The DOI matches its Crossref record.
Prospective Comparison of Mammography, Sonography, and MRI in Patients Undergoing Neoadjuvant Chemotherapy for Palpable Breast Cancer
Abstract
OBJECTIVE: The objective of our study was to determine the relative accuracy of mammography, sonography, and MRI in predicting residual tumor after neoadjuvant chemotherapy for breast cancer as compared with the gold standards of physical examination and pathology. SUBJECTS AND METHODS: Forty-one women with stage IIB-III palpable breast cancer were prospectively enrolled in a study investigating the effects of sequential single-agent chemotherapy (doxorubicin followed by paclitaxel or vice versa) on tumor imaging. The study cohort consisted of the first 31 patients (age range, 31-65 years; mean, 45 years) who completed the protocol. All underwent physical examination, mammography, sonography, and MRI before and after receiving each neoadjuvant chemotherapeutic drug. Imaging studies were reviewed by two radiologists using conventional lexicons for lesion analysis, and the findings were compared with clinical response and pathology results. RESULTS: Complete, partial, and stable clinical response as defined by clinical examination was seen in 15, 14, and two of the 31 patients, respectively. Agreement rates about the degree of response were 32%, 48%, and 55%, respectively, for mammography, sonography, and MRI compared with clinical evaluation and did not differ statistically. Agreement about the rate of response as measured by clinical examination, mammography, sonography, and MRI compared with the gold standard (pathology) was 19%, 26%, 35%, and 71%, respectively. Of the four, MRI agreed with the gold standard significantly more often (p < 0.002 for all three paired comparisons with MRI). When there was disagreement with the gold standard, none of the four exhibited a significant tendency to either under- or overestimate. CONCLUSION: MRI appears to provide the best correlation with pathology-better than physical examination, mammography, and sonography-in patients undergoing neoadjuvant chemotherapy. However, MRI may overestimate (6%) or underestimate (23%) residual disease in approximately 29% of the patients (95% confidence interval, 14-48%).
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
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
MRI for breast cancer screening, diagnosis, and treatment
Morrow, M., Waters, J., & Morris, E. (2011) · The Lancet · doi:10.1016/s0140-6736(11)61350-0 · Cited by 448
Marinovich, M. L., Houssami, N., Macaskill, P., Sardanelli, F., Irwig, L., Mamounas, E. P., von Minckwitz, G., Brennan, M. E., & Ciatto, S. (2013) · JNCI: Journal of the National Cancer Institute · doi:10.1093/jnci/djs528 · Cited by 382
Lobbes, M. B. I., Prevos, R., Smidt, M., Tjan-Heijnen, V. C. G., van Goethem, M., Schipper, R., Beets-Tan, R. G., & Wildberger, J. E. (2013) · Insights into Imaging · doi:10.1007/s13244-013-0219-y · Cited by 237
Gu, Y.-L., Pan, S.-M., Ren, J., Yang, Z.-X., & Jiang, G.-Q. (2017) · Clinical Breast Cancer · doi:10.1016/j.clbc.2016.12.010 · Cited by 128
Metadata
- Authors
- Yeh, E., Slanetz, P., Kopans, D. B., Rafferty, E., Georgian-Smith, D., Moy, L., Halpern, E., Moore, R., Kuter, I., & Taghian, A.
- Venue
- American Journal of Roentgenology
- Publisher
- American Roentgen Ray Society
- Published
- 2005-03
- Volume
- 184
- Issue
- 3
- Pages
- 868-877
- ISSN
- 0002-9580 (ISSN-L)
- 0361-803X
- 1546-3141
- OpenAlex
- W2042809940
- Cited by
- 403
- References
- 0
- FWCI
- 10.47
- 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: Prospective Comparison of Mammography, Sonography, and MRI in Patients Undergoing Neoadjuvant Chemotherapy for Palpable Breast Cancer. https://app.cochat.ai/papers/10.2214/ajr.184.3.01840868
- The paper
- Yeh, E., Slanetz, P., Kopans, D. B., Rafferty, E., Georgian-Smith, D., Moy, L., Halpern, E., Moore, R., Kuter, I., & Taghian, A. (2005). Prospective Comparison of Mammography, Sonography, and MRI in Patients Undergoing Neoadjuvant Chemotherapy for Palpable Breast Cancer. American Journal of Roentgenology. https://doi.org/10.2214/ajr.184.3.01840868
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.