Design optimization on the subsidence resistance of the vertebral body cage: Considering different insertion depth of the spikes
| Autor: | Fu-yu Hsu, 許富喻 |
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| Rok vydání: | 2010 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 98 The vertebral body cages (VBCs) play an important role in the treatment of spinal disorders. However, the VBCs subsiding into the vertebral body may cause some demerits, such as collapse, progression of kyphosis, or fusion failure. These complications may cause some symptoms including spinal pain, deformity, or nerve damage and so on. Based on the past researches, the maximum load was always used to evaluate the subsidence resistance of VBCs. In addition, the spikes of VBCs were assumed to be fully inserted into the vertebral body. However, different VBC designs may have a different load-deformation curve in mechanical tests, and the spikes of VBCs are not fully implanted into the vertebra in clinical applications. Therefore, the purpose of this study was to search the optimum VBC design under different insertion depths of the VBCs. To obtain the VBC design with excellent subsidence resistance, three-dimensional finite element models of the VBC with the vertebra were developed and analyzed by using ANSYS Workbench. Then, Taguchi methods and artificial neural networks were used to construct the objective functions of the VBCs. Finally, genetic algorithms were used to find the optimum designs of the VBCs. In this study, two kinds of the optimization problems are discussed including single insertion depth (1/4, 2/4, 3/4, or 4/4 of spike height) and multiple insertion depth (whole subsidence process). The results showed that the subsidence resistance of the VBCs had much difference in the situations with an insertion depth of 1/4, 2/4, and 3/4. However, it had no significant difference in the situation with an insertion depth of 4/4. Moreover, the optimum parameters of the VBCs for multiple insertion depth were the spike height of 1 mm, the spike width of 1.72 mm, the spike oblique of 1, 16 spike rows per 28 mm, and the spike diameter of 10 mm. In conclusion, the optimum designs of the VBCs revealed excellent subsidence resistance. The artificial neural network based genetic algorithms can effectively reduce the effort and time required for searching the optimum designs of the VBCs. The outcome of this study can directly provide the selection information to orthopedic surgeons. Keywords：Vertebral Body Cage；Subsidence；Finite element Analysis；Artificial Neural Network；Genetic Algorithms |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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