A Parametric Thoracic Spine Model Accounting for Geometric Variations by Age, Sex, Stature, and Body Mass Index
- Lihan Lian - University of Michigan, Transportation Research Institute, USA University of Michigan, Department of Mechanical Engineering, USA ,
- Michelle Baek - University of Michigan, Transportation Research Institute, USA ,
- Sunwoo Ma - University of Michigan, Transportation Research Institute, USA ,
- Monica Jones - University of Michigan, Transportation Research Institute, USA ,
- Jingwen Hu - University of Michigan, Transportation Research Institute, USA University of Michigan, Department of Mechanical Engineering, USA
Journal Article
09-11-02-0012
ISSN: 2327-5626, e-ISSN: 2327-5634
Sector:
Citation:
Lian, L., Baek, M., Ma, S., Jones, M. et al., "A Parametric Thoracic Spine Model Accounting for Geometric Variations by Age, Sex, Stature, and Body Mass Index," SAE Int. J. Trans. Safety 11(2):123-131, 2023, https://doi.org/10.4271/09-11-02-0012.
Language:
English
Abstract:
In this study, a parametric thoracic spine (T-spine) model was developed to
account for morphological variations among the adult population. A total of 84
CT scans were collected, and the subjects were evenly distributed among age
groups and both sexes. CT segmentation, landmarking, and mesh morphing were
performed to map a template mesh onto the T-spine vertebrae for each sampled
subject. Generalized procrustes analysis (GPA), principal component analysis
(PCA), and linear regression analysis were then performed to investigate the
morphological variations and develop prediction models. A total of 13
statistical models, including 12 T-spine vertebrae and a spinal curvature model,
were combined to predict a full T-spine 3D geometry with any combination of age,
sex, stature, and body mass index (BMI). A leave-one-out root mean square error
(RMSE) analysis was conducted for each node of the mesh predicted by the
statistical model for every T-spine vertebra. Most of the RMSEs were less than 2
mm across the 12 vertebral levels, indicating good accuracy. The presented
parametric T-spine model can serve as a geometry basis for parametric human
modeling or future crash test dummy designs to better assess T-spine injuries
accounting for human diversity.