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Lymph Node Metastasis in Early Esophageal Squamous Cell Carcinoma

NCT07050576 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 500

Last updated 2025-07-03

No results posted yet for this study

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.

Conditions

  • ESCC
  • Lymph Node Metastasis
  • Radiomics

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.

Sponsors & Collaborators

  • The First Affiliated Hospital of Anhui Medical University

    lead OTHER

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-05-01
Primary Completion
2025-10-01
Completion
2025-11-30

Countries

  • China

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07050576 on ClinicalTrials.gov