Clinical trial · Observational
Real-time AI-assisted Endocyroscopy for the Diagnosis of Colorectal Lesions
Real-time AI-assisted Endocytoscopy for the Diagnosis of Colorectal Lesions: a Multi-center, Prospective Clinical 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 the third most common malignancy and the second leading cause of cancer-related death worldwide. Colonoscopy is considered the preferred method of screening for colorectal cancer, and early and resection detection of colorectal neoplastic lesions can significantly reduce colorectal cancer morbidity and mortality. In order to improve the diagnostic accuracy of endoscopy for colorectal lesions, many endoscopic techniques, such as image-enhanced endoscopy, including narrow band imaging (narrow-band imaging, NBI), magnifying endoscopy, pigment endoscopy, confocal laser endoscopy, and endocytoscopy(EC), are applied clinically. However, with the increasing number of endoscopic resection, the costs associated with the pathological diagnosis of endoscopic resection and resection specimens increase year by year. In clinical practice, some non-neoplastic colorectal lesions may not require resection, so it is important to identify the nature of the lesion during colonoscopy. Leveraging deep neural networks, AI systems support both computer-aided detection (CADe) and computer-aided classification (CADx). CADe specifically focuses on identifying polyps in colonoscopy, with the goal of reducing adenoma miss rates. Hovever, CADx can predict the pathology of the lesion based on the surface condition of the lesion. Endocytoscopy is a kind of ultra-high magnification endoscopy. But it is not something that can be easily mastered by endoscopic doctors. The investigators have previously developed an artificial intelligence system that can assist in endocytoscopy. The investigators plan to conduct a prospective, multicenter clinical trial to verify the accuracy of this CADx in predicting the histological characteristics of colorectal lesions during real-time endocytoscopy.
Conditions
Conditions (2)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Colorectal Neoplasms | Colorectal Neoplasm | ONTOLOGY_EXACT | 0.98 |
| Colorectal Polyp | — | UNRESOLVED | — |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Computer-aided diagnosis (CADx) support tool | Diagnostic Test | — | UNRESOLVED |
Design
Arms and outcomes
Arms (1)
- label
- Patients with one or more colorectao lesion detected
- description
- During colonoscopy, the endoscopist inspect for the presence of colorectal lesions as per routine clinical practice with the CADx turned off. When a colorectal lesion is encountered, the endoscopist will make a prediction on the histology based on the endoscopic diagnosis. Following this, the CADx will be triggered and display the endoscopic image captured by the endoscopist. and the endoscopist will take note of the CADx prediction for the same image. In addition, other lesion features such as the size and location will be recorded, which is similar to what is performed in routine clinical practice. The lesion will be endoscopic resected or surgery and sent for pathological examination, which will form the "gold standard" for the diagnosis of polyp histology.
- interventionNames
- Diagnostic Test: Computer-aided diagnosis (CADx) support tool
Primary outcomes (1)
- measure
- To evaluate the diagnostic performance of the CAD-stained in diagnosing neoplastic lesions in a clinical setting.
- timeFrame
- 11 months
- description
- The diagnostic performance will be calculated for comparison with final histology as the gold standard for diagnosis
Secondary outcomes (4)
Eligibility
Eligibility (as posted)
- Sex
- All
Show eligibility criteria text
Inclusion Criteria: * Patients who have at least one colorectal lesion detected during endocytoscopy * Consent obtained for the study Exclusion Criteria: * lesions lacking high-quality images; * Inflammatory bowel disease, familial adenomatous polyposis and other special diseases; * Submucosal tumors; * Pathological diagnosis of inflammatory polyps, Peutz-Jeghers polyps, juvenile polyps, lymphoma and other special pathological types.
References
Publications (0)
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