Publication

Real-life benefit of artificial intelligence-based fracture detection in a pediatric emergency department

Authors:

Maria Ziegner, Johanna Pape, Martin Lacher, Annika Brandau, Tibor Kelety, Steffi Mayer, Franz Wolfgang Hirsch, Maciej Rosolowski & Daniel Gräfe

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Objective

This study evaluates how well RBfracture™ detects fractures in paediatric patients in a real-life clinical setting. It specifically assesses RBfracture’s standalone performance — both overall and on medicolegal-relevant fractures — and its impact on the diagnostic accuracy of less-experienced emergency physicians.

Key findings

  • RBfracture demonstrated a sensitivity of 92%, specificity of 83%, and accuracy of 87%
  • RBfracture demonstrated a sensitivity of 100% for proximal tibia fractures
  • Residents using RBfracture improved their sensitivity from 84% to 87%, specificity from 91% to 92%, and diagnostic accuracy from 88% to 90%
  • The performance of RBfracture in children <5 years old was not significantly lower than >5 years
  • Concerning medicolegal relevant fractures, RBfracture performed best on proximal tibia fractures (100% sensitivity) and medial ankle fractures (96% sensitivity)
  • Use of RBfracture resulted in a decrease of missed fractures of 22%

Open access

This research is open access

This original research can be read in European Radiology, published in February 2025.

Funding and conflicts of interests

Open Access funding was enabled and organized by Projekt DEAL. RBfracture was provided free of charge by ImageBiopsy Lab (software distributor). The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

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