External validation of the deep learning system "SpineNet" for grading radiological features of degeneration on MRIs of the lumbar spine.

Journal: European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
PMID: 35835892

Abstract

BACKGROUND: Magnetic resonance imaging (MRI) is used to detect degenerative changes of the lumbar spine. SpineNet (SN), a computer vision-based system, performs an automated analysis of degenerative features in MRI scans aiming to provide high accuracy, consistency and objectivity. This study evaluated SN's ratings compared with those of an expert radiologist.

Authors

  • Alexandra Grob
    Department of Spine Surgery and Neurosurgery, Schulthess Klinik, Zurich, Switzerland. grob.alexandra@gmx.ch.
  • Markus Loibl
    Department of Spine Surgery and Neurosurgery, Schulthess Klinik, Zurich, Switzerland.
  • Amir Jamaludin
    Department of Engineering Science, University of Oxford, Oxford, UK.
  • Sebastian Winklhofer
    Department of Neuroradiology, University Hospital Zurich, Zurich, Switzerland.
  • Jeremy C T Fairbank
    Nuffield Department of Rheumatology, Orthopaedics and Musculoskeletal Sciences, University of Oxford, Oxford, UK.
  • Tamás Fekete
    Department of Spine Surgery and Neurosurgery, Schulthess Klinik, Zurich, Switzerland.
  • François Porchet
    Department of Spine Surgery and Neurosurgery, Schulthess Klinik, Zurich, Switzerland.
  • Anne F Mannion
    Department of Teaching, Research and Development, Schulthess Klinik, Zurich, Switzerland.

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