerosis lesions is present irrespective of the T2* sequence at 3 T. J. Neuroimag. 27, 114–121 (2017).

  51. 51.

    et al. The central vein sign and its clinical evaluation for the diagnosis of multiple sclerosis: a consensus statement from the North American Imaging in Multiple Sclerosis Cooperative. Nat. Rev. Neurol. 12, 714–722 (2016). A comprehensive review of the central vein sign as a potential MRI feature that discriminates between MS and MS mimics.

  52. 52.

    et al. Improved in vivo detection of cortical lesions in multiple sclerosis using double inversion recovery MR imaging at 3 Tesla. Eur. Radiol. 20, 1675–1683 (2010).

  53. 53.

    et al. Consensus recommendations for MS cortical lesion scoring using double inversion recovery MRI. Neurology 76, 418–424 (2011).

  54. 54.

    , , , & Cerebral microinfarcts: a systematic review of neuropathological studies. J. Cereb. Blood Flow Metab. 32, 425–436 (2012).

  55. 55.

    et al. Risk factors and cognitive relevance of cortical cerebral microinfarcts in patients with ischemic stroke or transient ischemic attack. Stroke 47, 2450–2455 (2016).

  56. 56.

    et al. Cortical cerebral microinfarcts on 3T MRI: A novel marker of cerebrovascular disease. Neurology 87, 1583–1590 (2016).

  57. 57.

    , , , & Imaging spectrum of CNS vasculitis. Radiographics 34, 873–894 (2014).

  58. 58.

    Stroke and Fabry disease. J. Neurol. 259, 1019–1028 (2012).

  59. 59.

    et al. A practical approach to diagnosing adult onset leukodystrophies. J. Neurol. Neurosurg. Psychiatry 85, 770–781 (2014). This article presents a pattern-based approach to the diagnosis of leukodystrophies; characteristic imaging features for each of these rare multiple sclerosis mimics are discussed.

  60. 60.

    et al. Vessel wall contrast enhancement: a diagnostic sign of cerebral vasculitis. Cerebrovasc. Dis. 26, 23–29 (2008).

  61. 61.

    et al. Spinal cord MRI using multi-array coils and fast spin echo. I. Technical aspects and findings in healthy adults. Neurology 43, 2625–2631 (1993).

  62. 62.

    et al. Spinal cord magnetic resonance imaging in suspected multiple sclerosis. Eur. Radiol. 10, 368–376 (2000).

  63. 63.

    et al. Differentiation of multiple sclerosis from other inflammatory disorders and cerebrovascular disease: value of spinal MR imaging. Radiology 223, 46–56 (2002).

  64. 64.

    et al. Longitudinal extensive transverse myelitis — it's not all neuromyelitis optica. Nat. Rev. Neurol. 7, 688–698 (2011).

  65. 65.

    Spinal cord infarction in clinical neurology: a review of characteristics and long-term prognosis in comparison to cerebral infarction. Eur. Neurol. 76, 95–98 (2016).

  66. 66.

    , , & Migraine and structural changes in the brain: a systematic review and meta-analysis. Neurology 81, 1260–1268 (2013).

  67. 67.

    et al. Are periventricular lesions specific for multiple sclerosis? J. Neurol. Neurophysiol. 4, 150 (2013).

  68. 68.

    et al. 'Central vessel sign' on 3T FLAIR* MRI for the differentiation of multiple sclerosis from migraine. Ann. Clin. Transl Neurol. 3, 82–87 (2016).

  69. 69.

    et al. Diagnostic performance of central vein sign for multiple sclerosis with a simplified three-lesion algorithm. Mult. Scler. J. (2017).

  70. 70.

    et al. Migraine, white matter hyperintensities, and subclinical brain infarction in a diverse community: the northern Manhattan study. Stroke 45, 1830–1832 (2014).

  71. 71.

    , , , & An MR study of tissue damage in the cervical cord of patients with migraine. J. Neurol. Sci. 183, 43–46 (2001).

  72. 72.

    et al. Update on the diagnosis and treatment of neuromyelitis optica: recommendations of the Neuromyelitis Optica Study Group (NEMOS). J. Neurol. 261, 1–16 (2014).

  73. 73.

    Demyelinating disease: NMO spectrum disorders: clinical or molecular classification? Nat. Rev. Neurol. 12, 129–130 (2016).

