Computer Assisted Detection of Neoplasia During Colonoscopy Evaluation
NCT ID: NCT05888623
Last Updated: 2025-10-14
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
334200 participants
OBSERVATIONAL
2022-10-01
2023-12-31
Brief Summary
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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.
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Detailed Description
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Conditions
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Study Design
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OTHER
PROSPECTIVE
Study Groups
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Computer Assisted Detection
Colonoscopies performed at a VA facility with computer assisted detection (CADe) artificial intelligence available.
Computer Assisted Detection
Computer-assisted polyp detection system that utilizes artificial intelligence (AI) during colonoscopy
Conventional Colonoscopy
Colonoscopies performed at a VA facility without CADe artificial intelligence available
No interventions assigned to this group
Interventions
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Computer Assisted Detection
Computer-assisted polyp detection system that utilizes artificial intelligence (AI) during colonoscopy
Other Intervention Names
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Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
* Colonoscopy performed at a VA medical center where pathology results are not available
ALL
No
Sponsors
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VA Salt Lake City Health Care System
FED
San Francisco Veterans Affairs Medical Center
FED
VA Puget Sound Health Care System
FED
Responsible Party
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Jason A. Dominitz, MD, MHS
Executive Director, National Gastroenterology and Hepatology Program
Principal Investigators
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Jason A. Dominitz, MD, MHS
Role: STUDY_DIRECTOR
US Department of Veterans Affairs
Locations
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VA Puget Sound Health Care System
Seattle, Washington, United States
Countries
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References
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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.
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.
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.
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.
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.
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.
Provided Documents
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Document Type: Study Protocol and Statistical Analysis Plan
Other Identifiers
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VHA_NGHP_001
Identifier Type: -
Identifier Source: org_study_id
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