Detection of lymph-node metastases in patients with gastric carcinoma: comparison of three MR imaging pulse sequences View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2000-01

AUTHORS

M. Kato, S. Saji, M. Kanematsu, D. Fukada, K. Miya, T. Umemoto, K. Kunieda, Y. Sugiyama, H. Takao, Y. Kawaguchi, Y. Takagi, H. Kondo, H. Hoshi

ABSTRACT

Background: To compare the diagnostic accuracy of magnetic resonance (MR) images obtained with three different pulse sequences for lymph-node metastases in patients with gastric cancer.Methods: T1-weighted spin-echo (SE), breath-hold T2-weighted fast SE, and triphasic gadolinium-enhanced dynamic gradient-recall-echo (GRE) MR images obtained in 16 patients with gastric carcinoma were retrospectively reviewed. Regional lymph nodes were assigned to four different groups, and image review was conducted on a lymph-node group-by-group basis; 64 lymph-node groups were reviewed by two radiologists. Relative sensitivity, specificity, and accuracy were determined based on the findings with definitive surgery and follow-up imaging. Diagnostic accuracy was determined by means of receiver-operating-characteristic (ROC) analysis.Results: Relative sensitivities for lymph-node metastases with T1-weighted SE, breath-hold T2-weighted fast SE, and dynamic GRE images were 61%, 94%, and 59%, respectively. Relative sensitivity with breath-hold T2-weighted fast SE images was significantly greater than that with T1-weighted SE (p < 0.05) and dynamic GRE (p < 0.05) images. Diagnostic accuracy determined by ROC analysis was marginally higher with breath-hold T2-weighted fast SE (area under ROC curve [Az]= 0.87) than with T1-weighted SE (Az = 0.78, p= 0.08) and dynamic GRE (Az = 0.79, p= 0.12) images.Conclusion: Breath-hold T2-weighted fast SE sequence is useful in the detection of regional lymph-node metastases in patients with gastric carcinoma. More... »

PAGES

25-29

Identifiers

URI

http://scigraph.springernature.com/pub.10.1107/s002619910004

DOI

http://dx.doi.org/10.1107/s002619910004

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1106621707


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