Theoretical and algorithmic concepts for description of demand-adaptive bone growth
|Bearbeitung:||Prof.Dr.-Ing. Udo Nackenhorst, M.Sc. Andre Lutz, ext. B.Ebbecke|
|Förderung durch:||This work is in cooperation with the MHH (Medizinische Hochschule Hannover)|
Hip-joint endoprosthetics has been developed to standard surgery. However, there is a great variety of implant designs and surgery techniques and the question for an optimal solution is still not answered yet. Probably this question has to be answered individually from patient to patient. Computational methods have been developed for the prediction of the mechanical bio-compatibility of endoprostheses. Besides the stress-analysis of implant and the bone remodelling caused from changing mechanical stimulation of bone tissue is simulated. This approach enables studies of the bio-mechanical compatibility of different prosthesis designs under individual constitution and mobility. The 3D bone is given by [Viceconti 1996] and the muscle attachments can be found in [Viceconti 2003]. The first step of the computation treats the optimization of the boundary conditions (statically equivalent loads) in the sense that a bio-mechanical equilibrium state is found for a physiologically density distribution. [Ebbecke and Nackenhorst 2005], fig. 1. The bone mass density distribution for an equilibrated femur model is depicted in fig. 2 and fig. 3. The comparison with CT-data and radiograph matches well. The hollow bone as well as the characteristic trabecular structure of the cancellous proximal femur is approximated well by the finite element model. The bone remodelling caused from prostheses are shown in fig. 4 to fig. 6. These investigations of prosthesis are in close cooperations with the Medical Hight School of Hannover (MHH). The results from numerical simulations are in good agreement with clinical observations.
Figure 1: Starting with a homogenious density and the static equivalent load case to compute the mass density of the 3d healty femur.
Figure 2: Computed mass density distribution (left) in comparison with a radiograph.
Figure 3: Computed mass density distribution (left) in comparison with a CT data set mapped onto finite elements.
Figure 4: radiograph in comparison with computed mass density distribution: Spiron Prosthesis, postoperativ left site, long therm effect right site.
Figure 5: Bone remodelling caused from the Zweymueller-prosthesis.
Figure 6: Bone remodelling caused from the Spiron-prosthesis