  74. 74.

    et al. International consensus diagnostic criteria for neuromyelitis optica spectrum disorders. Neurology 85, 177–189 (2015). NMOSD diagnostic criteria, including the additional MRI requirements in antibody-negative patients.

  75. 75.

    et al. Longitudinally extensive transverse myelitis with and without aquaporin 4 antibodies. JAMA Neurol. 70, 1375 (2013).

  76. 76.

    et al. Isolated new onset 'atypical' optic neuritis in the NMO clinic: serum antibodies, prognoses and diagnoses at follow-up. J. Neurol. 263, 370–379 (2016).

  77. 77.

    et al. Distinction between MOG antibody-positive and AQP4 antibody-positive NMO spectrum disorders. Neurology 82, 474–481 (2014).

  78. 78.

    et al. Antibodies to MOG and AQP4 in adults with neuromyelitis optica and suspected limited forms of the disease. Mult. Scler. 21, 866–874 (2015).

  79. 79.

    & Does MOG Ig-positive AQP4-seronegative opticospinal inflammatory disease justify a diagnosis of NMO spectrum disorder? Neurol. Neuroimmunol. Neuroinflamm. 2, e62 (2015).

  80. 80.

    et al. Status of diagnostic approaches to AQP4-IgG seronegative NMO and NMO/MS overlap syndromes. J. Neurol. 263, 140–149 (2016).

  81. 81.

    et al. Clinical and neuroradiological differences of paediatric acute disseminating encephalomyelitis with and without antibodies to the myelin oligodendrocyte glycoprotein. J. Neurol. Neurosurg. Psychiatry 86, 265–272 (2015).

  82. 82.

    et al. Prognostic relevance of MOG antibodies in children with an acquired demyelinating syndrome. Neurology 89, 900–908 (2017).

  83. 83.

    et al. Diagnostic algorithm for relapsing acquired demyelinating syndromes in children. Neurology 89, 269–278 (2017).

  84. 84.

    et al. Autoantibodies to MOG in a distinct subgroup of adult multiple sclerosis. Neurol. Neuroimmunol. Neuroinflamm. 3, e257 (2016).

  85. 85.

    et al. Acute disseminated encephalomyelitis followed by recurrent or monophasic optic neuritis in pediatric patients. Mult. Scler. J. 19, 941–946 (2013).

  86. 86.

    et al. Myelin oligodendrocyte glycoprotein antibodies are associated with a non-MS course in children. Neurol. Neuroimmunol. Neuroinflamm. 2, e81 (2015).

  87. 87.

    et al. Distinct brain imaging characteristics of autoantibody-mediated CNS conditions and multiple sclerosis. Brain 140, 617–627 (2017). An example of a direct comparison between MS and antibody-mediated CNS disorders that identified imaging features that help to differentiate these disorders.

  88. 88.

    et al. MRI characteristics of neuromyelitis optica spectrum disorder: an international update. Neurology 84, 1165–1173 (2015).

  89. 89.

    et al. Short myelitis lesions in aquaporin-4-IgG-positive neuromyelitis optica spectrum disorders. JAMA Neurol. 72, 81–87 (2015).

  90. 90.

    , & Overlapping CNS inflammatory diseases: differentiating features of NMO and MS. J. Neurol. Neurosurg. Psychiatry 86, 20–25 (2015).

  91. 91.

    et al. Neuromyelitis optica unique area postrema lesions: nausea, vomiting, and pathogenic implications. Neurology 76, 1229–1237 (2011).

  92. 92.

    , , , & Cloud-like enhancement is a magnetic resonance imaging abnormality specific to neuromyelitis optica. Ann. Neurol. 66, 425–428 (2009).

  93. 93.

    , , , & Pencil-thin ependymal enhancement in neuromyelitis optica spectrum disorders. Mult. Scler. J. 18, 1050–1053 (2012).

  94. 94.

    et al. Characteristic brain magnetic resonance imaging abnormalities in central nervous system aquaporin-4 autoimmunity. Mult. Scler. 16, 1229–1236 (2010).

  95. 95.

    et al. Neuromyelitis optica spectrum disorders with aquaporin-4 and myelin-oligodendrocyte glycoprotein antibodies. JAMA Neurol. 71, 276 (2014).

