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Cited by 271Colorectal Cancer Screening and DetectionAI in cancer detectionColorectal Cancer Surgical Treatments

Artificial intelligence for polyp detection during colonoscopy: a systematic review and meta-analysis

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Barua, Ishita, Vinsard, Daniela Guerrero, Jodal, Henriette C., Løberg, Magnus, Kalager, Mette, Holme, Øyvind, Misawa, Masashi, Bretthauer, Michael +1 more·2021·Endoscopy
DOI 10.1055/a-1201-7165
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Abstract

Background Artificial intelligence (AI)-based polyp detection systems are used during colonoscopy with the aim of increasing lesion detection and improving colonoscopy quality. Patients and methods: We performed a systematic review and meta-analysis of prospective trials to determine the value of AI-based polyp detection systems for detection of polyps and colorectal cancer. We performed systematic searches in MEDLINE, EMBASE, and Cochrane CENTRAL. Independent reviewers screened studies and assessed eligibility, certainty of evidence, and risk of bias. We compared colonoscopy with and without AI by calculating relative and absolute risks and mean differences for detection of polyps, adenomas, and colorectal cancer. Results Five randomized trials were eligible for analysis. Colonoscopy with AI increased adenoma detection rates (ADRs) and polyp detection rates (PDRs) compared to colonoscopy without AI (values given with 95 %CI). ADR with AI was 29.6 % (22.2 % – 37.0 %) versus 19.3 % (12.7 % – 25.9 %) without AI; relative risk (RR] 1.52 (1.31 – 1.77), with high certainty. PDR was 45.4 % (41.1 % – 49.8 %) with AI versus 30.6 % (26.5 % – 34.6 %) without AI; RR 1.48 (1.37 – 1.60), with high certainty. There was no difference in detection of advanced adenomas (mean advanced adenomas per colonoscopy 0.03 for each group, high certainty). Mean adenomas detected per colonoscopy was higher for small adenomas (≤ 5 mm) for AI versus non-AI (mean difference 0.15 [0.12 – 0.18]), but not for larger adenomas (> 5 – ≤ 10 mm, mean difference 0.03 [0.01 – 0.05]; > 10 mm, mean difference 0.01 [0.00 – 0.02]; high certainty). Data on cancer are unavailable. Conclusions AI-based polyp detection systems during colonoscopy increase detection of small nonadvanced adenomas and polyps, but not of advanced adenomas.

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  • Overall, evidence strongly supports adoption of AI for improving lesion detection during colonoscopy.

    “Overall, the evidence strongly supports the adoption of AI for improving lesion detection during colonoscopy ( Tables 3 and 4 ) [76 , 78-81] .”

    From Enhancing human-AI collaboration: The case of colonoscopy (2024) · cites this paper as [78]

    The systematic review and meta-analysis section reports high-certainty evidence that AI-assisted colonoscopy increases polyp and adenoma detection rates. But the same section says the increase is chiefly in small polyps and non-advanced adenomas, with no difference in advanced adenoma detection, and cautions that the clinical value must be weighed against overdiagnosis and overtreatment. It therefore supports improved detection, but not the unqualified claim that evidence strongly supports adoption. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

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Authors
Barua, I., Vinsard, D. G., Jodal, H. C., Løberg, M., Kalager, M., Holme, Ø., Misawa, M., Bretthauer, M., & Mori, Y.
Affiliations
  • Oslo University Hospital (NO)
  • Mayo Clinic (US)
  • SHOWA Medical University Northern Yokohama Hospital (JP)
ORCID
Venue
Endoscopy
Publisher
Georg Thieme Verlag KG
Published
2020-06-17
Volume
53
Issue
03
Pages
277-284
ISSN
  • 0013-726X (ISSN-L)
  • 1438-8812
DOI
10.1055/a-1201-7165
OpenAlex
W3036426348
Cited by
271
References
7
Citations by year
2026: 29 · 2025: 52 · 2024: 48 · 2023: 47 · 2022: 48 · 2021: 39 · 2020: 7
FWCI
3.82
Type
journal article
Language
en
Open access
Locations
  • Endoscopy (publishedVersion)
  • PubMed (publishedVersion)
  • NORA - Norwegian Open Research Archives (submittedVersion, other-oa)
Funders
  • Norwegian Research Council (250256)
  • Norwegian Cancer Society (190345,6741288)
Topics
  • Health Sciences › Medicine › Oncology › Colorectal Cancer Screening and Detection
  • Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
  • Health Sciences › Medicine › Oncology › Colorectal Cancer Surgical Treatments
Keywords
artificial intelligence, polyp detection, colonoscopy, adenoma detection rate, colorectal cancer detection, advanced adenoma, small adenomas, colorectal polyps, colonoscopy quality
MeSH terms
Adenoma, Artificial Intelligence, Colonic Polyps, Colonoscopy, Humans, Prospective Studies

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