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Schematization of Cannulated Screw Fixations in Femoral Neck Fractures Using Genetic Algorithm and Finite Element Method

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Abstract

Purpose

Femoral neck fracture (FNF) is one of the most observed orthopedic injuries in elderly patients with accompanying osteoporosis, while treatment process could be highly troublesome in young patients. Therefore, it is necessary to apply a strong fixation to the FNFs. This study aims to suggest an approach for the optimum screw design for FNFs using genetic algorithm (GA) and finite element method (FEM) in a seriously shorter time, considering that a very large number for the design of the implants comes forward that would take a lifetime to solve individually.

Methods

In biomechanical studies conducted under laboratory conditions and focusing on stabilization, limited number of combinations have been tested with limited materials by now. However, ideal position, size and number of the screws are still subject of discussion. Unlike previous biomechanical studies; the present study addresses three types of CSFs (binary screw, triple screw and quadruple screw), while aiming to determine the optimum position, size and number of the screws using a design approach based on GA and FEM.

Results

This study emphasizes that screw configuration plays an important role on the treatment process of the femur. As a result of all evaluations and analyses, the most effective designs have been achieved for binary, triple and quadruple screw patterns.

Conclusion

In this study, all of the possible combinations and screw sizes have been evaluated to determine the optimum conditions for fracture stability. Suggested design approach could be used more effectively by healthcare disciplines such as orthopedics, in which biomechanical principles are significant. Moreover, cooperation between structural and biomechanical engineering is another remarkable eligibility of this research.

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Özkal, F.M., Cakir, F. & Sensoz, E. Schematization of Cannulated Screw Fixations in Femoral Neck Fractures Using Genetic Algorithm and Finite Element Method. J. Med. Biol. Eng. 40, 673–687 (2020). https://doi.org/10.1007/s40846-020-00528-5

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