  96. 96.

    et al. MOG-IgG in NMO and related disorders: a multicenter study of 50 patients. Part 3: brainstem involvement — frequency, presentation and outcome. J. Neuroinflamm. 13, 281 (2016).

  97. 97.

    , , & Brain abnormalities in neuromyelitis optica spectrum disorder. Mult. Scler. Int. 2012, 1–10 (2012).

  98. 98.

    et al. Disruption of the leptomeningeal blood barrier in neuromyelitis optica spectrum disorder. Neurol. Neuroimmunol. Neuroinflamm. 4, e343 (2017).

  99. 99.

    et al. Imaging surrogates of disease activity in neuromyelitis optica allow distinction from multiple sclerosis. PLoS ONE 10, e0137715 (2015).

  100. 100.

    et al. Cortical lesion load associates with progression of disability in multiple sclerosis. Brain 135, 2952–2961 (2012).

  101. 101.

    et al. No MRI evidence of cortical lesions in neuromyelitis optica. Neurology 79, 1671–1676 (2012).

  102. 102.

    et al. Absence of cortical demyelination in neuromyelitis optica. Neurology 75, 2103–2109 (2010).

  103. 103.

    et al. Differential patterns of spinal cord and brain atrophy in NMO and MS. Neurology 84, 1465–1472 (2015).

  104. 104.

    et al. Multimodal quantitative MR imaging of the thalamus in multiple sclerosis and neuromyelitis optica. Radiology 277, 784–792 (2015).

  105. 105.

    et al. Normal volumes and microstructural integrity of deep gray matter structures in AQP4+ NMOSD. Neurol. Neuroimmunol. Neuroinflamm. 3, e229 (2016).

  106. 106.

    et al. Deep gray matter atrophy in neuromyelitis optica spectrum disorder and multiple sclerosis. Eur. J. Neurol. 24, 437–445 (2017).

  107. 107.

    et al. Gray matter MRI differentiates neuromyelitis optica from multiple sclerosis using random forest. Neurology 87, 2463–2470 (2016).

  108. 108.

    et al. Use of advanced magnetic resonance imaging techniques in neuromyelitis optica spectrum disorder. JAMA Neurol. 72, 815 (2015).

  109. 109.

    et al. Advanced magnetic resonance imaging of neuromyelitis optica: a multiparametric approach. Mult. Scler. 18, 817–824 (2012).

  110. 110.

    et al. Pathogenesis of normal-appearing white matter damage in neuromyelitis optica: diffusion-tensor MR imaging. Radiology 246, 222–228 (2008).

  111. 111.

    et al. A tract-based diffusion study of cerebral white matter in neuromyelitis optica reveals widespread pathological alterations. Mult. Scler. J. 18, 1013–1021 (2012).

  112. 112.

    The value of the central vein sign at 3T to differentiate MS from seropositive-NMOSD. Neurology (2018).

  113. 113.

    et al. Low myo-inositol indicating astrocytic damage in a case series of neuromyelitis optica. Ann. Neurol. 74, 301–305 (2013).

  114. 114.

    et al. Magnetic resonance spectroscopy evaluation in patients with neuromyelitis optica. J. Neurol. Neurosurg. Psychiatry 81, 409–411 (2010).

  115. 115.

    et al. Radiological differentiation of optic neuritis with myelin oligodendrocyte glycoprotein antibodies, aquaporin-4 antibodies, and multiple sclerosis. Mult. Scler. 22, 470–482 (2016).

  116. 116.

    et al. MRI and retinal abnormalities in isolated optic neuritis with myelin oligodendrocyte glycoprotein and aquaporin-4 antibodies: a comparative study. J. Neurol. Neurosurg. Psychiatry 87, 446–448 (2016).

  117. 117.

    , , & The differential diagnosis of longitudinally extensive transverse myelitis. Mult. Scler. 18, 271–285 (2012).

  118. 118.

    et al. 'Bright spotty lesions' on spinal magnetic resonance imaging differentiate neuromyelitis optica from multiple sclerosis. Mult. Scler. J. 20, 331–337 (2014).

  119. 119.

    et al. Differentiating neuromyelitis optica from other causes of longitudinally extensive transverse myelitis on spinal magnetic resonance imaging. Mult. Scler. 22, 302–311 (2016).

