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INOUE Yuji
Department School of Medicine(Tokyo Women's Medical University Hospital), School of Medicine Position |
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| Article types | Original article |
| Language | English |
| Peer review | Non peer reviewed |
| Title | Computer-aided diagnosis of early-stage colorectal cancer using nonmagnified endoscopic white-light images (with videos) |
| Journal | Formal name：Gastrointestinal endoscopy Abbreviation：Gastrointest Endosc ISSN code：10976779/00165107 |
| Domestic / Foregin | Foregin |
| Volume, Issue, Page | 98(1),pp.90-99 |
| Author and coauthor | NEMOTO Daiki,Guo Zhe,KATSUKI Shinichi,TAKEZAWA Takahito,MAEMOTO Ryo,KAWASAKI Keisuke,INOUE Ken,AKUTAGAWA Takashi,TANAKA Hirohito,SATO Koichiro,OMORI Teppei,TAKANASHI Kunihiro,HAYASHI Yoshikazu,NAKAJIMA Yuki,MIYAKURA Yasuyuki,MATSUMOTO Takayuki,YOSHIDA Naohisa,ESAKI Motohiro,URAOKA Toshio,KATO Hiroyuki,INOUE Yuji, Peng Boyuan, Zhang Ruiyao,HISABE Takashi,MATSUDA Tomoki,YAMAMOTO Hironori,TANAKA Noriko, Lefor Alan Kawarai, Zhu Xin,TOGASHI Kazutomo |
| Publication date | 2023/07 |
| Summary | BACKGROUND AND AIMS:Differentiation of colorectal cancers (CRCs) with deep submucosal invasion (T1b) from CRCs with superficial invasion (T1a) or no invasion (Tis) is not straightforward. This study aimed to develop a computer-aided diagnosis (CADx) system to establish the diagnosis of early-stage cancers using nonmagnified endoscopic white-light images alone.METHODS:From 5108 images, 1513 lesions (Tis, 1074; T1a, 145; T1b, 294) were collected from 1470 patients at 10 academic hospitals and assigned to training and testing datasets (3:1). The ResNet-50 network was used as the backbone to extract features from images. Oversampling and focal loss were used to compensate class imbalance of the invasive stage. Diagnostic performance was assessed using the testing dataset including 403 CRCs with 1392 images. Two experts and 2 trainees read the identical testing dataset.RESULTS:At a 90% cutoff for the per-lesion score, CADx showed the highest specificity of 94.4% (95% confidence interval [CI], 91.3-96.6), with 59.8% (95% CI, 48.3-70.4) sensitivity and 87.3% (95% CI, 83.7-90.4) accuracy. The area under the characteristic curve was 85.1% (95% CI, 79.9-90.4) for CADx, 88.2% (95% CI, 83.7-92.8) for expert 1, 85.9% (95% CI, 80.9-90.9) for expert 2, 77.0% (95% CI, 71.5-82.4) for trainee 1 (vs CADx; P = .0076), and 66.2% (95% CI, 60.6-71.9) for trainee 2 (P < .0001). The function was also confirmed on 9 short videos.CONCLUSIONS:A CADx system developed with endoscopic white-light images showed excellent per-lesion specificity and accuracy for T1b lesion diagnosis, equivalent to experts and superior to trainees. (Clinical trial registration number: UMIN000037053.). |
| DOI | 10.1016/j.gie.2023.01.050 |
| PMID | 36738793 |