AI for detection, classification and prediction of loss of alignment of distal radius fractures; a systematic review.

Journal: European journal of trauma and emergency surgery : official publication of the European Trauma Society
PMID: 38981869

Abstract

PURPOSE: Early and accurate assessment of distal radius fractures (DRFs) is crucial for optimal prognosis. Identifying fractures likely to lose threshold alignment (instability) in a cast is vital for treatment decisions, yet prediction tools' accuracy and reliability remain challenging. Artificial intelligence (AI), particularly Convolutional Neural Networks (CNNs), can evaluate radiographic images with high performance. This systematic review aims to summarize studies utilizing CNNs to detect, classify, or predict loss of threshold alignment of DRFs.

Authors

  • Koen D Oude Nijhuis
    Department of Surgery and Perioperative Care, Dell Medical School at the University of Texas at Austin, Austin, TX, USA.
  • Lente H M Dankelman
    Trauma Research Unit, Department of Surgery, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, 3000 CA, Rotterdam, The Netherlands. l.dankelman@erasmusmc.nl.
  • Jort P Wiersma
    Department of Orthopedic Surgery, Groningen, Groningen University Medical Centre, Groningen, The Netherlands.
  • Britt Barvelink
    Department of Orthopedics and Sports Medicine, Erasmus University Medical Centre, Rotterdam, The Netherlands.
  • Frank F A Ijpma
    Department of Trauma Surgery, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
  • Michael H J Verhofstad
    Trauma Research Unit, Department of Surgery, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, 3000 CA, Rotterdam, The Netherlands.
  • Job N Doornberg
  • Joost W Colaris
    Department of Orthopedics, Erasmus University Medical Centre, Rotterdam, The Netherlands.
  • Mathieu M E Wijffels
    Trauma Research Unit, Department of Surgery, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, 3000 CA, Rotterdam, The Netherlands.

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