Computational efficient method for assessing the influence of surgical variability on primary stability of a contemporary femoral stem in a cohort of subjects

  • Rami M. A. Al-DiriniEmail author
  • Saulo Martelli
  • Mark Taylor
Original Paper


Finite element (FE) modelling can provide detailed information on implant stability; however, its computational cost limits the possibility of completing large numerical analyses into the effect of surgical variability in a cohort of patients. The aim of this study was to develop an efficient surrogate model for a cohort of patients implanted using a common cementless hip stem. FE models of implanted femora were generated from computed tomography images for 20 femora (11 males, 9 females; 50–80 years; 52–116 kg). An automated pipeline generated FE models for 61 different unique scenarios that span the femur-specific range of implant positions. Peak hip contact and muscle forces for stair climbing were scaled to the donors’ body weight and applied to the models. A cohort-specific surrogate for implant micromotion was constructed from Gaussian process models trained using data from FE simulations representing the median and extreme implant positions for each femur. A convergence study confirmed suitability of the sampling method for cohorts with 10+ femora. The final model was trained using data from the 20 femora. Results showed very good agreement between the FE and the surrogate predictions for a total of 1036 alignment scenarios [root mean squared error (RMSE) < 20 µm; \(R_{\text{validation}}^{2}\) = 0.81]. The total time required for the surrogate model to predict the micromotion range associated with surgical variability was approximately one-eighth of the corresponding full FE analysis. This confirms that the developed model is an accurate yet computationally cheaper alternative to full FE analysis when studying the implant robustness in a cohort of 10+ femora.


Primary stability Micromotion Efficient models Machine learning 



The authors are grateful to the staff of the Mortuary and the Donor Tissue Bank at the Victorian Institute of Forensic Medicine Australia for their assistance in collecting the material upon which this study is based. The authors are also grateful to the families of the donors who gave permission or the collection of the material expressly for research. The Australian Research Council (DP180103146, FT180100338) is also gratefully acknowledged.


This study was part of a project funded by the Australian Research Council (DP180103146, FT180100338), with partial funding from DePuy Synthes.

Compliance with ethical standards

Conflict of interest

Prof. Taylor and Dr. Martelli are chief investigators named on the ARC Grants. Dr. Al-Dirini was employed in these projects.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Rami M. A. Al-Dirini
    • 1
    Email author
  • Saulo Martelli
    • 1
  • Mark Taylor
    • 1
  1. 1.Medical Devices Research Institute, College of Science and EngineeringFlinders UniversityAdelaideAustralia

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