Clinical Endoscopy

The Korean Society of Gastrointestinal Endoscopy (대한소화기내시경학회)
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Impact of real-time artificial intelligence integration on detection of gastric lesions: an exploratory single-center before-and-after study using low-definition routine endoscopy

  • Received : 2025.08.09
  • Accepted : 2026.01.02
  • Published : 2026.05.30
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Abstract

Background/Aims: Early detection of gastric neoplasia, particularly subcentimeter lesions, using upper gastrointestinal (GI) endoscopy remains challenging. This study evaluated the impact of a real-time artificial intelligence (AI) detection system on the lesion detection rate (LDR) during routine upper GI endoscopy performed using a low-definition platform commonly used in resource-limited settings, with a focus on lesions ≤0.5 cm. Methods: Diagnostic upper GI endoscopies performed between September 2024 and May 2025 were analyzed. LDRs were compared between the pre- and post-AI periods, including subgroup analyses by lesion size and type. Results: A total of 2,329 patients were included (1,491 pre-AI, 838 post-AI). After AI implementation, overall LDR per person increased from 1.15±0.45 to 1.20±0.57 (p<0.05). Detection of lesions ≤0.5 cm increased from 18.0% to 19.8% (p<0.05), while detection of larger lesions remained unchanged. The biopsy rate decreased from 13.8% to 8.5% (p<0.05). Conclusions: Real-time AI modestly improved the detection of diminutive gastric lesions while reducing unnecessary biopsies without compromising malignancy detection, thereby supporting its utility in routine endoscopy under resource-limited conditions.

Keywords

Acknowledgement

This work was supported by the Korea International Cooperation Agency (KOICA) under the project entitled "Education and Research Capacity Building Project at University of Medicine and Pharmacy at Ho Chi Minh City," conducted from 2024 to 2025 (project no. 2021-00020-3).

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