Lymph Node Metastasis in Early Esophageal Squamous Cell Carcinoma

Deep Learning and Radiomics for Prediction of Lymph Node Metastasis in Early-stage Esophageal Squamous Cell Carcinoma

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.

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