Abstract
INTRODUCTION: Optical diagnosis is an essential part of a high-quality colonoscopy, but highly experience-dependent. Artificial intelligence in the form of computer-aided diagnosis (CADx) may bridge the gap between trainee endoscopists and experts. The aim of this study is to evaluate the diagnostic reliability of optical diagnosis of trainee endoscopists with the help of AI compared to experts.
PATIENTS AND METHODS: This prospective, observational study included patients undergoing trainee-performed CADx-supported (GI Genius®, Medtronic) colonoscopy. Resected polyps were recorded and video-reviewed without CADx information by experts. The primary outcome was the negative predictive value (NPV) for adenomatous histology of diminutive (≤5 mm) rectosigmoid polyps (DRSPs) of trainees versus experts and CADx output alone. Secondary outcomes were the NPV for rectosigmoid polyps of any size, and sensitivities and specificities of adenomas in the entire colon.
RESULTS: Overall, 630 polyps were resected in 225 patients (48.9% male, mean age 63.8 (SD 12.7) years). In the rectosigmoid 252 lesions (40%) were found, 223 (88.5%) of which were ≤5 mm. The NPV for DRSPs of trainees using CADx was 90.2% (95%CI 0.85;0.94), NPV of the experts without CADx was 90.3% (95%CI 0.84;0.94). There was no statistically significant difference in NPV between these two groups. The NPV of CADx alone was 93.2% (95%CI 0.88;0.97). The NPV for rectosigmoid polyps of any sizes were 90.1% (95%CI 0.85;0.94) for trainees, 90.4% (95%CI 0.85;0.95) for experts, and 93.4% (95%CI 0.88;0.97) for CADx alone.
CONCLUSION: OD of rectosigmoid polyps by trainee endoscopists with CADx is highly accurate, fulfilling PIVI 2 "diagnose-and-leave" strategy.
| Original language | English |
|---|---|
| Article number | 10.14309/ajg.0000000000003558 |
| Journal | The American journal of gastroenterology |
| Volume | 121 |
| Early online date | 28 May 2025 |
| DOIs | |
| Publication status | Published - 01 Mar 2026 |
Fields of science
- 101018 Statistics
- 305907 Medical statistics
JKU Focus areas
- Sustainable Development: Responsible Technologies and Management
- Digital Transformation
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