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In-silico predictions of TKR robustness to wear variability: a probabilistic cross-design comparison

In-silico predictions of TKR robustness to wear variability: a probabilistic cross-design comparison
In-silico predictions of TKR robustness to wear variability: a probabilistic cross-design comparison
Wear of TKR is a key concern for designers, but is highly variable in clinical retrievals. Conventional in-vitro knee wear simulators are limited to relatively small numbers of tests and cannot fully address this uncertainty; in-silico models can use large numbers of trials with low associated time & cost. Using probabilistic methods we can explore whether input variability (e.g. component mal-positioning) can account for the high degree of wear variability observed.

Because we are able to simulate many trials, we can also explore the predictions of different wear algorithms, and also run studies concurrently for different TKR designs, allowing us to compare implant designs and observe whether some are more robust to wear variability than others.
Strickland, Michael A.
6b639de6-cb09-4383-bf06-576eb6aef448
Taylor, Mark
e368bda3-6ca5-4178-80e9-41a689badeeb
Strickland, Michael A.
6b639de6-cb09-4383-bf06-576eb6aef448
Taylor, Mark
e368bda3-6ca5-4178-80e9-41a689badeeb

Strickland, Michael A. and Taylor, Mark (2009) In-silico predictions of TKR robustness to wear variability: a probabilistic cross-design comparison. 55th Annual Meeting of the Orthopaedic Research Society, , Las Vegas, United States. 22 - 25 Feb 2009. 1 pp .

Record type: Conference or Workshop Item (Poster)

Abstract

Wear of TKR is a key concern for designers, but is highly variable in clinical retrievals. Conventional in-vitro knee wear simulators are limited to relatively small numbers of tests and cannot fully address this uncertainty; in-silico models can use large numbers of trials with low associated time & cost. Using probabilistic methods we can explore whether input variability (e.g. component mal-positioning) can account for the high degree of wear variability observed.

Because we are able to simulate many trials, we can also explore the predictions of different wear algorithms, and also run studies concurrently for different TKR designs, allowing us to compare implant designs and observe whether some are more robust to wear variability than others.

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More information

Published date: February 2009
Venue - Dates: 55th Annual Meeting of the Orthopaedic Research Society, , Las Vegas, United States, 2009-02-22 - 2009-02-25
Organisations: Bioengineering Group

Identifiers

Local EPrints ID: 71731
URI: http://eprints.soton.ac.uk/id/eprint/71731
PURE UUID: 2c83044f-77b4-4afb-98f0-fb9d1b04094b

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Date deposited: 22 Dec 2009
Last modified: 13 Mar 2024 20:42

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Contributors

Author: Michael A. Strickland
Author: Mark Taylor

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