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Multimodal Deep Learning for Lymph Node Metastasis Prediction and Physician Performance Assessment in T1 Gastric Cancer

RECRUITINGSponsored by Qun Zhao
Actively Recruiting
SponsorQun Zhao
Started2025-01-01
Est. completion2025-12-30
Eligibility
Age18 Years+

Summary

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.

Eligibility

Age: 18 Years+
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

Conditions2

CancerT1 Gastric Cancer Lymph Node Metastasis Early Gastric Cancer Artificial Intelligence-Assisted Diagnosis Multimodal Data Integration

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