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Age- and sex-specific thorax finite element model development and simulation
Samantha L Schoell1, Ashley A Weaver, Nicholas A Vavalle
1a Virginia Tech-Wake Forest University Center for Injury Biomechanics , Wake Forest University School of Medicine , Winston-Salem , North Carolina.
Traffic Injury Prevention
|June 2, 2015
Summary
Finite element (FE) models of the thorax were adapted for different ages and sexes to assess injury risk. Older and male models showed increased fracture risk due to age- and sex-related thoracic geometry changes.
Area of Science:
- Biomechanics
- Computational modeling
- Human anatomy
Background:
- Thoracic skeleton geometry, bone density, and cortical thickness vary significantly with age and sex.
- These variations impact injury tolerance, particularly in elderly populations.
- Existing computational models lack representation for diverse ages and sexes.
Purpose of the Study:
- To morph a finite element (FE) model of the thorax to represent males and females at 30 and 70 years old.
- To investigate the influence of age- and sex-specific thoracic morphology on injury risk.
Main Methods:
- Developed age- and sex-specific FE models using thin-plate spline interpolation and Generalized Procrustes Analysis.
- Collected homologous landmark data from male and female rib and sternum images (ages 0-100).
- Simulated frontal hub and lateral impact loading cases to evaluate thoracic response.
Main Results:
- Thoracic response differed between age- and sex-specific models under frontal and lateral impacts.
- Increased thoracic stiffness with age, due to superior rib rotation, led to higher bone strain and fracture risk in 70-year-old models.
- Male models exhibited greater superior rib rotation, resulting in a higher predicted number of rib fractures compared to female models.
Conclusions:
- Developed and validated age- and sex-specific FE models of the thorax.
- These models enhance understanding of the relationship between thoracic geometry, age, sex, and injury risk.
- Facilitates improved injury risk assessment for diverse populations.
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