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

NCT07087418 | Recruiting

• 1 other identifier: 82270693
• Study Type: observational
• Target: 5,000
• Locations: 1 country
• Sites: 1

Brief 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; AI (Artificial Intelligence); Radiology; Imaging

Keywords

Radiology; Imaging; Digestive Diseases; Artificial Intelligence

Outcome Measures

Primary Outcomes (1)

• The area under the ROC curve (AUC) to assess the performance of diagnostic model.

  After baseline MR or CT scanning, patients were followed up.

  6 months

Interventions

Virtual endoscopy model-assisted diagnosis DIAGNOSTIC_TEST

Using the virtual endoscopy model to aid diagnosis

Eligibility Criteria

• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

This retrospective and prospective study included patients with digestive diseases. For the retrospective component, the investigators enrolled patients from 21 hospitals across China, including the First Affiliated Hospital of Sun Yat-sen University. For the prospective component, the investigators enrolled patients from the First Affiliated Hospital of Sun Yat-sen University and the Third Affiliated Hospital of Guangzhou Medical University.

You may qualify if:

• Patients with multimodal-confirmed diagnoses (clinical, imaging, endoscopic, and pathological) of:
• Inflammatory bowel disease (IBD; Crohn's disease or ulcerative colitis)
• Intestinal tuberculosis
• Behçet's disease
• Availability of ≥1 technically adequate CT or MR scan with high-quality colonoscopy performed within ±1 month of imaging.

You may not qualify if:

• ・Suboptimal imaging quality (e.g., low-dose artifacts, metal artifacts)
• Inadequate bowel preparation for endoscopy
• Incomplete examinations due to poor tolerance

Sponsors & Collaborators

• First Affiliated Hospital, Sun Yat-Sen University: lead

Study Sites (1)

XploreMET v3.0 system

Shanghai, China

RECRUITING

MeSH Terms

Conditions

Digestive System Diseases

Study Officials

• Xuehua Li

  Sun Yat-sen University First Affiliated Hospital Department of Radiology

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Xuehua Li

CONTACT

13580364103; lxueh@mail.sysu.edu.cn

Yaoqi Ke

CONTACT

18316712708; keyq3@mail2.sysu.edu.cn

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: OTHER
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: associate chief physician

Study Record Dates

• First Submitted: July 20, 2025
• First Posted: July 28, 2025
• Study Start: July 1, 2025
• Primary Completion (Estimated): August 1, 2026
• Study Completion (Estimated): August 1, 2026
• Last Updated: April 13, 2026

Record last verified: 2026-04

Locations

CN (1)