Literature DB >> 24583752

A computer system to be used with laser-based endoscopy for quantitative diagnosis of early gastric cancer.

Rie Miyaki1, Shigeto Yoshida, Shinji Tanaka, Yoko Kominami, Yoji Sanomura, Taiji Matsuo, Shiro Oka, Bisser Raytchev, Toru Tamaki, Tetsushi Koide, Kazufumi Kaneda, Masaharu Yoshihara, Kazuaki Chayama.   

Abstract

GOALS: To evaluate the usefulness of a newly devised computer system for use with laser-based endoscopy in differentiating between early gastric cancer, reddened lesions, and surrounding tissue.
BACKGROUND: Narrow-band imaging based on laser light illumination has come into recent use. We devised a support vector machine (SVM)-based analysis system to be used with the newly devised endoscopy system to quantitatively identify gastric cancer on images obtained by magnifying endoscopy with blue-laser imaging (BLI). We evaluated the usefulness of the computer system in combination with the new endoscopy system. STUDY: We evaluated the system as applied to 100 consecutive early gastric cancers in 95 patients examined by BLI magnification at Hiroshima University Hospital. We produced a set of images from the 100 early gastric cancers; 40 flat or slightly depressed, small, reddened lesions; and surrounding tissues, and we attempted to identify gastric cancer, reddened lesions, and surrounding tissue quantitatively.
RESULTS: The average SVM output value was 0.846 ± 0.220 for cancerous lesions, 0.381 ± 0.349 for reddened lesions, and 0.219 ± 0.277 for surrounding tissue, with the SVM output value for cancerous lesions being significantly greater than that for reddened lesions or surrounding tissue. The average SVM output value for differentiated-type cancer was 0.840 ± 0.207 and for undifferentiated-type cancer was 0.865 ± 0.259.
CONCLUSIONS: Although further development is needed, we conclude that our computer-based analysis system used with BLI will identify gastric cancers quantitatively.

Entities:  

Mesh:

Year:  2015        PMID: 24583752     DOI: 10.1097/MCG.0000000000000104

Source DB:  PubMed          Journal:  J Clin Gastroenterol        ISSN: 0192-0790            Impact factor:   3.062


  18 in total

1.  Spotting malignancies from gastric endoscopic images using deep learning.

Authors:  Jang Hyung Lee; Young Jae Kim; Yoon Woo Kim; Sungjin Park; Youn-I Choi; Yoon Jae Kim; Dong Kyun Park; Kwang Gi Kim; Jun-Won Chung
Journal:  Surg Endosc       Date:  2019-02-04       Impact factor: 4.584

2.  [Application of fiber Raman endoscopic probe in the diagnosis of gastric cancer].

Authors:  Zhong Wei; Hua Mao; Furong Huang; Huiqing Zhong; Liyun Huang; Yuanpeng Li; Min Lu; Shaoqin Jing
Journal:  Nan Fang Yi Ke Da Xue Xue Bao       Date:  2019-12-30

3.  [Screening of early gastric cancer using Pre-Activation Squeeze-and-Excitation ResNet].

Authors:  X Zhang; Y Wang; J Zhang; H Sun; D Wang; Y Chen; Z Zhou
Journal:  Nan Fang Yi Ke Da Xue Xue Bao       Date:  2021-11-20

Review 4.  Scoping out the future: The application of artificial intelligence to gastrointestinal endoscopy.

Authors:  Scott B Minchenberg; Trent Walradt; Jeremy R Glissen Brown
Journal:  World J Gastrointest Oncol       Date:  2022-05-15

5.  Diagnostic ability of magnifying endoscopy with blue laser imaging for early gastric cancer: a prospective study.

Authors:  Osamu Dohi; Nobuaki Yagi; Atsushi Majima; Yusuke Horii; Tomoko Kitaichi; Yuriko Onozawa; Kentaro Suzuki; Akira Tomie; Reiko Kimura-Tsuchiya; Toshifumi Tsuji; Nobuhisa Yamada; Nobukatsu Bito; Tetsuya Okayama; Naohisa Yoshida; Kazuhiro Kamada; Kazuhiro Katada; Kazuhiko Uchiyama; Takeshi Ishikawa; Tomohisa Takagi; Osamu Handa; Hideyuki Konishi; Yuji Naito; Akio Yanagisawa; Yoshito Itoh
Journal:  Gastric Cancer       Date:  2016-06-13       Impact factor: 7.370

6.  Blue Laser Imaging-Bright Improves Endoscopic Recognition of Superficial Esophageal Squamous Cell Carcinoma.

Authors:  Akira Tomie; Osamu Dohi; Nobuaki Yagi; Hiroaki Kitae; Atsushi Majima; Yusuke Horii; Tomoko Kitaichi; Yuriko Onozawa; Kentaro Suzuki; Reiko Kimura-Tsuchiya; Tetsuya Okayama; Naohisa Yoshida; Kazuhiro Kamada; Kazuhiro Katada; Kazuhiko Uchiyama; Takeshi Ishikawa; Tomohisa Takagi; Osamu Handa; Hideyuki Konishi; Yuji Naito; Yoshito Itoh
Journal:  Gastroenterol Res Pract       Date:  2016-09-22       Impact factor: 2.260

7.  Linked color imaging application for improving the endoscopic diagnosis accuracy: a pilot study.

Authors:  Xiaotian Sun; Tenghui Dong; Yiliang Bi; Min Min; Wei Shen; Yang Xu; Yan Liu
Journal:  Sci Rep       Date:  2016-09-19       Impact factor: 4.379

Review 8.  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

9.  Endoscopic features of lymphoid follicles using blue laser imaging (BLI) endoscopy in the colorectum and its association with chronic bowel symptoms.

Authors:  Tomomitsu Tahara; Kazuya Takahama; Sayumi Tahara; Dai Yoshida; Noriyuki Horiguchi; Tomohiko Kawamura; Masaaki Okubo; Mitsuo Nagasaka; Yoshihito Nakagawa; Makoto Urano; Tomoyuki Shibata; Tetsuya Tuskamoto; Hiro-O Ieda; Makoto Kuroda; Naoki Ohmiya
Journal:  PLoS One       Date:  2017-08-01       Impact factor: 3.240

10.  Evaluation of image-enhanced endoscopic technology using advanced diagnostic endoscopy for the detection of early gastric cancer: a pilot study.

Authors:  Daisuke Yamaguchi; Shinya Kodashima; Mitsuhiro Fujishiro; Satoshi Ono; Keiko Niimi; Satoshi Mochizuki; Yosuke Tsuji; Itsuko Asada-Hirayama; Yoshiki Sakaguchi; Satoki Shichijo; Chihiro Minatsuki; Nobutake Yamamichi; Kazuhiko Koike
Journal:  Endosc Int Open       Date:  2017-09-12
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