The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Meta-Analysis of MR Imaging in the Diagnosis of Breast Lesions
Abstract
PURPOSE: To determine, in a meta-analysis, the diagnostic performance of contrast material-enhanced magnetic resonance (MR) imaging in patients with breast lesions. MATERIALS AND METHODS: Studies to assess the diagnostic performance of MR imaging in patients suspected of having breast cancer who underwent MR imaging and biopsy from January 1985 through March 2005 were reviewed for inclusion. A summary receiver operating characteristic curve was constructed, and pooled weighted estimates of sensitivity and specificity were calculated by using the recently developed bivariate approach for diagnostic meta-analysis. RESULTS: Of 251 eligible studies, 44 were included in the meta-analysis (sample size range, 14-821; cancer prevalence, 23%-84%). Pooled weighted estimates of sensitivity and specificity were 0.90 (95% confidence interval: 0.88, 0.92) and 0.72 (95% confidence interval: 0.67, 0.77), respectively. The performance of breast MR imaging was influenced by the prevalence of cancer in the studied population (P = .05) and by whether two criteria (ie, morphology, enhancement, and kinetic enhancement pattern)--versus one or three criteria--were used to differentiate benign from malignant lesions (P = .02). CONCLUSION: MR imaging of the breast has high sensitivity and lower specificity in the evaluation of breast lesions. SUPPLEMENTAL MATERIAL: http://radiology.rsnajnls.org/cgi/content/full/2461061298/DC1.
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
Cites
No adjustments are needed for multiple comparisons.
Rothman, K. J. (1990) · Epidemiology · doi:10.1097/00001648-199001000-00010 · Cited by 5,965
Whiting, P., Rutjes, A. W., Reitsma, J. B., Bossuyt, P. M., & Kleijnen, J. (2003) · BMC Medical Research Methodology · doi:10.1186/1471-2288-3-25 · Cited by 3,592
Reitsma, J. B., Glas, A. S., Rutjes, A. W. S., Scholten, R. J. P. M., Bossuyt, P. M., & Zwinderman, A. H. (2005) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2005.02.022 · Cited by 3,369
Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative
Bossuyt, P. M., Reitsma, J. B., Bruns, D. E., Gatsonis, C. A., Glasziou, P. P., Irwig, L. M., Lijmer, J. G., Moher, D., Rennie, D., & de Vet, H. C. W. (2003) · BMJ · doi:10.1136/bmj.326.7379.41 · Cited by 3,215
Towards Complete and Accurate Reporting of Studies of Diagnostic Accuracy: The STARD Initiative
Bossuyt, P. M., Reitsma, J. B., Bruns, D. E., Gatsonis, C. A., Glasziou, P. P., Irwig, L. M., Lijmer, J. G., Moher, D., Rennie, D., & de Vet, H. C. W. (2003) · Radiology · doi:10.1148/radiol.2261021292 · Cited by 3,215
The diagnostic odds ratio: a single indicator of test performance
Glas, A. S., Lijmer, J. G., Prins, M. H., Bonsel, G. J., & Bossuyt, P. M. M. (2003) · Journal of Clinical Epidemiology · doi:10.1016/s0895-4356(03)00177-x · Cited by 2,261
Empirical evidence of design-related bias in studies of diagnostic tests.
Lijmer, J. G. (1999) · JAMA · doi:10.1001/jama.282.11.1061 · Cited by 1,861
Do multiple outcome measures require p-value adjustment?
Feise, R. J. (2002) · BMC Medical Research Methodology · doi:10.1186/1471-2288-2-8 · Cited by 1,299
Moons, K. G. M., van Es, G.-A., Deckers, J. W., Habbema, J. D. F., & Grobbee, D. E. (1997) · Epidemiology · doi:10.1097/00001648-199701000-00002 · Cited by 189
Self-citation
Cited by
Magnetic resonance imaging of the breast: Recommendations from the EUSOMA working group
Sardanelli, F., Boetes, C., Borisch, B., Decker, T., Federico, M., Gilbert, F. J., Helbich, T., Heywang-Köbrunner, S. H., Kaiser, W. A., Kerin, M. J., et al. (2010) · European Journal of Cancer · doi:10.1016/j.ejca.2010.02.015 · Cited by 992
Metadata
- Authors
- Peters, N. H. G. M., Borel Rinkes, I. H. M., Zuithoff, N. P. A., Mali, W. P. T. M., Moons, K. G. M., & Peeters, P. H. M.
- Venue
- Radiology
- Published
- 2008-01
- Volume
- 246
- Issue
- 1
- Pages
- 116-124
- ISSN
- 0033-8419 (ISSN-L)
- 1527-1315
- OpenAlex
- W2013703224
- Cited by
- 529
- References
- 9
- FWCI
- 2.08
- 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: Meta-Analysis of MR Imaging in the Diagnosis of Breast Lesions. https://app.cochat.ai/papers/10.1148/radiol.2461061298
- The paper
- Peters, N. H. G. M., Borel Rinkes, I. H. M., Zuithoff, N. P. A., Mali, W. P. T. M., Moons, K. G. M., & Peeters, P. H. M. (2008). Meta-Analysis of MR Imaging in the Diagnosis of Breast Lesions. Radiology. https://doi.org/10.1148/radiol.2461061298
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.
