An interpretable ensemble model combining handcrafted radiomics and deep learning for predicting the overall survival of hepatocellular carcinoma patients after stereotactic body radiation therapy.

Journal: Journal of cancer research and clinical oncology
PMID: 39948208

Abstract

PURPOSE: Hepatocellular carcinoma (HCC) remains a global health concern, marked by increasing incidence rates and poor outcomes. This study seeks to develop a robust predictive model by integrating radiomics and deep learning features with clinical data to predict 2-year survival in HCC patients treated with stereotactic body radiation therapy (SBRT).

Authors

  • Yi Chen
    Department of Anesthesiology and Perioperative Medicine, General Hospital of Ningxia Medical University, Yinchuan, China.
  • David Pasquier
    Academic Department of Radiation Oncology, Centre Oscar Lambret, 3 rue Frédéric Combemale, BP 307, 59020, LILLE Cedex, France. d-pasquier@o-lambret.fr.
  • Damon Verstappen
    The D-Lab, Department of Precision Medicine, GROW-Research Institute for Oncology and Reproduction, Maastricht University, Maastricht, The Netherlands.
  • Henry C Woodruff
    The D-Lab, Department of Precision Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands.
  • Philippe Lambin
    Department of Radiation Oncology (MAASTRO Clinic), Dr. Tanslaan 12, Maastricht, The Netherlands.

Keywords

External Resources

Popular Topics
Recent Journals