MRI criteria for the diagnosis of multiple sclerosis: MAGNIMS consensus guidelines
Open accessAbstract
In patients presenting with a clinically isolated syndrome, MRI can support and substitute clinical information in the diagnosis of multiple sclerosis by showing disease dissemination in space and time and by helping to exclude disorders that can mimic multiple sclerosis. MRI criteria were first included in the diagnostic work-up for multiple sclerosis in 2001, and since then several modifications to the criteria have been proposed in an attempt to simplify lesion-count models for showing disease dissemination in space, change the timing of MRI scanning to show dissemination in time, and increase the value of spinal cord imaging. Since the last update of these criteria, new data on the use of MRI to establish dissemination in space and time have become available, and MRI technology has improved. State-of-the-art MRI findings in these patients were discussed in a MAGNIMS workshop, the goal of which was to provide an evidence-based and expert-opinion consensus on proposed modifications to MRI criteria for the diagnosis of multiple sclerosis.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Routine imaging of the whole spinal cord in all patients with suspected MS has recently been proposed.
“Therefore routine imaging of the whole spinal cord in all patients with suspected MS has recently been proposed.68”
From Diagnosis of multiple sclerosis: progress and challenges (2017) · cites this paper as [68]
The Methods section (‘Spinal cord imaging’; page unavailable) recommends imaging the entire cord when spinal cord MRI is used to assess dissemination in space. It recommends spinal cord imaging at symptom onset for specified patient groups, however, not routinely for all patients with suspected MS. (LLM, conf=0.88)
Experimental — accuracy not yet measuredDespite the current usefulness of the McDonald criteria, the MAGNIMS network have recently proposed a number of modifications, such as inclusion of optic nerve, cortical and symptomatic lesions in dissemination in space and standardisation of dissemination in space criteria for RRMS, PPMS and RIS.
“Despite the current usefulness of the McDonald criteria, the MAGNIMS network have recently proposed a number of modifications, such as inclusion of optic nerve, cortical and symptomatic lesions in dissemination in space and standardisation of dissemination in space criteria for RRMS, PPMS and RIS.68”
From Diagnosis of multiple sclerosis: progress and challenges (2017) · cites this paper as [68]
Cortical grey matter lesions may be helpful in making a diagnosis of MS.
“Cortical grey matter lesions may be helpful in making a diagnosis of MS 68,73”
From Diagnosis of multiple sclerosis: progress and challenges (2017) · cites this paper as [68]
Cortical grey matter is frequently involved in MS pathologically.
“Cortical grey matter is frequently involved in MS pathologically”
From Diagnosis of multiple sclerosis: progress and challenges (2017) · cites this paper as [68]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria
Polman, C. H., Reingold, S. C., Banwell, B., Clanet, M., Cohen, J. A., Filippi, M., Fujihara, K., Havrdova, E., Hutchinson, M., Kappos, L., et al. (2011) · Annals of Neurology · doi:10.1002/ana.22366 · Cited by 9,802 · see citing works
Self-citationPeterson, J. W., Bö, L., Mörk, S., Chang, A., & Trapp, B. D. (2001) · Annals of Neurology · doi:10.1002/ana.1123 · Cited by 1,403 · see citing works
MRI criteria for MS in patients with clinically isolated syndromes
