CompletedNCT07454967

Development and Validation of a Multimodal Artificial Intelligence Model Integrating CT Radiomics, Pathomics, and Clinical Features for the Diagnosis, Risk Stratification, and Genotype Prediction of Gastrointestinal Stromal Tumors

Sponsor: Qun Zhao

Trial Details

ConditionGastrointestinal Stromal Tumors, Gastric Subepithelial Tumors, Gastric Leiomyoma, Artificial Intelligence (AI), Multimodal Imaging
InterventionMultimodal AI Analysis System
StatusCompleted
Participants300
Est. Completion1 Jan 2026
Last Updated29 July 2026

Primary Outcome

Diagnostic Accuracy of the AI Model for Distinguishing GIST from Non-GIST Tumors

Eligibility Criteria

Inclusion Criteria

Inclusion Criteria: Age ≥ 18 years, gender not limited. Clinical diagnosis of gastric submucosal tumor (SMT) or suspected gastrointestinal stromal tumor (GIST) based on gastroscopy or ultrasound. Scheduled for surgical resection or endoscopic biopsy at the study center. Standard preoperative contrast-enhanced CT scans are available (performed within 2 weeks prior to surgery). Patients or their legal guardians have signed the informed consent form. Exclusion Criteria: Received neoadjuvant therapy (e.g., Imatinib, chemotherapy, or radiotherapy) prior to surgery/biopsy. Poor quality of CT images (e.g., severe motion artifacts) affecting radiomics analysis. Insufficient tissue samples for pathological diagnosis or genetic testing. Confirmed diagnosis of other primary malignancies. Incomplete clinical data or lost to follow-up immediately after surgery.

Trial Sites

Countries

China
View Registry Entry

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