Published online Jan 16, 2025. doi: 10.4253/wjge.v17.i1.101233
Revised: November 21, 2024
Accepted: December 6, 2024
Published online: January 16, 2025
Processing time: 129 Days and 20.3 Hours
Recent advancements in artificial intelligence (AI) have significantly enhanced the capabilities of endoscopic-assisted diagnosis for gastrointestinal diseases. AI has shown great promise in clinical practice, particularly for diagnostic support, offering real-time insights into complex conditions such as esophageal squamous cell carcinoma.
In this study, we introduce a multimodal AI system that successfully identified and delineated a small and flat carcinoma during esophagogastroduodenoscopy, highlighting its potential for early detection of malignancies. The lesion was confirmed as high-grade squamous intraepithelial neoplasia, with pathology results supporting the AI system’s accuracy. The multimodal AI system offers an integrated solution that provides real-time, accurate diagnostic information directly within the endoscopic device interface, allowing for single-monitor use without disrupting endoscopist’s workflow.
This work underscores the transformative potential of AI to enhance endoscopic diagnosis by enabling earlier, more accurate interventions.
Core Tip: This study introduces a novel multimodal artificial intelligence system (MAIS) based on the QueryInst network for real-time detection and delineation of esophageal squamous cell carcinoma and precancerous lesions during endoscopy. Unlike traditional artificial intelligence systems, MAIS integrates directly into the endoscopic device, allowing for single-monitor use without altering the endoscopist’s workflow. This case report demonstrates its ability to accurately identify a flat esophageal lesion, which was confirmed as high-grade squamous intraepithelial neoplasia. The findings highlight potential of MAIS for improving early diagnosis and biopsy accuracy in high-risk gastrointestinal conditions such as esophageal squamous cell carcinoma.