Montalban, X., Tintoré, M., Swanton, J., Barkhof, F., Fazekas, F., Filippi, M., Frederiksen, J., Kappos, L., Palace, J., Polman, C., et al. (2010) · Neurology · doi:10.1212/wnl.0b013e3181cec45c · Cited by 252 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 90
- [1]McDonald WI Compston A Edan G Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the diagnosis of multiple sclerosis Ann Neurol 2001 50 1 121 7 11456302
- [2]Paty DW Oger JJ Kastrukoff LF MRI in the diagnosis of MS: a prospective study with comparison of clinical evaluation, evoked potentials, oligoclonal banding, and CT Neurology 1988 38 2 180 5 3340277
- [3]Fazekas F Offenbacher H Fuchs S Criteria for an increased specificity of MRI interpretation in elderly subjects with suspected multiple sclerosis Neurology 1988 38 12 1822 5 3057397
- [4]Barkhof F Filippi M Miller DH Comparison of MRI criteria at first presentation to predict conversion to clinically definite multiple sclerosis Brain 1997 120 Pt 11 2059 69 9397021
- [5]Swanton JK Fernando K Dalton CM Modification of MRI criteria for multiple sclerosis in patients with clinically isolated syndromes J Neurol Neurosurg Psychiatry 2006 77 7 830 3 16043456 PMC2117493
- [6]Swanton JK Rovira A Tintore M MRI criteria for multiple sclerosis in patients presenting with clinically isolated syndromes: a multicentre retrospective study Lancet Neurol 2007 6 8 677 86 17616439
- [7]Rovira A Swanton J Tintore M A single, early magnetic resonance imaging study in the diagnosis of multiple sclerosis Arch Neurol 2009 66 5 587 92 19433658
- [8]Polman CH Reingold SC Edan G Diagnostic criteria for multiple sclerosis: 2005 revisions to the “McDonald Criteria” Ann Neurol 2005 58 6 840 6 16283615
- [11]Rovira A Wattjes MP Tintore M Evidence-based guidelines: MAGNIMS consensus guidelines on the use of MRI in multiple sclerosis-clinical implementation in the diagnostic process Nat Rev Neurol 2015 11 8 471 82 26149978
- [12]Tintoré M Rovira A Río J Factors that determine disease course: the symptomatic lesion matters. 1000 CIS subgroup analysis ECTRIMS conference 2014 P759
- [13]Caucheteux N Maarouf A Genevray M Criteria improving multiple sclerosis diagnosis at the first MRI J Neurol 2015 262 4 979 87 25683762
- [15]Kang H Metz LM Traboulsee AL 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 2014 20 4 458 63 23970502
- [16]Sombekke MH Wattjes MP Balk LJ Spinal cord lesions in patients with clinically isolated syndrome: A powerful tool in diagnosis and prognosis Neurology 2013 80 1 69 75 23243070
- [17]Bot JC Barkhof F Polman CH Spinal cord abnormalities in recently diagnosed MS patients: added value of spinal MRI examination Neurology 2004 62 2 226 33 14745058
- [18]Weier K Mazraeh J Naegelin Y Biplanar MRI for the assessment of the spinal cord in multiple sclerosis Mult Scler 2012 18 11 1560 9 22539086
- [19]Nair G Absinta M Reich DS Optimized T1-MPRAGE sequence for better visualization of spinal cord multiple sclerosis lesions at 3T AJNR Am J Neuroradiol 2013 34 11 2215 22 23764721 PMC4278432
- [20]Kelly SB Kinsella K Duggan M Tubridy N McGuigan C Hutchinson M A proposed modification to the McDonald 2010 criteria for the diagnosis of primary progressive multiple sclerosis Mult Scler 2013 19 8 1095 100 23132903
- [21]Bigi S Marrie RA Verhey L Yeh EA Banwell B 2010 McDonald criteria in a pediatric cohort: is positivity at onset associated with a more aggressive multiple sclerosis course? Mult Scler 2013 19 10 1359 62 23620544
- [22]Hummel HM Bruck W Dreha-Kulaczewski S Gartner J Wuerfel J Pediatric onset multiple sclerosis: McDonald criteria 2010 and the contribution of spinal cord MRI Mult Scler 2013 19 10 1330 5 23828866
- [23]Sadaka Y Verhey LH Shroff MM 2010 McDonald criteria for diagnosing pediatric multiple sclerosis Ann Neurol 2012 72 2 211 23 22926854
