Impact of AI on Trainee ADR
Impact of Artificial Intelligence on Trainee Adenoma Detection Rate
1 other identifier
interventional
25
1 country
1
Brief Summary
Adenoma detection rate (ADR) is a validated quality metric for colonoscopy with higher ADR correlated with improved colorectal cancer outcomes. Artificial intelligence (AI) can automatically detect polyps on the video monitor which may allow endoscopists in training to improve their ADR. Objective and Purpose of the study: Measure the effect of AI in a prospective, randomized manner to determine its impact on ADR of Gastroenterology trainees.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at below P25 for not_applicable
Started Jan 2023
Typical duration for not_applicable
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
Click on a node to explore related trials.
Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
April 26, 2022
CompletedFirst Posted
Study publicly available on registry
June 21, 2022
CompletedStudy Start
First participant enrolled
January 1, 2023
CompletedPrimary Completion
Last participant's last visit for primary outcome
June 1, 2025
CompletedStudy Completion
Last participant's last visit for all outcomes
September 1, 2025
CompletedMarch 6, 2023
March 1, 2023
2.4 years
April 26, 2022
March 2, 2023
Conditions
Outcome Measures
Primary Outcomes (1)
Average adenoma detection rate
Adenoma detection rate with and without AI
Throughout study, an average of 2 years
Secondary Outcomes (1)
Average of polyps detection rate
Through out study, an average of 2 years
Study Arms (2)
Artificial Intelligence Endoscopy Room
ACTIVE COMPARATORThe fellows will be randomized on a daily basis to perform colonoscopies in a room with AI (intervention)
Non-Artificial Intelligence Endoscopy Room
ACTIVE COMPARATORThe fellows will be randomized on a daily basis to perform colonoscopies in a non-AI endoscopy room (standard of care).
Interventions
The use of AI versus no AI in comparing the detection of adenomas during Endoscopy procedures.
Non-AI use in comparing the detection of adenomas during Endoscopy procedures.
Eligibility Criteria
You may qualify if:
- All Gastroenterology fellows at USC performing Endoscopies will be included in the study.
You may not qualify if:
- If fellows refuse informed consent they will be excluded.
- Procedures performed in the intensive care unit or the operating room will not be counted toward the study metrics as the AI system will only be available in the endoscopy unit.
- If procedures are performed only by faculty, in which the fellow is not the primary operator, they will not be used for study metrics.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
LAC+USC Medical Center
Los Angeles, California, 90033, United States
Related Publications (12)
Siegel RL, Miller KD, Fedewa SA, Ahnen DJ, Meester RGS, Barzi A, Jemal A. Colorectal cancer statistics, 2017. CA Cancer J Clin. 2017 May 6;67(3):177-193. doi: 10.3322/caac.21395. Epub 2017 Mar 1.
PMID: 28248415BACKGROUNDWinawer SJ, Zauber AG, Ho MN, O'Brien MJ, Gottlieb LS, Sternberg SS, Waye JD, Schapiro M, Bond JH, Panish JF, et al. Prevention of colorectal cancer by colonoscopic polypectomy. The National Polyp Study Workgroup. N Engl J Med. 1993 Dec 30;329(27):1977-81. doi: 10.1056/NEJM199312303292701.
PMID: 8247072BACKGROUNDZauber AG, Winawer SJ, O'Brien MJ, Lansdorp-Vogelaar I, van Ballegooijen M, Hankey BF, Shi W, Bond JH, Schapiro M, Panish JF, Stewart ET, Waye JD. Colonoscopic polypectomy and long-term prevention of colorectal-cancer deaths. N Engl J Med. 2012 Feb 23;366(8):687-96. doi: 10.1056/NEJMoa1100370.
PMID: 22356322BACKGROUNDRex DK, Boland CR, Dominitz JA, Giardiello FM, Johnson DA, Kaltenbach T, Levin TR, Lieberman D, Robertson DJ. Colorectal Cancer Screening: Recommendations for Physicians and Patients from the U.S. Multi-Society Task Force on Colorectal Cancer. Am J Gastroenterol. 2017 Jul;112(7):1016-1030. doi: 10.1038/ajg.2017.174. Epub 2017 Jun 6.
PMID: 28555630BACKGROUNDCorley DA, Jensen CD, Marks AR, Zhao WK, Lee JK, Doubeni CA, Zauber AG, de Boer J, Fireman BH, Schottinger JE, Quinn VP, Ghai NR, Levin TR, Quesenberry CP. Adenoma detection rate and risk of colorectal cancer and death. N Engl J Med. 2014 Apr 3;370(14):1298-306. doi: 10.1056/NEJMoa1309086.
PMID: 24693890BACKGROUNDAbadir AP, Ali MF, Karnes W, Samarasena JB. Artificial Intelligence in Gastrointestinal Endoscopy. Clin Endosc. 2020 Mar;53(2):132-141. doi: 10.5946/ce.2020.038. Epub 2020 Mar 30.
PMID: 32252506BACKGROUNDUrban G, Tripathi P, Alkayali T, Mittal M, Jalali F, Karnes W, Baldi P. Deep Learning Localizes and Identifies Polyps in Real Time With 96% Accuracy in Screening Colonoscopy. Gastroenterology. 2018 Oct;155(4):1069-1078.e8. doi: 10.1053/j.gastro.2018.06.037. Epub 2018 Jun 18.
PMID: 29928897BACKGROUNDRepici 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: 32371116BACKGROUNDCalderwood AH, Jacobson BC. Comprehensive validation of the Boston Bowel Preparation Scale. Gastrointest Endosc. 2010 Oct;72(4):686-92. doi: 10.1016/j.gie.2010.06.068.
PMID: 20883845BACKGROUNDKaminski MF, Regula J, Kraszewska E, Polkowski M, Wojciechowska U, Didkowska J, Zwierko M, Rupinski M, Nowacki MP, Butruk E. Quality indicators for colonoscopy and the risk of interval cancer. N Engl J Med. 2010 May 13;362(19):1795-803. doi: 10.1056/NEJMoa0907667.
PMID: 20463339BACKGROUNDJovani M, Campbell EJ, Hur C, Joshi AD, Nishioka NS. Effect of video monitor size on polyp detection: a prospective, randomized, controlled trial. Gastrointest Endosc. 2019 Aug;90(2):254-258.e2. doi: 10.1016/j.gie.2019.03.1172. Epub 2019 Apr 12.
PMID: 30986402BACKGROUNDChang PW, Nguyen DD, Kong N, Wang D, Wang S, Ong J, Amini MM, Sharma N, Bui A, Bakr O, Bruce D, Lee H, Dodge JL, Sahakian AB, Buxbaum JL. Impact of artificial intelligence-assisted colonoscopy on gastroenterology fellow performance: a pragmatic randomized controlled trial. Gastrointest Endosc. 2025 Sep 27:S0016-5107(25)02063-2. doi: 10.1016/j.gie.2025.09.045. Online ahead of print.
PMID: 41022225DERIVED
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
James L Buxbaum, MD
University of Southern California
Central Study Contacts
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- NONE
- Purpose
- DIAGNOSTIC
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Associate Professor
Study Record Dates
First Submitted
April 26, 2022
First Posted
June 21, 2022
Study Start
January 1, 2023
Primary Completion
June 1, 2025
Study Completion
September 1, 2025
Last Updated
March 6, 2023
Record last verified: 2023-03
Data Sharing
- IPD Sharing
- Will not share