Current state of radiomics in pediatric neuro-oncology practice: a systematic review.

Journal: Pediatric radiology
PMID: 37195305

Abstract

BACKGROUND: Radiomics is the process of converting radiological images into high-dimensional data that may be used to create machine learning models capable of predicting clinical outcomes, such as disease progression, treatment response and survival. Pediatric central nervous system (CNS) tumors differ from adult CNS tumors in terms of their tissue morphology, molecular subtype and textural features. We set out to appraise the current impact of this technology in clinical pediatric neuro-oncology practice.

Authors

  • Ibrahem Albalkhi
    Department of Neuroradiology, Alfaisal University, Great Ormond Street Hospital NHS Foundation Trust, London WC1N 3JH, United Kingdom.
  • Aashim Bhatia
    Department of Neuroradiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
  • Nico Lösch
    Biomedical Data Science Lab, University of Technology Sydney, Ultimo, Australia.
  • Robert Goetti
    Department of Medical Imaging, The Children's Hospital at Westmead, University of Sydney, Sydney, Australia.
  • Kshitij Mankad
    Department of Neuroradiology, Great Ormond Street Hospital NHS Foundation Trust, Great Ormond St, London, WC1N 3JH, UK.

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