- [24]Tantsis EM Prelog K Brilot F Dale RC Risk of multiple sclerosis after a first demyelinating syndrome in an Australian Paediatric cohort: clinical, radiological features and application of the McDonald 2010 MRI criteria Mult Scler 2013 19 13 1749 59 23579092
- [25]Kornek B Schmitl B Vass K Evaluation of the 2010 McDonald multiple sclerosis criteria in children with a clinically isolated syndrome Mult Scler 2012 18 12 1768 74 22526931
- [26]Williams MT Tapos DO Juhasz C Use of the 2010 McDonald criteria can facilitate early diagnosis of pediatric multiple sclerosis in a predominantly black cohort Pediatr Neurol 2014 51 6 826 30 25283753
- [27]Banwell B Bar-Or A Arnold DL Clinical, environmental, and genetic determinants of multiple sclerosis in children with acute demyelination: a prospective national cohort study Lancet Neurol 2011 10 5 436 45 21459044
- [28]Huh SY Kim SH Kim W Evaluation of McDonald MRI criteria for dissemination in space in Korean patients with clinically isolated syndromes Mult Scler 2014 20 4 492 5 23886829
- [29]Hsueh CJ Kao HW Chen SY Comparison of the 2010 and 2005 versions of the McDonald MRI criteria for dissemination-in-time in Taiwanese patients with classic multiple sclerosis J Neurol Sci 2013 329 1–2 51 4 23597668
- [30]Patrucco L Rojas JI Miguez JS Cristiano E Application of the McDonald 2010 criteria for the diagnosis of multiple sclerosis in an Argentinean cohort of patients with clinically isolated syndromes Mult Scler 2013 19 10 1297 301 23388165
- [31]Belova AN Shalenkov IV Shakurova DN Boyko AN Revised McDonald criteria for multiple sclerosis diagnostics in central Russia: sensitivity and specificity Mult Scler 2014 20 14 1896 9 25145690
- [32]Absinta M Rocca MA Colombo B Patients with migraine do not have MRI-visible cortical lesions J Neurol 2012 259 2695 8 22714135
- [33]Ruet A Arrambide G Brochet B Early predictors of multiple sclerosis after a typical clinically isolated syndrome Mult Scler 2014 20 13 1721 6 24842960
- [34]Ruet A Deloire MS Ouallet JC Molinier S Brochet B Predictive factors for multiple sclerosis in patients with clinically isolated spinal cord syndrome Mult Scler 2011 17 3 312 8 21071465
- [35]Moraal B Pohl C Uitdehaag BM Magnetic resonance imaging predictors of conversion to multiple sclerosis in the BENEFIT study Arch Neurol 2009 66 11 1345 52 19901165
- [36]Kim SS Richman DP Johnson WO Hald JK Agius MA 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 2014 20 1 57 63 23736535
- [37]Verhey LH Branson HM Shroff MM MRI parameters for prediction of multiple sclerosis diagnosis in children with acute CNS demyelination: a prospective national cohort study Lancet Neurol 2011 10 12 1065 73 22067635
- [38]Miller D Barkhof F Montalban X Thompson A Filippi M Clinically isolated syndromes suggestive of multiple sclerosis, part I: natural history, pathogenesis, diagnosis, and prognosis Lancet Neurol 2005 4 5 281 8 15847841
- [39]Tintore M Rovira A Rio J Defining high, medium and low impact prognostic factors for developing multiple sclerosis Brain 2015 138 1863 74 25902415
- [40]Kuhle J Disanto G Dobson R Conversion from clinically isolated syndrome to multiple sclerosis: A large multicentre study Mult Scler 2015 8 21 1013 24 25680984
- [41]Sorensen TL Frederiksen JL Bronnum-Hansen H Petersen HC Optic neuritis as onset manifestation of multiple sclerosis: a nationwide, long-term survey Neurology 1999 53 3 473 8 10449106
- [42]Tintore M Rovira A Rio J Is optic neuritis more benign than other first attacks in multiple sclerosis? Ann Neurol 2005 57 2 210 5 15668965
- [43]Wilejto M Shroff M Buncic JR Kennedy J Goia C Banwell B The clinical features, MRI findings, and outcome of optic neuritis in children Neurology 2006 67 2 258 62 16864818
