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Standard Cruciate-Retaining Total Knee Arthroplasy Implants Can Reproduce Native Kinematics

4 pagesPublished: September 25, 2020

Abstract

Total knee arthroplasty (TKA) is a common procedure that has become the standard of treatment for severe cases of knee osteoarthritis. Biomechanics and quality of movement similar to healthy were found to improve patient-reported outcomes.
In this study, an evaluated musculoskeletal model predicted ligament, contact and muscle forces together with secondary tibiofemoral kinematics. An artificial neural network applied to the musculoskeletal model searched for the optimal implant position in a given range that will minimize the root-mean-square-error (RMSE) between post- TKA and native experimental tibiofemoral kinematics during a squat.
We found that, using a cruciate-retaining implant, native kinematics could be accurately reproduced (average RMSE 1.47 mm (± 0.89 mm) for translations and 2.89° (± 2.83°) for rotations between native and optimal TKA alignment). The required implant positions changes maximally 2.96 mm and 2.40o. This suggests that when using pre- operative planning, off-the-shelf CR implants allow for reproducing native knee kinematics post-operatively.

Keyphrases: artificial neural network, cruciate retaining, musculoskeletal model, tibiofemoral kinematics, total knee arthroplasty

In: Ferdinando Rodriguez Y Baena and Fabio Tatti (editors). CAOS 2020. The 20th Annual Meeting of the International Society for Computer Assisted Orthopaedic Surgery, vol 4, pages 61-64.

BibTeX entry
@inproceedings{CAOS2020:Standard_Cruciate_Retaining_Total,
  author    = {David Leandro Dejtiar and Laura Bartsoen and Mariska Wesseling and Roel Wirix-Speetjens and Jos Vander Sloten and Maria Angeles Perez},
  title     = {Standard Cruciate-Retaining Total Knee Arthroplasy Implants Can Reproduce Native Kinematics},
  booktitle = {CAOS 2020. The 20th Annual Meeting of the International Society for Computer Assisted Orthopaedic Surgery},
  editor    = {Ferdinando Rodriguez Y Baena and Fabio Tatti},
  series    = {EPiC Series in Health Sciences},
  volume    = {4},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-5305},
  url       = {/publications/paper/bdJg},
  doi       = {10.29007/lj2j},
  pages     = {61-64},
  year      = {2020}}
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