Clinical trial · Interventional
Assessing the Additional Neoplasia Yield of Computer-aided Colonoscopy in a Screening Setting
Resa Diagnostica Aggiuntiva Dell'Intelligenza Artificiale Nella Colonscopia (GENIAL COLONOSCOPY), Per lo Screening Del Carcinoma Colorettale
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
Even if colonoscopy is considered the reference standard for the detection of colonic neoplasia, polyps are still missed. The risk of early post-colonoscopy cancer appeared to be independently predicted by a relatively low polyp/adenoma detection rate. When considering the very high prevalence of advanced neoplasia in the FIT-positive enriched population, the risk of post-colonoscopy interval cancer due to a suboptimal quality of colonoscopy may be substantial. Available evidence justifies therefore the implementation of efforts aimed at improving adenoma detection rate, based on retraining interventions and on the adoption of innovative technologies, designed to enhance the accuracy of the endoscopic examination. Artificial intelligence seems to improve the quality of medical diagnosis and treatment. In the field of gastrointestinal endoscopy, two potential roles of AI in colonoscopy have been examined so far: automated polyp detection (CADe) and automated polyp histology characterization (CADx). CADe can minimize the probability of missing a polyp during colonoscopy, thereby improving the adenoma detection rate (ADR) and potentially decreasing the incidence of interval cancer. GI Genius is the AI software that will be used in the present trial and is intended to be used as an adjunct to colonic endoscopy procedures to help endoscopists to detect in real time mucosal lesions (such as polyps and adenomas, including those with flat (non-polypoid) morphology) during standard screening and surveillance endoscopic mucosal evaluations. It is not intended to replace histopathological sampling as a means of diagnosis. The objective of this study was to compare the diagnostic yield obtained by using CADe colonoscopy to the yield obtained by the standard colonoscopy (SC).
Conditions
Conditions (5)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Colonic Adenocarcinoma | Colon Adenocarcinoma | ALIAS | 0.90 |
| Colonic Neoplasms | Colon Neoplasm | ALIAS | 0.90 |
| Polyps of Colon | — | UNRESOLVED | — |
| Rectal Adenocarcinoma | Rectal Adenocarcinoma | ONTOLOGY_EXACT | 0.98 |
| Rectal Neoplasms | Rectal Neoplasm | ONTOLOGY_EXACT | 0.98 |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| CADe colonoscopy using GI Genius device | Device | — | UNRESOLVED |
Design
Arms and outcomes
Arms (2)
- type
- EXPERIMENTAL
- label
- Artificial intelligence arm
- description
- Patients undergoing colonoscopy with artificial intelligence.
- interventionNames
- Device: CADe colonoscopy using GI Genius device
- type
- ACTIVE_COMPARATOR
- label
- standard colonoscopy arm
- description
- Patients undergoing colonoscopy with standard colonscopy
- interventionNames
- Device: CADe colonoscopy using GI Genius device
Primary outcomes (2)
- measure
- Rate of advanced adenomas
- timeFrame
- When available the histological report of polyps removed (up to 3 weeks).
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 50 Years
- Maximum age
- 69 Years
Show eligibility criteria text
Inclusion Criteria: * Patients aged 50 to 69 undergoing colonoscopy examination following a positive fecal immunochemical test (FIT) performed in the context of a regional mass-screening program. Exclusion Criteria: * Patients unwilling or unable to give informed consent. * Patients reporting use of anti-platelet agents or anticoagulants precluding removal of polyps.
References
Publications (1)
- DERIVEDSpada C, Cesaro P, Fuccio L, Salvi D, Ferrari C, Barbaro F, Bizzotto A, Butitta F, Gerardi V, Lovera M, Milluzzo SM, Minelli Grazioli L, Olivari N, Pecere S, Piccirelli S, Pugliano CL, Pesatori EV, Quadarella A, Tettoni E, Zani C, Ricciardiello L, Costamagna G. Impact of Artificial Intelligence for Detection of Precancerous Colonic Lesions in a Fecal Immunochemical Blood Test-Based Organized Screening Program in Italy: A Randomized Control Trial. United European Gastroenterol J. 2026 Feb;14(1):e70176. doi: 10.1002/ueg2.70176. PMID 41563802