Digestive DiseasesNCT07087418
AI-Driven Multimodal Imaging Integration for Diagnosis and Prognostication of Digestive System Diseases
An observational study of Digestive Diseases and Radiology, run by First Affiliated Hospital, Sun Yat-Sen University at 1 site in China.
Trial 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… Read more about this study
- Who is it for?
- Any ageHealthy volunteers can take part
- Conditions the study is for
- Digestive Diseases, Radiology, AI (Artificial Intelligence)
- What is being tested?
- Virtual endoscopy model-assisted diagnosis
- How many people
- 5,000 participants
- Where
- 1 siteChina
- Study dates
- 1 Jul 2025to 1 Aug 2026
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
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.
Who may be able to join
- 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.
Who cannot join
- ・Suboptimal imaging quality (e.g., low-dose artifacts, metal artifacts)
- Inadequate bowel preparation for endoscopy
- Incomplete examinations due to poor tolerance
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
China1 site, 1 recruiting
- Recruiting
XploreMET v3.0 system
Shanghai
Xuehua Li, 13580364103, lxueh@mail.sysu.edu.cn
About this study
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
- Being tested
- Virtual endoscopy model-assisted diagnosis
- Keywords
- Radiology, Imaging, Digestive Diseases, Artificial Intelligence
- Medical subject headings
- Digestive System Diseases
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Virtual endoscopy model-assisted diagnosisDiagnostic test
Using the virtual endoscopy model to aid diagnosis
What is being measured
The primary outcome is the main question the study is designed to answer.
The area under the ROC curve (AUC) to assess the performance of diagnostic model.
After baseline MR or CT scanning, patients were followed up.
Measured: 6 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted28 Jul 2025
- Study start1 Jul 2025
- Primary completion1 Aug 2026 (estimated)
- Study completion1 Aug 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Digestive DiseasesStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Other
- Time perspective
- Other
- Enrolment
- 5,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- First Affiliated Hospital, Sun Yat-Sen University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Xuehua Li, First Affiliated Hospital, Sun Yat-Sen University
- Investigators
- Xuehua Li, Principal investigator, Sun Yat-sen University First Affiliated Hospital Department of Radiology
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07087418
- Sponsor's protocol ID
- 82270693
- Status last verified
- Apr 2026
- First submitted
- 20 Jul 2025
- Last updated
- 13 Apr 2026
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 13 Apr 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- AI-Driven Multimodal Imaging Integration for Diagnosis and Prognostication of Digestive System Diseases
- ClinicalTrials.gov ID
- NCT07087418
- Acronym / sponsor ID
- 82270693
- Conditions
- Digestive Diseases, Radiology, AI (Artificial Intelligence), Imaging
- Keywords
- Radiology, Imaging, Digestive Diseases, Artificial Intelligence
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 5,000 participants (estimated)
- Lead sponsor
- First Affiliated Hospital, Sun Yat-Sen UniversityUniversity, hospital or other
- Study start
- 1 Jul 2025 (actual)
- Primary completion
- 1 Aug 2026 (estimated)
- Study completion
- 1 Aug 2026 (estimated)
- First posted
- 28 Jul 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Observational model
- Other
- Time perspective
- Other
Who may qualify
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
- 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.
Key inclusion criteria (5 listed)
- Patients with multimodal-confirmed diagnoses (clinical, imaging, endoscopic, and pathological) of:
- Availability of ≥1 technically adequate CT or MR scan with high-quality colonoscopy performed within ±1 month of imaging.
Key exclusion criteria (3 listed)
- ・Suboptimal imaging quality (e.g., low-dose artifacts, metal artifacts)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Virtual endoscopy model-assisted diagnosisUsing the virtual endoscopy model to aid diagnosis | Diagnostic test | – |
Primary outcome
The area under the ROC curve (AUC) to assess the performance of diagnostic model.
Time frame: 6 months
After baseline MR or CT scanning, patients were followed up.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 13 Apr 2026.
- Individual participant dataSharing planned: Undecided
Related trials for Digestive Diseases
Recruiting
MRD Monitoring in Colorectal Cancer Using ctDNA
Colorectal Neoplasms, Colorectal Cancer (Diagnosis)
Recruiting
Implementation of a Pain Management Plan in Major Open Abdominal Surgeries.
Abdomen Cancer, Pancreas Adenocarcinoma (MSI-H)
RecruitingPhase 1/2
A Study to Investigate ALE.P02 as a Monotherapy or in Combination With Pembrolizumab in Adult Patients With Selected CLDN1+ Solid Tumors
Squamous Non-small-cell Lung Cancer, Head and Neck Squamous Cell Carcinoma
Not yet recruitingPhase 1
Study of ACC-1898 in Adult Participants With Advanced Solid Tumors
Hepatocellular Carcinoma, Renal Cell Carcinoma
Not yet recruitingObservational study
AI-Assisted Differentiation of Autoimmune Pancreatitis and Pancreatic Cancer Using EUS: A Multicenter Ambispective Study
Autoimmune Pancreatitis, Pancreatic Ductal Adenocarcinoma (PDAC)
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Xuehua Li principal investigator
Sun Yat-sen University First Affiliated Hospital Department of Radiology
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Digestive Diseases and Radiology, run by First Affiliated Hospital, Sun Yat-Sen University at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 13 Apr 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Xuehua Li (13580364103, lxueh@mail.sysu.edu.cn), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
The area under the ROC curve (AUC) to assess the performance of diagnostic model. (time frame: 6 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 13 Apr 2026.