Predictive anthropometric measurements for humeral head curvature

Abstract

Estimation of size, shape, and curvature of the humeral head is important for shoulder replacement procedures and allograft transplantation, especially as we try to recreate normal anatomy. The purpose of this study was to investigate the value of various anthropometric measurements for predicting humeral head curvature. Cadaveric humeri were scanned with a 3-dimensional laser scanner. Length of the humerus, epicondylar breadth, and humeral head curvature were determined using data from the scans. A linear regression was performed for the length of the humerus, epicondylar breadth, gender, age, height, and weight. A stepwise linear regression with forward and backward substitution (α = 0.15) was performed for the most predictive variables from the initial linear regression. An equation for the prediction of humeral head radius of curvature was generated using this data. The most predictive factors (R(2) > 0.5) were epicondylar breadth, height, sex, and humeral length. These 4 factors were included in a forward and backward stepwise regression. The resulting equation had an R(2) value of 0.812. Of the predicted measurements evaluated, patient height, maximum humeral length, epicondylar breadth, and gender were most correlated with humeral head curvature. Including these 4 factors in a linear regression model increased the R(2) value to 0.812. If only a single measurement can be used to size the humeral head curvature, patient height will give the same accuracy as epicondylar breadth and can more easily be obtained. A patient's height can help accurately predict the patient's humeral head anatomy.