Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Class |
|---|---|
| VA Salt Lake City Health Care System | FED |
| San Francisco Veterans Affairs Medical Center | FED |
Not provided
Not provided
Not provided
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.
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Computer Assisted Detection | Colonoscopies performed at a VA facility with computer assisted detection (CADe) artificial intelligence available. |
| |
| Conventional Colonoscopy | Colonoscopies performed at a VA facility without CADe artificial intelligence available |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Computer Assisted Detection | Device | Computer-assisted polyp detection system that utilizes artificial intelligence (AI) during colonoscopy |
|
| Measure | Description | Time Frame |
|---|---|---|
| Adenoma Detection Rate | Change in the proportion of colonoscopies in which one or more adenomas are detected | Baseline and 6 months |
| Measure | Description | Time Frame |
|---|---|---|
| Adenocarcinoma detection rate | Change in the proportion of colonoscopies where colorectal cancer is detected | Baseline and 6 months |
| Sessile serrated lesion detection rate | Proportion of colonoscopies with one or more sessile serrated lesions detected |
Not provided
Inclusion Criteria:
Exclusion Criteria:
Not provided
Not provided
Not provided
Not provided
Veterans undergoing colonoscopy for any indication at VA facilities across the United States.
Not provided
| Name | Affiliation | Role |
|---|---|---|
| Jason A. Dominitz, MD, MHS | US Department of Veterans Affairs | Study Director |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| VA Puget Sound Health Care System | Seattle | Washington | 98108 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 36001408 | Background | 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. | |
| 36528131 | 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. |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| Prot_SAP | Yes | Yes | No | Study Protocol and Statistical Analysis Plan | Oct 8, 2025 | Oct 8, 2025 | Prot_SAP_000.pdf |
Not provided
| ID | Term |
|---|---|
| D015179 | Colorectal Neoplasms |
| D000236 | Adenoma |
| ID | Term |
|---|---|
| D007414 | Intestinal Neoplasms |
| D005770 | Gastrointestinal Neoplasms |
| D004067 | Digestive System Neoplasms |
| D009371 | Neoplasms by Site |
Not provided
Not provided
Not provided
Not provided
Not provided
|
| Baseline and 6 months |
| Proportion of colonoscopies with pathology obtained | Proportion of colonoscopies where specimens were obtained for pathologic review | Baseline and 6 months |
| Proportion of pathology without adenoma or adenocarcinoma | As a surrogate for false positive lesion identification during use of CADe | Baseline and 6 months |
| 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). | Baseline and 6 months |
| Provider satisfaction with computer assisted detection for colonoscopy | Provider ratings of satisfaction with the CADe device | Approximately 6 months after deployment |
| 35304117 | 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. |
| 32371116 | 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. |
| 32598963 | 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. |
| 33029706 | 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. |
| 42250891 | Derived | 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. |
| D009369 | Neoplasms |
| D004066 | Digestive System Diseases |
| D005767 | Gastrointestinal Diseases |
| D003108 | Colonic Diseases |
| D007410 | Intestinal Diseases |
| D012002 | Rectal Diseases |
| D009375 | Neoplasms, Glandular and Epithelial |
| D009370 | Neoplasms by Histologic Type |