- [44]Kidd D Barkhof F McConnell R Algra PR Allen IV Revesz T Cortical lesions in multiple sclerosis Brain 1999 122 Pt 1 17 26 10050891
- [46]Bo L Vedeler CA Nyland HI Trapp BD Mork SJ Subpial demyelination in the cerebral cortex of multiple sclerosis patients J Neuropathol Exp Neurol 2003 62 7 723 32 12901699
- [47]Geurts JJ Pouwels PJ Uitdehaag BM Polman CH Barkhof F Castelijns JA Intracortical lesions in multiple sclerosis: improved detection with 3D double inversion-recovery MR imaging Radiology 2005 236 1 254 60 15987979
- [48]Nelson F Poonawalla AH Hou P Huang F Wolinsky JS Narayana PA Improved identification of intracortical lesions in multiple sclerosis with phase-sensitive inversion recovery in combination with fast double inversion recovery MR imaging AJNR Am J Neuroradiol 2007 28 9 1645 9 17885241 PMC8134176
- [49]Sethi V Yousry TA Muhlert N Improved detection of cortical MS lesions with phase-sensitive inversion recovery MRI J Neurol Neurosurg Psychiatry 2012 83 9 877 82 22807559
- [50]Favaretto A Poggiali D Lazzarotto A Rolma G Causin F Gallo P The Parallel Analysis of Phase Sensitive Inversion Recovery (PSIR) and Double Inversion Recovery (DIR) Images Significantly Improves the Detection of Cortical Lesions in Multiple Sclerosis (MS) since Clinical Onset PLoS One 2015 10 5 e0127805 26010425 PMC4444021
- [51]Nelson F Poonawalla A Hou P Wolinsky JS Narayana PA 3D MPRAGE improves classification of cortical lesions in multiple sclerosis Mult Scler 2008 14 9 1214 9 18952832 PMC2650249
- [52]Seewann A Vrenken H Kooi EJ Imaging the tip of the iceberg: visualization of cortical lesions in multiple sclerosis Mult Scler 2011 17 1202 10 21561955
- [53]Seewann A Kooi EJ Roosendaal SD Postmortem verification of MS cortical lesion detection with 3D DIR Neurology 2012 78 5 302 8 22218278
- [54]Calabrese M De Stefano N Atzori M Detection of cortical inflammatory lesions by double inversion recovery magnetic resonance imaging in patients with multiple sclerosis Arch Neurol 2007 64 10 1416 22 17923625
- [55]Filippi M Rocca MA Calabrese M Intracortical lesions: relevance for new MRI diagnostic criteria for multiple sclerosis Neurology 2010 75 22 1988 94 21115953
- [56]Calabrese M Oh MS Favaretto A No MRI evidence of cortical lesions in neuromyelitis optica Neurology 2012 79 16 1671 6 22993282
- [57]Geurts JJ Roosendaal SD Calabrese M Consensus recommendations for MS cortical lesion scoring using double inversion recovery MRI Neurology 2011 76 5 418 24 21209373
- [58]van Walderveen MA Kamphorst W Scheltens P Histopathologic correlate of hypointense lesions on T1-weighted spin-echo MRI in multiple sclerosis Neurology 1998 50 5 1282 8 9595975
- [59]Giorgio A Stromillo ML Bartolozzi ML Relevance of hypointense brain MRI lesions for long-term worsening of clinical disability in relapsing multiple sclerosis Mult Scler 2014 20 2 214 9 23877971
- [60]Enzinger C Fuchs S Pichler A Predicting the severity of relapsing-remitting MS: the contribution of cross-sectional and short-term follow-up MRI data Mult Scler 2011 17 6 695 701 21228028
- [61]Mitjana R Tintore M Rocca MA Diagnostic value of brain chronic black holes on T1-weighted MR images in clinically isolated syndromes Mult Scler 2014 20 11 1471 7 24576831
- [62]Sastre-Garriga J Tintore M Rovira A Specificity of Barkhof criteria in predicting conversion to multiple sclerosis when applied to clinically isolated brainstem syndromes Arch Neurol 2004 61 2 222 4 14967770
- [63]Montalban X Sastre-Garriga J Filippi M Primary progressive multiple sclerosis diagnostic criteria: a reappraisal Mult Scler 2009 15 12 1459 65 19995843
