The DOI matches its Crossref record.
MRI in the diagnosis of MS: A prospective study with comparison of clinical evaluation, evoked potentials, oligoclonal banding, and CT
Abstract
We compared the diagnostic capabilities of MRI to CT, evoked potentials (EP), and CSF oligoclonal banding analysis in a prospective evaluation of 200 patients with suspected multiple sclerosis (MS). MRI was the best method for demonstrating dissemination in space. An abnormal appropriate EP in monosymptomatic disease was usually supported by MRI and CSF analysis as being predictive of MS as a clinical diagnosis. A normal appropriate EP study was not satisfactory because MRI and CSF analysis often did not support a diagnosis of non-MS. When there is agreement between three of these paraclinical studies, the diagnosis of MS is probably unequivocal. For use in research studies, laboratory-supported definite MS (LSDMS) could be diagnosed in 85 patients of the total 200 (42.5%), in 19/38 (50%) of optic neuritis (ON) patients, and in 24/52 (46%) of chronic progressive myelopathy (CPM) patients. MRI was 100% successful in identifying patients who qualified for LSDMS in the ON and CPM groups. In a short follow-up (less than 1 year), 19/200 (10%) went on to develop clinically definite MS (CDMS), and MRI predicted that diagnosis in 18/19 (95%). Only long-term follow-up will show how well these studies and the category of LSDMS predict the development of CDMS. The clinical diagnosis of MS (CDMS), even though only 95% accurate, must remain the gold standard.
Overview
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
Verification
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.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
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
McDonald, W. I., Compston, A., Edan, G., Goodkin, D., Hartung, H., Lublin, F. D., McFarland, H. F., Paty, D. W., Polman, C. H., Reingold, S. C., et al. (2001) · Annals of Neurology · doi:10.1002/ana.1032 · Cited by 6,969
Self-citationBarkhof, F. (1997) · Brain · doi:10.1093/brain/120.11.2059 · Cited by 1,251
MRI criteria for the diagnosis of multiple sclerosis: MAGNIMS consensus guidelines
Filippi, M., Rocca, M. A., Ciccarelli, O., De Stefano, N., Evangelou, N., Kappos, L., Rovira, A., Sastre-Garriga, J., Tintorè, M., Frederiksen, J. L., et al. (2016) · The Lancet Neurology · doi:10.1016/s1474-4422(15)00393-2 · Cited by 880
Neuromyelitis Optica Study Group (NEMOS), Trebst, C., Jarius, S., Berthele, A., Paul, F., Schippling, S., Wildemann, B., Borisow, N., Kleiter, I., Aktas, O., et al. (2014) · Journal of Neurology · doi:10.1007/s00415-013-7169-7 · Cited by 595
Metadata
- Authors
- Paty, D. W., Oger, J. J. F., Kastrukoff, L. F., Hashimoto, S. A., Hooge, J. P., Eisen, A. A., Eisen, K. A., Purves, S. J., Low, M. D., Brandejs, V., Robertson, W. D., & B. Li, D. K.
- Venue
- Neurology
- Published
- 1988-02
- Volume
- 38
- Issue
- 2
- Pages
- 180-180
- ISSN
- 0028-3878 (ISSN-L)
- 1526-632X
- OpenAlex
- W2057119898
- Cited by
- 639
- References
- 0
- FWCI
- 19.61
- Type
- journal article
- Language
- en
- Open access
- closed
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: MRI in the diagnosis of MS: A prospective study with comparison of clinical evaluation, evoked potentials, oligoclonal banding, and CT. https://app.cochat.ai/papers/10.1212/wnl.38.2.180
- The paper
- Paty, D. W., Oger, J. J. F., Kastrukoff, L. F., Hashimoto, S. A., Hooge, J. P., Eisen, A. A., Eisen, K. A., Purves, S. J., Low, M. D., Brandejs, V., Robertson, W. D., & B. Li, D. K. (1988). MRI in the diagnosis of MS: A prospective study with comparison of clinical evaluation, evoked potentials, oligoclonal banding, and CT. Neurology. https://doi.org/10.1212/wnl.38.2.180
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.