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Activity and Loading Influence the Predicted Bone Remodeling around Cemented Hip Replacements

Activity and Loading Influence the Predicted Bone Remodeling around Cemented Hip Replacements
Activity and Loading Influence the Predicted Bone Remodeling around Cemented Hip Replacements
Periprosthetic bone remodeling is frequently observed after total hip replacement. Reduced bone density increases the implant and bone fracture risk, and a gross loss of bone density challenges fixation in subsequent revision surgery. Computational approaches allow bone remodelling to be predicted in agreement with the general clinical observations of proximal resorption and distal hypertrophy. However, these models do not reproduce other clinically observed bone density trends, including faster stabilising mid-stem density losses, and loss-recovery trends around the distal stem. These may resemble trends in postoperative joint loading and activity, during recovery and rehabilitation, but the established remodelling prediction approach is often used with identical pre- and postoperative load and activity assumptions. Therefore, this study aimed to evaluate the influence of pre- to postoperative changes in activity and loading upon the predicted progression of remodeling.

A strain-adaptive finite element model of a femur implanted with a cemented Charnley stem was generated, to predict 60 months of periprosthetic remodeling. A control set of model input data assumed identical pre- and postoperative loading and activity, and was compared to the results obtained from another set of inputs with three varying activity and load profiles. These represented activity changes during rehabilitation for weak, intermediate and strong recoveries, and pre- to postoperative joint force changes due to hip centre translation and the use of walking aids. Predicted temporal bone density change trends were analysed, and absolute bone density changes and the time to homeostasis were inspected, alongside virtual x-rays.

The predicted periprosthetic bone density changes obtained using modified loading inputs demonstrated closer agreement with clinical measurements than the control. The modified inputs also predicted the clinically observed temporal density change trends, but still under-estimated density loss during the first 3 postoperative months. This suggests that other mechanobiological factors have an influence, including the repair of surgical micro-fractures, thermal damage and vascular interruption.

This study demonstrates the importance of accounting for pre- to postoperative changes in joint loading and patient activity when predicting periprosthetic bone remodeling. The study’s main weakness is the use of an individual patient model; computational expense is a limitation of all previously reported iterative remodeling analysis studies. However, this model showed sufficient computational efficiency for application in probabilistic analysis, and is an easily implemented modification of a well-established technique.
0148-0731
Dickinson, A.S.
10151972-c1b5-4f7d-bc12-6482b5870cad
Dickinson, A.S.
10151972-c1b5-4f7d-bc12-6482b5870cad

Dickinson, A.S. (2014) Activity and Loading Influence the Predicted Bone Remodeling around Cemented Hip Replacements. Journal of Biomechanical Engineering, 136 (4). (doi:10.1115/1.4026256).

Record type: Article

Abstract

Periprosthetic bone remodeling is frequently observed after total hip replacement. Reduced bone density increases the implant and bone fracture risk, and a gross loss of bone density challenges fixation in subsequent revision surgery. Computational approaches allow bone remodelling to be predicted in agreement with the general clinical observations of proximal resorption and distal hypertrophy. However, these models do not reproduce other clinically observed bone density trends, including faster stabilising mid-stem density losses, and loss-recovery trends around the distal stem. These may resemble trends in postoperative joint loading and activity, during recovery and rehabilitation, but the established remodelling prediction approach is often used with identical pre- and postoperative load and activity assumptions. Therefore, this study aimed to evaluate the influence of pre- to postoperative changes in activity and loading upon the predicted progression of remodeling.

A strain-adaptive finite element model of a femur implanted with a cemented Charnley stem was generated, to predict 60 months of periprosthetic remodeling. A control set of model input data assumed identical pre- and postoperative loading and activity, and was compared to the results obtained from another set of inputs with three varying activity and load profiles. These represented activity changes during rehabilitation for weak, intermediate and strong recoveries, and pre- to postoperative joint force changes due to hip centre translation and the use of walking aids. Predicted temporal bone density change trends were analysed, and absolute bone density changes and the time to homeostasis were inspected, alongside virtual x-rays.

The predicted periprosthetic bone density changes obtained using modified loading inputs demonstrated closer agreement with clinical measurements than the control. The modified inputs also predicted the clinically observed temporal density change trends, but still under-estimated density loss during the first 3 postoperative months. This suggests that other mechanobiological factors have an influence, including the repair of surgical micro-fractures, thermal damage and vascular interruption.

This study demonstrates the importance of accounting for pre- to postoperative changes in joint loading and patient activity when predicting periprosthetic bone remodeling. The study’s main weakness is the use of an individual patient model; computational expense is a limitation of all previously reported iterative remodeling analysis studies. However, this model showed sufficient computational efficiency for application in probabilistic analysis, and is an easily implemented modification of a well-established technique.

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More information

Accepted/In Press date: 9 December 2013
Published date: 24 March 2014
Organisations: Bioengineering Group

Identifiers

Local EPrints ID: 360492
URI: http://eprints.soton.ac.uk/id/eprint/360492
ISSN: 0148-0731
PURE UUID: 1ff7b864-4620-4d84-83fd-cdc8557356cb
ORCID for A.S. Dickinson: ORCID iD orcid.org/0000-0002-9647-1944

Catalogue record

Date deposited: 11 Dec 2013 16:35
Last modified: 18 Feb 2021 17:08

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