- [64]Okuda DT Mowry EM Beheshtian A Incidental MRI anomalies suggestive of multiple sclerosis: the radiologically isolated syndrome Neurology 2009 72 9 800 5 19073949
- [65]Okuda DT Unanticipated demyelinating pathology of the CNS Nat Rev Neurol 2009 5 11 591 7 19806149
- [66]Stromillo ML Giorgio A Rossi F Brain metabolic changes suggestive of axonal damage in radiologically isolated syndrome Neurology 2013 80 23 2090 4 23635962
- [67]Giorgio A Stromillo ML Rossi F Cortical lesions in radiologically isolated syndrome Neurology 2011 77 1896 9 22076541
- [68]Okuda DT Siva A Kantarci O Radiologically isolated syndrome: 5-year risk for an initial clinical event PLoS One 2014 9 3 e90509 24598783 PMC3943959
- [69]Lebrun C Bensa C Debouverie M Association between clinical conversion to multiple sclerosis in radiologically isolated syndrome and magnetic resonance imaging, cerebrospinal fluid, and visual evoked potential: follow-up of 70 patients Arch Neurol 2009 66 7 841 6 19597085
- [70]Okuda DT Mowry EM Cree BA Asymptomatic spinal cord lesions predict disease progression in radiologically isolated syndrome Neurology 2011 76 8 686 92 21270417 PMC3053327
- [71]Charil A Yousry TA Rovaris M MRI and the diagnosis of multiple sclerosis: expanding the concept of “no better explanation” Lancet Neurol 2006 5 10 841 52 16987731
- [72]Miller DH Weinshenker BG Filippi M Differential diagnosis of suspected multiple sclerosis: a consensus approach Mult Scler 2008 14 9 1157 74 18805839 PMC2850590
- [73]Aliaga ES Barkhof F MRI mimics of multiple sclerosis Handbook of clinical neurology 2014 122 291 316 24507523
- [74]Kim HJ Paul F Lana-Peixoto MA MRI characteristics of neuromyelitis optica spectrum disorder: an international update Neurology 2015 84 11 1165 73 25695963 PMC4371410
- [75]Wingerchuk DM Banwell B Bennett JL International consensus diagnostic criteria for neuromyelitis optica spectrum disorders Neurology 2015 14 177 89 26092914 PMC4515040
- [76]Wattjes MP Lutterbey GG Harzheim M Higher sensitivity in the detection of inflammatory brain lesions in patients with clinically isolated syndromes suggestive of multiple sclerosis using high field MRI: an intraindividual comparison of 1.5 T with 3.0 T Eur Radiol 2006 16 9 2067 73 16649033
- [77]Nielsen K Rostrup E Frederiksen JL Magnetic resonance imaging at 3.0 tesla detects more lesions in acute optic neuritis than at 1. 5 tesla Invest Radiol 2006 41 2 76 82 16428976
- [78]Simon B Schmidt S Lukas C Improved in vivo detection of cortical lesions in multiple sclerosis using double inversion recovery MR imaging at 3 Tesla Eur Radiol 2010 20 7 1675 83 20094887 PMC2882050
- [79]Wattjes MP Harzheim M Lutterbey GG Does high field MRI allow an earlier diagnosis of multiple sclerosis? J Neurol 2008 255 8 1159 63 18446305
- [80]Mistry N Tallantyre EC Dixon JE Focal multiple sclerosis lesions abound in ‘normal appearing white matter’ Mult Scler 2011 17 11 1313 23 21788249
- [81]Ge Y Zohrabian VM Grossman RI Seven-Tesla magnetic resonance imaging: new vision of microvascular abnormalities in multiple sclerosis Arch Neurol 2008 65 6 812 6 18541803 PMC2579786
- [82]Hammond KE Metcalf M Carvajal L Quantitative in vivo magnetic resonance imaging of multiple sclerosis at 7 Tesla with sensitivity to iron Ann Neurol 2008 64 6 707 13 19107998
- [83]Tallantyre EC Brookes MJ Dixon JE Morgan PS Evangelou N Morris PG Demonstrating the perivascular distribution of MS lesions in vivo with 7-Tesla MRI Neurology 2008 70 22 2076 8 18505982
- [84]Tallantyre EC Morgan PS Dixon JE A comparison of 3T and 7T in the detection of small parenchymal veins within MS lesions Invest Radiol 2009 44 9 491 4 19652606
