Standardized Fixation Zones and Cone Assessments for Revision Total Knee Arthroplasty Using Deep Learning.

Journal: The Journal of arthroplasty
PMID: 36791885

Abstract

BACKGROUND: Achieving adequate implant fixation is critical to optimize survivorship and postoperative outcomes after revision total knee arthroplasty (rTKA). Three anatomical zones (ie, epiphysis, metaphysis, and diaphysis) have been proposed to assess fixation, but are not well-defined. The purpose of the study was to develop a deep learning workflow capable of automatically delineating rTKA zones and cone placements in a standardized way on postoperative radiographs.

Authors

  • Seong J Jang
    Department of Orthopaedic Surgery, Adult Reconstruction and Joint Replacement Service, New York, New York, USA.
  • Dimitrios A Flevas
    Stavros Niarchos Foundation Complex Joint Reconstruction Center, Hospital for Special Surgery, New York, New York.
  • Kyle N Kunze
    Department of Orthopedic Surgery, Hospital for Special Surgery, New York, NY, USA.
  • Christopher G Anderson
    Stavros Niarchos Foundation Complex Joint Reconstruction Center, Hospital for Special Surgery, New York, New York.
  • Mark A Fontana
    Weill Cornell College of Medicine, New York, New York; Center for Analytics, Modeling, and Performance, Hospital for Special Surgery, New York, New York.
  • Friedrich Boettner
    Department of Orthopaedic Surgery, Hospital for Special Surgery, New York, NY.
  • Thomas P Sculco
    Department of Orthopaedic Surgery, Hospital for Special Surgery, New York, NY.
  • Andrea Baldini
    Institute for Complex Arthroplasty and Revisions (ICAR), Villa Ulivella Clinic, Florence, Italy.
  • Peter K Sculco
    The Stavros Niarchos Foundation Complex Joint Reconstruction Center, Department of Orthopaedic Surgery, Hospital for Special Surgery, Washington, District of Columbia, USA.

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