ISSN 1004-4140
CN 11-3017/P
Volume 27 Issue 2
Apr.  2018
Turn off MathJax
Article Contents
Abstract
Related Articles
HAN Xin, TIAN Feng, YU Sheng-feng. Value of Multi-detector Row Computed Tomography on Preoperative T Staging of Gastric Cancer[J]. CT Theory and Applications, 2018, 27(2): 249-255. DOI: 10.15953/j.1004-4140.2018.27.02.13
Citation: HAN Xin, TIAN Feng, YU Sheng-feng. Value of Multi-detector Row Computed Tomography on Preoperative T Staging of Gastric Cancer[J]. CT Theory and Applications, 2018, 27(2): 249-255. DOI: 10.15953/j.1004-4140.2018.27.02.13
shu

Value of Multi-detector Row Computed Tomography on Preoperative T Staging of Gastric Cancer

  • a). Department of Ultrasonography;b). Department of Radiology, the People's Hospital of Taihe County, Taihe 236600

More Information
  • Received Date: November 12, 2017
  • Available Online: November 07, 2021
    Graphical Abstract
    • Abstract
  • Objective: To study the value of multi-detector row computed tomography (MDCT) before operation in the diagnosis of T-staging of gastric cancer. Methods: 616 patients with gastric cancer underwent MDCT before operation. The results were compared with operative and pathologic T (pT) staging. Especially, we evaluated the correlations among the diagnostic accuracy of T staging and various clinicopathologic parameters by focusing on 276 patients who had detectable lesions by MDCT. Results: The overall diagnostic accuracy of preoperative T staging by MDCT was 91% (560/616). For each pathologic T stage, the accuracy was 95% for pT1, 78% for pT2-3, 89% for pT4a, and 75% for pT4b, respectively. Antral tumors (P=0.045), and Borrmann type1 tumors (P=0.0001) were incorrectly T staged by MDCT. Conclusion: Preoperative T staging of gastric cancer by MDCT have higher clinical value.
    • FullText(HTML)
    • References (0)
    • Related Articles

  • Related Articles

    [1]YAN Xin, ZHAO Jianhua. Computed Tomography and Magnetic Resonance Imaging Diagnosis of Intracranial Solitary Fibrous Tumor: A Clinical Case Analysis[J]. CT Theory and Applications, 2024, 33(3): 365-370. DOI: 10.15953/j.ctta.2023.126
    [2]WANG Shan, ZHAO Jianhua. Research Progress in Imaging Radiomics Based on Computed Tomography and Magnetic Resonance in Ischemic Stroke[J]. CT Theory and Applications, 2024, 33(1): 83-89. DOI: 10.15953/j.ctta.2023.080
    [3]WANG Wei, CHEN Jianghong, YANG Zhenghan, JIN Erhu. Atypical Computed Tomography and Magnetic Resonance Imaging Findings of Posterior Inferior Mediastinal Bronchogenic Cysts: A Clinical Case Analysis[J]. CT Theory and Applications, 2024, 33(1): 76-82. DOI: 10.15953/j.ctta.2023.074
    [4]JIA Sulan, DU Jingbo, SU Xiaohua. The Diagnostic Efficacy of Version 2018 LI-RADS for Hepatocellular Carcinoma on Enhanced Magnetic Resonance Imaging[J]. CT Theory and Applications, 2024, 33(1): 35-41. DOI: 10.15953/j.ctta.2023.073
    [5]SUN Pengtao, DOU Xuechao, YAN Yuchang, LIAN Yufei, LIU Chenpeng, PAN Zhenyu. Application of T2WI 3D-SPACE Imaging in Preoperative Evaluation of Rectal Cancer[J]. CT Theory and Applications, 2021, 30(3): 340-346. DOI: 10.15953/j.1004-4140.2021.30.03.07
    [6]ZHU Lan, PAN Zi-lai. The Utilization of Diffusion-weighted Magnetic Resonance Imaging in the Detection of Lymph-node Metastasis in Rectal Cancer[J]. CT Theory and Applications, 2014, 23(3): 527-533.
    [7]LI Jing-ying, WANG Xiu-ling, WU Meng. Imaging Features of Solid Pseudopapillary Tumor of the Pancreas on Computed Tomography and Magnetic Resonance Imaging[J]. CT Theory and Applications, 2013, 22(1): 161-166.
    [8]JIANG Li-hua, CHEN Xiao-bo, YUE Yun-long, ZHAO Li-jun, DUAN Yong-li, FU Yan. Magnetic Resonance Imanging Diagnosis of Limbs Lymphangioma[J]. CT Theory and Applications, 2012, 21(2): 313-319.
    [9]YANG Hai-peng, JIN Er-hu, ZHANG Jie, CHEN Bu-dong, MA Da-qing. Diagnosis of Gallbladder Enlargement on Magnetic Resonance Cholangiopancreatography Combined with Conventional MR Images[J]. CT Theory and Applications, 2011, 20(3): 403-414.
    [10]WANG Wei-dong, BAO Shang-lian. Decomposition of Magnetic Resonance Images by Estimating MR Physical Parameters[J]. CT Theory and Applications, 2006, 15(4): 73-78.

  • Cited by

    Periodical cited type(2)

    1. 张科，张春晓. 基于深度残差网络的儿科肺炎辅助诊断算法. 中国医疗设备. 2022(09): 42-46+56 .
    2. 周丽媛，赵启军，高定国. 基于注意力引导深度纹理特征学习的复杂背景藏药材切片图像识别. 世界科学技术-中医药现代化. 2022(12): 4825-4832 .

    Other cited types(5)

Catalog

    Get Citation
    PDF
    XML
    Article views PDF downloads Cited by(7)
    Related

    Website Copyright © Editorial Office of Computerized Tomography Theory and Applications

    Address：No.5 Minzudaxue Nanlu,Haidian District,Beijing 100081,P.R.China（100081）

    E-mail：cttacn@cea-igp.ac.cn

    Phone：010-68729234

    京ICP备08002722号-11

    震球期刊
    CT理论与应用研究-中英文
    E-mail
    RSS

    Supported by: Beijing Renhe Information Technology Co. Ltd     Baidu Analytics

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return