Conference PaperPDF Available
11th World Congress on Computational Mechanics (WCCM XI)
5th European Conference on Computational Mechanics (ECCM V)
6th European Conference on Computational Fluid Dynamics (ECFD VI)
July 20–25, 2014, Barcelona, Spain
OPTIMIZED PATIENT–SPECIFIC IMPLANTS
Michael Roland1, Tim Dahmen2, Thorsten Tjardes3, Robin Otchwemah3,
Philipp Slusalleck2and Stefan Diebels1
1Saarland University, Chair of Applied Mechanics, Campus A4 2, 66123 Saarbr¨ucken,
m.roland@mx.uni-saarland.de and s.diebels@mx.uni-ssarland.de
2DFKI GmbH, Agents and Simulated Reality, Campus D3 2, 66123 Saarbr¨ucken,
Tim.Dahmen@dfki.de and Philipp.Slusalleck@dfki.de
3Kliniken der Stadt K¨oln gGmbH, Neufelder Strae 34, 51067 K¨oln, ttjardes@me.com and
robin.otchwemah@freenet.de
Key words: patient–specific implants, segementation, volume mesh generation, finite
element simulation
Today fractures of the long bones, i.e. tibia or femur, are treated surgically. This means
that implants are used that allow early post operative weight bearing and physiotherapy
of the injured limb. However, the implants currently used in orthopaedic trauma surgery
do not account for individual specificities of the patient and of the fracture.
A personalized approach to fracture therapy necessitates the integration of knowledge
and techniques from mechanics, orthopaedic trauma surgery, computer science and image
processing. Here, we will merge the relevant knowledge from these disciplines into an
integrated workflow.
Routinely acquired computed tomography data sets are subjected to an automated seg-
mentation procedure using edge–enhancing nonlinear anisotropic diffusion (EED) filter-
ing. Thereafter, a volume mesh is generated using an adaptive, octree based scheme that
allows a locally heterogeneous resolution exploiting the concept of hanging nodes.
Mechanical FEM simulations are used to compute the stresses and strains arising in the
implant and the bone structure. Based on the results of the FEM simulations, new
therapeutic approaches for revision surgery are developed. With the help of optimisation
algorithms, a blue print of the mechanically optimal configuration of the cancellous bone
transplantation is computed to achieve fracture fusion.
Using these results the surgeon will be able to use a targeted approach with surgical inter-
vention only in those areas of the non union where load peaks of the bone–implant system
occur. With iterative automated optimisations and mechanical simulations we generate
also an patient specific implant model. The process integrates the biomechanical needs,
M. Roland, T. Dahmen, T. Tjardes, R. Otchwemah, P.Slusalleck and S. Diebels
i.e. optimal neutralisation of torsion loads, and the anatomical needs, i.e. minimally
invasive surgical technique, into the implant.
The resulting FEM model represents the individual patient fracture including the implant
that have been used to fix the fracture initially. This model will support the surgeon in
answering the key questions of a personalised therapeutic concept:
How much fusion area is necessary for the fracture?
Is the implant suitable for the fracture?
Does the patient need a customised implant?
Figure 1: Individual slice of the original computed tomography image (left); results of the segmentation
process of the same slice (middle); cut through the octree based volume mesh with hanging nodes structure
(right).
Figure 2: patient–specific volume mesh with implant and fracture area (left); von Mises stress of the
bone–implant system (right).
REFERENCES
[1] J. Weickert. Anisotropic Diffusion in Image Processing. Teubner, 2005.
[2] J. M¨obius and L. Kobbelt. OpenFlipper: An Open Source Geometry Processing and
Rendering Framework. volume 6920 of Lecture Notes in Computer Science, Springer
Berlin / Heidelberg, 2012.
2
ResearchGate has not been able to resolve any citations for this publication.
Thesis
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