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Anzors Sept 2012
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Anzors Sept 2012

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Moving Towards Population Based Computational Modelling of Total Joint Replacement …

Moving Towards Population Based Computational Modelling of Total Joint Replacement

ANZOR\'s 2012 keynote lecture slides.

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Transcript

  • 1. Moving Towards Population Based Computational Modelling of Total Joint Replacement Professor Mark Taylor
  • 2. Total Joint Replacement Excellent survivorship at 10 years New designs regularly enter the market Increasingly difficult to assess whether design changes will improve performance
  • 3. Sources of Variability The Patient Surgery •Experience •Personal preference •Age/activity level •Alignment•Bone quality/geometry •Surgical approach •Soft tissue quality •Body weight
  • 4. Femoral Head Resurfacing Initial early-mid term clinical results impressiveHowever: High incidence of femoral neck fracture in first 6 months 5 fold increase in revision rate in small diameter heads as compared to large diameter heads1 http://www.orthoassociates.com1Shimmin et al, JBJS(Br), 2010
  • 5. FE analysis of theresurfaced femoral head:Modelling of an individual patient
  • 6. Subject specific models3x BW 1x BW
  • 7. Subject specific models- Significant strain shielding within the head- Increase in strain on the superior aspect of the neck- Peak strain occurs around the inferior aspect of the neck
  • 8. Comparison of a small vs. large femur Small femur Large femur
  • 9. Typical FE analysis of the resurfaced femoral head Typically model the “average” patient Ideal implantation, single size Parametric studies on limited number of variables Attempt to extrapolate results to larger patient population Patient variability swamps differences?
  • 10. Typical FE analysis of the resurfaced femoral head Typically model the “average” patient Ideal implantation, single size will not predict small percentage of failures This Parametric studies on limited Radical re-think of pre-clinical testing needed! number of variables Attempt to extrapolate results to larger patient population Patient variability swamps differences?
  • 11. FE analysis of theresurfaced femoral head: Modelling of 10’s of patients
  • 12. The brute force approach - Model multiple femurs from a range of patients - Examine mean, standard xN deviation, range…. - Perform statistical tests when comparing designs Radcliffe et al, Clin. Biomech., 2007
  • 13. The brute force approach Patient Data 200 45 180 40 160Height (cm) / Weight 35 140 30 120 25 (kg) BMI 100 20 80 15 60 40 10 20 5 0 0 Hip 609 Hip 613 Hip 628 Hip 631 Hip 636 Hip 608 Hip 626 Hip 607 Hip 625 Hip 612 Hip 610 Hip 630 Hip 614 Hip 635 Hip 627 Hip 634 Hip Number Height (cm) Weight (kg) BMI Weight: 95.312 kg (54 – 136) Height: 1.76 m (1.57 – 1.88) Age: 40.75 years (18 – 57) Gender: male dominated
  • 14. Influence of cementing the stem N=16Radcliffe et al, PhD Thesis, 2007
  • 15. Influence of cementing the stem N=16Radcliffe et al, PhD Thesis, 2007
  • 16. Influence of implant position N=16Radcliffe et al, PhD Thesis, 2007
  • 17. The brute force approach N=16 - Very labour intensive -Impractical to examine 100’s of femurs - Still difficult to compare differences across sizesRadcliffe et al, PhD Thesis, 2007
  • 18. FE analysis of theresurfaced femoral head: Modelling of 100’s of patients
  • 19. Principal Component Analysis Construction of a Statistical Model
  • 20. Statistical Shape and Intensity Model (n=46) Mode 1 – Scaling of morphology and properties Mode 2 – Scaling and neck anteversion Model 3 – Neck anteversion and head/neck ratio Bryan et al, Med. Eng. Phys., 2010
  • 21. Generation of New Instances• Using governing PCA equation it is possible to generate new, realistic femur models from the variations captured by the model
  • 22. Automated ImplantationAutomated Implantation – Run through MatlabHypermesh (Booleans) -> Ansys ICEM (meshing)-> Marc MSC(FE) Fully scripted from statistical model to FE results
  • 23. Representative examples from N=400ModulusModulus Strain
  • 24. Results (N=400)Bryan et al, J. Biomech., 2012
  • 25. Results (N=400)Bryan et al, J. Biomech., 2012
  • 26. Results - Comparison between head sizes N=20 N=25Small diameter heads show: Bryan et al, J. Biomech., 2012- Increased strain shielding- Elevated strains at the superior femoral neck
  • 27. Statistical Shape and Intensity Model• Developed methodology has significant potential for improving preclinical assessment• There are issues: • Statistical shape and intensity models only as good as the training set • Robust automation • Forces may need to link with musculoskeletal models • Verification/validation
  • 28. Future directions……. Drive for ‘real time’ toolsFemoral neck fracture Diaphyseal fracture reduction(KAIST, Korea) Implant Positioning (Imperial College, UK) (Brainlab, Germany)
  • 29. Rapid patient specific modelling……… Surrogate model FR = axb + cyd +……100’s to 1000sof simulations
  • 30. FE simulation Surrogate modelApprox. 300 secs Approx. 0.2 secs
  • 31. Acknowledgements Dr Rebecca Bryan Dr Ian Radcliffe Dr Mike StricklandDr Francis Galloway Dr Martin Browne Dr Prasanth Nair

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