External Validation of a Novel Landmark-Based Deep Learning Automated Tibial Slope Measurement Algorithm Applied on Short Radiographs Obtained in Patients With ACL Injuries.

Journal: Orthopaedic journal of sports medicine
Published Date: May 5, 2025

Abstract

BACKGROUND: Deep learning algorithms can aid medical decision-making by performing routine tasks without any human error. Reading of standardized radiographs lends itself well to a computerized approach. The posterior tibial slope is increasingly recognized as a factor in lower leg biomechanics. Slope readings should, therefore, be readily available when considering knee ligament or knee replacement surgery.

Authors

  • Kyle R Martin
    Department of Orthopaedic Surgery, University of Minnesota, Minneapolis, Minnesota, USA.
  • Sanna Haaland
    Sports Traumatology Arthroscopy Research Group, Faculty of Medicine, University of Bergen, Bergen, Hordaland, Norway.
  • Andreas Persson
    Oslo Sports Trauma Research Center, Norwegian School of Sports Sciences, Oslo, Norway.
  • Sung Eun Kim
    Department of Pediatrics, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
  • ByeongYeong Ryu
    Department of Orthopaedic Surgery, Seoul National College of Medicine, Seoul, Republic of Korea.
  • Jun Woo Nam
    Connecteve Co, Ltd, Seoul, Republic of Korea.
  • Du Huy Ro
    Department of Orthopaedic Surgery, Seoul National College of Medicine, Seoul, Republic of Korea.
  • Eivind Inderhaug
    Sports Traumatology Arthroscopy Research Group, Faculty of Medicine, University of Bergen, Bergen, Hordaland, Norway.

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