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Using musculoskeletal models to estimate in vivo total knee replacement kinematics and loads: effect of differences between models

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Title: Using musculoskeletal models to estimate in vivo total knee replacement kinematics and loads: effect of differences between models
Authors: Curreli, C
Di Puccio, F
Davico, G
Modenese, L
Viceconti, M
Item Type: Journal Article
Abstract: Total knee replacement (TKR) is one of the most performed orthopedic surgeries to treat knee joint diseases in the elderly population. Although the survivorship of knee implants may extend beyond two decades, the poor outcome rate remains considerable. A recent computational approach used to better understand failure modes and improve TKR outcomes is based on the combination of musculoskeletal (MSK) and finite element models. This combined multiscale modeling approach is a promising strategy in the field of computational biomechanics; however, some critical aspects need to be investigated. In particular, the identification and quantification of the uncertainties related to the boundary conditions used as inputs to the finite element model due to a different definition of the MSK model are crucial. Therefore, the aim of this study is to investigate this problem, which is relevant for the model credibility assessment process. Three different generic MSK models available in the OpenSim platform were used to simulate gait, based on the experimental data from the fifth edition of the “Grand Challenge Competitions to Predict in vivo Knee Loads.” The outputs of the MSK analyses were compared in terms of relative kinematics of the knee implant components and joint reaction (JR) forces and moments acting on the tibial insert. Additionally, the estimated knee JRs were compared with those measured by the instrumented knee implant so that the “global goodness of fit” was quantified for each model. Our results indicated that the different kinematic definitions of the knee joint and the muscle model implemented in the different MSK models influenced both the motion and the load history of the artificial joint. This study demonstrates the importance of examining the influence of the model assumptions on the output results and represents the first step for future studies that will investigate how the uncertainties in the MSK models propagate on disease-specific finite element model results.
Issue Date: 28-Jul-2021
Date of Acceptance: 23-Jun-2021
URI: http://hdl.handle.net/10044/1/91179
DOI: 10.3389/fbioe.2021.703508
ISSN: 2296-4185
Publisher: Frontiers Media
Start Page: 1
End Page: 10
Journal / Book Title: Frontiers in Bioengineering and Biotechnology
Volume: 9
Copyright Statement: © 2021 Curreli, Di Puccio, Davico, Modenese and Viceconti. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Keywords: 0699 Other Biological Sciences
0903 Biomedical Engineering
1004 Medical Biotechnology
Publication Status: Published
Open Access location: https://doi.org/10.3389/fbioe.2021.703508
Online Publication Date: 2021-07-28
Appears in Collections:Civil and Environmental Engineering

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