A Computer System To Be Used With Laser-based Endoscopy for Quantitative Diagnosis of Early Gastric Cancer. Issue 2 (February 2015)

• Record Type: Journal Article
• Authors: Miyaki, Rie; Yoshida, Shigeto; Tanaka, Shinji; Kominami, Yoko; Sanomura, Yoji; Matsuo, Taiji; Oka, Shiro; Raytchev, Bisser; Tamaki, Toru; Koide, Tetsushi; Kaneda, Kazufumi; Yoshihara, Masaharu; Chayama, Kazuaki
• Is Part Of: Journal of clinical gastroenterology. Volume 49:Issue 2(2015)
• Publication Date: 2015-02
• Subjects: laser-based endoscopy -- early gastric cancer -- magnifying endoscopy -- quantitative analysis; Gastroenterology -- Periodicals; Digestive organs -- Diseases -- Periodicals; Gastroenterology -- Periodicals; Digestive organs -- Diseases; Gastroenterology; Periodicals; Periodicals; 616.33005
• DOI: 10.1097/MCG.0000000000000104
• Languages: English
• ISSNs: 0192-0790

Abstract

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.