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

NCT ID: NCT07087418

Last Updated: 2025-07-28

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

5000 participants

Study Classification

OBSERVATIONAL

Study Start Date

2025-07-01

Study Completion Date

2026-08-01

Brief Summary

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The goal of this observational study is to 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.

Participants will be randomly assigned to either conventional endoscopy or virtual endoscopy groups. The predictive performance of both groups for prognostic indicators, such as clinical remission rate and recurrence risk, will be compared during follow-up to verify the non-inferiority of the virtual endoscopy group.

Detailed Description

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Conditions

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Digestive Diseases Radiology AI (Artificial Intelligence) Imaging

Study Design

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Observational Model Type

OTHER

Study Time Perspective

PROSPECTIVE

Study Groups

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Conventional endoscopy group

Prognostic indicators (e.g., clinical remission rate, recurrence risk) were predicted using conventional endoscopy at baseline.

Kaplan-Meier analysis with log-rank testing

Intervention Type DIAGNOSTIC_TEST

The non-inferiority of the virtual endoscopy group will be verified by comparing the predictive performance for prognostic indicators (e.g., clinical remission rate, recurrence risk) between the two groups during follow-up.

Virtual endoscopy group

Prognostic indicators were predicted using virtual endoscopy at baseline.

Kaplan-Meier analysis with log-rank testing

Intervention Type DIAGNOSTIC_TEST

The non-inferiority of the virtual endoscopy group will be verified by comparing the predictive performance for prognostic indicators (e.g., clinical remission rate, recurrence risk) between the two groups during follow-up.

Interventions

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Kaplan-Meier analysis with log-rank testing

The non-inferiority of the virtual endoscopy group will be verified by comparing the predictive performance for prognostic indicators (e.g., clinical remission rate, recurrence risk) between the two groups during follow-up.

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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Inclusion Criteria

* 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.

Exclusion Criteria

* ・Suboptimal imaging quality (e.g., low-dose artifacts, metal artifacts)

* Inadequate bowel preparation for endoscopy
* Incomplete examinations due to poor tolerance
Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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First Affiliated Hospital, Sun Yat-Sen University

OTHER

Sponsor Role lead

Responsible Party

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Xuehua Li

associate chief physician

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Xuehua Li

Role: PRINCIPAL_INVESTIGATOR

Sun Yat-sen University First Affiliated Hospital Department of Radiology

Locations

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XploreMET v3.0 system

Shanghai, , China

Site Status RECRUITING

Countries

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China

Central Contacts

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Xuehua Li

Role: CONTACT

13580364103

Yaoqi Ke

Role: CONTACT

18316712708

Facility Contacts

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Xuehua Li

Role: primary

13580364103

Other Identifiers

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82270693

Identifier Type: -

Identifier Source: org_study_id

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