Literature DB >> 27494455

Impact of an automated system for endocytoscopic diagnosis of small colorectal lesions: an international web-based study.

Yuichi Mori1, Shin-Ei Kudo1, Philip Wai Yan Chiu2, Rajvinder Singh3, Masashi Misawa1, Kunihiko Wakamura1, Toyoki Kudo1, Takemasa Hayashi1, Atsushi Katagiri1, Hideyuki Miyachi1, Fumio Ishida1, Yasuharu Maeda1, Haruhiro Inoue4, Yukitaka Nimura5, Masahiro Oda6, Kensaku Mori7.   

Abstract

Background and study aims: Optical diagnosis of colorectal polyps is expected to improve the cost-effectiveness of colonoscopy, but achieving a high accuracy is difficult for trainees. Computer-aided diagnosis (CAD) is therefore receiving attention as an attractive tool. This study aimed to validate the efficacy of the latest CAD model for endocytoscopy (380-fold ultra-magnifying endoscopy). Patients and methods: This international web-based trial was conducted between August and November 2015. A web-based test comprising one white-light and one endocytoscopic image of 205 small colorectal polyps (≤ 10 mm) from 123 patients was undertaken by both CAD and by endoscopists (three experts and ten non-experts from three countries). Outcome measures were accuracy in identifying neoplastic change in diminutive (≤ 5 mm) and small (≤ 10 mm) polyps, and accuracy in predicting post-polypectomy surveillance intervals according to current guidelines for high confidence optical diagnoses of diminutive polyps.
Results: Of the 205 small polyps (147 neoplastic and 58 non-neoplastic), 139 were diminutive. CAD was accurate for 89 % (95 % confidence interval [CI] 83 % - 94 %) of diminutive polyps and 89 % (84 % - 93 %) of small polyps, which was significantly greater than results for the non-experts (73 % [71 % - 76 %], P < 0.001; and 76 % [74 % - 78 %], P < 0.001, respectively) and comparable with the experts' results (90 % [87 % - 93 %], P = 0.703; and 91 % [89 % - 93 %], P = 0.106, respectively). The surveillance interval predicted by CAD provided 98 % (93 % - 100 %) and 96 % (91 % - 99 %) agreement with pathology-directed intervals of the European and American guidelines, respectively. Conclusions: The use of CAD in endocytoscopy can be effective in the management of diminutive/small colorectal polyps.UMIN Clinical Trial Registry: UMIN000018185. © Georg Thieme Verlag KG Stuttgart · New York.

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Mesh:

Year:  2016        PMID: 27494455     DOI: 10.1055/s-0042-113609

Source DB:  PubMed          Journal:  Endoscopy        ISSN: 0013-726X            Impact factor:   10.093


  23 in total

Review 1.  Computer-aided diagnosis for colonoscopy.

Authors:  Yuichi Mori; Shin-Ei Kudo; Tyler M Berzin; Masashi Misawa; Kenichi Takeda
Journal:  Endoscopy       Date:  2017-05-24       Impact factor: 10.093

Review 2.  Endocytoscopy: technology and clinical application in the lower GI tract.

Authors:  Hiroyuki Takamaru; Shih Yea Sylvia Wu; Yutaka Saito
Journal:  Transl Gastroenterol Hepatol       Date:  2020-07-05

Review 3.  Current status and limitations of artificial intelligence in colonoscopy.

Authors:  Alexander Hann; Joel Troya; Daniel Fitting
Journal:  United European Gastroenterol J       Date:  2021-06-07       Impact factor: 4.623

Review 4.  Current Status and Future Perspectives of Artificial Intelligence in Colonoscopy.

Authors:  Yu Kamitani; Kouichi Nonaka; Hajime Isomoto
Journal:  J Clin Med       Date:  2022-05-22       Impact factor: 4.964

5.  Development of a computer-aided tool for the pattern recognition of facial features in diagnosing Turner syndrome: comparison of diagnostic accuracy with clinical workers.

Authors:  Shi Chen; Zhou-Xian Pan; Hui-Juan Zhu; Qing Wang; Ji-Jiang Yang; Yi Lei; Jian-Qiang Li; Hui Pan
Journal:  Sci Rep       Date:  2018-06-18       Impact factor: 4.379

Review 6.  Advanced Endoscopic Imaging in Colonic Neoplasia.

Authors:  Timo Rath; Nadine Morgenstern; Francesco Vitali; Raja Atreya; Markus F Neurath
Journal:  Visc Med       Date:  2020-01-21

Review 7.  Artificial Intelligence in Endoscopy.

Authors:  Yutaka Okagawa; Seiichiro Abe; Masayoshi Yamada; Ichiro Oda; Yutaka Saito
Journal:  Dig Dis Sci       Date:  2021-06-21       Impact factor: 3.199

8.  Endocystoscopy for colonic polyps: Is there a future for this diagnostic modality in routine practice?

Authors:  Yasushi Sano; Mineo Iwatate
Journal:  Endosc Int Open       Date:  2021-06-17

9.  Artificial intelligence-based endoscopic diagnosis of colorectal polyps using residual networks.

Authors:  Yoriaki Komeda; Hisashi Handa; Ryoma Matsui; Shohei Hatori; Riku Yamamoto; Toshiharu Sakurai; Mamoru Takenaka; Satoru Hagiwara; Naoshi Nishida; Hiroshi Kashida; Tomohiro Watanabe; Masatoshi Kudo
Journal:  PLoS One       Date:  2021-06-22       Impact factor: 3.240

Review 10.  Potential applications of artificial intelligence in colorectal polyps and cancer: Recent advances and prospects.

Authors:  Ke-Wei Wang; Ming Dong
Journal:  World J Gastroenterol       Date:  2020-09-14       Impact factor: 5.742

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