- [85]Kilsdonk ID Lopez-Soriano A Kuijer JP Morphological features of MS lesions on FLAIR* at 7 T and their relation to patient characteristics J Neurol 2014 261 7 1356 64 24777693
- [86]Tan IL van Schijndel RA Pouwels PJ MR venography of multiple sclerosis AJNR Am J Neuroradiol 2000 21 6 1039 42 10871010 PMC7973892
- [87]Sati P George IC Shea CD Gaitan MI Reich DS FLAIR*: a combined MR contrast technique for visualizing white matter lesions and parenchymal veins Radiology 2012 265 3 926 32 23074257 PMC3504317
- [88]Mainero C Benner T Radding A In vivo imaging of cortical pathology in multiple sclerosis using ultra-high field MRI Neurology 2009 73 12 941 8 19641168 PMC2754332
- [89]Tallantyre EC Dixon JE Donaldson I Ultra-high-field imaging distinguishes MS lesions from asymptomatic white matter lesions Neurology 2011 76 6 534 9 21300968 PMC3053180
- [90]Gaitan MI Sati P Inati SJ Reich DS Initial investigation of the blood-brain barrier in MS lesions at 7 tesla Mult Scler 2013 19 1068 73 23246799 PMC4744645
- [91]Absinta M Sati P Gaitan MI Seven-tesla phase imaging of acute multiple sclerosis lesions: A new window into the inflammatory process Ann Neurol 2013 74 5 669 78 23813441 PMC3812397
- [92]Sinnecker T Dorr J Pfueller CF Distinct lesion morphology at 7-T MRI differentiates neuromyelitis optica from multiple sclerosis Neurology 2012 79 7 708 14 22855861
- [93]Wuerfel J Sinnecker T Ringelstein EB Lesion morphology at 7 Tesla MRI differentiates Susac syndrome from multiple sclerosis Mult Scler 2012 18 11 1592 9 22711711
- [94]Bian W Harter K Hammond-Rosenbluth KE A serial in vivo 7T magnetic resonance phase imaging study of white matter lesions in multiple sclerosis Mult Scler 2012 19 1 69 75 22641301
Cited by
Sorted by citations
Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria
Thompson, A. J., Banwell, B. L., Barkhof, F., Carroll, W. M., Coetzee, T., Comi, G., Correale, J., Fazekas, F., Filippi, M., Freedman, M. S., et al. (2018) · The Lancet Neurology · doi:10.1016/s1474-4422(17)30470-2 · Cited by 8,167 · see citing works
Self-citationTreatment of Multiple Sclerosis: A Review
Hauser, S. L., & Cree, B. A. C. (2020) · The American Journal of Medicine · doi:10.1016/j.amjmed.2020.05.049 · Cited by 969 · see citing works
Diagnosis of multiple sclerosis: progress and challenges
Brownlee, W. J., Hardy, T. A., Fazekas, F., & Miller, D. H. (2017) · The Lancet · doi:10.1016/s0140-6736(16)30959-x · Cited by 701 · see citing works
Eitel, F., Soehler, E., Bellmann-Strobl, J., Brandt, A. U., Ruprecht, K., Giess, R. M., Kuchling, J., Asseyer, S., Weygandt, M., Haynes, J.-D., et al. (2019) · NeuroImage: Clinical · doi:10.1016/j.nicl.2019.102003 · Cited by 171 · see citing works
Atypical inflammatory demyelinating syndromes of the CNS
Hardy, T. A., Reddel, S. W., Barnett, M. H., Palace, J., Lucchinetti, C. F., & Weinshenker, B. G. (2016) · The Lancet Neurology · doi:10.1016/s1474-4422(16)30043-6 · Cited by 161 · see citing works
Self-citationBorrelli, S., Martire, M. S., Stölting, A., Vanden Bulcke, C., Pedrini, E., Guisset, F., Bugli, C., Yildiz, H., Pothen, L., Elands, S., et al. (2024) · Neurology Neuroimmunology & Neuroinflammation · doi:10.1212/nxi.0000000000200253 · Cited by 61 · see citing works
Self-citationŞahin (2024) · doi:10.1002/brb3.3587 · Cited by 5 · see citing works
Aldraihem, M., Alyami, W., AlQahtani, E., Saeed, L., AlDosary, R., Altowaijri, G., & Almutlaq, A. (2025) · Multiple Sclerosis and Related Disorders · doi:10.1016/j.msard.2025.106779
- Authors
- Filippi, M., Rocca, M. A., Ciccarelli, O., De Stefano, N., Evangelou, N., Kappos, L., Rovira, A., Sastre-Garriga, J., Tintorè, M., Frederiksen, J. L., Gasperini, C., Palace, J., Reich, D. S., Banwell, B., Montalban, X., & Barkhof, F.
