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Cited by 294

The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.

A Systematic Approach to the Interpretation of Preoperative Staging MRI for Rectal Cancer

Taylor, Fiona G. M., Swift, Robert I., Blomqvist, Lennart, Brown, Gina·2008·American Journal of Roentgenology

Abstract

OBJECTIVE: The purpose of this article is to provide an aid to the systematic evaluation of MRI in staging rectal cancer. CONCLUSION: MRI has been shown to be an effective tool for the accurate preoperative staging of rectal cancer. In the Magnetic Resonance Imaging and Rectal Cancer European Equivalence Study (MERCURY), imaging workshops were held for participating radiologists to ensure standardization of scan acquisition techniques and interpretation of the images. In this article, we report how the information was obtained and give examples of the images and how they are interpreted, with the aim of providing a systematic approach to the reporting process.

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Registry

Crossref · 10.2214/ajr.08.1004

Cites

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Metadata

Authors
Taylor, F. G. M., Swift, R. I., Blomqvist, L., & Brown, G.
Venue
American Journal of Roentgenology
Published
2008-12
Volume
191
Issue
6
Pages
1827-1835
ISSN
  • 0002-9580 (ISSN-L)
  • 0361-803X
  • 1546-3141
OpenAlex
W2081697820
Cited by
294
References
36
FWCI
4.93
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A Systematic Approach to the Interpretation of Preoperative Staging MRI for Rectal Cancer. https://app.cochat.ai/papers/10.2214/ajr.08.1004
The paper
Taylor, F. G. M., Swift, R. I., Blomqvist, L., & Brown, G. (2008). A Systematic Approach to the Interpretation of Preoperative Staging MRI for Rectal Cancer. American Journal of Roentgenology. https://doi.org/10.2214/ajr.08.1004

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.