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RECRUITING
NCT07050576

Lymph Node Metastasis in Early Esophageal Squamous Cell Carcinoma

Sponsor: The First Affiliated Hospital of Anhui Medical University

View on ClinicalTrials.gov

Summary

This study aims to develop a predictive model using deep learning and radiomics to assess the likelihood of lymph node metastasis in patients with early-stage esophageal squamous cell carcinoma (ESCC). Lymph node metastasis is a critical factor in determining the treatment approach and prognosis for ESCC patients. By analyzing medical imaging data, we hope to create a non-invasive method that can assist doctors in making more accurate treatment decisions. This research could improve patient outcomes by enabling earlier and more tailored interventions.

Official title: Deep Learning and Radiomics for Prediction of Lymph Node Metastasis in Early-stage Esophageal Squamous Cell Carcinoma

Key Details

Gender

All

Age Range

Any - Any

Study Type

OBSERVATIONAL

Enrollment

500

Start Date

2024-05-01

Completion Date

2025-11-30

Last Updated

2025-07-03

Healthy Volunteers

No

Interventions

DIAGNOSTIC_TEST

The prediction model of lymph node metastasis in early esophageal squamous cell carcinoma

The predictive performance of the model was validated in the test set. The optimal prediction model was determined based on the AUC and ACC. To assess the robustness of the chosen model, ROC analysis was conducted on the external validation set.

Locations (1)

The First Affiliated Hospital of Anhui Medical University

Hefei, Anhui, China