ARUP; ISBN: 978-0-9562121-5-3 - CMBBE 2012 - Cardiff University

METHODS TO ACCELERATE FINITE ELEMENT CALCULATION IN
BIOMECHANICS USING A STATISTICAL DATABASE OF PRE-
CALCULATED SIMULATIONS
M. Kistler 1 , S. Bonaretti 2 , C. Boichon 3 , M. Rochette 4 and Philippe Büchler 5
1. ABSTRACT
Finite element (FE) models developed from CT data are commonly used to evaluate the
mechanical performance of bones or orthopedic implants. However, the construction of
a numerical model for a specific patient involves many steps, which is time consuming
and limits this approach to a small number of cases. In this work, we propose to
combine a statistical model of appearance (SMA) with pre-calculated FE calculations to
reduce the time required to obtain patient-specific mechanical simulations. A SMA was
built from a training set of 72 CT of female femurs. The SMA was used to generate
1000 FE models, covering 75% of the variability of the training population. Calculated
stresses and displacements were used to build a database of numerical results. Nonlinear
iterative partial least squares method was used to predict stresses and displacements for
new bone instances without additional FE calculations. The accuracy of the predictions
was evaluated on 25 bones samples. The method failed to predict bone response if only
shape and material properties are considered. By including the loading scenario, the
predictions error was about 0.5 MPa for stresses and 0.001 mm for displacements.
2. INTRODUCTION
Over the last decades, the biomechanical community invested efforts to develop patient
specific models. A popular approach to create such models is the finite element method.
Finite element (FE) models developed from CT data are used to evaluate the mechanical
performance of bones, load transfer from implant to bone, bone-cement interface
mechanics and fracture risks [1, 2, 3]. FE models are build out of CT scan data by first
label the desired bony structure (segmentation), followed by creating a 3D
representation of the anatomical structure out of the segmented CT data and by the
creation of a finite element mesh to solve the mechanical problem. However, the
construction of these numerical models for a specific patient and solving the FE
1 MSc, Institute for Surgical Technology and Biomechanics, University of Bern, Stauffacherstrasse 78,
3014 Bern, Switzerland
2 PhD, Institute for Surgical Technology and Biomechanics, University of Bern, Stauffacherstrasse 78,
3014 Bern, Switzerland
3 Ansys Inc. 11 Avenue Albert Einstei, 69100 Villeurbanne, France
4 PhD, Ansys Inc, 11 Avenue Albert Einstein, 69100 Villeurbanne, France
5 PhD, Institute for Surgical Technology and Biomechanics, University of Bern, Stauffacherstrasse 78,
3014 Bern, Switzerland