Development of a Patient-Specific Finite Element Model for Predicting Implant Failure in Pelvic Ring Fracture Fixation

Author:

Shim Vickie12ORCID,Höch Andreas3,Grunert Ronny3ORCID,Peldschus Steffen4,Böhme Jörg3ORCID

Affiliation:

1. Auckland Bioengineering Institute, University of Auckland, 70 Symonds Street, Auckland, New Zealand

2. Menzies Health Institute, Griffith University, Gold Coast, QLD, Australia

3. Department of Trauma, Plastic and Reconstructive Surgery, University of Leipzig, Liebigstr. 20, 04103 Leipzig, Germany

4. Institute of Forensic Medicine, Ludwig-Maximilians-University Munich, Munich, Germany

Abstract

Introduction. The main purpose of this study is to develop an efficient technique for generating FE models of pelvic ring fractures that is capable of predicting possible failure regions of osteosynthesis with acceptable accuracy. Methods. Patient-specific FE models of two patients with osteoporotic pelvic fractures were generated. A validated FE model of an uninjured pelvis from our previous study was used as a master model. Then, fracture morphologies and implant positions defined by a trauma surgeon in the preoperative CT were manually introduced as 3D splines to the master model. Four loading cases were used as boundary conditions. Regions of high stresses in the models were compared with actual locations of implant breakages and loosening identified from follow-up X-rays. Results. Model predictions and the actual clinical outcomes matched well. For Patient A, zones of increased tension and maximum stress coincided well with the actual locations of implant loosening. For Patient B, the model predicted accurately the loosening of the implant in the anterior region. Conclusion. Since a significant reduction in time and labour was achieved in our mesh generation technique, it can be considered as a viable option to be implemented as a part of the clinical routine to aid presurgical planning and postsurgical management of pelvic ring fracture patients.

Publisher

Hindawi Limited

Subject

Applied Mathematics,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,Modeling and Simulation,General Medicine

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