The geometric morphometrics method (GMM) is a technique to study scale and shape relationships of structures using Cartesian geometric coordinates rather than linear, areal (of area), or volumetric variables. The GMM has been shown to be of great value in many biological studies, but does not appear to have been used to examine equine skulls. In this exploratory study, 29 normal equine heads of three different age groups: <5 years old (N=9), 6-15 years old (N=10) and >16 years old (N=10) were examined using the GMM technique. Computed tomography (CT) bone window DICOM images of equine skulls were reconstructed into isosurfaces (3-dimensional contoured surfaces), onto which anatomical landmarks were added using Stratovan Checkpoint® software. Data from 29 different landmarks were analysed using MorphoJ analysis, which applies a Procrustes fit, prior to reducing data dimensionality through principal component (PC) analysis. PCs with and without allometry (shape variation that can be explained by size changes) were considered. Allometric shape described by PC1 analysis accounted for 27% of variance. Loading pertaining to the following skull landmarks: the pterygoid process, bilaterally; caudal aspect of hard palate; tip of nasal bone; ethmoid sinuses, bilaterally; caudal aspect of the ventral conchal bulla, bilaterally and caudal aspect of the vomer bone suggest that these anatomical structures are predictive of age group. When allometric effects were removed, PC1 analysis was unable to distinguish horses by age group. Allometric shape differences could distinguish the youngest versus the two older age groups. The potential applications of GMM in equine diagnostic imaging are wide ranging and include the investigation of genetic-related changes in the equine skull shape and a more complete characterisation of the many conformation-related diseases affecting the teeth, jaws and sinonasal compartments of horses.
- geometric morphometric measurements (GMM)
- computed tomography
- equine skull shape
- principal component analysis