Deep learning-based prediction of enhanced CT scans for lymph node metastasis in esophageal squamous cell carcinoma.

Journal: Japanese journal of radiology
Published Date: Apr 11, 2025

Abstract

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) poses a significant global health challenge with a particularly grim prognosis. Accurate prediction of lymph node metastasis (LNM) in ESCC is crucial for optimizing treatment strategies and improving patient outcomes. This study leverages the power of deep learning, specifically Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks, to analyze arterial phase enhanced CT images and predict LNM in ESCC patients.

Authors

  • Hao Wu
    Zhejiang Institute of Tianjin University (Shaoxing), Shaoxing, China.
  • Xiaoli Wu
    Burn Department of Maoming People's Hospital, Maoming Guangdong 525000, China.
  • Shouliang Miao
    Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.
  • Guoquan Cao
    Department of Radiology, Key Laboratory of Intelligent Medical Imaging of Wenzhou, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
  • Huang Su
    Department of Gastroenterology, Wenzhou Central Hospital, Wenzhou, 325000, Zhejiang, China. suda0huan9@gmail.com.
  • Jie Pan
  • Yilun Xu
    Department of Gastroenterology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China.
  • Jianwei Zhou
    Institute of Physical Education, Xuchang University, Xuchang, Henan 461000, China.

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