Radiomics-Based AI Model for Predicting Para-Aortic Lymph Node Metastasis in Gastric Cancer Patients

Enrolling by invitationOBSERVATIONAL
Enrollment

120

Participants

Timeline

Start Date

January 1, 2025

Primary Completion Date

June 30, 2025

Study Completion Date

June 30, 2025

Conditions
Gastric CancerPara-Aortic Lymph Node MetastasisLymphatic MetastasisPreoperative Imaging AssessmentRadiomicsArtificial Intelligence
Interventions
DIAGNOSTIC_TEST

Radiomics-Based AI Imaging Analysis

This intervention involves the development and application of a radiomics-based artificial intelligence (AI) model to analyze preoperative abdominal CT images of patients with gastric cancer. The AI algorithm extracts high-dimensional imaging features from the para-aortic region to predict the presence or absence of para-aortic lymph node metastasis (PALNM). This non-invasive method aims to assist clinicians in preoperative risk stratification and treatment planning. The model will be trained and validated using manually segmented lymph node regions and correlated with postoperative pathological findings to ensure accuracy and clinical relevance.

Trial Locations (1)

050011

the Fourth Hospital of Hebei Medical University, Shijiazhuang

All Listed Sponsors
collaborator

First Hospital of Shijiazhuang City

OTHER

collaborator

Baoding First Central Hospital

OTHER

collaborator

Hengshui People's Hospital

OTHER

lead

Qun Zhao

OTHER