Population trends in human rib cross-sectional shapes

Area of Science:

• Biomechanics and Computational Modeling
• Human Anatomy and Physiology
• Injury Biomechanics

Background:

• Rib fractures are common in motor vehicle crashes, necessitating accurate computational human body models (HBMs).
• Existing HBMs lack detailed rib geometry due to limited cross-sectional shape data, often using simplified sections from single individuals.
• Accurate rib geometry is crucial for simulating thoracic injuries and developing effective mitigation strategies.

Purpose of the Study:

• To collect and analyze detailed human rib cross-sectional shape data across a diverse adult population.
• To establish associations between rib shape, cortical bone thickness, and demographic factors (sex, age, height, weight).
• To provide data for creating more accurate HBMs for injury simulation and safety design.

Main Methods:

• Collected chest CT scans from 240 adult males and females across the full age range.
• Utilized a cortical bone mapping algorithm to extract cross-sectional geometry (periosteal position, cortex thickness).
• Applied Principal Component Analysis (PCA) for dimensionality reduction and Linear Regression to identify demographic associations.

Main Results:

• Significant associations found between principal component scores and sex, age, height, and weight at all rib levels.
• Average female ribs showed smaller total cross-sectional area (20-36%) and cortical bone area (up to 18%) compared to males.
• Age correlated with reduced cortical bone area (up to 37%), with height and weight influencing both total and cortical areas differently across sexes and rib levels.

Conclusions:

• The study provides comprehensive data on human rib cross-sectional shapes across diverse demographics.
• These detailed geometries can significantly improve the accuracy of computational human body models.
• Enhanced HBMs will enable more precise simulation of rib fractures and development of targeted injury mitigation strategies.