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CompletedNCT05888623CADeNCEUpdated Oct 14, 2025

Computer Assisted Detection of Neoplasia During Colonoscopy Evaluation

An observational study in Colorectal Neoplasms, sponsored by VA Puget Sound Health Care System. Completed at 1 site in United States. Per ClinicalTrials.gov, last updated 2025-10-14.

Sponsored by VA Puget Sound Health Care System · Observational

Study type
Observational
Model
Other
Time perspective
Prospective
Enrollment
334,200
Sex
All
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Study 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.

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Conditions studied

  • Colorectal Neoplasms

Keywords

  • colonoscopy
  • artificial intelligence
  • adenoma
  • Veterans
  • quality assurance
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In context

Colorectal Neoplasms

5,599 studies on the registry are indexed under Colorectal Neoplasms; 1,459 are open to participants now.

This study's enrollment of 334,200 is above the median of 250 across 1,226 observational studies indexed under Colorectal Neoplasms.

Browse Colorectal Neoplasms studies →

Lead sponsor

VA Puget Sound Health Care System is the lead sponsor of 25 studies on the registry; 1 is open to participants now.

Counted across the registry records on this site, refreshed daily.

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Who can participate

Ages eligible
Child (0–17), Adult (18–64), Older adult (65+)
Sexes eligible
All
Accepts healthy volunteers
No
Sampling method
Non-probability sample

Study population

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

Inclusion criteria

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

Exclusion criteria

Exclusion Criteria:

  • 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
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Study design

Observational model
Other
Time perspective
Prospective
Enrollment
334,200 participants (actual)
Patient registry
No

Groups and cohorts

  • 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

  • DeviceComputer Assisted Detection

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

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

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What researchers measure

Primary outcomes

  1. Adenoma Detection Rate

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

    Time frame: Baseline and 6 months

Secondary outcomes

  1. Adenocarcinoma detection rate

    Change in the proportion of colonoscopies where colorectal cancer is detected

    Time frame: Baseline and 6 months

  2. Sessile serrated lesion detection rate

    Proportion of colonoscopies with one or more sessile serrated lesions detected

    Time frame: Baseline and 6 months

  3. Proportion of colonoscopies with pathology obtained

    Proportion of colonoscopies where specimens were obtained for pathologic review

    Time frame: Baseline and 6 months

  4. Proportion of pathology without adenoma or adenocarcinoma

    As a surrogate for false positive lesion identification during use of CADe

    Time frame: Baseline and 6 months

  5. Withdrawal time without interventions

    Change in the duration of colonoscope withdrawal when no intervention (e.g., polypectomy, biopsy) is performed. This outcome can only be assessed at a subset of sites due to data availability issues (i.e., Provation MD sites).

    Time frame: Baseline and 6 months

  6. Provider satisfaction with computer assisted detection for colonoscopy

    Provider ratings of satisfaction with the CADe device

    Time frame: Approximately 6 months after deployment

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Study locations

1 site
  • VA Puget Sound Health Care System
    Seattle, Washington 98108, United States
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References and documents

Publications

  • 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. PubMed 36001408 ↗
  • 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. PubMed 36528131 ↗
  • 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. PubMed 35304117 ↗
  • 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. PubMed 32371116 ↗
  • 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. PubMed 32598963 ↗
  • 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. PubMed 33029706 ↗
  • Dominitz JA, Gawron AJ, McKee GB, Hoggatt KJ, Kaltenbach T. Impact of Availability of Computer-Aided Detection Devices on Adenoma Detection During Colonoscopy: A Cluster Randomized Study. Gastroenterology. 2026 Jun 5:S0016-5085(26)06941-6. doi: 10.1053/j.gastro.2026.05.018. Online ahead of print. PubMed 42250891 ↗

Study documents

  • Protocol and statistical analysis plan · Oct 8, 2025

Documents are hosted by the registry — open the source record to download them.

Individual participant data

Plan to share: No

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Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Oct 14, 2025, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
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Registry details

Key details

Study ID
NCT05888623
Lead sponsor
VA Puget Sound Health Care System
Collaborators
VA Salt Lake City Health Care System, San Francisco Veterans Affairs Medical Center
Responsible party
Jason A. Dominitz, MD, MHS (Executive Director, National Gastroenterology and Hepatology Program, VA Puget Sound Health Care System) — Principal investigator
First posted
Jun 5, 2023
Start date
Oct 1, 2022
Primary completion
Jun 30, 2023
Completion
Dec 31, 2023
Last update
Oct 14, 2025

Study contacts

Jason A. Dominitz, MD, MHS
study director · US Department of Veterans Affairs

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
Yes
View the source record on ClinicalTrials.gov ↗

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This study is completed, as verified in Oct 2025. You cannot join it, but the record below documents what was studied.

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