Parameter optimization in a finite element mandibular fracture fixation model using the design of experiments approach

材料科学 有限元法 植入 流离失所(心理学) 断裂(地质) 固定(群体遗传学) 复合材料 变形(气象学) 下颌骨(节肢动物口器) 生物医学工程 结构工程 化学 外科 医学 心理学 生物化学 植物 生物 工程类 冶金 心理治疗师 基因
作者
Michaela Maintz,Bilal Msallem,Michael de Wild,Daniel Seiler,Sven Herrmann,Stefanie Feiler,Neha Sharma,Federico Dalcanale,Philippe C. Cattin,Florian M. Thieringer
出处
期刊:Journal of The Mechanical Behavior of Biomedical Materials [Elsevier BV]
卷期号:144: 105948-105948 被引量:4
标识
DOI:10.1016/j.jmbbm.2023.105948
摘要

Only a few mandibular bone finite element (FE) models have been validated in literature, making it difficult to assess the credibility of the models. In a comparative study between FE models and biomechanical experiments using a synthetic polyamide 12 (PA12) mandible model, we investigate how material properties and boundary conditions affect the FE model's accuracy using the design of experiments approach. Multiple FE parameters, such as contact definitions and the materials' elastic and plastic deformation characteristics, were systematically analyzed for an intact mandibular model and transferred to the fracture fixation model. In a second step, the contact definitions for the titanium screw and implant (S–I), implant and PA12 mandible (I-M), and interfragmentary (IF) PA12 segments were optimized. Comparing simulated deformations (from 0 to −5 mm) and reaction forces (from 10 to 1′415 N) with experimental results showed a strong sensitivity to FE mechanical properties and contact definitions. The results suggest that using the bonded definition for the screw-implant contact of the fracture plate is ineffective. The contact friction parameter set with the highest agreement was identified: titanium screw and implant μ = 0.2, implant and PA12 mandible μ = 0.2, interfragmentary PA12 mandible μ = 0.1. The simulated reaction force (RMSE = 26.60 N) and surface displacement data (RMSE = 0.19 mm) of the FE analysis showed a strong agreement with the experimental biomechanical data. The results were generated through parameter optimization which means that our findings need to be validated in the event of a new dataset with deviating anatomy. Conclusively, the predictive capability of the FE model can be improved by FE model calibration through experimental testing. Validated preoperative quasi-static FE analysis could allow engineers and surgeons to accurately estimate how the implant's choice and placement suit the patient's biomechanical needs.
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