Artificial Intelligence Approach in Hip Prosthesis Identification and Addressing Radiographic Outcome Measures.

Journal: Arthroplasty today
Published Date: Jun 3, 2025

Abstract

BACKGROUND: Radiographic assessment is crucial for the success of a hip arthroplasty procedure as a correctly positioned prosthesis indicates favorable long-term outcomes. This project aims to develop a novel artificial intelligence (AI)-based method that can (1) automatically identify the presence of a hip resurfacing prosthesis in radiographs and (2) calculate the radiographic neck-shaft angle (NSA) of the prosthesis from 2-dimensional plane images using both anterior-posterior (AP) and lateral radiographs with high accuracy.

Authors

  • Omar Musbahi
    Department of Surgery and Cancer, Imperial College London, White City Campus, London W12 0BZ, United Kingdom.
  • Savvas Hadjixenophontos
    MSk Lab, White City Campus, Imperial College London, London, UK.
  • Saran S Gill
    Imperial Brain & Spine Initiative, Imperial College London, London, UK.
  • Iris Soteriou
    MSk Lab, White City Campus, Imperial College London, London, UK.
  • Kyriacos Pouris
    MSk Lab, White City Campus, Imperial College London, London, UK.
  • Takuro Ueno
    Department of Orthopaedic Surgery, Toyama Prefectural Central Hospital, Toyama, Japan.
  • Justin P Cobb
    MSk Lab, Imperial College London, Sir Michael Uren Hub, 86 Wood Lane, London, W12 0BZ, UK.

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