Andrea Robinson ^1,2* Bowen Zheng ³ B W. von Kleeck III ^1,2 Josh Tan ⁴ Francis S. Gayzik ^1,2*

• ¹ Wake Forest University School of Medicine, Center for Injury Biomechanics, School of Biomedical Engineering and Sciences, Virginia Tech - Wake Forest University, Winston-Salem, United States
• ² Department of Biomedical Engineering, School of Medicine, Wake Forest University, Winston-Salem, North Carolina, United States
• ³ Department of Biomedical Engineering, The Fu Foundation School of Engineering and Applied Science, Columbia University, New York City, New York, United States
• ⁴ Department of Radiology, School of Medicine, Wake Forest University, Winston-Salem, North Carolina, United States

Traumatic injuries to the thorax are a common occurrence, and given the disparity in outcomes, injury risk is non-uniformly distributed within the population. Rib cage geometry, in conjunction with well-established biomechanical characteristics, is thought to influence injury tolerance, but quantifiable descriptions of adult rib cage shape as a whole are lacking. Here, we develop an automated pipeline to extract whole rib cage measurements from a large population and produce distributions of these measurements to assess variability in rib cage shape. Ten measurements of whole rib cage shape were collected from 1,719 individuals aged 25-45 years old including angular, linear, areal, and volumetric measures. The resulting pipeline produced measurements with a mean percent difference to manually collected measurements of 1.7 ± 1.6 %, and the whole process takes 30 seconds per scan. Each measurement followed a normal distribution with a maximum absolute skew value of 0.43 and a maximum absolute excess kurtosis value of 0.6. Significant differences were found between the sexes (p < 0.001) in all except angular measures. Multivariate regression revealed that demographic predictors explain 29-68% of the variance in the data. The angular measurements had the three lowest R 2 values and were also the only three to have little correlation with subject stature. Unlike other measures, rib cage height had a negative correlation with BMI. Stature was the dominant demographic factor in predicting rib cage height, coronal area, sagittal area, and volume. Subject weight was the dominant demographic factor for rib cage width, depth, axial area, and angular measurements. Age was minimally important in this cohort of adults from a narrow age range. Individuals of similar height and weight had average rib cage measurements near the regression predictions, but the range of values across all subjects encompassed a large portion of their respective distributions.Our findings characterize the variability in adult rib cage geometry, including the variation within narrow demographic criteria. In future work, these can be integrated into computer aided engineering workflows to assess the influence of whole rib cage shape on the biomechanics of the adult human thorax.