Pediatric Cranioplasty Using Hydroxyapatite Cement: A Retrospective Review and Preliminary Computational Model.

IIntroduction Cranioplasty is a standard technique for skull defect repair. Restoration of cranial defects is imperative for brain protection and allowing for homeostasis of cerebral spinal fluid within the cranial vault. Calcium phosphate hydroxyapatite (HA) is a synthetic-organic material that is commonly used in cranioplasty. We evaluate a patient series undergoing HA cement cranioplasty with underlying bioresorbable mesh for various cranial defects and propose a preliminary computational model for understanding skull osteointegration. Methods A retrospective review was performed at the institution for all pediatric patients who underwent HA cement cranioplasty. 17 patients were identified and success of cranioplasty was determined based on clinical and radiographic follow-up. A preliminary computational model was developed using bone growth and scaffold decay equations from previously published literature. The model was dependent on defect size and shape. Patient data was used to optimize the computational model. Results Seventeen patients were identified with an average age of 6±5.6 years. Average defect size was 11.7±16.8 cm2. Average time to last follow-up CT scan was 10±6 months. Three patients had failure of cranioplasty, all with a defect size above 15 cm2. The computational model developed shows a constant decay rate of the scaffold, regardless of size or shape. The bone growth rate was dependent on the shape and number of edges within the defect. Thus, a star-shaped defect obtained a higher rate of growth than a circular defect because of faster growth rates at the edges. The computational simulations suggest that shape and size of defects may alter success of osteointegration. Conclusion Pediatric cranioplasty is a necessary procedure for cranial defects with a relatively higher rate of failure than adults. Here, we use hydroxyapatite cement to perform the procedure while creating a preliminary computational model to understand osteointegration. Based on the findings, cranioplasty shape may alter rate of integration and lead to higher success rates.