» Articles » PMID: 18937292

Diagnostic Accuracy of T and N Stages with Endoscopy, Stomach Protocol CT, and Endoscopic Ultrasonography in Early Gastric Cancer

Overview
Journal J Surg Oncol
Date 2008 Oct 22
PMID 18937292
Citations 62
Authors
Affiliations
Soon will be listed here.
Abstract

Background: Preoperative accurate diagnosis of the T and N stages in early gastric cancer (EGC) is important in determining the application of various limited treatments. The aim of this study is to analyze the accuracy of T and N staging of EGC with esophagogastroduodenoscopy (EGD), Stomach protocol CT (S-CT), and endoscopic ultrasonography (EUS), and the factors influencing the accuracy.

Methods: Four hundred and thirty-four patients preoperatively diagnosed as EGC using EGD or S-CT and undergoing curative gastrectomy at Seoul National University Hospital in 2005 were included. The T and N stage reviewed by experienced personnel were compared with the surgical pathology.

Results: The predictive values for EGC of EGD, S-CT, and EUS were 87.4%, 92.2%, and 94.1%, respectively. The predictive values for node negativity of S-CT, and EUS were 90.1% and 92.6%, respectively. The factors leading to underestimation of T stage with EGD were the upper third location, the size greater than 2 cm, and diffuse type of tumor. Those with S-CT were female sex, the upper third location and lesion size greater than 2 cm.

Conclusions: Before applying limited treatment for EGC, a surgeon should consider the risk factors of underestimation of T stage with EGD or S-CT.

Citing Articles

A quantitative model using multi-parameters in dual-energy CT to preoperatively predict serosal invasion in locally advanced gastric cancer.

Liu Y, Yuan M, Zhao Z, Zhao S, Chen X, Fu Y Insights Imaging. 2024; 15(1):264.

PMID: 39480564 PMC: 11528085. DOI: 10.1186/s13244-024-01844-z.


Enhancing Preoperative Diagnosis Accuracy of Stage III Gastric Cancer with Circulating circRNAs.

Matsutoka K, Shoda K, Higuchi Y, Nakayama T, Saito R, Maruyama S Ann Surg Oncol. 2024; 32(1):333-341.

PMID: 39433719 DOI: 10.1245/s10434-024-16387-2.


Preoperative predictive model for the probability of lymph node metastasis in gastric cancer: a retrospective study.

Teng F, Zhu Q, Zhou X, Shi Y, Sun H Front Oncol. 2024; 14:1473423.

PMID: 39399177 PMC: 11466724. DOI: 10.3389/fonc.2024.1473423.


Development and Validation of a Computed Tomography-Based Model for Noninvasive Prediction of the T Stage in Gastric Cancer: Multicenter Retrospective Study.

Tao J, Liu D, Hu F, Zhang X, Yin H, Zhang H J Med Internet Res. 2024; 26:e56851.

PMID: 39382960 PMC: 11499715. DOI: 10.2196/56851.


An artificial intelligence system for comprehensive pathologic outcome prediction in early gastric cancer through endoscopic image analysis (with video).

Lee S, Jeon J, Park J, Chang Y, Shin C, Oh M Gastric Cancer. 2024; 27(5):1088-1099.

PMID: 38954175 PMC: 11335909. DOI: 10.1007/s10120-024-01524-3.