Stature estimation based on radial and ulnar lengths using three-dimensional images from multidetector computed tomography in a Japanese population

• We assess the correlation between stature and radial and ulnar lengths.
• All measured lengths were positively correlated with stature.
• We derive modern regression formulae for estimating stature in a Japanese population.
• Multiple regression equations were more accurate than the single regression ones.

The aim of our study was to evaluate correlations between cadaver stature (CS) and radial and ulnar lengths based on three-dimensional (3D) computed tomography (CT) images, and to develop modern regression equations for estimating CS in a Japanese population. Measurements were performed on 245 Japanese subjects (123 males and 122 females) who underwent postmortem CT between May 2011 and December 2013. A 3D reconstructed image was used for assessment. The linear distances of the left radial (LR) and right radial (RR) lengths were measured as a straight-line distance from the most anteroproximal point of the head to the most distal end of the styloid process. The linear distances of the left ulnar (LU) and right ulnar (RU) lengths were measured as a straight-line distance from the most posteroproximal point of the olecranon to the most distal end of the styloid process. The correlation between CS and each parameter (LR, LU, RR, and RU) was assessed using Pearson product-moment correlation coefficients and regression analysis was performed for stature estimation. There were significant correlations between CS and each parameter regardless of sex, indicating that the radial and ulnar lengths measured on 3D CT images can be predictive of stature estimation. Simple regression equations for stature estimation calculated from LR provided the lowest standard error of estimation (SEE) (all subjects, SEE = 4.18 cm; males, SEE = 4.09 cm; females, SEE = 4.21 cm). In addition, multiple regression equations were more accurate and reliable than the single linear regression equations.