  120. 120.

    et al. Modifications of longitudinally extensive transverse myelitis and brainstem lesions in the course of neuromyelitis optica (NMO): a population-based, descriptive study. BMC Neurol. 13, 33 (2013).

  121. 121.

    et al. MRI of the spinal cord in neuromyelitis optica and recurrent longitudinal extensive myelitis. J. Neuroradiol. 36, 199–205 (2009).

  122. 122.

    et al. Distinctive clinical and neuroimaging characteristics of longitudinally extensive transverse myelitis associated with aquaporin-4 autoantibodies. J. Neurol. 260, 2396–2402 (2013).

  123. 123.

    , , , & Predictive value of MRI parameters in severity and recovery of first-episode myelitis in aquaporin-4 antibody disease. J. Neurol. Sci. 355, 49–53 (2015).

  124. 124.

    et al. Ring-enhancing spinal cord lesions in neuromyelitis optica spectrum disorders. J. Neurol. Neurosurg. Psychiatry 88, 218–225 (2017).

  125. 125.

    , , & Diagnosis of multiple sclerosis: progress and challenges. Lancet 6736, 292–302 (2016).

  126. 126.

    & The diagnosis of MS: white spots and red flags. Neurology 70, 1071–1072 (2008).

  127. 127.

    et al. Differential diagnosis of suspected multiple sclerosis: a consensus approach. Mult. Scler. J. 14, 1157–1174 (2008).

  128. 128.

    , & Adulthood leukodystrophies. Nat. Rev. Neurol. (2018).

  129. 129.

    Diagnostic algorithm for the differentiation of leukodystrophies in early MS. J. Neurol. 255 (Suppl.), 123–126 (2008).

  130. 130.

    , , & Acute disseminated encephalomyelitis. Neurology 68, S23–36 (2007).

  131. 131.

    et al. Diagnostic criteria for Susac syndrome. J. Neurol. Neurosurg. Psychiatry 87, 1287–1295 (2016).

  132. 132.

    et al. Splenial lesions of the corpus callosum: disease spectrum and MRI findings. Kor. J. Radiol. 18, 710 (2017).

  133. 133.

    et al. Lesions of the corpus callosum: MR imaging and differential considerations in adults and children. Am. J. Roentgenol. 179, 251–257 (2002).

  134. 134.

    et al. Investigations in GABAA receptor antibody-associated encephalitis. Neurology 88, 1012–1020 (2017).

  135. 135.

    et al. Punctate pattern:a promising imaging marker for the diagnosis of natalizumab-associated PML. Neurology 86, 1516–1523 (2016).

  136. 136.

    et al. The chameleon of neuroinflammation: magnetic resonance imaging characteristics of natalizumab-associated progressive multifocal leukoencephalopathy. Mult. Scler. J. 19, 1826–1840 (2013).

  137. 137.

    et al. Punctate lesion pattern suggestive of perivascular inflammation in acute natalizumab-associated progressive multifocal leukoencephalopathy: productive JC virus infection or preclinical PML-IRIS manifestation? J. Neurol. Neurosurg. Psychiatry 84, 1176–1177 (2013).

  138. 138.

    et al. Magnetic resonance imaging pattern in natalizumab-associated progressive multifocal leukoencephalopathy. Ann. Neurol. 72, 779–787 (2012).

  139. 139.

    et al. MRI pattern in asymptomatic natalizumab-associated PML. J. Neurol. Neurosurg. Psychiatry 86, 793–798 (2015).

  140. 140.

    et al. MRI criteria differentiating asymptomatic PML from new MS lesions during natalizumab pharmacovigilance. J. Neurol. Neurosurg. Psychiatry 87, 1138–1145 (2016).

  141. 141.

    Neuroimaging in mitochondrial disorders. Neurotherapeutics 10, 273–285 (2013).

  142. 142.

    , & Neuroimaging of natalizumab complications in multiple sclerosis: PML and other associated entities. Mult. Scler. Int. 2015, 809252 (2015).

  143. 143.

    et al. Brain histopathology in patients with systemic lupus erythematosus: identification of lesions associated with clinical neuropsychiatric lupus syndromes and the role of complement. Rheumatology 56, 77–86 (2017).

  144. 144.

    & Imaging manifestations of the leukodystrophies, inherited disorders of white matter. Radiol. Clin. North Am. 52, 279–319 (2014).

