Reference : Inverse Finite Element Modeling for Characterization of Local Elastic Properties in I...
Scientific journals : Article
Engineering, computing & technology : Multidisciplinary, general & others
http://hdl.handle.net/2268/183019
Inverse Finite Element Modeling for Characterization of Local Elastic Properties in Image-Guided Failure Assessment of Human Trabecular Bone
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Zwahlen, Alexander [Muller, R (Reprint Author), ETH, Inst Biomech, Vladimir Prelog Weg 3, CH-8093 Zurich, Switzerland. Zwahlen, Alexander]
Christen, David [Christen, David]
Ruffoni, Davide mailto [Université de Liège > Département d'aérospatiale et mécanique > Mécanique des matériaux biologiques et bioinspirés >]
Schneider, Philipp [Schneider, Philipp]
Schmoelz, Werner [Mueller, Ralph, ETH, Inst Biomech, CH-8093 Zurich, Switzerland. Schmoelz, Werner, Med Univ Innsbruck, Dept Trauma Surg, A-6020 Innsbruck, Austria.]
Mueller, Ralph [> >]
2015
JOURNAL OF BIOMECHANICAL ENGINEERING-TRANSACTIONS OF THE ASME
ASME
137
1
Yes (verified by ORBi)
International
0148-0731
TWO PARK AVE, NEW YORK, NY 10016-5990 USA
[en] The local interpretation of microfinite element (mu FE) simulations plays a pivotal role for studying bone structure-function relationships such as failure processes and bone remodeling. In the past mu FE simulations have been successfully validated on the apparent level however, at the tissue level validations are sparse and less promising. Furthermore, intratrabecular heterogeneity of the material properties has been shown by experimental studies. We proposed an inverse mu FE algorithm that iteratively changes the tissue level Young's moduli such that the mu FE simulation matches the experimental strain measurements. The algorithm is setup as a feedback loop where the modulus is iteratively adapted until the simulated strain matches the experimental strain. The experimental strain of human trabecular bone specimens was calculated from time-lapsed images that were gained by combining mechanical testing and synchrotron radiation microcomputed tomography (SR mu CT). The inverse mu FE algorithm was able to iterate the heterogeneous distribution of moduli such that the resulting mu FE simulations matched artificially generated and experimentally measured strains.
http://hdl.handle.net/2268/183019
10.1115/1.4028991
Article

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