Artificial intelligence in musculoskeletal oncology imaging: A critical review of current applications.

Journal: Diagnostic and interventional imaging
Published Date: Oct 18, 2022

Abstract

Artificial intelligence (AI) is increasingly being studied in musculoskeletal oncology imaging. AI has been applied to both primary and secondary bone tumors and assessed for various predictive tasks that include detection, segmentation, classification, and prognosis. Still, in the field of clinical research, further efforts are needed to improve AI reproducibility and reach an acceptable level of evidence in musculoskeletal oncology. This review describes the basic principles of the most common AI techniques, including machine learning, deep learning and radiomics. Then, recent developments and current results of AI in the field of musculoskeletal oncology are presented. Finally, limitations and future perspectives of AI in this field are discussed.

Authors

  • Maxime Lacroix
    Department of Nuclear Medicine, Avicenne Hospital, APHP, Bobigny, Paris, France.
  • Theodore Aouad
    Université Paris-Saclay, CentraleSupélec, Inria, Centre for Visual Computing, 91190, Gif-sur-Yvette, France.
  • Jean Feydy
    Université Paris Cité, HeKA team, Inria Paris, Inserm, 75006, Paris, France.
  • David Biau
    Université Paris Cité, Faculté de Médecine, Paris, 75006, France; Department of Orthopedic Surgery, Hôpital Cochin, Assistance Publique-Hôpitaux de Paris, Paris, 75014, France.
  • Frédérique Larousserie
    Université Paris Cité, Faculté de Médecine, Paris, 75006, France; Department of Pathology, Hôpital Cochin, Assistance Publique-Hôpitaux de Paris, Paris, 75014, France.
  • Laure Fournier
    PARCC UMRS 970, INSERM, Paris, France; Université Paris Cité, AP-HP, Hopital européen Georges Pompidou, Paris, France.
  • Antoine Feydy
    Department of Radiology B, Cochin Hospital, AP-HP, 75014 Paris, France; Université de Paris, 75006 Paris, France.

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