Computer Assisted Detection of Neoplasia During Colonoscopy Evaluation

NCT05888623 | Completed FDA Device

• 1 other identifier: VHA_NGHP_001
• Study Type: observational
• Target: 334,200
• Locations: 1 country
• Sites: 1

Brief Summary

The goal of this cluster randomized study is to determine if artificial intelligence systems used during colonoscopy can improve the detection of precancerous polyps in the colon. The primary question it aims to answer is whether computer-assisted detection devices improve the proportion of colonoscopies found to have precancerous adenomatous polyps. Secondary aims will assess if computer-assisted detection devices improve the proportion of colonoscopies found to other types of precancerous polyps known as sessile serrated lesions, or cancer of the colon and rectum. The study will also assess possible negative effects of use of computer-assisted detection (e.g., prolonging the procedure time or false-positive biopsies) and survey device users to learn about their experience with this technology. The study team will provide computer-assisted detection devices to randomly chosen VA medical centers for use during colonoscopy and compare colonoscopy findings for patients who undergo colonoscopy at facilities that are equipped with these devices to the findings of patients who undergo colonoscopy at VA facilities that do not have these devices. A survey will be distributed to physicians who perform colonoscopy to assess their experience using computer-assisted detection devices.

Conditions

Colorectal Neoplasms

Keywords

colonoscopy; artificial intelligence; adenoma; Veterans; quality assurance

Outcome Measures

Primary Outcomes (1)

• Adenoma Detection Rate

  Change in the proportion of colonoscopies in which one or more adenomas are detected

  Baseline and 6 months

Secondary Outcomes (6)

• Adenocarcinoma detection rate

  Baseline and 6 months

• Sessile serrated lesion detection rate

  Baseline and 6 months

• Proportion of colonoscopies with pathology obtained

  Baseline and 6 months

• Proportion of pathology without adenoma or adenocarcinoma

  Baseline and 6 months

• Withdrawal time without interventions

  Baseline and 6 months

Study Arms (2)

Computer Assisted Detection

Colonoscopies performed at a VA facility with computer assisted detection (CADe) artificial intelligence available.

Device: Computer Assisted Detection

Conventional Colonoscopy

Colonoscopies performed at a VA facility without CADe artificial intelligence available

Interventions

Computer Assisted Detection DEVICE

Computer-assisted polyp detection system that utilizes artificial intelligence (AI) during colonoscopy

Also known as: GI Genius Intelligent Endoscopy Module (Medtronic)

Computer Assisted Detection

Eligibility Criteria

• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Veterans undergoing colonoscopy for any indication at VA facilities across the United States.

You may qualify if:

• Colonoscopy performed at a Veterans Affairs (VA) medical center

You may not qualify if:

• Colonoscopy performed at VA medical centers that acquired computer-assisted detection artificial intelligence devices through non-random assignment
• Colonoscopy performed at a VA medical center where pathology results are not available

Sponsors & Collaborators

• VA Puget Sound Health Care System: lead
• VA Salt Lake City Health Care System: collaborator
• San Francisco Veterans Affairs Medical Center: collaborator

Study Sites (1)

VA Puget Sound Health Care System

Seattle, Washington, 98108, United States

Location

Related Publications (6)

• Levy I, Bruckmayer L, Klang E, Ben-Horin S, Kopylov U. Artificial Intelligence-Aided Colonoscopy Does Not Increase Adenoma Detection Rate in Routine Clinical Practice. Am J Gastroenterol. 2022 Nov 1;117(11):1871-1873. doi: 10.14309/ajg.0000000000001970. Epub 2022 Aug 23.

  PMID: 36001408 BACKGROUND

• Ladabaum U, Shepard J, Weng Y, Desai M, Singer SJ, Mannalithara A. Computer-aided Detection of Polyps Does Not Improve Colonoscopist Performance in a Pragmatic Implementation Trial. Gastroenterology. 2023 Mar;164(3):481-483.e6. doi: 10.1053/j.gastro.2022.12.004. Epub 2022 Dec 15. No abstract available.

  PMID: 36528131 BACKGROUND

• Wallace MB, Sharma P, Bhandari P, East J, Antonelli G, Lorenzetti R, Vieth M, Speranza I, Spadaccini M, Desai M, Lukens FJ, Babameto G, Batista D, Singh D, Palmer W, Ramirez F, Palmer R, Lunsford T, Ruff K, Bird-Liebermann E, Ciofoaia V, Arndtz S, Cangemi D, Puddick K, Derfus G, Johal AS, Barawi M, Longo L, Moro L, Repici A, Hassan C. Impact of Artificial Intelligence on Miss Rate of Colorectal Neoplasia. Gastroenterology. 2022 Jul;163(1):295-304.e5. doi: 10.1053/j.gastro.2022.03.007. Epub 2022 Mar 15.

  PMID: 35304117 BACKGROUND

• Repici A, Badalamenti M, Maselli R, Correale L, Radaelli F, Rondonotti E, Ferrara E, Spadaccini M, Alkandari A, Fugazza A, Anderloni A, Galtieri PA, Pellegatta G, Carrara S, Di Leo M, Craviotto V, Lamonaca L, Lorenzetti R, Andrealli A, Antonelli G, Wallace M, Sharma P, Rosch T, Hassan C. Efficacy of Real-Time Computer-Aided Detection of Colorectal Neoplasia in a Randomized Trial. Gastroenterology. 2020 Aug;159(2):512-520.e7. doi: 10.1053/j.gastro.2020.04.062. Epub 2020 May 1.

  PMID: 32371116 BACKGROUND

• Hassan C, Spadaccini M, Iannone A, Maselli R, Jovani M, Chandrasekar VT, Antonelli G, Yu H, Areia M, Dinis-Ribeiro M, Bhandari P, Sharma P, Rex DK, Rosch T, Wallace M, Repici A. Performance of artificial intelligence in colonoscopy for adenoma and polyp detection: a systematic review and meta-analysis. Gastrointest Endosc. 2021 Jan;93(1):77-85.e6. doi: 10.1016/j.gie.2020.06.059. Epub 2020 Jun 26.

  PMID: 32598963 BACKGROUND

• Gawron AJ, Yao Y, Gupta S, Cole G, Whooley MA, Dominitz JA, Kaltenbach T. Simplifying Measurement of Adenoma Detection Rates for Colonoscopy. Dig Dis Sci. 2021 Sep;66(9):3149-3155. doi: 10.1007/s10620-020-06627-2. Epub 2020 Oct 8.

  PMID: 33029706 BACKGROUND

MeSH Terms

Conditions

Colorectal Neoplasms; Adenoma

Condition Hierarchy (Ancestors)

Intestinal Neoplasms; Gastrointestinal Neoplasms; Digestive System Neoplasms; Neoplasms by Site; Neoplasms; Digestive System Diseases; Gastrointestinal Diseases; Colonic Diseases; Intestinal Diseases; Rectal Diseases; Neoplasms, Glandular and Epithelial; Neoplasms by Histologic Type

Study Officials

• Jason A. Dominitz, MD, MHS

  US Department of Veterans Affairs

  STUDY DIRECTOR

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: PROSPECTIVE
• Sponsor Type: FED
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Executive Director, National Gastroenterology and Hepatology Program

Study Record Dates

• First Submitted: May 15, 2023
• First Posted: June 5, 2023
• Study Start: October 1, 2022
• Primary Completion: June 30, 2023
• Study Completion: December 31, 2023
• Last Updated: October 14, 2025

Record last verified: 2025-10

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)