1. Ability of artificial intelligence to detect T1 esophageal squamous cell carcinoma from endoscopic videos and the effects of real-time assistance
- Author
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Naoki Akazawa, Natsuko Yoshizawa, Toshiyuki Yoshio, Shoichi Yoshimizu, Ken Namikawa, Yoshimasa Horie, Yusuke Horiuchi, Sho Shiroma, Tomohiro Tsuchida, Toshiaki Hirasawa, Yusuke Kato, Tomohiro Tada, Akiyoshi Ishiyama, Junichi Akiyama, Junko Fujisaki, and Yoshitaka Tokai
- Subjects
Male ,Esophageal Neoplasms ,Science ,Sensitivity and Specificity ,Esophageal squamous cell carcinoma ,Article ,Cancer screening ,03 medical and health sciences ,0302 clinical medicine ,Artificial Intelligence ,medicine ,White light ,Humans ,Cancer ,Multidisciplinary ,medicine.diagnostic_test ,business.industry ,Esophagogastroduodenoscopy ,Gastroenterology ,Reproducibility of Results ,Endoscopy ,Esophageal cancer ,medicine.disease ,Predictive value ,030220 oncology & carcinogenesis ,Carcinoma, Squamous Cell ,Medicine ,Female ,030211 gastroenterology & hepatology ,Neural Networks, Computer ,Artificial intelligence ,business ,Algorithms - Abstract
Diagnosis using artificial intelligence (AI) with deep learning could be useful in endoscopic examinations. We investigated the ability of AI to detect superficial esophageal squamous cell carcinoma (ESCC) from esophagogastroduodenoscopy (EGD) videos. We retrospectively collected 8428 EGD images of esophageal cancer to develop a convolutional neural network through deep learning. We evaluated the detection accuracy of the AI diagnosing system compared with that of 18 endoscopists. We used 144 EGD videos for the two validation sets. First, we used 64 EGD observation videos of ESCCs using both white light imaging (WLI) and narrow-band imaging (NBI). We then evaluated the system using 80 EGD videos from 40 patients (20 with superficial ESCC and 20 with non-ESCC). In the first set, the AI system correctly diagnosed 100% ESCCs. In the second set, it correctly detected 85% (17/20) ESCCs. Of these, 75% (15/20) and 55% (11/22) were detected by WLI and NBI, respectively, and the positive predictive value was 36.7%. The endoscopists correctly detected 45% (25–70%) ESCCs. With AI real-time assistance, the sensitivities of the endoscopists were significantly improved without AI assistance (p
- Published
- 2021