NCT07087418

AI-Driven Multimodal Imaging Integration for Diagnosis and Prognostication of Digestive System Diseases

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 5,000 (estimated)
• Sponsor: First Affiliated Hospital, Sun Yat-Sen University · Academic / Other
• Sex: All
• Age: —
• Healthy volunteers: Accepted

Summary

The goal of this observational, retrospective and prospective study is to develop a noninvasive disease assessment system by leveraging artificial intelligence (AI) to comprehensively analyze multi-modal imaging features, including magnetic resonance enterography (MRE) and computed tomography enterography (CTE), for the diagnosis and prognostication of digestive diseases. To this end, the investigators retrospectively enrolled imaging, endoscopic, and clinical data from 21 centers across China to construct and iteratively optimize the AI model. The model's performance will be prospectively validated in two centers, and its accuracy in lesion localization will be verified through real-world deployment in endoscopy suites.

Conditions

• Digestive Diseases
• Radiology
• AI (Artificial Intelligence)
• Imaging

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	Virtual endoscopy model-assisted diagnosis	Using the virtual endoscopy model to aid diagnosis

Timeline

• Start date: 2025-07-01
• Primary completion: 2026-08-01
• Completion: 2026-08-01
• First posted: 2025-07-28
• Last updated: 2026-04-13

Locations

1 site across 1 country: China