Simulation-based particle swarm optimization and mechanical validation of screw position and number for the fixation stability of a femoral locking compression plate

Abstract Locking compression plates (LCPs) have been used to fix femoral shaft fractures. Previous studies have attempted to identify the best LCP screw positions and numbers to achieve the fixation stability. However, the determined screw positions and numbers were mainly based on the surgeons’ exp...

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Veröffentlicht in:Medical engineering & physics 2014-01, Vol.36 (1), p.57-64
Hauptverfasser: Lee, Chian-Her, Shih, Kao-Shang, Hsu, Ching-Chi, Cho, Tomas
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Sprache:eng
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Zusammenfassung:Abstract Locking compression plates (LCPs) have been used to fix femoral shaft fractures. Previous studies have attempted to identify the best LCP screw positions and numbers to achieve the fixation stability. However, the determined screw positions and numbers were mainly based on the surgeons’ experiences. The aim of this study was to discover the best number and positions of LCP screws to achieve acceptable fixation stability. Three-dimensional numerical models of a fractured femur with the LCP were first developed. Then, the best screw position and number of LCPs were determined by using a simulation-based particle swarm optimization algorithm. Finally, the results of the numerical study were validated by conducting biomechanical tests. The results showed that the LCP with six locking screws resulted in the necessary fixation stability, and the best combination of positions of locking screws inserted into the LCP was 1-5-6-7-8-12 (three locking screws on either side of the bone fragment with two locking screws as close as practicable to the fracture site). In addition, the numerical models and algorithms developed in this study were validated by the biomechanical tests. Both the numerical and experimental results can provide clinical suggestions to surgeons and help them to understand the biomechanics of LCP systems.
ISSN:1350-4533
1873-4030
DOI:10.1016/j.medengphy.2013.09.005