Literature DB >> 22728475

Two years' intensive training in endoscopic diagnosis facilitates detection of early gastric cancer.

Tetsuro Yamazato1, Tsuneo Oyama, Toshifumi Yoshida, Yasumasa Baba, Kohei Yamanouchi, Yoshitomo Ishii, Fumio Inoue, Shuji Toda, Kotaro Mannen, Ryo Shimoda, Ryuichi Iwakiri, Kazuma Fujimoto.   

Abstract

OBJECTIVE: Early detection of gastric cancer by screening endoscopy facilitates endoscopic treatment in place of open surgery. The aim of this study was to evaluate whether 2 years intensive training improved the detection of gastric cancer by screening endoscopy.
METHODS: An endoscopist who had trained for 6 years as a general physician, performed screening endoscopy at Imari Arita Kyoritsu Hospital before (group I) and after (group II) intensive training in the diagnosis of early gastric cancer in consecutive patients.
RESULTS: Background characteristics, including age (61.6 vs. 62.2 years) and sex, did not differ between the groups. Before training, 10 gastric neoplasms were detected in 937 patients in group I: four early gastric cancers, one gastric adenoma, and five advanced gastric cancer. After training, 36 gastric neoplasms were detected in 937 patients in group II: 18 early gastric cancers, 11 gastric adenoma, five advanced gastric cancer, and one each of gastric carcinoid and malignant lymphoma. The detection rate for early gastric cancer was significantly improved by training [group I: 4/937 (0.4%) vs. group II: 18/937 (1.9%)], although the detection rate for advanced gastric cancer did not differ before and after training. The proportion of early gastric cancer + adenoma to advanced cancer was higher in group II (5/5 vs. 29/5 in group I).
CONCLUSION: Intensive training in upper gastrointestinal endoscopy screening dramatically improved the detection rate for early gastric cancer, although the detection rate for advanced gastric cancer was not affected.

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Year:  2012        PMID: 22728475     DOI: 10.2169/internalmedicine.51.7414

Source DB:  PubMed          Journal:  Intern Med        ISSN: 0918-2918            Impact factor:   1.271


  11 in total

1.  Application of artificial intelligence using a convolutional neural network for detecting gastric cancer in endoscopic images.

Authors:  Toshiaki Hirasawa; Kazuharu Aoyama; Tetsuya Tanimoto; Soichiro Ishihara; Satoki Shichijo; Tsuyoshi Ozawa; Tatsuya Ohnishi; Mitsuhiro Fujishiro; Keigo Matsuo; Junko Fujisaki; Tomohiro Tada
Journal:  Gastric Cancer       Date:  2018-01-15       Impact factor: 7.370

Review 2.  Quality indicators in esophagogastroduodenoscopy.

Authors:  Sang Yoon Kim; Jae Myung Park
Journal:  Clin Endosc       Date:  2022-05-16

3.  Artificial Intelligence-Assisted Endoscopic Diagnosis of Early Upper Gastrointestinal Cancer: A Systematic Review and Meta-Analysis.

Authors:  Fei Kuang; Juan Du; Mengjia Zhou; Xiangdong Liu; Xinchen Luo; Yong Tang; Bo Li; Song Su
Journal:  Front Oncol       Date:  2022-06-10       Impact factor: 5.738

4.  Assigning a different endoscopist for each annual follow-up may contribute to improved gastric cancer detection rates.

Authors:  Shuhei Unno; Kimihiro Igarashi; Hiroaki Saito; Dai Hirasawa; Toru Okuzono; Yukari Tanaka; Masato Nakahori; Tomoki Matsuda
Journal:  Endosc Int Open       Date:  2022-10-17

5.  Training in early gastric cancer diagnosis improves the detection rate of early gastric cancer: an observational study in China.

Authors:  Qiang Zhang; Zhen-Yu Chen; Chu-di Chen; Tao Liu; Xiao-Wei Tang; Yu-Tang Ren; Si-Lin Huang; Xiao-Bing Cui; Sheng-Li An; Bing Xiao; Yang Bai; Si-de Liu; Bo Jiang; Fa-Chao Zhi; Wei Gong
Journal:  Medicine (Baltimore)       Date:  2015-01       Impact factor: 1.889

6.  Revision of Quality Indicators for the Endoscopy Quality Improvement Program of the National Cancer Screening Program in Korea.

Authors:  Jun Ki Min; Jae Myung Cha; Yu Kyung Cho; Jie-Hyun Kim; Soon Man Yoon; Jong Pil Im; Yunho Jung; Jeong Seop Moon; Jin-Oh Kim; Yoon Tae Jeen
Journal:  Clin Endosc       Date:  2018-05-31

7.  Development and validation of a real-time artificial intelligence-assisted system for detecting early gastric cancer: A multicentre retrospective diagnostic study.

Authors:  Dehua Tang; Lei Wang; Tingsheng Ling; Ying Lv; Muhan Ni; Qiang Zhan; Yiwei Fu; Duanming Zhuang; Huimin Guo; Xiaotan Dou; Wei Zhang; Guifang Xu; Xiaoping Zou
Journal:  EBioMedicine       Date:  2020-11-27       Impact factor: 8.143

8.  Accuracy of endoscopic diagnosis of Helicobacter pylori infection according to level of endoscopic experience and the effect of training.

Authors:  Kazuhiro Watanabe; Naoyoshi Nagata; Takuro Shimbo; Ryo Nakashima; Etsuko Furuhata; Toshiyuki Sakurai; Naoki Akazawa; Chizu Yokoi; Masao Kobayakawa; Junichi Akiyama; Masashi Mizokami; Naomi Uemura
Journal:  BMC Gastroenterol       Date:  2013-08-15       Impact factor: 3.067

9.  Differences in upper gastrointestinal neoplasm detection rates based on inspection time and esophagogastroduodenoscopy training.

Authors:  Shoichi Yoshimizu; Toshiaki Hirasawa; Yusuke Horiuchi; Masami Omae; Akiyoshi Ishiyama; Toshiyuki Yoshio; Tomohiro Tsuchida; Junko Fujisaki
Journal:  Endosc Int Open       Date:  2018-10-08

10.  Detecting early gastric cancer: Comparison between the diagnostic ability of convolutional neural networks and endoscopists.

Authors:  Yohei Ikenoyama; Toshiaki Hirasawa; Mitsuaki Ishioka; Ken Namikawa; Shoichi Yoshimizu; Yusuke Horiuchi; Akiyoshi Ishiyama; Toshiyuki Yoshio; Tomohiro Tsuchida; Yoshinori Takeuchi; Satoki Shichijo; Naoyuki Katayama; Junko Fujisaki; Tomohiro Tada
Journal:  Dig Endosc       Date:  2020-06-02       Impact factor: 6.337

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