What happened
The European Society of Gastrointestinal Endoscopy (ESGE) convened 23 members from 15 countries to advise on computer-aided detection (CADe) during colonoscopy. Only members without financial interests in CADe makers could vote. The panel used evidence from the BMJ Rapid Recommendations initiative and the MAGIC Evidence Ecosystem Foundation. In a review of 44 randomized trials, adenomas were found in 44.7% of patients with CADe against 36.7% without. In a microsimulation over 10 years, CADe led to 11 fewer colorectal cancers and 2 fewer cancer deaths per 10,000 patients. In the same model, 635 more patients per 10,000 needed surveillance colonoscopy. On 18 December 2024, 13 of 19 voters backed CADe for screening and surveillance, and 6 voted against. ESGE published the weak recommendation on 27 March 2025. No trial measured cancer incidence or deaths, and the modeled effects carry low or very low certainty. The BMJ's guideline panel, working from the same evidence, made a weak recommendation against routine use.
Sources
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Peer-reviewed study, by authors with no tie to the system.
Soleymanjahi S, Huebner J, Elmansy L, et al. Artificial Intelligence-Assisted Colonoscopy for Polyp Detection: A Systematic Review and Meta-analysis. Annals of Internal Medicine 2024;177:1652-1663. doi:10.7326/ANNALS-24-00981. Results, sensitivity analysis by CADe platform (archived copy). No funding was received.
On comparing the performance across different CADe platforms, we found a trend toward increased overall ADR in studies using a CADe that was developed on the basis of You Only Look Once (YOLO) (https://arxiv.org/abs/1506.02640) (944 of 3279 [29%] vs. 740 of 3315 [22%], RR = 1.36 [CI, 1.14 to 1.62]), compared with studies using GI Genius (Medtronic) (2105 of 3830 [55%] vs. 1906 of 3819 [50%], RR = 1.16 [CI, 1.00 to 1.34]) (Supplement Figure 3). Studies using Fujifilm CAD EYE (1479 of 2796 [53%] vs. 1043 of 2399 [43%], RR = 1.21 [CI, 1.10 to 1.34]) and EndoScreener (developed based on SegNet) (729 of 2332 [31%] vs. 596 of 2331 [26%], RR = 1.22 [CI, 1.11 to 1.35]) exhibited similar performance in ADR.
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Assessment report, by authors with no tie to the system.
European Society of Gastrointestinal Endoscopy. Bretthauer M, Ahmed J, Antonelli G, et al. Use of computer-assisted detection (CADe) colonoscopy in colorectal cancer screening and surveillance: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement. Endoscopy 2025;57(6):667-673, published online 27 March 2025. doi:10.1055/a-2543-0370. Abstract, Recommendation.
The panel believes that most well-informed patients who have already decided to undergo colonoscopy for screening or surveillance would favor CADe assistance during colonoscopy. This is due to the potential benefits, although limited, of reduction in colorectal cancer incidence and mortality.
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Assessment report, by authors with no tie to the system. Context or contrary evidence.
Foroutan F, Vandvik PO, Helsingen LM, et al. Computer aided detection and diagnosis of polyps in adult patients undergoing colonoscopy: a living clinical practice guideline. BMJ Rapid Recommendations, BMJ 2025;388:e082656. PMID 40147837. Abstract, Recommendation.
For adults who have agreed to undergo colonoscopy, we suggest against the routine use of CADe (weak recommendation).
Details
AI system
- Workflow
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CADe analyzed the live colonoscopy video and flagged possible polyps for the endoscopist. The trials randomized patients to colonoscopy with or without CADe.
Follow-up
- Conditions for replication
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Patients undergo colonoscopy for primary screening, after a positive fecal immunochemical test or for polyp surveillance. Patients accept more surveillance colonoscopies and more removal of polyps that would not have become cancer.
Entry details
- Sector
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Healthcare.
- Purpose
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Medtronic, Fujifilm, Wision AI and other makers built CADe systems to flag possible polyps to the endoscopist in real time during colonoscopy.
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Cite this record
Peter H. Vartanian. (2026). European endoscopists weakly back CADe in screening colonoscopy (AIBD-1125). Artificial Intelligence Benefits Database, edition of 1 November 2026. https://petervartanian.xyz/aibd/records/AIBD-1125.html (archived at https://doi.org/10.7910/DVN/AADSII, version 7.0)