Predicting lymph node spread in early esophageal squamous cell carcinoma
Deep Learning and Radiomics for Prediction of Lymph Node Metastasis in Early-stage Esophageal Squamous Cell Carcinoma
This project will use deep learning on preoperative CT scans to try to predict whether people with early-stage esophageal squamous cell carcinoma have lymph node metastasis.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 500 (estimated) |
| Sex | All |
| Sponsor | The First Affiliated Hospital of Anhui Medical University Academic / other |
| Locations | 1 site (Hefei, Anhui) |
| Trial ID | NCT07050576 on ClinicalTrials.gov |
What this trial studies
This observational effort uses contrast-enhanced CT images taken within two weeks before surgery from patients with pathologically confirmed T1 esophageal squamous cell carcinoma who have not received prior treatment. Radiomics features will be extracted from imaging and combined with deep-learning methods to build a predictive model of lymph node metastasis. The model development is based on surgical pathology as the reference standard and excludes cases with poor image quality or incomplete pathology. The goal is a non-invasive tool to help guide clinical treatment decisions about the need for more extensive surgery or additional therapies.
Who should consider this trial
Good fit: Ideal candidates are patients with pathologically confirmed T1 ESCC who have preoperative contrast-enhanced CT performed within two weeks before surgical resection and who have not received neoadjuvant or endoscopic therapy.
Not a fit: Patients with more advanced disease (beyond T1), prior neoadjuvant or endoscopic treatment, poor or missing CT imaging, incomplete pathology, or distant metastases are unlikely to benefit from this model.
Why it matters
Potential benefit: If successful, the model could help clinicians identify lymph node metastasis non-invasively and guide more personalized surgical or treatment planning.
How similar studies have performed: Previous radiomics and AI studies for predicting lymph node metastasis in esophageal cancer have shown promising but variable accuracy, so this work builds on emerging but not yet definitive evidence.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Patients with pathologically confirmed early-stage (T1) ESCC * Preoperative contrast-enhanced CT data within 2 weeks before surgery * Without any treatment before surgical resection Exclusion Criteria: * Patients who underwent neoadjuvant therapy or endoscopic treatment * Insufficient CT imaging or poor CT quality * Incomplete pathology results * Presence of metastatic disease
Where this trial is running
Hefei, Anhui
- The First Affiliated Hospital of Anhui Medical University — Hefei, Anhui, China (Recruiting)
Study contacts
- Study coordinator: Hao Zheng, MD
- Email: pojunayfy@gmail.com
- Phone: +86 139 1793 6873
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.