  145. 145.

    et al. Adult onset leukodystrophy with neuroaxonal spheroids and demyelinating plaque-like lesions. Neuropathology 32, 285–292 (2012).

  146. 146.

    & Acute disseminated encephalomyelitis: current knowledge and open questions. J. Neurovirol. 21, 473–479 (2015).

  147. 147.

    , & Central pontine myelinolysis: a metabolic disorder of myelin. J. Neuropsychiatry Clin. Neurosci. 23, 369–374 (2011).

  148. 148.

    et al. Thalamic lesions: a radiological review. Behav. Neurol. 2014, 154631 (2014).

  149. 149.

    et al. Adult-onset genetic leukoencephalopathies: a MRI pattern-based approach in a comprehensive study of 154 patients. Brain 138, 284–292 (2015).

  150. 150.

    et al. MR imaging findings in alcoholic and nonalcoholic acute Wernicke's encephalopathy: a review. Biomed. Res. Int. 2014, 503596 (2014).

  151. 151.

    , & Overview of neurosarcoidosis: recent advances. J. Neurol. 262, 258–267 (2015).

  152. 152.

    , , , & Differential diagnosis of posterior fossa multiple sclerosis lesions—neuroradiological aspects. Neurol. Sci. 22 (Suppl. 2), S79–S83 (2001).

  153. 153.

    , , , & Neuroimaging and clinical features in type II (late-onset) Alexander disease. Neurology 82, 49–56 (2014).

  154. 154.

    et al. The spectrum of magnetic resonance findings in cerebrotendinous xanthomatosis: redefinition and evidence of new markers of disease progression. J. Neurol. 264, 862–874 (2017).

  155. 155.

    & Tumefactive demyelinating lesions in multiple sclerosis and associated disorders. Curr. Neurol. Neurosci. Rep. 16, 26 (2016).

  156. 156.

    et al. Distinguishing tumefactive demyelinating lesions from glioma or central nervous system lymphoma: added value of unenhanced CT compared with conventional contrast-enhanced MR imaging. Radiology 251, 467–475 (2009).

  157. 157.

    et al. Widespread inflammation in CLIPPERS syndrome indicated by autopsy and ultra-high-field 7T MRI. Neurol. Neuroimmunol. Neuroinflamm. 3, e226 (2016).

  158. 158.

    , & Lyme neuroborreliosis-epidemiology, diagnosis and management. Nat. Rev. Neurol. 11, 446–456 (2015).

  159. 159.

    et al. Characteristics of Susac syndrome: a review of all reported cases. Nat. Rev. Neurol. 9, 307–316 (2013).

  160. 160.

    et al. Bilateral trigeminal enhancement on magnetic resonance imaging in a patient with multiple sclerosis and trigeminal neuralgia. Mult. Scler. 13, 814–816 (2007).

  161. 161.

    , & Correlation of MR imaging findings and clinical manifestations in neurosarcoidosis. AJNR Am. J. Neuroradiol. 30, 953–961 (2009).

  162. 162.

    et al. Leptomeningeal gadolinium enhancement across the spectrum of chronic neuroinflammatory diseases. Neurology 88, 1439–1444 (2017).

  163. 163.

    et al. Central canal enhancement and the trident sign in spinal cord sarcoidosis. Neurology 87, 743–744 (2016).

  164. 164.

    et al. Specific pattern of gadolinium enhancement in spondylotic myelopathy. Ann. Neurol. 76, 54–65 (2014).

  165. 165.

    , & Differential diagnosis of T2 hyperintense spinal cord lesions: part A. J. Med. Imag. Radiat. Oncol. 52, 535–543 (2008).

  166. 166.

    et al. Myeloneuropathy due to copper deficiency: clinical and MRI findings after copper supplementation. Neurol. Sci. 30, 521–524 (2009).

  167. 167.

    , , & Imaging features of copper deficiency myelopathy: a study of 25 cases. Neuroradiology 48, 78–83 (2006).

  168. 168.

    , , , & Spine MR imaging features of subacute combined degeneration patients. Eur. Spine J. 23, 1052–1058 (2014).

  169. 169.

    et al. Progressive solitary sclerosis: Gradual motor impairment from a single CNS demyelinating lesion. Neurology 87, 1713–1719 (2016).

