RecruitingNCT07078136

Multicenter Observational Study of Multimodal AI for Upper GI Mesenchymal Tumor Diagnosis

Multicenter Observational Study of a Multimodal AI Model Using EUS, White-Light Endoscopy, and Clinical Data for Diagnosis of Upper GI Mesenchymal Tumors and Risk Stratification of Gastric GISTs


Sponsor

Huazhong University of Science and Technology

Enrollment

130 participants

Start Date

Jul 28, 2025

Study Type

OBSERVATIONAL

Conditions

Summary

This study develops a multimodal AI model using endoscopic ultrasound, white-light endoscopy, and clinical information to support the diagnosis of upper GI mesenchymal tumors and the risk stratification of gastric GISTs.


Eligibility

Min Age: 18 Years

Plain Language Summary

Simplified for easier understanding

This study is using artificial intelligence to analyze ultrasound images (endoscopic ultrasound, or EUS) of tumors in the upper digestive tract to improve diagnosis — specifically to tell apart GISTs (gastrointestinal stromal tumors) from other similar-looking growths. **You may be eligible if...** - You are 18 years or older - You have a small tumor or lesion (subepithelial lesion) in your upper digestive tract found by endoscopy - You have completed an endoscopic ultrasound (EUS) examination - Your tumor has been diagnosed by tissue sampling or surgical removal - The quality of your EUS images meets the study's technical standards **You may NOT be eligible if...** - Your EUS images do not meet the required quality standards - You have not had a tissue diagnosis or your lesion has not been adequately evaluated - You are under 18 years old Talk to your doctor to see if this trial is right for you.

This summary was AI-generated to explain the trial in plain language. It is not medical advice. Always discuss eligibility with your doctor before enrolling in a clinical trial.

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Interventions

DIAGNOSTIC_TESTMultimodal AI Model

Patients' endoscopic images, EUS images, and clinical data will be analyzed by a multimodal AI model for lesion classification and GIST risk stratification.

DIAGNOSTIC_TESTExpert Endoscopist Assessment

Endoscopic ultrasound images will be interpreted by experienced endoscopists for comparison with the AI model.


Locations(1)

Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology

Wuhan, Hubei, China

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NCT07078136


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