Evaluation and validation of 2D biomechanical models of the knee for radiograph-based preoperative planning in total knee arthroplasty.

Thorough preoperative planning in total knee arthroplasty is essential to reduce implant failure by proper implant sizing and alignment. The "gold standard" in conventional preoperative planning is based on anterior-posterior long-leg radiographs. However, the coronal component alignment i...

Full description

Bibliographic Details
Main Authors: Malte Asseln, Jörg Eschweiler, Adam Trepczynski, Philipp Damm, Klaus Radermacher
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2020-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0227272
Description
Summary:Thorough preoperative planning in total knee arthroplasty is essential to reduce implant failure by proper implant sizing and alignment. The "gold standard" in conventional preoperative planning is based on anterior-posterior long-leg radiographs. However, the coronal component alignment is still an open discussion in literature, since studies have reported contradictory outcomes on survivorship, indicating that optimal individual alignment goals still need to be defined. Two-dimensional biomechanical models of the knee have the potential to predict joint forces and, therefore, objectify therapy planning. Previously published two-dimensional biomechanical models were evaluated and validated for the first time in this study by comparison of model predictions to corresponding in vivo measurements obtained from telemetric implants for a one- and two-leg stance. Model input parameters were acquired from weight-bearing anterior-posterior long-leg radiographs and statistical assumptions for patient-specific model adaptation. The overall time from initialization to load prediction was in the range of 7-8 minutes per patient for all models. However, no model could accurately predict the correct trend of knee joint forces over patients. Two dimensional biomechanical models of the knee have the potential to improve preoperative planning in total knee arthroplasty by providing additional individual biomechanical information to the surgeon. Although integration into the clinical workflow might be performed with acceptable costs, the models' accuracy is insufficient for the moment. Future work is needed for model optimization and more sophisticated modelling approaches.
ISSN:1932-6203