Predicting Overall Survival of Glioblastoma Patients Using Deep Learning Classification Based on MRIs.

Journal: Studies in health technology and informatics
PMID: 39234740

Abstract

INTRODUCTION: Glioblastoma (GB) is one of the most aggressive tumors of the brain. Despite intensive treatment, the average overall survival (OS) is 15-18 months. Therefore, it is helpful to be able to assess a patient's OS to tailor treatment more specifically to the course of the disease. Automated analysis of routinely generated MRI sequences (FLAIR, T1, T1CE, and T2) using deep learning-based image classification has the potential to enable accurate OS predictions.

Authors

  • Katharina Ott
    IT-Infrastructure for Translational Medical Research, University of Augsburg, Germany.
  • Santiago Cepeda
    Neurosurgery Department, Rio Hortega University Hospital, 47012 Valladolid, Spain.
  • Dennis Hartmann
    IT-Infrastructure for Translational Medical Research, University of Augsburg, Germany.
  • Frank Kramer
    IT-Infrastructure for Translational Medical Research, Faculty of Applied Computer Science, Faculty of Medicine, University of Augsburg, Augsburg, Germany.
  • Dominik Müller
    IT-Infrastructure for Translational Medical Research, University of Augsburg, 86159 Augsburg, Germany.

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