Hybrid simulation of brain–skull growth. (January 2014)

• Record Type: Journal Article
• Authors: Jin, Jing; Shahbazi, Sahar; Lloyd, John; Fels, Sidney; de Ribaupierre, Sandrine; Eagleson, Roy
• Is Part Of: Simulation. Volume 90:Number 1(2014:Jan.)
• Page Start: 3
• Page End: 10
• Publication Date: 2014-01
• Subjects: Hybrid deformation model -- surgical simulation -- brain–skull growth -- craniosynostosis; Computer simulation -- Periodicals; 003.3
• DOI: 10.1177/0037549713516691
• Languages: English
• ISSNs: 0037-5497

Abstract

This paper describes a hybrid model that includes both a standard finite element model and also volume-preserving structural modeling for a clinical application involving skull development in infants, with particular application to craniostosis modeling. To accommodate the growing brain, the skull needs to grow quickly in the first few months of life, and most of the growth of the skull at that time occurs at the sutures. Craniosynostosis, which is a developmental abnormality, occurs when one or more sutures are fused early in life (even in utero) while the skull is growing, resulting in an abnormal skull shape. To study normal brain–skull growth and to develop a model of craniosynostosis, we have developed a hybrid computational model to simulate the relationship between the growing deformable brain and the rigid skull. Our model is composed of the nine segmented skull plates as rigid surfaces, deformable sutures, and a volumetrically controllable deformable brain. The Cranial Index (ratio of biparietal width to fronto-occipital length) is measured during the simulation, showing a characteristic peak during development. Measures of linear growth along each dimension show characteristic increases over time. The hybrid simulation framework shows promise to support further investigations into abnormal skull development. By varying the properties of the sutures in our model, we can now simulate different craniosynostosis models, such as scaphocephaly and trigonocephaly. In this paper, we show results on the evolution of the Cranial Index as calculated using standard landmarks and compare to the normal index, and thereby evaluate our model by comparing it with patient data.