Two-Phase Deep Learning Algorithm for Detection and Differentiation of Ewing Sarcoma and Acute Osteomyelitis in Paediatric Radiographs.

Journal: Anticancer research
PMID: 36039445

Abstract

BACKGROUND/AIM: Ewing sarcoma is a highly malignant tumour predominantly found in children. The radiological signs of this malignancy can be mistaken for acute osteomyelitis. These entities require profoundly different treatments and result in completely different prognoses. The purpose of this study was to develop an artificial intelligence algorithm, which can determine imaging features in a common radiograph to distinguish osteomyelitis from Ewing sarcoma.

Authors

  • Sarah Consalvo
    Department of Orthopaedics and Sports Orthopaedic, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany; sarah.consalvo@mri.tum.de.
  • Florian Hinterwimmer
    Department of Orthopaedics and Sports Orthopaedics, Klinikum Rechts der Isar, Technical University Munich, Ismaningerstr. 22, 81675, Munich, Germany. florian.hinterwimmer@tum.de.
  • Jan Neumann
    Department of Radiology, Klinikum Rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675, Munich, Germany.
  • Marc Steinborn
    Institute for Diagnostic and Interventional Radiology and Paediatric Radiology, Klinikum Schwabing, Munich, Germany.
  • Maya Salzmann
    Department of Orthopaedics and Sports Orthopaedic, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.
  • Fritz Seidl
    Department of Trauma Surgery, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.
  • Ulrich Lenze
    Department of Orthopaedics and Sports Orthopaedic, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.
  • Carolin Knebel
    From the Department of Radiology (C.E.v.S., V.S.S., Y.L., F.G.G., S.C.F., F.T.G., M.R.M., K.W., A.S.G.), Department for Orthopedics and Orthopedic Sports Medicine (N.J.W., C.K., R.v.E., R.B.), and Institute of Pathology (C.M.), Klinikum Rechts der Isar, Technische Universität München, Ismaninger Str 22, 81675 Munich, Germany; and the Department of Diagnostic and Interventional Radiology, Medical Center-University of Freiburg, Faculty of Medicine, Freiburg, Germany (M.J., P.M.J., M.F.R.).
  • Daniel Rueckert
    Biomedical Image Analysis (BioMedIA) Group, Department of Computing, Imperial College London, UK. Electronic address: d.rueckert@imperial.ac.uk.
  • Rainer H H Burgkart
    Department of Orthopaedics and Sports Orthopaedic, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.

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