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
| Condition | Gastrointestinal Stromal Tumors, Gastric Subepithelial Tumors, Gastric Leiomyoma, Artificial Intelligence (AI), Multimodal Imaging |
| Intervention | Multimodal AI Analysis System |
| Status | Completed |
| Participants | 300 |
| Est. Completion | 1 Jan 2026 |
| Last Updated | 29 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
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