Deep learning-based quantification of temporalis muscle has prognostic value in patients with glioblastoma.

Journal: British journal of cancer
Published Date: Nov 30, 2021

Abstract

BACKGROUND: Glioblastoma is the commonest malignant brain tumour. Sarcopenia is associated with worse cancer survival, but manually quantifying muscle on imaging is time-consuming. We present a deep learning-based system for quantification of temporalis muscle, a surrogate for skeletal muscle mass, and assess its prognostic value in glioblastoma.

Authors

  • Ella Mi
    University of Oxford Oxford UK.
  • Radvile Mauricaite
    Computational Oncology Group, Institute of Global Health Innovation, Imperial College London, London, UK.
  • Lillie Pakzad-Shahabi
    Computational Oncology Group, Institute of Global Health Innovation, Imperial College London, London, UK.
  • Jiarong Chen
    Computational Oncology Group, Institute of Global Health Innovation, Imperial College London, London, UK.
  • Andrew Ho
    Computational Oncology Group, Institute of Global Health Innovation, Imperial College London, London, UK.
  • Matt Williams
    Computational Oncology Group, Institute of Global Health Innovation, Imperial College London, London, UK. matthew.williams@imperial.ac.uk.

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