The nature of human craniofacial growth studied with finite element analytical approach

Predictive Statistical Model of Early Cranial Development

OBJECTIVE

We present a data-driven method to build a spatiotemporal statistical shape model predictive of normal cranial growth from birth to the age of 2 years.

METHODS

The model was constructed using a normative cross-sectional computed tomography image dataset of 278 subjects. First, we propose a new standard representation of the calvaria using spherical maps to establish anatomical correspondences between subjects at the cranial sutures - the main areas of cranial bone expansion. Then, we model the cranial bone shape as a bilinear function of two factors: inter-subject anatomical variability and temporal growth. We estimate these factors using principal component analysis on the spatial and temporal dimensions, using a novel coarse-to-fine temporal multi-resolution approach to mitigate the lack of longitudinal images of the same patient.

RESULTS

Our model achieved an accuracy of 1.54 ± 1.05 mm predicting development on an independent longitudinal dataset. We also used the model to calculate the cranial volume, cephalic index and cranial bone surface changes during the first two years of age, which were in agreement with clinical observations.

SIGNIFICANCE

To our knowledge, this is the first data-driven and personalized predictive model of cranial bone shape development during infancy and it can serve as a baseline to study abnormal growth patterns in the population.

Finite element growth analysis for the craniofacial skeleton in patients with cleft lip and palate

The purpose of this study was to clarify the differences in the nature of craniofacial growth between subjects with normal occlusion and patients with unilateral cleft lip and palate (CLP) in terms of the size, shape and principal growth direction of craniofacial skeleton using finite element method (FEM). Lateral cephalograms were taken of 40 subjects as normal group and 178 patients as CLP group. These subjects were divided into seven developmental ages of 4-, 6-, 8-, 10-, 12-, 14- and 18-year-old. For the finite element analysis, the craniofacial complex was discretized into seven structures or elements with three nodal points in each after tracing each lateral cephalogram on acetate paper. For each stage, the growth parameters in CLP group were compared to those in normal group. The growth of upper facial skeleton and maxillary complex was more remarkably inhibited in CLP than in normal group. Especially, the growth inhibition of posterior maxillary complex in a vertical direction was remarkable in CLP group at any ages. Difference in the size and shape of entire mandibular skeleton between CLP and normal groups was not apparent. It is suggested that grow timing and peak velocity, an essential and key determinant to the success in orthodontic treatment, have been clarified in this study more clearly than in previous studies. It is hopefully anticipated to explore some key determinants to predict individual growth of the craniofacial skeleton near future.