  170. 170.

    et al. Using atypical symptoms and red flags to identify non-demyelinating disease. J. Neurol. Neurosurg. Psychiatry 83, 44–48 (2012).

  171. 171.

    et al. Clinical analysis of anti-Ma2-associated encephalitis. Brain 127, 1831–1844 (2004).

  172. 172.

    et al. DARS-associated leukoencephalopathy can mimic a steroid-responsive neuroinflammatory disorder. Neurology 84, 226–230 (2015).

Download references


The authors would like to thank Ricardo Franca for his help with the design of Figure 2.

Author information


  1. Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, Oxford, UK.

    • Ruth Geraldes
    •  & Jacqueline Palace
  2. University College London, London, UK.

    • Olga Ciccarelli
    •  & Frederik Barkhof
  3. National Institute for Health Research, University College London Hospitals Biomedical Research Centre, London, UK.

    • Olga Ciccarelli
    •  & Frederik Barkhof
  4. Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, Netherlands.

    • Frederik Barkhof
  5. Neurology and Neurometabolic Unit, Department of Neurological and Behavioural Sciences, University of Siena, Siena, Italy.

    • Nicola De Stefano
  6. Department of Neurology, Medical University of Graz, Graz, Austria.

    • Christian Enzinger
    •  & Franz Fazekas
  7. Division of Neuroradiology, Vascular and Interventional Radiology, Medical University of Graz, Graz, Austria.

    • Christian Enzinger
  8. Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.

    • Massimo Filippi
    •  & Paolo Preziosa
  9. Neuropathology Department, John Radcliffe Hospital, Oxford, UK.

    • Monika Hofer
  10. NeuroCure Clinical Research Center and Experimental and Clinical Research Center, Max Delbrück Center for Molecular Medicine and Charité – Universitätsmedizin Berlin, Berlin, Germany.

    • Friedemann Paul
  11. Magnetic Resonance Unit, Department of Radiology, Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona, Barcelona, Spain.

    • Alex Rovira
  12. Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, Oxford, UK.

    • Gabriele C. DeLuca
  13. Department of Neurology, University Hospital Basel, Basel, Switzerland.

    • Ludwig Kappos
  14. Institute of Neurology, Queen Square, London, UK.

    • Tarek Yousry
  15. Department of Neurology, Rigshospitalet Glostrup and University of Copenhagen, Copenhagen, Denmark.

    • Jette Frederiksen
  16. Multiple Sclerosis Centre, Department of Neurosciences, San Camillo-Forlanini Hospital, Rome, Italy.

    • Claudio Gasperini
  17. Centre d'Esclerosi Multiple de Catalunya (Cemcat), Department of Neurology/Neuroimmunology, Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona, Barcelona, Spain.

    • Jaume Sastre-Garriga
  18. Division of Neurosciences, School of Medicine, University of Nottingham, Queen's Medical Centre Campus, Nottingham, UK.

    • Nikos Evangelou


  1. on behalf of the MAGNIMS study group


  1. Search for Ruth Geraldes in:

  2. Search for Olga Ciccarelli in:

  3. Search for Frederik Barkhof in:

  4. Search for Nicola De Stefano in:

  5. Search for Christian Enzinger in:

  6. Search for Massimo Filippi in:

  7. Search for Monika Hofer in:

  8. Search for Friedemann Paul in:

  9. Search for Paolo Preziosa in:

  10. Search for Alex Rovira in:

  11. Search for Gabriele C. DeLuca in:

  12. Search for Ludwig Kappos in:

  13. Search for Tarek Yousry in:

  14. Search for Franz Fazekas in:

  15. Search for Jette Frederiksen in:

  16. Search for Claudio Gasperini in:

  17. Search for Jaume Sastre-Garriga in:

  18. Search for Nikos Evangelou in:

  19. Search for Jacqueline Palace in:


R.G., O.C., F.B., C.E., M.H., F.P., P.P., A.R., N.E. and J.P. researched data for the article. R.G., O.C., F.B., M.F., F.P., P.P., A.R., N.E. and J.P. made substantial contributions to discussion of the content. R.G., O.C., F.B., F.P., P.P., N.E. and J.P. wrote the article. All authors reviewed and edited the article before submission.

