Effect of a Computer-Aided Device on Endoscopists' Biopsy Practice for Gastric Neoplasms: A Secondary Analysis of a Randomized Controlled Trial
In brief
AI red-box alerts raised gastric neoplasm biopsy efficiency to 8.2%
In this secondary analysis of a randomized trial, lesions marked high-risk by AI had an 8.2% neoplasm biopsy efficiency, compared with 1.8% in standard screening; documented lesions were also less often left unbiopsied. False-positive alerts were not linked to more biopsies, but the subgroup findings show association, not proof that AI improves cancer detection or outcomes.
- Journal
- Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society (Q1)
- Published
- 1 October 2026
- Study design
- Randomized controlled trial
- Evidence level
- Level 1, High (CEBM 1b)
- Authors
- Hongliu Du, Shuzhe Tan, Ziyi Zeng, Xinran Zhang, Zehua Dong, Mei Deng, et al.
- PMID
- 42839852
- DOI
- 10.1111/den.70302
Why clinicians should know about it
- Picked for Pathology and Forensic Medicine (paper of the day, 9 October 2026): Red-box AI increased targeted biopsy, improving sampling efficiency
Abstract
BACKGROUND: Endoscopic biopsy is fundamental for diagnosing gastrointestinal lesions, yet the effectiveness of AI assistance on endoscopists' biopsy strategies and efficiency for detecting gastric neoplasms remains unclear. This study aims to investigate this effectiveness. METHODS: This study is a secondary analysis of a randomized controlled trial (AI group: n = 13,440; control: n = 12,561) compared AI-assisted versus standard screening. The AI system marked high-risk and low-risk lesions with red and blue boxes, respectively. The AI group was stratified into red-box and non-red-box subgroups. Outcomes included neoplasm biopsy efficiency and proportion of non-biopsied documented lesions. The patient-level correlation between false-positive alerts and biopsy counts was examined. All analyses were based on the pathological results after centralized pathology review. RESULTS: The non-biopsy rate was significantly lower in the red-box group than in the non-red box group and the control group (18.00% vs. 43.26%, 18.00% vs. 45.60%, both p < 0.001), suggesting that lesions were biopsied more frequently in the red-box group. Neoplasm biopsy efficiency was higher in the red-box group (8.19% vs. 0.36%, 8.19% vs. 1.77%, both p < 0.001). In negative binomial regression, red-box classification remained associated with a lower non-biopsy rate (IRR 0.393, 95% CI 0.360-0.429, p < 0.001). False-positive alerts showed a weak inverse correlation with biopsy counts (ρ = -0.182, p < 0.001). CONCLUSIONS: Red-box classification was associated with more targeted biopsy sampling, while false-positive prompts were not associated with indiscriminate biopsies.
Abstract as published, via PubMed.
For healthcare professionals. The summary is generated by AI from the published abstract, and the evidence level is assigned automatically from the study design on the Oxford CEBM hierarchy. Neither is medical advice. Read the full paper before changing practice.