Probabilistic analysis of an uncemented total hip replacement
Probabilistic analysis of an uncemented total hip replacement
This paper describes the application of probabilistic design methods to the analysis of the behaviour of an uncemented total hip replacement femoral component implanted in a proximal femur. Probabilistic methods allow variations in factors which control the behaviour of the implanted femur (the input parameters) to be taken into account in determining the performance of the construct. Monte Carlo sampling techniques were applied and the performance indicator was the maximum strain in the bone. The random input parameters were the joint load, the angle of the applied load and the material properties of the bone and the implant. Two Monte Carlo based simulations were applied, direct sampling and latin hypercube sampling. The results showed that the convergence of the mean value of the maximum strain improved gradually as a function of the number of simulations and it stabilised around a value of 0.008 after 6,200 simulations. A similar trend was observed for the cumulative distribution function of the output. The strain output was most sensitive to the bone stiffness, followed very closely by the magnitude of the applied load. The application of latin hypercube sampling with 1,000 simulations gave similar results to direct sampling with 10,000 simulations in a much reduced time. The results suggested that the number of simulations and the selection of parameters and models are important for the reliability of both the probability values and the sensitivity analyses.
470-476
Dopico-Gonzalez, Carolina
dfe0b5c7-9362-476b-bb32-2444c7b6492f
New, Andrew M.
d2fbaf80-3abd-4bc5-ae36-9c77dfdde0d6
Browne, Martin
6578cc37-7bd6-43b9-ae5c-77ccb7726397
May 2009
Dopico-Gonzalez, Carolina
dfe0b5c7-9362-476b-bb32-2444c7b6492f
New, Andrew M.
d2fbaf80-3abd-4bc5-ae36-9c77dfdde0d6
Browne, Martin
6578cc37-7bd6-43b9-ae5c-77ccb7726397
Dopico-Gonzalez, Carolina, New, Andrew M. and Browne, Martin
(2009)
Probabilistic analysis of an uncemented total hip replacement.
Medical Engineering & Physics, 31 (4), .
(doi:10.1016/j.medengphy.2009.01.002).
Abstract
This paper describes the application of probabilistic design methods to the analysis of the behaviour of an uncemented total hip replacement femoral component implanted in a proximal femur. Probabilistic methods allow variations in factors which control the behaviour of the implanted femur (the input parameters) to be taken into account in determining the performance of the construct. Monte Carlo sampling techniques were applied and the performance indicator was the maximum strain in the bone. The random input parameters were the joint load, the angle of the applied load and the material properties of the bone and the implant. Two Monte Carlo based simulations were applied, direct sampling and latin hypercube sampling. The results showed that the convergence of the mean value of the maximum strain improved gradually as a function of the number of simulations and it stabilised around a value of 0.008 after 6,200 simulations. A similar trend was observed for the cumulative distribution function of the output. The strain output was most sensitive to the bone stiffness, followed very closely by the magnitude of the applied load. The application of latin hypercube sampling with 1,000 simulations gave similar results to direct sampling with 10,000 simulations in a much reduced time. The results suggested that the number of simulations and the selection of parameters and models are important for the reliability of both the probability values and the sensitivity analyses.
Text
final_proof.pdf
- Version of Record
Restricted to Repository staff only
Request a copy
More information
Published date: May 2009
Identifiers
Local EPrints ID: 143373
URI: http://eprints.soton.ac.uk/id/eprint/143373
ISSN: 1350-4533
PURE UUID: fabdab55-f700-41c2-8674-16927dcc242c
Catalogue record
Date deposited: 08 Apr 2010 14:30
Last modified: 14 Mar 2024 02:39
Export record
Altmetrics
Contributors
Author:
Carolina Dopico-Gonzalez
Author:
Andrew M. New
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics