CoChat
Sign Up
Cited by 1,251Multiple Sclerosis Research StudiesPolyomavirus and related diseasesClinical Reasoning and Diagnostic Skills

Comparison of MRI criteria at first presentation to predict conversion to clinically definite multiple sclerosis

Open access
Barkhof, F·1997·Brain
DOI 10.1093/brain/120.11.2059
Open this paper in CoChat — free account

Abstract

We compared MRI criteria used to predict conversion of suspected multiple sclerosis to clinically definite multiple sclerosis. Seventy-four patients with clinically isolated neurological symptoms suggestive of multiple sclerosis were studied with MRI. Logistic regression analysis was used to remove redundant information, and a diagnostic model was built after each MRI parameter was dichotomized according to maximum accuracy using receiver operating characteristic analysis. Clinically definite multiple sclerosis developed in 33 patients (prevalence 45%). The optimum cut-off point (number of lesions) was one for most MRI criteria (including gadolinium-enhancement and juxta-cortical lesions), but three for periventricular lesions, and nine for the total number of T2-lesions. Only gadolinium-enhancement and juxta-cortical lesions provided independent information. A final model which, in addition, included infratentorial and periventricular lesions, had an accuracy of 80%, and having more abnormal criteria, predicted conversion to clinically definite multiple sclerosis strongly. The model performed better than the criteria of Paty et al. (Neurology 1988; 38: 180-5) and of Fazekas et al. (Neurology 1988; 38: 1822-5). We concluded that a four-parameter dichotomized MRI model including gadolinium-enhancement, juxtacortical, infratentorial and periventricular lesions best predicts conversion to clinically definite 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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1093/brain/120.11.2059

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.

A few free checks a day · papers already verified open instantly · results are public

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?

  • The lesions detected by special MRI techniques for cortical lesions are primarily of the leukocortical type; subpial lesions are rarely detected.

    “The lesions detected by these techniques are primarily of the leukocortical type; subpial lesions are rarely detected.”

    From Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria (2018) · cites this paper as [77]

    The Methods (p. 4) score juxtacortical lesions, and the Discussion (p. 10) mentions their detection with FLAIR. Neither passage classifies detected lesions as primarily leukocortical or says subpial lesions are rarely detected. Searches for leukocortical, subpial, and cortical-lesion detection found no passage addressing that comparison. (LLM, conf=0.75)

    Experimental — accuracy not yet measured

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

No references could be resolved yet.

