Predicting calvarial growth in normal and craniosynostotic mice using a computational approach.

During postnatal calvarial growth the brain grows gradually and the overlying bones and sutures accommodate that growth until the later juvenile stages. The whole process is coordinated through a complex series of biological, chemical and perhaps mechanical signals between various elements of the craniofacial system. The aim of this study was to investigate to what extent a computational model can accurately predict the calvarial growth in wild-type (WT) and mutant type (MT) Fgfr2 mice displaying bicoronal suture fusion. A series of morphological studies were carried out to quantify the calvarial growth at P3, P10 and P20 in both mouse types. MicroCT images of a P3 specimen were used to develop a finite element model of skull growth to predict the calvarial shape of WT and MT mice at P10. Sensitivity tests were performed and the results compared with ex vivo P10 data. Although the models were sensitive to the choice of input parameters, they predicted the overall skull growth in the WT and MT mice. The models also captured the difference between the ex vivoWT and MT mice. This modelling approach has the potential to be translated to human skull growth and to enhance our understanding of the different reconstruction methods used to manage clinically the different forms of craniosynostosis, and in the long term possibly reduce the number of re-operations in children displaying this condition and thereby enhance their quality of life.