Artificial Intelligence to Identify Arthroplasty Implants From Radiographs of the Hip.

Journal: The Journal of arthroplasty
Published Date: Nov 16, 2020

Abstract

BACKGROUND: The surgical management of complications surrounding patients who have undergone hip arthroplasty necessitates accurate identification of the femoral implant manufacturer and model. Failure to do so risks delays in care, increased morbidity, and further economic burden. Because few arthroplasty experts can confidently classify implants using plain radiographs, automated image processing using deep learning for implant identification may offer an opportunity to improve the value of care rendered.

Authors

  • Jaret M Karnuta
    Department of Orthopedic Surgery, Cleveland Clinic, Cleveland, OH.
  • Heather S Haeberle
    Department of Orthopaedic Surgery, Baylor College of Medicine, Houston, TX.
  • Bryan C Luu
    Orthopaedic Machine Learning Lab, Cleveland Clinic, Cleveland, Ohio, U.S.A.; Department of Orthopaedic Surgery, Baylor College of Medicine, Houston, Texas, U.S.A.
  • Alexander L Roth
    Orthopaedic Machine Learning Laboratory, Cleveland Clinic, Cleveland, OH.
  • Robert M Molloy
    Orthopaedic Machine Learning Laboratory, Cleveland Clinic, Cleveland, OH.
  • Lukas M Nystrom
    Orthopaedic Machine Learning Laboratory, Cleveland Clinic, Cleveland, OH.
  • Nicolas S Piuzzi
    Orthopaedic Machine Learning Laboratory, Cleveland Clinic, Cleveland, OH.
  • Jonathan L Schaffer
    Machine Learning Arthroplasty Lab, Cleveland Clinic, Cleveland, OH.
  • Antonia F Chen
    Department of Orthopaedic Surgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
  • Richard Iorio
    Department of Orthopaedic Surgery, Brigham & Women's Hospital, Boston, MA.
  • Viktor E Krebs
    Department of Orthopedic Surgery, Cleveland Clinic, Cleveland, OH.
  • Prem N Ramkumar
    Department of Orthopedic Surgery, Cleveland Clinic, Cleveland, OH.

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