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

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 remodeling 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 stabilizing 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 remodeling 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 center translation and the use of walking aids. Predicted temporal bone density change trends were analyzed, 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 three 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.

Activity intensity, assistive devices and joint replacement influence predicted remodelling in the proximal femur

“…Clinical DXA scanning in Furlong and Charnley stems in patients with one of each prosthesis (Chandran et al 2012) demonstrated higher BMD in all Gruen Zones except for 4, reaching significant levels in GZs 2,3,5 and 6. This is consistent with the trends predicted by the models in the present and preceding study (Dickinson 2014) (Table 2, Figure 7), in particular proximally, and the focus of distal hypertrophy predicted by the present Furlong model study can be attributed to the relatively large size implant selected for the selected bone, which fills the canal and thus leaves little space for trabecular densification in GZs 3 and 5.…”

“…In the THR model, bone remodelling alone was considered. In the RHR model, a combined periprosthetic defect healing -bone remodelling process was used (Dickinson et al 2012), which accounted for the diffusion of mesenchymal stem cells into the surgical defect created to accommodate the implant metaphyseal stem, and their subsequent differentiation and maturation in response to mechanobiological stimuli (Claes and Heigele 1999 Time-varying activity and loading factors (Fact and Fload) were applied to the remodelling stimuli to account for the described effects of walking aid use preoperatively and during rehabilitation, and gradual recovery from surgery to a higher level activity than the symptomatic preoperative reference case (Dickinson 2014). These scaling factors were applied directly to the remodelling stimulus signal, rather than to the FE model loading; the validity of this method holds while the FE model maintains approximately linear load-strain behaviour.…”

“…The methodology of the present study was based closely upon that presented for the Charnley cemented THR in preceding work (Dickinson 2014), and is summarised below.…”

“…Postoperative joint loading may also be reduced as a result of medialisation of the joint centre location by around 10% (Johnston et al 1979;Bonnin et al 2012). Activity and load scaling factors were devised to augment the established strain adaptive remodelling process, and were demonstrated to improve the predicted temporal trends and homeostatic levels of periprosthetic BMD change in response to cemented total hip replacement (Dickinson 2014). Recognising that this approach is based on a phenomenological model and literature-based adjustment factors, the present study set out to perform a further objective evaluation of its performance, using cementless total hip replacement and hip resurfacing implant case studies.…”

Full-field in vitro measurements and in silico predictions of strain shielding in the implanted femur after total hip arthroplasty

“…However, Gruen zones 4 and 5 exhibited maximum mineral recovery (~1 -5%) after 4 post-operative years. The early drop in BMD in the short postoperative term is likely to be related to surgically introduced microdamage and reduced immediate postoperative activity and joint loading, 39 and the osteoclastic remodelling transient which occurs prior to osteoblastic bone densification, which is measurable following THA. 40 In an extended follow-up study (mean duration of follow-up 22.5 years) with hydroxyapatite-coated (HAC) Furlong stems, Sandiford et al 41 reported localized bone resorption immediately under the collar (Gruen zone 7).…”