Clinical trial · Observational
Real-World Validation of an Artificial Intelligence Characterization Support (CADx) System
Real-World Validation of an Artificial Intelligence Characterization Support (CADx) System for Prediction of Polyp Histology in Colonoscopy: A Prospective Multicentre Study
- 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)
Colorectal cancer (CRC) is a leading cause of cancer-related morbidity and mortality worldwide, with rates of CRC predicted to increase. Colonoscopy is currently the gold standard of screening for CRC. Artificial intelligence (AI) is seen as a solution to bridge this gap in adenoma detection, which is a quality indicator in colonoscopy. AI systems utilize deep neural networks to enable computer-aided detection (CADe) and computer-aided classification (CADx). CADe is concerned with the detection of polyps during colonoscopy, which in turn is postulated to help decrease the adenoma miss-rate. In contrast, CADx deals with the interpretation of polyp appearance during colonoscopy to determine the predicted histology. Prediction of polyp histology is crucial in helping Clinicians decide on a "resect and discard" or "diagnose and leave strategy". It is also useful for the Clinician to be aware of the predicted histology of a colorectal polyp in determining the appropriate method of resection in terms of safety and efficacy. While CADe has been studied extensively in randomized controlled trials, there is a lack of prospective data validating the use of CADx in a clinical setting to predict polyp histology. The investigators plan to conduct a prospective, multi-centre clinical trial to validate the accuracy of CADx support for prediction of polyp histology in real-time colonoscopy.
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 |
|---|---|---|---|
| Colonic Dysplasia | — | UNRESOLVED | — |
| Colonic Neoplasms | Colon Neoplasm | ALIAS | 0.90 |
| Colonic Polyp | — | UNRESOLVED | — |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Computer-aided diagnosis (CADx) support tool | Device | — | UNRESOLVED |
Design
Arms and outcomes
Arms (1)
- label
- Patients with one or more polyps detected
- description
- During colonoscopy, the Clinician inspect for the presence of polyps as per routine clinical practice with the CAD EYE function turned off. When a polyp is encountered, the Clinician will make a prediction on the histology based on the white light and BLI features of the polyp with and without optical magnification, as per routine clinical practice. Following this, the CAD EYE function will be switched on and the Clinician will take note of the CADx prediction for the same polyp, which will be either "neoplastic" or "hyperplastic". In addition, other polyp features such as the size and location will be recorded, which is similar to what is performed in routine clinical practice. The polyp will be resected and sent for pathological examination, which will form the "gold standard" for the diagnosis of polyp histology.
- interventionNames
- Device: Computer-aided diagnosis (CADx) support tool
Primary outcomes (1)
- measure
- To evaluate the diagnostic performance of the CADx support tool compared to optical prediction of polyp histology by the Clinician in real-time colonoscopy in a clinical setting
- timeFrame
- 1 year
- description
- Polyp histology used as gold standard
Secondary outcomes (1)
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 40 Years
Show eligibility criteria text
Inclusion Criteria: 1. Patients who have an indication for colonoscopy and who have at least one polyp detected during colonoscopy 2. 40 years of age and above 3. Consent obtained for the study Exclusion Criteria: 1. Less than 39 years of age 2. Declined participation in study 3. Patients with no polyps detected during colonoscopy 4. Patients with inflammatory bowel disease 5. Patients with known unresected colorectal cancer
References
Publications (28)
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