Research works printed but not linked: 37

  1. Barkhof F, Scheltens P, Frequin STFM, Nauta JJ, Tas MW, Valk J, et al. Relapsing-remitting multiple sclerosis: sequential enhanced MR imaging vs clinical findings in determining disease activity. AJR Am J Roentgenol 1992; 159: 1041-7.
  2. Caldemeyer KS, Smith RR, Harris TM, Edwards MK. MRI in acute disseminated encephalomyelitis. Neuroradiology 1994; 36: 216-20.
  3. Campi A, Filippi M, Comi G, Martinelli V, Baratti C, Rovaris M, et al. Acute transverse myelopathy: spinal and cranial MR study with clinical follow-up. Am J Neuroradiol 1995; 16: 115-23.
  4. Dawson JW. The histology of disseminated sclerosis. Trans Roy Soc Edinb 1916; 50: 517-740.
  5. Fazekas F, Offenbacher H, Fuchs S, Schmidt R, Niederkorn K, Horne S, et al. Criteria for an increased specificity of MRI interpretation in elderly subjects with suspected multiple sclerosis. Neurology 1988; 38: 1822-5.
  6. Filippi M, Horsfield MA, Morrissey SP, MacManus DG, Rudge P, McDonald WI, et al. Quantitative brain MRI lesion load predicts the course of clinically isolated syndromes suggestive of multiple sclerosis. Neurology 1994; 44: 635-41.
  7. Gean-Marton AD, Vezina LG, Marton KI, Stimac GK, Peyster RG, Taveras JM, et al. Abnormal corpus callosum: a sensitive and specific indicator of multiple sclerosis [see comments]. Radiology 1991; 180: 215-21. Comment in: Radiology 1991; 180: 15-7.
  8. Gebarski SS, Gabrielsen TO, Gilman S, Knake JE, Latack JT, Aisen AM. The initial diagnosis of multiple sclerosis: clinical impact of magnetic resonance imaging. Ann Neurol 1985; 17: 469-74.
  9. Grossman RI, Gonzalez-Scarano F, Atlas SW, Galetta S, Silberberg DH. Multiple sclerosis: gadolinium enhancement in MR imaging. Radiology 1986; 161: 721-5.
  10. Hashemi RH, Bradley WG Jr, Chen DY, Jordan JE, Queralt JA, Cheng AE, et al. Suspected multiple sclerosis: MR imaging with a thin-section fast FLAIR pulse sequence. Radiology 1995; 196: 505-10.
  11. Hawkins CP, Munro PMG, MacKenzie F, Kesselring J, Tofts PS, du Boulay EP, et al. Duration and selectivity of blood-brain barrier breakdown in chronic relapsing experimental allergic encephalomyelitis studied by gadolinium-DTPA and protein markers. Brain 1990; 113: 365-78.
  12. Herndon RM, Brooks B. Misdiagnosis of multiple sclerosis. Semin Neurol 1985; 5: 94-8.
  13. Heun R, Kappos L, Bittkau S, Sta ¨dt D, Rohrbach E, Schuknecht B. Magnetic resonance imaging and early diagnosis of multiple sclerosis [letter]. Lancet 1988; 2: 1202-3.
  14. Horowitz AL, Kaplan RD, Grewe G, White RT, Salberg LM. The ovoid lesion: a new MR observation in patients with multiple sclerosis. AJNR Am J Neuroradiol 1989; 10: 303-5.
  15. Katz D, Taubenberger J, Raine C, McFarlin D, McFarland H. Gadolinium-enhancing lesions on magnetic resonance imaging: neuropathological findings [abstract]. Ann Neurol 1990; 28: 243.
  16. Kazui S, Naritomi H, Imakita S, Yamada N, Ogawa M, Sawada T. Sequential gadoliniumDTPA enhanced MRI studies in neuroBehc ¸et's disease. Neuroradiology 1991; 33: 136-9.
  17. Lee KH, Hashimoto S, Hooge JP, Kastrukoff LF, Oger JJ, Li DK, et al. Magnetic resonance imaging of the head in the diagnosis of multiple sclerosis: a prospective 2-year follow-up with comparison of clinical evaluation, evoked potentials, oligoclonal banding, and CT. Neurology 1991; 41: 657-60.
  18. Lee DH, Vellet AD, Eliasziw M, Vidito L, Ebers GC, Rice GP, et al. MR imaging field strength: prospective evaluation of the diagnostic accuracy of MR for diagnosis of multiple sclerosis at 0.5 and 1.5 T. Radiology 1995; 194: 257-62.
  19. Lumsden CE. The neuropathology of multiple sclerosis. In: Vinken PJ, Bruyn GW, editors. Handbook of clinical neurology, Vol. 9. Amsterdam: North-Holland, 1970: 217-309.
  20. Miller DH, Ormerod IEC, Gibson A, du Boulay EPGH, Rudge P, McDonald WI. MR brain scanning in patients with vasculitis: differentiation from multiple sclerosis. Neuroradiology 1987; 29: 226-31.
  21. Morissey SP, Miller Dh, Kendall BE, Kingsley DP, Kelly MA, Francis DA, et al. The significance of brain magnetic resonance imaging abnormalities at presentation with clinically isolated syndromes suggestive of multiple sclerosis. A 5-year follow-up study. Brain 1993; 116: 135-46.
  22. Morrissey SP, Stodal H, Zettl U, Simonis C, Jung S, Kiefer R, et al. In vivo MRI and its histological correlates in acute adoptive transfer experimental allergic encephalomyelitis. Quantification of inflammation and oedema. Brain 1996; 119: 239-48.
  23. Namer IJ. Yu O, Mauss Y, Dumitresco BE, Chambron J. An evaluation of the significance of areas of intense signal in the MR brain images of patients with multiple sclerosis. Magn Reson Imaging 1993; 11: 311-7.
  24. Nesbit GM, Forbes GS, Scheithauer BW, Okazaki H, Rodriguez M. Multiple sclerosis: histopathologic and MR and/or CT correlation in 37 cases at biopsy and three cases at autopsy. Radiology 1991; 180: 467-74.
  25. Offenbacher H, Fazekas F, Schmidt R, Fiedl W, Flooh E, Payer F, et al. Assessment of MRI criteria for a diagnosis of MS Neurology 1993; 43: 905-9.
  26. Paty DW, Oger JJF, Kastrukoff LF, Hashimoto SA, Hooge JP, Eisen AA, et al. MRI in the diagnosis of MS: a prospective study with comparison of clinical evaluation, evoked potentials, oligoclonal banding, and CT.Neurology 1988; 38: 180-5.
  27. Poser CM, Paty DW, Scheinberg L, McDonald WI, Davis FA, Ebers GC, et al. New diagnostic criteria for multiple sclerosis: guidelines for research protocols. Ann Neurol 1983; 13: 227-31.
  28. Runge VM, Price AC, Kirshner HS, Allen JH, Partain CL, James AE Jr. Magnetic resonance imaging of multiple sclerosis: a study of pulse-technique efficacy. AJR Am J Roentgenol 1984; 143: 1015-26.
  29. Schumacher GA, Beebe G, Kibler RE, Kurland LT, Kurtzke JF, Mcdowell F, et al. 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 1965; 122: 552-68.
  30. Sherman JL, Stern BJ. Sarcoidosis of the CNS: comparison of unenhanced and enhanced MR images. AJNR Am J Neuroradiol 1990; 11: 915-23.
  31. Simon JH, Holtås SL, Schiffer RB, Rudick RA, Herndon RN, Kido DK, et al. Corpus callosum and subcallosal-periventricular lesions in multiple sclerosis: detection with MR. Radiology 1986; 160: 363-7.
  32. Tas MW, Barkhof F, van Walderveen MAA, Polman CH, Hommes OR, Valk J. The effect of gadolinium on the sensitivity and specificity of MR in the initial diagnosis of multiple sclerosis. AJNR Am J Neuroradiol 1995; 16: 259-64.
  33. Thorpe JW, Kidd D, Moseley IF, Thompson AJ, MacManus DG, Compston DA, et al. Spinal MRI in patients with suspected multiple sclerosis and negative brain MRI. Brain 1996; 119: 709-14.
  34. Uhlenbrock D, Sehlen S. The value of T 1 -weighted images in the differentiation between MS, white matter lesions, and subcortical arteriosclerotic encephalopathy (SAE). [Review]. Neuroradiology 1989; 31: 203-12.
  35. van der Knaap MS, Valk J. Magnetic resonance of myelin, myelination, and myelin disorders. 2nd ed. Berlin: Springer Verlag, 1995.
  36. van Walderveen MAA, Barkhof F, Hommes OR, Polman CH, Tobi H, Frequin STFM, et al. Correlating MRI and clinical disease activity in multiple sclerosis: relevance of hypointense lesions on short-TR/short-TE (T 1 -weighted) spin-echo images. Neurology 1995; 45: 1684-90.
  37. Youl BD, Turano G, Miller DH, Towell AD, MacManus DG, Moore SG, et al. The pathophysiology of acute optic neuritis. An association of gadolinium leakage with clinical and electrophysiological deficits. Brain 1991; 114: 2437-50.

