Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/3634
Title: Stress Distribution and Stability Evaluation of Difference Number of Screws for Treating Tibia Transverse Fracture: Analysis on Patient-Specific Data
Authors: Suaimi M.K.A. 
Ab Rashid A.M. 
Nasution A.K. 
Seng G.H. 
Wui N.B. 
Ramlee M.H. 
Keywords: Biomechanics;Finite element;Number of screws;Tibia plate;Transverse fracture
Issue Date: May-2022
Publisher: Universiti Putra Malaysia Press
Journal: Malaysian Journal of Medicine and Health Sciences 
Abstract: 
Introduction: Screws placement may influence the stress distribution and stability of the plate and bone. Implant failures are normally happened in clinical practise when inappropriate number of screws is implemented. Therefore, intensive investigations are needed to provide additional quantitative data on the use of different number of screws. Therefore, this study was conducted to investigate the biomechanical performance of different number of screws configurations on Locking compression plate (LCP) assembly when treating transverse fractures of the tibia bone. Methods: Finite element method was used to simulate tibia bone fracture treated with LCP in standing phase simulation. To accomplish this, a three-dimensional tibia model was reconstructed using CT dataset images. 11 holes of LCP and 36mm of locking screws were developed using SolidWorks software. From this study, there are three models in total have been developed with different number of screws and screw placements. A diaphysis transverse tibia fracture of 4 mm was constructed. Results: In terms of stress distribution, all configurations provide sufficient stress and do not exceeding the yield strength of that material. Conclusion: In conclusion, eight numbers of screws were the optimum configurations in order to provide ideal stability to the bone with displacement of 0.37 mm and 0.91 mm at plate and bone, respectively.
Description: 
Scopus
URI: http://hdl.handle.net/123456789/3634
ISSN: 16758544
Appears in Collections:Faculty of Data Science and Computing - Journal (Scopus/WOS)

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