Literature DB >> 21789552

Gastric cancer: imaging and staging with MDCT based on the 7th AJCC guidelines.

Mi Hee Lee1, Dongil Choi, Min Jung Park, Min Woo Lee.   

Abstract

Gastric cancer is a common deadly cancer worldwide. The tumor-node-metastasis (TNM) staging system is one of the most commonly used staging systems, and is accepted and maintained by the International Union against Cancer (UICC) and the American Joint Committee on Cancer (AJCC). The TNM system is well known to effectively predict the prognosis of gastric cancer patients. The latest revision of TNM staging was presented in the 7th edition of the AJCC in 2009. Multi-detector row CT (MDCT) is a powerful test for non-invasive evaluation and can assess metastatic and locoregional staging simultaneously. Current MDCT with isotropic imaging and 3D images has increased the accuracy of T and N staging in patients with gastric cancer. Multi-planar reformatted images permit the radiologist to select the optimal imaging plane to accurately evaluate tumor invasion depth of the gastric wall and perigastric infiltration to identify a fat plane between a tumor and adjacent organs, to avoid partial volume averaging effects, and to differentiate lymph nodes from small perigastric vessels. Thus, MDCT provides a useful all-in-one diagnostic method for the pre-operative evaluation of patients with known, or strongly suspected, gastric cancer according to the 7th AJCC TNM staging system.

Entities:  

Mesh:

Year:  2012        PMID: 21789552     DOI: 10.1007/s00261-011-9780-3

Source DB:  PubMed          Journal:  Abdom Imaging        ISSN: 0942-8925


  16 in total

1.  Application value of multi-slice spiral computed tomography for imaging determination of metastatic lymph nodes of gastric cancer.

Authors:  Chun-Lai Dai; Zhi-Gang Yang; Li-Ping Xue; Yu-Mei Li
Journal:  World J Gastroenterol       Date:  2013-09-14       Impact factor: 5.742

2.  Preoperative locoregional staging of gastric cancer: is there a place for magnetic resonance imaging? Prospective comparison with EUS and multidetector computed tomography.

Authors:  Francesco Giganti; Elena Orsenigo; Paolo Giorgio Arcidiacono; Roberto Nicoletti; Luca Albarello; Alessandro Ambrosi; Annalaura Salerno; Antonio Esposito; Maria Chiara Petrone; Damiano Chiari; Carlo Staudacher; Alessandro Del Maschio; Francesco De Cobelli
Journal:  Gastric Cancer       Date:  2015-01-23       Impact factor: 7.370

Review 3.  Gut wrenching: cases of missed gastrointestinal tumors and their mimics on computed tomography.

Authors:  Nina Capiro; Carl Flink; Victor Sai; Katrina Beckett
Journal:  Emerg Radiol       Date:  2020-10-06

4.  Usefulness of histologic differences and perivascular infiltration for preoperative T staging of advanced gastric cancer using computed tomography.

Authors:  Ji Youn Kim; Woo-Suk Chung; Hyeun Jin Lee; Ji Hae An; Jang Shin Son
Journal:  Jpn J Radiol       Date:  2019-10-17       Impact factor: 2.374

Review 5.  Beyond gastric adenocarcinoma: Multimodality assessment of common and uncommon gastric neoplasms.

Authors:  Danielle M Richman; Sree Harsha Tirumani; Jason L Hornick; Charles S Fuchs; Stephanie Howard; Katherine Krajewski; Nikhil Ramaiya; Michael Rosenthal
Journal:  Abdom Radiol (NY)       Date:  2017-01

Review 6.  State-of-the-art preoperative staging of gastric cancer by MDCT and magnetic resonance imaging.

Authors:  Joon-Il Choi; Ijin Joo; Jeong Min Lee
Journal:  World J Gastroenterol       Date:  2014-04-28       Impact factor: 5.742

7.  MDCT features in the differentiation of T4a gastric cancer from less-advanced gastric cancer: significance of the hyperattenuating serosa sign.

Authors:  T U Kim; S Kim; J W Lee; N K Lee; T Y Jeon; D Y Park
Journal:  Br J Radiol       Date:  2013-07-19       Impact factor: 3.039

8.  The prediction of survival of patients with gastric cancer with PD-L1 expression using contrast-enhanced ultrasonography.

Authors:  Lin-Ang Wang; Xi Wei; Qing Li; Lin Chen
Journal:  Tumour Biol       Date:  2015-12-15

9.  Enhancement patterns of gastric carcinoma on contrast-enhanced ultrasonography: relationship with clinicopathological features.

Authors:  Fang Wei; Pintong Huang; Shiyan Li; Jian Chen; Ying Zhang; Yurong Hong; Shumei Wei; David Cosgrove
Journal:  PLoS One       Date:  2013-09-06       Impact factor: 3.240

10.  Using the K-nearest neighbor algorithm for the classification of lymph node metastasis in gastric cancer.

Authors:  Chao Li; Shuheng Zhang; Huan Zhang; Lifang Pang; Kinman Lam; Chun Hui; Su Zhang
Journal:  Comput Math Methods Med       Date:  2012-10-24       Impact factor: 2.238

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