Clinical trial · Observational
Single-center, Randomized, Superiority Pivotal Clinical Study to Evaluate the Efficacy of Artificial Intelligence-based Upper Gastrointestinal Endoscopy Image
Single-center, Single Group, Randomized, Superiority Pivotal Clinical Study to Evaluate the Efficacy and Safety of Artificial Intelligence-based Upper Gastrointestinal Endoscopy Image Diagnosis Aid Software
- 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)
We will conduct a single-center retrospective study at a university hospital. A total of 3,385 gastroscopic white-light images from patients with pathologically confirmed findings will be analyzed. The AI software will automatically identify images as non-neoplastic or neoplastic (low-grade dysplasia, high-grade dysplasia, early gastric cancer with mucosal or submucosal invasion, or advanced gastric cancer) and highlighted lesion locations. Two experienced endoscopists will independently review the same image set without AI assistance for comparison. Primary outcomes are sensitivity and specificity of the AI in detecting gastric neoplasms (by category and overall), and the localization accuracy measured by the localization receiver operating characteristic (LROC) curve area. Secondary outcomes is includes comparison of the AI's diagnostic performance with that of endoscopists.
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 |
|---|---|---|---|
| Artificial Intelligence | — | UNRESOLVED | — |
| Gastric Lesion | — | UNRESOLVED | — |
| Gastric Neoplasm | Gastric Neoplasm | ONTOLOGY_EXACT | 0.98 |
Interventions
Interventions (0)
Data not yet available
Design
Arms and outcomes
Arms (0)
[]Primary outcomes (1)
- measure
- AI performance
- timeFrame
- Day 1
- description
- sensitivity and specificity of the AI in detecting gastric neoplasms (by category and overall), and the localization accuracy measured by the localization receiver operating characteristic (LROC) curve area.
Secondary outcomes (1)
- measure
- comparison of the AI's diagnostic performance with that of endoscopists.
- timeFrame
- Day 1
- description
- Secondary outcomes included comparison of the AI's diagnostic performance with that of endoscopists. (sensitivity and specificity of the AI in detecting gastric neoplasms (by category and overall), and the localization accuracy measured by the localization receiver operating characteristic (LROC) curve area.)
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 20 Years
- Maximum age
- 100 Years
Show eligibility criteria text
Inclusion Criteria: * Age 19 or older * At least one gastric lesion biopsied with a definitive pathological diagnosis * Availability of high-quality white-light endoscopy images of the lesion and surrounding mucosa Exclusion Criteria: * Poor-quality images (e.g., out of focus or obscured) * Lack of histopathological confirmation of the lesion
References
Publications (0)
Data not yet available