Electronic Thesis and Dissertation Repository

Degree

Doctor of Philosophy

Program

Biomedical Engineering

Supervisor(s)

Roy Eagleson

Abstract

Craniosynostosis is a pathology in infants when one or more sutures prematurely closed, leading to abnormal skull shape. It has been classified according to the specific suture that has been closed, each of which has a typical skull shape. Surgery is the common treatment to correct the deformed skull shape and to reduce the excessive intracranial pressure. Since every case is unique, the cranial facial teams have difficulties to select an optimum solution for a specific patient from multiple options. In addition, there is not an appropriate quantified measurement existed currently to help cranial facial team to quantitatively evaluate their surgeries.

We aimed to develop a head model of a craniosynostosis patient, which allows neurosurgeons to perform any potential surgeries on it so as to simulate the postoperative head development. Therefore, neurosurgeons could foresee the surgical results and is able to select the optimal one. In this thesis, we have developed a normal head model, and built mathematical models for possible dynamic behaviors. We also modified this model by closing one or two sutures to simulate common types of craniosynostosis. The abnormal simulation results showed a qualitative match with real cases and the normal simulation indicated a higher growth rate of cranial index than clinical data. We believed that this discrepancy caused by the rigidity of our skull plates, which will be adapted to deformable object in the future.

In order to help neurosurgeons to better evaluate a surgery, we hope to develop an algorithm to quantify the level of deformity of a skull. We have designed a set of work flow and targeted curvatures as the key role. A training data was carefully selected to search for an optimal system to characterize different shapes. A set of test data was used to validate our algorithm to assess the performance of the optimal system. With a stable evaluating system, we can evaluate a surgery by comparing the preoperative and postoperative skulls from the patient. An effective surgery can be considered if the postoperative skull shifted toward normal shape from preoperative shape.


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