Actively Recruiting
AI-Driven Multimodal Imaging Integration for Diagnosis and Prognostication of Digestive System Diseases
Led by First Affiliated Hospital, Sun Yat-Sen University · Updated on 2026-04-13
5000
Participants Needed
1
Research Sites
56 weeks
Total Duration
On this page
AI-Summary
What this Trial Is About
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
Official Title
AI-Driven Multimodal Imaging Integration for Diagnosis and Prognostication of Digestive System Diseases
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Patients with confirmed diagnoses of inflammatory bowel disease (Crohn's disease or ulcerative colitis), intestinal tuberculosis, or Behçet's disease based on clinical, imaging, endoscopic, and pathological data
- Availability of at least one technically adequate CT or MR scan with a high-quality colonoscopy performed within plus or minus one month of imaging
You will not qualify if you...
- Suboptimal imaging quality, such as low-dose artifacts or metal artifacts
- Inadequate bowel preparation for endoscopy
- Incomplete examinations due to poor tolerance
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Trial Site Locations
Total: 1 location
1
XploreMET v3.0 system
Shanghai, China
Actively Recruiting
Research Team
X
Xuehua Li
CONTACT
Y
Yaoqi Ke
CONTACT
How is the study designed?
Study Type
OBSERVATIONAL
Masking
N/A
Allocation
N/A
Model
N/A
Primary Purpose
N/A
Number of Arms
0
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