aDepartment of Gastroenterology, Foundation for Detection of Early Gastric Carcinoma, Tokyo, Japan
bDepartment of Gastroenterology, Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan
cDepartment of Pathology, Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan
dMedical Simulation Center, Jichi Medical University, Tochigi, Japan
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Article / Publication DetailsFirst-Page Preview
Received: June 07, 2022
Accepted: November 12, 2022
Published online: January 04, 2023
Number of Print Pages: 9
Number of Figures: 3
Number of Tables: 3
ISSN: 0012-2823 (Print)
eISSN: 1421-9867 (Online)
For additional information: https://www.karger.com/DIG
AbstractIntroduction: Computer-aided diagnostic systems are emerging in the field of gastrointestinal endoscopy. In this study, we assessed the clinical performance of the computer-aided detection (CADe) of colonic adenomas using a new endoscopic artificial intelligence system. Methods: This was a single-center prospective randomized study including 415 participants allocated into the CADe group (n = 207) and control group (n = 208). All endoscopic examinations were performed by experienced endoscopists. The performance of the CADe was assessed based on the adenoma detection rate (ADR). Additionally, we compared the adenoma miss rate for the rectosigmoid colon (AMRrs) between the groups. Results: The basic demographic and procedural characteristics of the CADe and control groups were as follows: mean age, 54.9 and 55.9 years; male sex, 73.9% and 69.7% of participants; and mean withdrawal time, 411.8 and 399.0 s, respectively. The ADR was 59.4% in the CADe group and 47.6% in the control group (p = 0.018). The AMRrs was 11.9% in the CADe group and 26.0% in the control group (p = 0.037). Conclusion: The colonoscopy with the CADe system yielded an 11.8% higher ADR than that performed by experienced endoscopists alone. Moreover, there was no need to extend the examination time or request the assistance of additional medical staff to achieve this improved effectiveness. We believe that the novel CADe system can lead to considerable advances in colorectal cancer diagnosis.
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Received: June 07, 2022
Accepted: November 12, 2022
Published online: January 04, 2023
Number of Print Pages: 9
Number of Figures: 3
Number of Tables: 3
ISSN: 0012-2823 (Print)
eISSN: 1421-9867 (Online)
For additional information: https://www.karger.com/DIG
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