Journal of Orthopaedic Surgery and Research (Dec 2019)

Patient-specific instrumentation improved three-dimensional accuracy in total knee arthroplasty: a comparative radiographic analysis of 1257 total knee arthroplasties

  • Leo Pauzenberger,
  • Martin Munz,
  • Georg Brandl,
  • Julia K. Frank,
  • Philipp R. Heuberer,
  • Brenda Laky,
  • Eva Schwameis,
  • Werner Anderl

DOI
https://doi.org/10.1186/s13018-019-1465-6
Journal volume & issue
Vol. 14, no. 1
pp. 1 – 7

Abstract

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Abstract Background The purpose of this study was to compare restoration of mechanical limb alignment and three-dimensional component-positioning between conventional and patient-specific instrumentation in total knee arthroplasty. Methods Radiographic data of patients undergoing mobile-bearing total knee arthroplasty (n = 1257), using either conventional (n = 442) or patient-specific instrumentation (n = 812), were analyzed. To evaluate accuracy of axis restoration and 3D-component-positioning between conventional and patient-specific instrumentation, absolute deviations from the targeted neutral mechanical limb alignment and planned implant positions were determined. Measurements were performed on standardized coronal long-leg and sagittal knee radiographs. CT-scans were evaluated for accuracy of axial femoral implant rotation. Outliers were defined as deviations from the targeted neutral mechanical axis of > ± 3° or from the intraoperative component-positioning goals of > ± 2°. Deviations greater than ± 5° from set targets were considered to be severe outliers. Results Deviations from a neutral mechanical axis (conventional instrumentation: 2.3°± 1.7° vs. patient-specific instrumentation: 1.7°± 1.2°; p ± 5° deviation). Use of patient-specific instrumentation proved to be superior to conventional instrumentation in achieving more accurate limb alignment and 3D-component positioning, particularly regarding femoral component rotation. Furthermore, the use of patient-specific instrumentation successfully prevented severe (> 5° deviation) outliers.

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