Moving Towards Population Based Computational

Modelling of Total Joint Replacement

Professor Mark Taylor

Total Joint Replacement

Excellent survivorship at 10 years

New designs regularly enter the market

Increasingly difficult to assess whether design changes will improve performance

Sources of VariabilityThe Patient Surgery

•Age/activity level•Bone quality/geometry

•Soft tissue quality•Body weight

•Experience•Personal preference

•Alignment •Surgical approach

Femoral Head Resurfacing

Initial early-mid term clinical results impressive

However: 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.com

1Shimmin et al, JBJS(Br), 2010

FE analysis of the resurfaced femoral head:Modelling of an individual

patient

1x BW

3x BW

Subject specific models

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

Comparison of a small vs. large femur

Small femur Large femur

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?

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?

This will not predict small percentage of failuresRadical re-think of pre-clinical testing needed!

FE analysis of the resurfaced femoral head:

Modelling of 10’s of patients

x N

- Model multiple femurs from a range of patients- Examine mean, standard deviation, range….- Perform statistical tests when comparing designs

The brute force approach

Radcliffe et al, Clin. Biomech., 2007

Weight: 95.312 kg (54 – 136)Height: 1.76 m (1.57 – 1.88) Age: 40.75 years (18 – 57)Gender: male dominated

Patient Data

0

20

40

60

80

100

120

140

160

180

200

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

Hei

ght (

cm) /

Wei

ght

(kg)

0

5

10

15

20

25

30

35

40

45

BM

I

Height (cm) Weight (kg) BMI

The brute force approach

Radcliffe et al, PhD Thesis, 2007

N=16

Influence of cementing the stem

Radcliffe et al, PhD Thesis, 2007

N=16

Influence of cementing the stem

Radcliffe et al, PhD Thesis, 2007

N=16

Influence of implant position

Radcliffe et al, PhD Thesis, 2007

N=16

- Very labour intensive-Impractical to examine 100’s of

femurs- Still difficult to compare differences

across sizes

The brute force approach

FE analysis of the resurfaced femoral head:

Modelling of 100’s of patients

Construction of a Statistical ModelPrincipal Component Analysis

Bryan et al, Med. Eng. Phys., 2010

Statistical Shape and Intensity Model (n=46)

Mode 1 – Scaling of morphology and properties

Mode 2 – Scaling and neck anteversion

Model 3 – Neck anteversionand head/neck ratio

• Using governing PCA equation it is possible to generate new, realistic femur models from the variations captured by the model

Generation of New Instances

Automated Implantation – Run through MatlabHypermesh (Booleans) -> Ansys ICEM (meshing)-> Marc MSC (FE)

Fully scripted from statistical model to FE results

Automated Implantation

Representative examples from N=400

Modulus

Modulus

Strain

Results (N=400)

Bryan et al, J. Biomech., 2012

Results (N=400)

Bryan et al, J. Biomech., 2012

Results - Comparison between head sizes

Small diameter heads show:- Increased strain shielding- Elevated strains at the superior femoral neck

N=20

N=25

Bryan et al, J. Biomech., 2012

• 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

Statistical Shape and Intensity Model

Drive for ‘real time’ tools

Future directions…….

Femoral neck fracture

(KAIST, Korea) Implant Positioning (Imperial College, UK)

Diaphyseal fracture reduction

(Brainlab, Germany)

Rapid patient specific modelling………

Surrogate modelFR = axb + cyd +……

100’s to 1000s of simulations

FE simulation

Approx. 300 secs

Surrogate model

Approx. 0.2 secs

Acknowledgements

Dr Rebecca BryanDr Ian Radcliffe

Dr Mike StricklandDr Francis Galloway

Dr Martin BrowneDr Prasanth Nair