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Real-Time Computer-Aided Detection of Colorectal Neoplasia During Colonoscopy: A Systematic Review and Meta-analysis
Abstract
BACKGROUND: Artificial intelligence computer-aided detection (CADe) of colorectal neoplasia during colonoscopy may increase adenoma detection rates (ADRs) and reduce adenoma miss rates, but it may increase overdiagnosis and overtreatment of nonneoplastic polyps. PURPOSE: To quantify the benefits and harms of CADe in randomized trials. DESIGN: Systematic review and meta-analysis. (PROSPERO: CRD42022293181). DATA SOURCES: Medline, Embase, and Scopus databases through February 2023. STUDY SELECTION: Randomized trials comparing CADe-assisted with standard colonoscopy for polyp and cancer detection. DATA EXTRACTION: Adenoma detection rate (proportion of patients with ≥1 adenoma), number of adenomas detected per colonoscopy, advanced adenoma (≥10 mm with high-grade dysplasia and villous histology), number of serrated lesions per colonoscopy, and adenoma miss rate were extracted as benefit outcomes. Number of polypectomies for nonneoplastic lesions and withdrawal time were extracted as harm outcomes. For each outcome, studies were pooled using a random-effects model. Certainty of evidence was assessed using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) framework. DATA SYNTHESIS: Twenty-one randomized trials on 18 232 patients were included. The ADR was higher in the CADe group than in the standard colonoscopy group (44.0% vs. 35.9%; relative risk, 1.24 [95% CI, 1.16 to 1.33]; low-certainty evidence), corresponding to a 55% (risk ratio, 0.45 [CI, 0.35 to 0.58]) relative reduction in miss rate (moderate-certainty evidence). More nonneoplastic polyps were removed in the CADe than the standard group (0.52 vs. 0.34 per colonoscopy; mean difference [MD], 0.18 polypectomy [CI, 0.11 to 0.26 polypectomy]; low-certainty evidence). Mean inspection time increased only marginally with CADe (MD, 0.47 minute [CI, 0.23 to 0.72 minute]; moderate-certainty evidence). LIMITATIONS: This review focused on surrogates of patient-important outcomes. Most patients, however, may consider cancer incidence and cancer-related mortality important outcomes. The effect of CADe on such patient-important outcomes remains unclear. CONCLUSION: The use of CADe for polyp detection during colonoscopy results in increased detection of adenomas but not advanced adenomas and in higher rates of unnecessary removal of nonneoplastic polyps. PRIMARY FUNDING SOURCE: European Commission Horizon 2020 Marie Skłodowska-Curie Individual Fellowship.
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“Meta-analyses report a ~14% relative improvement in the ADR over standard colonoscopy [39,40].”
From Artificial Intelligence in Clinical Oncology: From Productivity Enhancement to Creative Discovery (2025) · cites this paper as [40]
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“Additionally, a meta-analysis including 12 studies found little or no effect of CADe on serrated polyp detection and noted an increased rate of noncancerous polyp removal [90].”
Large language model for interpreting the Paris classification of colorectal polyps
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Artificial Intelligence for Gastroenterology Practice: A Modified Delphi Consensus
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“%) saw a 56% relative improvement with AI, whereas in high-ADR contexts ( > 40%), the improvement was only 16% [ 18].”
Computer-Assisted Colonoscopy in High–Adenoma Detection Rate Settings in a High-Risk Population
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From Staining Techniques to Artificial Intelligence: A Review of Colorectal Polyps Characterization
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MethodImpact of Artificial Intelligence on Pancreaticobiliary Endoscopy
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Metadata
- Authors
- Hassan, C., Spadaccini, M., Mori, Y., Foroutan, F., Facciorusso, A., Gkolfakis, P., Tziatzios, G., Triantafyllou, K., Antonelli, G., Khalaf, K., Rizkala, T., Vandvik, P. O., Fugazza, A., Rondonotti, E., Glissen-Brown, J. R., Kamba, S., Maida, M., Correale, L., Bhandari, P., Jover, R., Sharma, P., Rex, D. K., & Repici, A.
- Affiliations
- Humanitas University (IT)
- University of Oslo (NO)
- University Health Network (CA)
- University of Foggia (IT)
- Université Libre de Bruxelles (BE)
- National and Kapodistrian University of Athens (GR)
- Hepatogastroenterology Unit, Second Department of Internal Medicine-Propaedeutic, Medical School, National and Kapodistrian University of Athens, Attikon University General Hospital, Athens, Greece (G.T., K.T.)
- Sapienza University of Rome (IT)
- Lovisenberg Diakonale Sykehus (NO)
- IRCCS Humanitas Research Hospital (IT)
- Ospedale Valduce (IT)
- Center for Advanced Endoscopy, Division of Gastroenterology and Hepatology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts (J.R.G.)
- Jikei University School of Medicine (JP)
- Gastroenterology and Endoscopy Unit, S. Elia-Raimondi Hospital, Caltanissetta, Italy (M.M.)
- Queen Alexandra Hospital (GB)
- Hospital General Universitario de Alicante Doctor Balmis (ES)
- Kansas City VA Medical Center (US)
- Indiana University Hospital (US)
- Corresponding author
- Hassan, Cesare
- Spadaccini, Marco
- ORCID
- Hassan, Cesare
- Spadaccini, Marco
- Mori, Yuichi
- Foroutan, Farid
- Facciorusso, Antonio
- Gkolfakis, Paraskevas
- Tziatzios, Georgios
- Antonelli, Giulio
- Khalaf, Kareem
- Rizkala, Tommy
- Vandvik, Per Olav
- Fugazza, Alessandro
- Rondonotti, Emanuele
- Glissen-Brown, Jeremy R.
- Kamba, Shunsuke
- Maida, Marcello
- Correale, Loredana
- Bhandari, Pradeep
- Jover, Rodrigo
- Sharma, Prateek
- Rex, Douglas K.
- Repici, Alessandro
- Venue
- Annals of Internal Medicine
- Publisher
- American College of Physicians
- Published
- 2023-09
- Volume
- 176
- Issue
- 9
- Pages
- 1209-1220
- ISSN
- 0003-4819 (ISSN-L)
- 1539-3704
- OpenAlex
- W4386213466
- Cited by
- 216
- References
- 37
- Citations by year
- 2026: 62 · 2025: 88 · 2024: 58 · 2023: 8
- FWCI
- 6.99
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Annals of Internal Medicine (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Japan Society for the Promotion of Science (23K24615)
- 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
- computer-aided detection, colorectal neoplasia, colonoscopy, adenoma detection rate, advanced adenoma, serrated lesions, polypectomy, overdiagnosis, artificial intelligence, colorectal cancer screening, withdrawal time, inspection time, adenoma miss rate, colorectal cancer
- MeSH terms
- Artificial Intelligence, Colonoscopy, Computers, Humans, Colorectal Neoplasms, Databases, Factual
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