Individual thigh muscle and proximal femoral features predict displacement in femoral neck Fractures: An AI-driven CT analysis.

Journal: Computers in biology and medicine
Published Date: Jun 1, 2025

Abstract

INTRODUCTION: Hip fractures, particularly among the elderly, impose a significant public health burden due to increased morbidity and mortality. Femoral neck fractures, commonly resulting from low-energy falls, can lead to severe complications such as avascular necrosis, and often necessitate total hip arthroplasty. This study harnesses AI to enhance musculoskeletal assessments by performing automatic muscle segmentation on whole thigh CT scans and detailed cortical measurements using the StradView program. The primary aim is to improve the prediction and prevention of severe femoral neck fractures, ultimately supporting more effective rehabilitation and treatment strategies.

Authors

  • Jun-Il Yoo
    Department of Orthopedic Surgery, Inha University Hospital, Inha University College of Medicine, Incheon, South Korea.
  • Hyeon Su Kim
    Department of Orthopedic Surgery, Inha University Hospital, Inha University College of Medicine, Incheon, South Korea.
  • Deog-Yoon Kim
    Department of Nuclear Medicine, Kyung Hee University Hospital, Kyung Hee University School of Medicine, Seoul, South Korea.
  • Dong-Won Byun
    Division of Endocrinology and Metabolism, Department of Internal Medicine, Soonchunhyang University Hospital, Soonchunhyang University College of Medicine, Seoul, South Korea.
  • Yong-Chan Ha
    Department of Orthopaedic Surgery, Seoul Bumin Hospital, Seoul, South Korea.
  • Yong-Kyun Lee
    Department of Orthopaedic Surgery, Seoul National University Bundang Hospital, Seongnam, South Korea.

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