Cited by

Sorted by citations

Authors
Barkhof, F.
Affiliations
Amsterdam UMC Location Vrije Universiteit Amsterdam (NL)
Corresponding author
Barkhof, F
ORCID
Barkhof, F
Venue
Brain
Publisher
Oxford University Press (OUP)
Published
1997-11-01
Volume
120
Issue
11
Pages
2059-2069
ISSN
  • 0006-8950 (ISSN-L)
  • 1460-2156
DOI
10.1093/brain/120.11.2059
OpenAlex
W2122894564
Cited by
1,251
References
0
Citations by year
2026: 18 · 2025: 16 · 2024: 21 · 2023: 30 · 2022: 22 · 2021: 34 · 2020: 26 · 2019: 33 · 2018: 50 · 2017: 54 · 2016: 46 · 2015: 59 · 2014: 53 · 2013: 69 · 2012: 74
FWCI
10.25
Type
journal article
Language
en
Open access
Licence
other-oa
Locations
  • Brain (publishedVersion)
  • PubMed (publishedVersion)
  • Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion, other-oa)
  • Pure Amsterdam UMC (submittedVersion, other-oa)
  • Digital Academic REpository of VU University Amsterdam (Vrije Universiteit Amsterdam) (submittedVersion)
  • UCL Discovery (University College London) (submittedVersion)
  • Archivio Istituzionale della Ricerca - Università Vita-Salute San Raffaele (submittedVersion)
  • Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
Funders
  • Multiple Sclerosis Society
  • Stichting MS Research
Topics
  • Health Sciences › Medicine › Pathology and Forensic Medicine › Multiple Sclerosis Research Studies
  • Health Sciences › Medicine › Oncology › Polyomavirus and related diseases
  • Health Sciences › Medicine › Family Practice › Clinical Reasoning and Diagnostic Skills
Keywords
multiple sclerosis, clinically isolated syndrome, conversion to multiple sclerosis, gadolinium-enhancing lesions, juxtacortical lesions, periventricular lesions, infratentorial lesions, T2 lesions, diagnostic model
MeSH terms
False Negative Reactions, False Positive Reactions, Gadolinium, Humans, Magnetic Resonance Imaging, Multiple Sclerosis, Predictive Value of Tests, Time Factors

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