- Affiliations
- Vita-Salute San Raffaele University (IT)
- National Institute for Health and Care Research (GB)
- University of Nottingham (GB)
- University of Basel (CH)
- University of Copenhagen (DK)
- Azienda Ospedaliera San Camillo-Forlanini (IT)
- University of Oxford (GB)
- National Institutes of Health (US)
- Children's Hospital of Philadelphia (US)
- Amsterdam UMC Location Vrije Universiteit Amsterdam (NL)
- Corresponding author
- Filippi, Massimo
- ORCID
- Venue
- The Lancet Neurology
- Publisher
- Elsevier BV
- Published
- 2016-03
- Volume
- 15
- Issue
- 3
- Pages
- 292-303
- ISSN
- 1474-4422 (ISSN-L)
- PMC
- PMC4760851
- OpenAlex
- W2280334572
- Cited by
- 880
- References
- 3
- Citations by year
- 2026: 60 · 2025: 62 · 2024: 65 · 2023: 80 · 2022: 66 · 2021: 96 · 2020: 82 · 2019: 103 · 2018: 127 · 2017: 98 · 2016: 38 · 2015: 1 · 2012: 1
- FWCI
- 19.16
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- cc-by-nc-nd
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- Locations
- The Lancet Neurology (publishedVersion)
- PubMed (publishedVersion)
- Pure Amsterdam UMC (publishedVersion)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion, cc-by-nc-nd)
- PubMed Central (acceptedVersion, cc-by-nc-nd)
- Dipòsit Digital de Documents de la UAB (Universitat Autònoma de Barcelona) (submittedVersion, cc-by-nc-nd)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, cc-by-nc-nd)
- UCL Discovery (University College London) (submittedVersion)
- Archivio Istituzionale della Ricerca - Università Vita-Salute San Raffaele (submittedVersion)
- Use Siena air (University of Siena) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Funders
- Eli Lilly and Company
- Pfizer
- Sanofi
- Biogen
- Teva Pharmaceutical Industries
- CSL Behring
- McGill University
- European Commission
- Bayer HealthCare
- National Research Foundation
- Siemens
- National Institutes of Health (Z99 NS999999)
- Chugai Pharmaceutical
- Medical Research Council (MC_PC_12019)
- National Institute of Neurological Disorders and Stroke (ZIANS003119)
- Topics
- Health Sciences › Medicine › Pathology and Forensic Medicine › Multiple Sclerosis Research Studies
- Health Sciences › Medicine › Family Practice › Clinical Reasoning and Diagnostic Skills
- Health Sciences › Medicine › Oncology › Polyomavirus and related diseases
- Keywords
- multiple sclerosis, MRI diagnostic criteria, clinically isolated syndrome, dissemination in space, dissemination in time, lesion counting, spinal cord imaging, differential diagnosis
- MeSH terms
- Humans, Magnetic Resonance Imaging, Multiple Sclerosis, Practice Guidelines as Topic, Consensus
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review