In-silico wear prediction for knee replacements - methodology and corroboration
Strickland, M.A. and Taylor, M. (2009) In-silico wear prediction for knee replacements - methodology and corroboration. Journal of Biomechanics, 42, (10), 1469-1474. (doi:10.1016/j.jbiomech.2009.04.022). (PMID:19464013).
PDF (Post-reviewer, pre-proofing version of J.Biomechanics article)
- Accepted Manuscript
The capability to predict in-vivo wear of knee replacements is a valuable pre-clinical analysis tool for implant designers. Traditionally, time-consuming experimental tests provided the principal means of investigating wear. Today, computational models offer an alternative. However, the validity of these models has not been demonstrated across a range of designs and test conditions, and several different formulas are in contention for estimating wear rates, limiting confidence in the predictive power of these in-silico models.
This study collates and retrospectively simulates a wide range of experimental wear tests using fast rigid-body computational models with extant wear prediction algorithms, to assess the performance of current in-silico wear prediction tools.
The number of tests corroborated gives a broader, more general assessment of the performance of these wear-prediction tools, and provides better estimates of the wear ‘constants’ used in computational models. High-speed rigid-body modelling allows a range of alternative algorithms to be evaluated. Whilst most cross-shear (CS)-based models perform comparably, the ‘A/A+B’ wear model appears to offer the best predictive power amongst existing wear algorithms. However, the range and variability of experimental data leaves considerable uncertainty in the results. More experimental data with reduced variability and more detailed reporting of studies will be necessary to corroborate these models with greater confidence. With simulation times reduced to only a few minutes, these models are ideally suited to large-volume ‘design of experiment’ or probabilistic studies (which are essential if pre-clinical assessment tools are to begin addressing the degree of variation observed clinically and in explanted components)
|Keywords:||knee, tkr, wear, mechanics, computational, experimental, validation, corroboration|
|Subjects:||R Medicine > RZ Other systems of medicine
T Technology > TJ Mechanical engineering and machinery
|Divisions:||University Structure - Pre August 2011 > School of Engineering Sciences > Bioengineering Sciences
Faculty of Engineering and the Environment > Engineering Sciences > Bioengineering Research Group
|Date Deposited:||20 Jan 2010|
|Last Modified:||06 Aug 2015 02:56|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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