Artificial intelligence‐assisted colonoscopy: A prospective, multicenter, randomized controlled trial of polyp detection. (3rd September 2021)
- Record Type:
- Journal Article
- Title:
- Artificial intelligence‐assisted colonoscopy: A prospective, multicenter, randomized controlled trial of polyp detection. (3rd September 2021)
- Main Title:
- Artificial intelligence‐assisted colonoscopy: A prospective, multicenter, randomized controlled trial of polyp detection
- Authors:
- Xu, Lei
He, Xinjue
Zhou, Jianbo
Zhang, Jie
Mao, Xinli
Ye, Guoliang
Chen, Qiang
Xu, Feng
Sang, Jianzhong
Wang, Jun
Ding, Yong
Li, Youming
Yu, Chaohui - Abstract:
- Abstract: Background: Artificial intelligence (AI) assistance has been considered as a promising way to improve colonoscopic polyp detection, but there are limited prospective studies on real‐time use of AI systems. Methods: We conducted a prospective, multicenter, randomized controlled trial of patients undergoing colonoscopy at six centers. Eligible patients were randomly assigned to conventional colonoscopy (control group) or AI‐assisted colonoscopy (AI group). AI assistance was our newly developed AI system for real‐time colonoscopic polyp detection. Primary outcome is polyp detection rate (PDR). Secondary outcomes include polyps per positive patient (PPP), polyps per colonoscopy (PPC), and non‐first polyps per colonoscopy (PPC‐Plus). Results: A total of 2352 patients were included in the final analysis. Compared with the control, AI group did not show significant increment in PDR (38.8% vs. 36.2%, p = 0.183), but its PPC‐Plus was significantly higher (0.5 vs. 0.4, p < 0.05). In addition, AI group detected more diminutive polyps (76.0% vs. 68.8%, p < 0.01) and flat polyps (5.9% vs. 3.3%, p < 0.05). The effects varied somewhat between centers. In further logistic regression analysis, AI assistance independently contributed to the increment of PDR, and the impact was more pronounced for male endoscopists, shorter insertion time but longer withdrawal time, and elderly patients with larger waist circumference. Conclusion: The intervention of AI plays a limited role inAbstract: Background: Artificial intelligence (AI) assistance has been considered as a promising way to improve colonoscopic polyp detection, but there are limited prospective studies on real‐time use of AI systems. Methods: We conducted a prospective, multicenter, randomized controlled trial of patients undergoing colonoscopy at six centers. Eligible patients were randomly assigned to conventional colonoscopy (control group) or AI‐assisted colonoscopy (AI group). AI assistance was our newly developed AI system for real‐time colonoscopic polyp detection. Primary outcome is polyp detection rate (PDR). Secondary outcomes include polyps per positive patient (PPP), polyps per colonoscopy (PPC), and non‐first polyps per colonoscopy (PPC‐Plus). Results: A total of 2352 patients were included in the final analysis. Compared with the control, AI group did not show significant increment in PDR (38.8% vs. 36.2%, p = 0.183), but its PPC‐Plus was significantly higher (0.5 vs. 0.4, p < 0.05). In addition, AI group detected more diminutive polyps (76.0% vs. 68.8%, p < 0.01) and flat polyps (5.9% vs. 3.3%, p < 0.05). The effects varied somewhat between centers. In further logistic regression analysis, AI assistance independently contributed to the increment of PDR, and the impact was more pronounced for male endoscopists, shorter insertion time but longer withdrawal time, and elderly patients with larger waist circumference. Conclusion: The intervention of AI plays a limited role in overall polyp detection, but increases detection of easily missed polyps; ChiCTR.org.cn number, ChiCTR1800015607. Abstract : Artificial intelligence (AI) assistance plays a limited role in overall polyp detection. AI system increases detection of easily missed polyps, including non‐first polyps, diminutive and flat polyps. The impact is greater for male operators, longer withdrawal time, and elderly obese patients. … (more)
- Is Part Of:
- Cancer medicine. Volume 10:Number 20(2021)
- Journal:
- Cancer medicine
- Issue:
- Volume 10:Number 20(2021)
- Issue Display:
- Volume 10, Issue 20 (2021)
- Year:
- 2021
- Volume:
- 10
- Issue:
- 20
- Issue Sort Value:
- 2021-0010-0020-0000
- Page Start:
- 7184
- Page End:
- 7193
- Publication Date:
- 2021-09-03
- Subjects:
- artificial intelligence -- cancer prevention -- colorectal polyps -- endoscopy -- image analysis
616.994005 - Journal URLs:
- http://onlinelibrary.wiley.com/ ↗
http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2045-7634 ↗ - DOI:
- 10.1002/cam4.4261 ↗
- Languages:
- English
- ISSNs:
- 2045-7634
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 19587.xml