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

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

Recruiting
18 years and older
All
Phase N/A
  • Technical (Original)
  • Simplified (AI rewritten)

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Overview

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

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

Study details
    T1 Gastric Cancer Lymph Node Metastasis Early Gastric Cancer Artificial Intelligence-Assisted Diagnosis Multimodal Data Integration

NCT07124754

Qun Zhao

15 October 2025

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