Clinical trial · Interventional
A Clinical Study To Measure The Effect Of Use Of Artificial Intelligence (AI) Enabled Computer Aided Detection (CADe) Assistance Software In Detecting Colon Polyps During Standard Colonoscopy Procedures
A Prospective, Multi-Center, Randomized Controlled Clinical Study To Measure The Effect Of Use Of Artificial Intelligence (AI) Enabled Computer Aided Detection (CADe) Assistance Software In Detecting Colon Polyps During Standard Colonoscopy Procedures
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Why stopped (as posted): Decision made based on Interim Analysis Results
Summary
Brief summary (as posted)
EndoVigilant software device augments existing colonoscopy procedure video in real-time by highlighting colon polyps and mucosal abnormalities. It is intended to assist gastroenterologists in detection of adenomas and serrated polyps. The device is an adjunctive tool and is not intended to replace physicians' decision making related to detection, diagnosis or treatment. This study with an adaptive design measures the clinical benefit (increase in detection of adenomatous and serrated polyps) and increased risk (increased extraction of non-adenomas) during standard colonoscopy procedures when EndoVigilant software device is used.
Conditions
Conditions (3)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Colon Adenoma | Colon Adenoma | ONTOLOGY_EXACT | 0.98 |
| Colon Neoplasm | Colon Neoplasm | ONTOLOGY_EXACT | 0.98 |
| Colon Polyp | — | UNRESOLVED | — |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| EndoVigilant Software | Device | — | UNRESOLVED |
Design
Arms and outcomes
Arms (2)
- type
- EXPERIMENTAL
- label
- Colonoscopy Procedure with EndoVigilant Software
- description
- Colonoscopy Procedure is performed with EndoVigilant Software assisting the gastroenterologist during colonoscopy procedure.
- interventionNames
- Device: EndoVigilant Software
- type
- NO_INTERVENTION
- label
- Colonoscopy Procedure without EndoVigilant Software
- description
- Colonoscopy Procedure is performed without EndoVigilant Software assisting the gastroenterologist during colonoscopy procedure.
Primary outcomes (2)
- measure
- Average Number of Adenomas Per Colonoscopy
- timeFrame
- Receipt of pathology results for procedure findings (typically within 2 weeks after the procedure)
- description
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 45 Years
Show eligibility criteria text
Inclusion Criteria: 1. Patient is 45 years old or older. 2. Patient is presenting for colon cancer screening or low-risk surveillance colonoscopy. Low risk surveillance is defined as the patient qualifying for a colonoscopy surveillance interval of 5 years based on US Multi-Society Task Force 2020 Guidelines (i.e., up to 4 tubular adenomas \<1cm, up to 4 sessile serrated polyps \<1cm on most recent colonoscopy). 3. Informed consent document for participating in the study signed by patient or patient's guardian. Exclusion Criteria: 1. Patient has known history of inflammatory bowel disease (ulcerative colitis, Crohn's disease). 2. Patient has known or suspected polyposis or hereditary colon cancer syndrome (such as familial adenomatous polyposis, hereditary nonpolyposis colorectal cancer). 3. Patient referred for diagnostic colonoscopy to work up symptoms (such as abdominal pain or bleeding), laboratory abnormalities (such as anemia) or imaging findings (such as masses found on imaging). 4. Patient has history of colon resection (not including appendectomy).
References
Publications (10)
- BACKGROUNDZauber 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 22356322
- BACKGROUNDKlare P, Sander C, Prinzen M, Haller B, Nowack S, Abdelhafez M, Poszler A, Brown H, Wilhelm D, Schmid RM, von Delius S, Wittenberg T. Automated polyp detection in the colorectum: a prospective study (with videos). Gastrointest Endosc. 2019 Mar;89(3):576-582.e1. doi: 10.1016/j.gie.2018.09.042. Epub 2018 Oct 17. PMID 30342029
- BACKGROUNDSingh S, Singh PP, Murad MH, Singh H, Samadder NJ. Prevalence, risk factors, and outcomes of interval colorectal cancers: a systematic review and meta-analysis. Am J Gastroenterol. 2014 Sep;109(9):1375-89. doi: 10.1038/ajg.2014.171. Epub 2014 Jun 24. PMID 24957158
- BACKGROUNDZhao S, Wang S, Pan P, Xia T, Chang X, Yang X, Guo L, Meng Q, Yang F, Qian W, Xu Z, Wang Y, Wang Z, Gu L, Wang R, Jia F, Yao J, Li Z, Bai Y. Magnitude, Risk Factors, and Factors Associated With Adenoma Miss Rate of Tandem Colonoscopy: A Systematic Review and Meta-analysis. Gastroenterology. 2019 May;156(6):1661-1674.e11. doi: 10.1053/j.gastro.2019.01.260. Epub 2019 Feb 6. PMID 30738046
- BACKGROUNDFernandez-Esparrach G, Bernal J, Lopez-Ceron M, Cordova H, Sanchez-Montes C, Rodriguez de Miguel C, Sanchez FJ. Exploring the clinical potential of an automatic colonic polyp detection method based on the creation of energy maps. Endoscopy. 2016 Sep;48(9):837-42. doi: 10.1055/s-0042-108434. Epub 2016 Jun 10. PMID 27285900
- BACKGROUNDMisawa M, Kudo SE, Mori Y, Cho T, Kataoka S, Yamauchi A, Ogawa Y, Maeda Y, Takeda K, Ichimasa K, Nakamura H, Yagawa Y, Toyoshima N, Ogata N, Kudo T, Hisayuki T, Hayashi T, Wakamura K, Baba T, Ishida F, Itoh H, Roth H, Oda M, Mori K. Artificial Intelligence-Assisted Polyp Detection for Colonoscopy: Initial Experience. Gastroenterology. 2018 Jun;154(8):2027-2029.e3. doi: 10.1053/j.gastro.2018.04.003. Epub 2018 Apr 11. No abstract available.