AGA Living Clinical Practice Guideline on Computer-Aided Detection-Assisted Colonoscopy

Shahnaz Sultan; Dennis L Shung; Jennifer M Kolb; Farid Foroutan; Cesare Hassan; Charles J Kahi; Peter S Liang; Theodore R Levin; Shazia Mehmood Siddique; Benjamin Lebwohl

doi:10.1053/j.gastro.2025.01.002

AGA Living Clinical Practice Guideline on Computer-Aided Detection-Assisted Colonoscopy

Gastroenterology. 2025 Apr;168(4):691-700. doi: 10.1053/j.gastro.2025.01.002.

Authors

Affiliations

¹ Division of Gastroenterology, Hepatology, and Nutrition, University of Minnesota, Minneapolis, Minnesota; Minneapolis Veterans Affairs Healthcare System, Minneapolis, Minnesota.
² Department of Medicine, Section of Digestive Diseases, Yale School of Medicine, New Haven, Connecticut.
³ Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine at University of California Los Angeles, Los Angeles, California; Division of Gastroenterology, Hepatology and Parenteral Nutrition, Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, California.
⁴ MAGIC Evidence Ecosystem Foundation, Oslo, Norway; Ted Rogers Centre for Heart Research, University Health Network, Toronto, Ontario, Canada.
⁵ IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy; Department of Biomedical Sciences, Humanitas University, Milan, Italy.
⁶ Department of Gastroenterology, Indiana University Medical Center, Indianapolis, Indiana.
⁷ Department of Medicine, Division of Gastroenterology and Hepatology, NYU Langone Health, New York, New York; Department of Medicine, Veterans Affairs New York Harbor Health Care System, New York, New York.
⁸ Division of Research, Kaiser Permanente Northern California, Pleasanton, California; Department of Gastroenterology, Kaiser Permanente Walnut Creek, Walnut Creek, California.
⁹ Division of Gastroenterology, University of Pennsylvania, Philadelphia, Pennsylvania; Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania; Center for Healthcare Improvement and Patient Safety, University of Pennsylvania, Philadelphia, Pennsylvania.
¹⁰ Department of Medicine, Columbia University Irving Medical Center, New York, New York; Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York.

Abstract

Background & aims: This American Gastroenterological Association (AGA) guideline is intended to provide an overview of the evidence and support endoscopists and patients on the use of computer-aided detection (CADe) systems for the detection of colorectal polyps during colonoscopy.

Methods: A multidisciplinary panel of content experts and guideline methodologists used the Grading of Recommendations Assessment, Development and Evaluation framework and relied on the following sources of evidence: (1) a systematic review examining the desirable and undesirable effects (ie, benefits and harms) of CADe-assisted colonoscopy, (2) a microsimulation study estimating the effects of CADe on longer-term patient-important outcomes, (3) a systematic search of evidence evaluating the values and preferences of patients undergoing colonoscopy, and (4) a systematic review of studies evaluating health care providers' trust in artificial intelligence technology in gastroenterology.

Results: The panel reached the conclusion that no recommendation could be made for or against the use of CADe-assisted colonoscopy in light of very low certainty of evidence for the critical outcomes, desirable and undesirable (11 fewer colorectal cancers per 10,000 individuals and 2 fewer colorectal cancer deaths per 10,000 individuals), increased burden of more intensive surveillance colonoscopies (635 more per 10,000 individuals), and cost and resource implications. The panel acknowledged the 8% (95% CI, 6%-10%) increase in adenoma detection rate and 2% (95% CI, 0%-4%) increase in advanced adenoma and/or sessile serrated lesion detection rate.

Conclusions: This guideline highlights the close tradeoff between desirable and undesirable effects and the limitations in the current evidence to support a recommendation. The panel acknowledged the potential for CADe to continually improve as an iterative artificial intelligence application. Ongoing publications providing evidence for critical outcomes will help inform a future recommendation.

Keywords: Artificial Intelligence; Colonoscopy; Colorectal Cancer; Computer-Aided Detection.

Publication types

Practice Guideline
Systematic Review
Research Support, N.I.H., Extramural

MeSH terms

Artificial Intelligence
Colonic Polyps* / diagnosis
Colonic Polyps* / diagnostic imaging
Colonic Polyps* / pathology
Colonoscopy* / adverse effects
Colonoscopy* / methods
Colonoscopy* / standards
Colorectal Neoplasms* / diagnosis
Diagnosis, Computer-Assisted* / standards
Evidence-Based Medicine / standards
Gastroenterology* / standards
Humans
Predictive Value of Tests
Societies, Medical / standards
United States

Abstract

Publication types

MeSH terms

Grants and funding