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Density-Based Topology Optimization for a Defined External State of Stress in Individualized Endoprosthesis

Published online by Cambridge University Press:  26 May 2022

P. Müller ,
P. C. Gembarski  and
R. Lachmayer
P. Müller*
Affiliation:
Leibniz Universität Hannover, Germany
P. C. Gembarski
Affiliation:
Leibniz Universität Hannover, Germany
R. Lachmayer
Affiliation:
Leibniz Universität Hannover, Germany
*
[email protected]

Abstract

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Endoprosthesis are exposed to the risk of aseptic loosening. The design of the prosthesis shaft to achieve physiological force application is therefore of great importance. Additive manufacturing offers the potential to fabricate highly variable topologies, but challenges the designer with a large number of design variables. In this work, a method is developed to determine an optimized density topology that approximates a given mechanical stress state in the bone after implantation. For this purpose, a topology optimization of the density distribution of the implant is performed.

Keywords

healthcare designadditive manufacturingtopological optimisationeffect engineeringindividualised hip endoprosthesis
Type
Article
Information
Proceedings of the Design Society , Volume 2: DESIGN2022 , May 2022 , pp. 533 - 542
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2022.

References

Al-Tamimi, A.A., Fernandes, P.R., Peach, C., Cooper, G., Diver, C. et al. . (2017), “Metallic bone fixation implants: a novel design approach for reducing the stress shielding phenomenon”, Virtual and Physical Prototyping, Vol. 12, Nr. 2, pp. 141–151. doi:10.1080/17452759.2017.1307769Google Scholar
Arabnejad, S. and Pasini, D., (2012), “Multiscale Design and Multiobjective Optimization of Orthopedic Hip Implants with Functionally Graded Cellular Material”, Journal of biomechanical engineering, Vol. 134, Nr. 3. 10.1115/1.4006115Google Scholar
Arabnejad, S., Johnston, B., Tanzer, M, and Pasini, Damiano (2017), “Fully porous 3D printed titanium femoral stem to reduce stress-shielding following total hip arthroplasty”, Journal of Orthopaedic Research, Vol. 35, Nr. 8, pp. 1774–1783. 10.1002/jor.23445Google ScholarPubMed
Bagge, M. (2000), “A model of bone adaptation as an optimization process”, Journal of Biomechanics, Vol. 33, Nr. 11, pp. 1349–1357. 10.1016/S0021-9290(00)00124-XGoogle Scholar
Bendsoe, M. P. and Sigmund, O. (2003), “Topology optimization: theory, methods, and applications”. Springer Science & Business Media.Google Scholar
Chang, C.L., Chen, C.S., Huang, C.H. and Hsu, M. L. (2012) “Finite element analysis of the dental implant using a topology optimization method”, Medical engineering & physics, Vol. 34, Nr. 7, pp. 999–1008. 10.1016/j.medengphy.2012.06.004CrossRefGoogle ScholarPubMed
Choy, W.J., Mobbs, R.J., Wilcox, B., Phan, S., Phan, K. et al. . (2017). “Reconstruction of thoracic spine using a personalized 3d-printed vertebral body in adolescent with t9 primary bone tumor”, World Neurosurgery 105. 10.1016/j.wneu.2017.05.133CrossRefGoogle ScholarPubMed
Deng, X., Wang, Y., Yan, J., Liu, T. and Wang, S., (2016), “Topology Optimization of Total Femur Structure: Application of Parameterized Level Set Method Under Geometric Constraints”, Journal of Mechanical Design, Vol. 138, Nr. 1. 10.1115/1.4031803Google Scholar
Grimberg, A, Jansson, V. and Lützner, J. (2020), EPRD Jahresbericht 2020. [online] EPRD Deutsche Endoprothesenregister gGmbH. Available at: https://www.eprd.de/fileadmin/user_upload/Dateien/Publikationen/Berichte/Jahresbericht2020-Web_2020-12-11_F.pdf (accessed 03.02.2022).Google Scholar
Iqbal, T., Wang, L., Li, D., Dong, E., Fan, H. et al. . (2019), “A general multi-objective topology optimization methodology developed for customized design of pelvic prostheses”, Medical engineering & physics, Vol. 69, pp. 8–16. 10.1016/j.medengphy.2019.06.008Google ScholarPubMed
Jerosch, J., Filler, T. an Koch, F.W. (2017), “Allgemeine Aspekte”, In: Jerosch, J. (eds), Kurzschaftendoprothesen an der Hüfte, Springer, Berlin, Heidelberg. 10.1007/978-3-662-52744-3_1.Google Scholar
Müller, P., Gembarski, P.C., Lachmayer, R. (2021a), “Parametric Topology Synthesis of a Short-Stem Hip Endoprosthesis Based on Patient-Specific Osteology”, In: Andersen, A.L. et al. (eds) Towards Sustainable Customization: Bridging Smart Products and Manufacturing Systems, CARV 2021, MCPC 2021, Lecture Notes in Mechanical Engineering, Springer, Cham. 10.1007/978-3-030-90700-6_76.CrossRefGoogle Scholar
Müller, P., Gembarski, P.C. and Lachmayer, R. (2021b), “Design Automation of a Patient-Specific Endoprosthesis with Multi-Objective Optimized Lattice Structures” (accepted).Google Scholar
Plappert, S., Gembarski, P.C. and Lachmayer, R. (2020), “Product Configuration with Bayesian Network”, Conference: Mass Customization and Personalization Community of Europe MCP-CE 2020, At: Novi SadVolume: Proceedings of the 9thInternational Conference on Mass Customization and Personalization – Community of Europe (MCP-CE 2020). 10.15488/11553Google Scholar
Popovich, A., Sufiiarov, V., Polozov, I., Borisov, E. and Masaylo, D. (2016), “Producing hip implants of titanium alloys by additive manufacturing”, International Journal of Bioprinting, Vol. 2, Nr. 2. doi:10.18063/ijb.2016.02.004Google Scholar
Quevedo Gonzalez, F. J, . (2012), Computational Design of functionally graded hip implants by means of additively manufactured porous materials, [PhD Thesis], Montreal, École de technologie supérieure.Google Scholar
Roth, A. and Winzer, T. (2002), “Periprothetische Osteopenie”, In: Peters, K. M: Knochenkrankheiten, 1. Edition, Steinkopff-Verlag Heidelberg, pp. 105-108.Google Scholar
Sigmund, O. and Maute, K. (2013), “Topology optimization approaches”, Structural and Multidisciplinary Optimization, Vol. 48, Nr. 6, pp. 1031–1055. doi:10.1007/s00158-013-0978-6Google Scholar
Sutradhar, A., Paulino, G. H. and Miller, M. (2010), “Topological optimization for designing patient-specific large craniofacial segmental bone replacements”, Proceedings of the National Academy of Sciences, Vol. 107, Nr. 30, pp. 13222–13227. 10.1073/pnas.1001208107CrossRefGoogle ScholarPubMed
Xiong, Y., Gao, R., Zhang, H. and Li, X. (2019), “Design and fabrication of a novel porous titanium dental implant with micro/nano surface”, International Journal of Applied Electromagnetics and Mechanics, Vol. 59, Nr. 3, pp. 1097–1102. doi:10.3233/jae-171166Google Scholar