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This study aims to develop and validate an artificial intelligence (AI) model that integrates clinical, pathological, and imaging data to predict the presence of lymph node metastasis (LNM) in patients with T1-stage gastric cancer.
The study will also compare the diagnostic performance of physicians with and without AI assistance, including clinicians with varying levels of experience.
The goal is to improve early decision-making and support more personalized treatment strategies for patients with early gastric cancer.
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Multimodal Artificial Intelligence Diagnostic Model for Lymph Node Metastasis in T1 Gastric Cancer | Diagnostic Test | This intervention involves the use of a custom-built artificial intelligence (AI) diagnostic model that integrates multimodal data-including clinical variables, histopathological features, and imaging data-to predict lymph node metastasis in patients with T1-stage gastric cancer. The model provides risk probability scores and classification outputs that assist physicians in diagnostic decision-making. The AI system will be compared with physician performance at different levels of experience (resident, attending, senior) to assess its impact on diagnostic accuracy and clinical decision support. |
| Measure | Description | Time Frame |
|---|---|---|
| Diagnostic Accuracy of the AI Model for Predicting Lymph Node Metastasis in T1 Gastric Cancer | Immediately after surgery (within 7 days postoperatively, based on final pathological report) | |
| Diagnostic Accuracy of the AI Model for Predicting Lymph Node Metastasis in T1 Gastric Cancer | At the time of final pathological diagnosis (typically within 3-7 days after surgery) |
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Inclusion Criteria:
Age 18 years or older
Histologically confirmed primary gastric adenocarcinoma
Clinical stage T1 (T1a or T1b) confirmed by endoscopy and imaging
Undergoing radical gastrectomy with lymph node dissection
Preoperative data available: clinical variables, CT imaging, and pathology slides
Written informed consent provided
Exclusion Criteria:
History of other malignancies within the past 5 years
Received neoadjuvant chemotherapy or radiotherapy
Incomplete clinical or pathological data
Poor quality or missing CT or histopathology images
Patients with distant metastasis (M1) at diagnosis
Inability or refusal to provide informed consent
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Patients diagnosed with T1-stage gastric adenocarcinoma who undergo radical gastrectomy with lymph node dissection at participating centers. Participants must have available preoperative clinical, imaging, and pathological data for AI model input and postoperative histopathological confirmation of lymph node status.
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| the Fourth Hospital of Hebei Medical University | Recruiting | Shijiazhuang | None Selected | 050011 | China |
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