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Active Not RecruitingNCT07074535

CT and Endoscopic Biopsy Image-Based Deep Learning for Predicting Left Recurrent Laryngeal Nerve Lymph Node Metastasis in Esophageal Cancer

Status
Active Not Recruiting
Phase
Study type
Observational
Enrollment
500 (estimated)
Sponsor
Daping Hospital and the Research Institute of Surgery of the Third Military Medical University · Academic / Other
Sex
All
Age
18 Years – 80 Years
Healthy volunteers
Not accepted

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.

Conditions

Timeline

Start date
2019-01-01
Primary completion
2026-07-30
Completion
2027-12-30
First posted
2025-07-20
Last updated
2025-07-20

Locations

1 site across 1 country: China

Source: ClinicalTrials.gov record NCT07074535. Inclusion in this directory is not an endorsement.

CT and Endoscopic Biopsy Image-Based Deep Learning for Predicting Left Recurrent Laryngeal Nerve Lymph Node Metastasis i (NCT07074535) · Clinical Trials Directory