Statistical Shape Modelling for the Analysis of Head Shape Variations

The aim of this study is, firstly, to create a population-based 3D head shape model for the 0 to 2-year-old subjects to describe head shape variability within a normal population and, secondly, to test a combined normal and sagittal craniosynostosis (SAG) population model, able to provide surgical outcome assessment. 3D head shapes of patients affected by non-cranial related pathologies and of SAG patients (pre- and post-op) were extracted either from head CTs or 3D stereophotography scans, and processed. Statistical shape modelling (SSM) was used to describe shape variability using two models - a normal population model (MODEL1) and a combined normal and SAG population model (MODEL2). Head shape variability was described via principal components analysis (PCA) which calculates shape modes describing specific shape features. MODEL1 (n = 65) mode 1 showed statistical correlation (p < 0.001) with width (125.8 ± 13.6 mm), length (151.3 ± 17.4 mm) and height (112.5 ± 11.1 mm) whilst mode 2 showed correlation with cranial index (83.5 mm ± 6.3 mm, p < 0.001). The remaining 9 modes showed more subtle head shape variability. MODEL2 (n = 159) revealed that post-operative head shape still did not achieve full shape normalization with either spring cranioplasty or total calvarial remodelling. This study proves that SSM has the potential to describe detailed anatomical variations in a paediatric population.