Actively Recruiting
Deep Learning and Radiomics to Predict Lymph Node Metastasis in Early-stage Esophageal Squamous Cell Carcinoma
Led by The First Affiliated Hospital of Anhui Medical University · Updated on 2025-07-03
500
Participants Needed
1
Research Sites
8 weeks
Total Duration
On this page
AI-Summary
What this Trial Is About
Researchers are developing a predictive model using deep learning and radiomics to assess the risk of lymph node metastasis in patients with early-stage esophageal squamous cell carcinoma (ESCC). Lymph node metastasis is crucial in deciding treatment plans and predicting outcomes for ESCC patients. This study aims to create a non-invasive tool to help doctors make more accurate treatment decisions and improve patient care by enabling earlier, more personalized interventions. The study involves analyzing medical imaging data from a total of 500 patients with early-stage ESCC. Four hundred patients from one center are divided into training and test groups to develop and validate the model, while one hundred patients from another center are used for external validation. The predictive model is assessed by measuring its ability to accurately predict lymph node metastasis using the area under the curve (AUC) and accuracy (ACC) values. Participants provide preoperative contrast-enhanced CT scans taken within two weeks before surgery, and their pathological results are reviewed. The model's performance is tested on separate patient groups to ensure reliability. The primary outcome measured is the AUC value of the model over four years, which reflects how well the model can differentiate between patients with and without lymph node metastasis. The study is observational and does not involve treatment interventions or changes to usual care.
CONDITIONS
Brief Title
Lymph Node Metastasis in Early Esophageal Squamous Cell Carcinoma
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Patients with pathologically confirmed early-stage (T1) esophageal squamous cell carcinoma
- Preoperative contrast-enhanced CT scan performed within 2 weeks before surgery
- No prior treatment before surgical resection
You will not qualify if you...
- Patients who have undergone neoadjuvant therapy or endoscopic treatment
- CT imaging that is insufficient or of poor quality
- Incomplete pathology results
- Presence of metastatic disease
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Your Study Journey
Duration - 2 to 4 weeks
Participants are screened for eligibility to participate in the trial.
1 visit (in-person)
Duration - Within 2 weeks before surgery
Participants undergo diagnostic procedures including a preoperative contrast-enhanced CT scan to evaluate lymph node metastasis using a predictive model.
1 visit (imaging)
Duration - 4 years
Participants are monitored to assess the predictive performance of the model over time, including the area under the curve (AUC) values over 4 years.
Periodic follow-up visits for assessments
Trial Site Locations
Total: 1 location
1
The First Affiliated Hospital of Anhui Medical University
Hefei, Anhui, China, 230022
Actively Recruiting
Research Team
H
Hao Zheng, MD
How is the study designed?
Study Type
OBSERVATIONAL
Masking
N/A
Allocation
N/A
Model
N/A
Primary Purpose
N/A
Number of Arms
2
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