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Single-center, Randomized, Superiority Pivotal Clinical Study to Evaluate the Efficacy of Artificial Intelligence-based Upper Gastrointestinal Endoscopy Image

NCT06969794 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 3385

Last updated 2025-05-14

No results posted yet for this study

Summary

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

  • Gastric Neoplasm
  • Gastric Lesion
  • Artificial Intelligence

Sponsors & Collaborators

  • Chuncheon Sacred Heart Hospital

    lead OTHER

Principal Investigators

  • Chang Seok Bang, MD, PhD · HALLYM UNIVERSITY COLLEGE OF MEDICINE, Korea

Eligibility

Min Age
20 Years
Max Age
100 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-07-01
Primary Completion
2023-08-01
Completion
2023-08-17

Countries

  • South Korea

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06969794 on ClinicalTrials.gov