CT and Endoscopic Biopsy Image-Based Deep Learning for Predicting Left Recurrent Laryngeal Nerve Lymph Node Metastasis in Esophageal Cancer
Condition(s) studied
Study summary
The goal of this observational study is to develop a predictive model for left recurrent laryngeal nerve (RLN) lymph node metastasis using deep learning algorithms. The model will be developed using clinical data from previous esophageal cancer surgeries, including preoperative CT imaging, and histopathological images from gastroscopic biopsies. The model will also be validated through prospective clinical trials to guide the intraoperative lymph node dissection, thereby reducing postoperative risks of RLN injury.
Eligibility
Primary outcome measure(s)
- AUROC (Area Under the Receiver Operating Characteristic Curve) — From enrollment to the end of treatment at 4 weeks
The discriminant ability of the comprehensive evaluation model at different thresholds (positive vs. negative)
Trial sites (1)
| Facility | City | Region | Status |
|---|---|---|---|
| Daping Hospital | Chongqing | China |
More Daping Hospital and the Research Institute of Surgery of the Third Military Medical University trials in China
Other trials for the same condition
This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.
View NCT07074535 on ClinicalTrials.gov ↗ ← All trials in China