Development and Validation of a Multimodal Artificial Intelligence Model for Predicting Lymph Node Metastasis in T1 Gastric Cancer and Its Impact on Physician Diagnostic Performance
Development and Validation of a Multimodal Artificial Intelligence Model for Predicting Lymph Node Metastasis in T1 Gastric Cancer and Its Impact on Physician Diagnostic Performance
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.
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