Competing interests

M.H., G.C.D. and F.F. declare no competing interests. R.G. has received support for scientific meetings and courses and honoraria for advisory work from Bayer, Biogen, Merck, Novartis. O.C. serves as a consultant for Biogen, Novartis and General Electric, for which honoraria are all paid to the University College London Institute of Neurology. F.B. serves as a consultant for Biogen, Bayer, Genzyme, Jansen Research, Merck, Novartis, Roche, Synthon BV and Teva. N.D.S. has received honoraria from Biogen, Genzyme, Merck, Novartis, Schering and Teva for consulting services, speaking and travel support. He serves on advisory boards for Biogen, Merck and Novartis. C.E. has received funding for travel and speaker honoraria from Biogen, Bayer, Genzyme, Merck, Novartis, Shire and Teva, funding for research from Biogen, Merck and Teva, and has served on scientific advisory boards for Bayer, Biogen, Merck, Novartis, Roche and Teva. M.F. serves on a scientific advisory board for Teva, has received compensation for consulting services and/or speaking activities from Biogen, Merck, Novartis and Teva, and has received research support from Biogen, Novartis and Teva. F.P. has served on scientific advisory boards for MedImmune and the Novartis OCTIMS study, has received travel funding and/or speaker honoraria from Alexion-Chugai, Bayer, Biogen, MedImmune, Merck, Novartis, Sanofi, Shire Pharmaceuticals and Teva, has consulted for Alexion, Biogen, MedImmune, Sanofi and Shire Pharmaceuticals, and has received research support from Alexion, Bayer, Biogen, Merck, Novartis, Sanofi and Teva. P.P. has received speaker honoraria from Biogen, EXCEMED and Novartis. A.R. serves on scientific advisory boards for Novartis, OLEA Medical and Sanofi, has received speaker honoraria from Bayer, Biogen, Bracco, Merck, Novartis, Roche, Sanofi and Teva, and has research agreements with Siemens AG. L.K.'s institute (University Hospital Basel, Switzerland) has received, and used exclusively for research support, steering committee, advisory board and consultancy fees from Actelion, Addex, Bayer, Biogen, Biotica, Genzyme, Eli-Lilly, Merck, Mitsubishi, Novartis, Ono Pharma, Pfizer, Receptos, Sanofi, Santhera, Siemens, Teva, UCB and XenoPort, speaker fees from Bayer, Biogen, Merck, Novartis, Sanofi and Teva, support of educational activities from Bayer, Biogen, CSL Behring, Genzyme, Merck, Novartis, Sanofi and Teva, royalties from Neurostatus, and grants from Bayer Healthcare, Biogen, Merck, Novartis, Roche and Roche Research Foundations.T.Y. has received consultant, clinical trial or travel fees from Biogen, the European Society of Radiology, GlaxoSmithKline, IXICO, Novartis and Merck. J.F. has served on scientific advisory boards for, and received funding of travel for participation in scientific advisory boards and honoraria from, Biogen, Genzyme, Merck, Novartis, Sanofi, Takeda and Teva. C.G. has received compensation for consulting from Bayer and Biogen, and speaker fees for lectures from Biogen, Bayer, Genzyme, Merck, Novartis and Teva. C.G. has received speaker fees from Bayer, Biogen, Genzyme, Merck and Teva. J.S.-G. has received compensation for serving on scientific advisory boards or on speaker bureaus from Biogen, Merck, Novartis, Sanofi and Teva. N.E. has received honoraria from Biogen, Genzyme and Novartis for consulting services, speaking and travel support. He serves on advisory boards for Biogen, Merck and Novartis. J.P. has received support for scientific meetings and honoraria for advisory work from ABIDE, Alexion, Biogen, Bayer, Chugai Pharma, MedImmune, Merck, Novartis, Roche and Teva, and unrestricted grants from Bayer, Biogen, Merck and Novartis.

Corresponding author

Correspondence to Jacqueline Palace.


Dawson fingers

Elongated lesions along the subependymal veins, and thus perpendicular to the walls of the lateral ventricles, that are characteristic of MS.


Small (3–15 mm diameter) round or ovoid subcortical infarcts in the territory of one perforating arteriole with an MRI signal similar to that of CSF.


Short association fibres that connect adjacent gyri of the brain, located within the cortex or immediately beneath it in the outermost parts of the subcortical white matter.

About this article

Publication history