The probability of whole-bone fatigue fracture can be accurately predicted using specimen-specific finite element analysis incorporating a stochastic failure model

被引:2
|
作者
Haider, Ifaz T. [1 ,2 ,4 ]
Pohl, Andrew J. [1 ]
Edwards, W. Brent [1 ,2 ,3 ]
机构
[1] Univ Calgary, Fac Kinesiol, Human Performance Lab, Calgary, AB, Canada
[2] Univ Calgary, McCaig Inst Bone & Joint Hlth, Cumming Sch Med, Calgary, AB, Canada
[3] Univ Calgary, Schulich Sch Engn, Dept Biomed Engn, Calgary, AB, Canada
[4] Human Performance Lab, Calgary, AB, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Stress fracture; Microdamage; Fracture risk; Weibull; Mechanical fatigue; LIFE; DAMAGE;
D O I
10.1016/j.jbiomech.2022.111273
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
A better understanding of the mechanisms of mechanical fatigue in bone could help improve understanding of the etiology of stress fractures. Investigations of small material samples of bone have identified a nonlinear relationship between strain magnitude, strained volume, and fatigue life, but it is non-trivial to extend these principles to predict the fatigue-life of whole bones which experience complex loading and non-uniform strain distribution. The purpose of this investigation was to experimentally validate a specimen-specific finite element (FE) model that predicts whole-bone fatigue failure using a stochastic model based on strain magnitude and volume. Thirty-four rabbit tibiae were previously tested to failure under cyclic compression, torsion, or both. Strain distribution during the test was estimated from computed-tomography based specimen-specific FE models, and a stochastic failure model based on strain magnitude and volume was used to predict the probability of failure as a function of loading cycles. Model predicted fracture risk matched experimental observations. Respectively, for the 25%, 50%, 75%, and 95% probabilistic predictions, we observed experimental failure <= model predicted values in 41%, 53%, 76%, and 80% of the tested specimens. A Brier scoring rule further demonstrated that this model, using strain magnitude and volume, more accurately predicted failure probability compared to two reference models that considered strain magnitude only. In conclusion, the stochastic model may be a powerful tool in future studies to assess mechanical factors that influence stress fracture risk.
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页数:4
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