Enhanced Virtual Surgical Planning for Maxillary Reconstruction

What I did

Maxillary reconstruction after tumour resection or trauma is technically demanding and highly individualized. Working with supervisors at Western University and the University of British Columbia, I:

• Built a craniofacial statistical shape model using CT data from patients with normal anatomy.

• Developed an algorithm to predict the “ideal” missing maxillary segment in cases of bilateral defects.

• Integrated the model into a virtual surgical planning pipeline, allowing surgeons to visualize reconstructions, design cutting guides, and plan graft positioning before surgery.

• Led the validation study, comparing virtual reconstructions against expert-defined ground truth and evaluating accuracy, symmetry, and clinical usability.

Results

• Demonstrated that a data-driven model can recreate missing maxillary anatomy with clinically acceptable precision, providing a quantitative foundation for reconstruction plans.

• Presented the work at international OMFS conferences and published in the International Journal of Oral and Maxillofacial Surgery.

• Laid the groundwork for next-generation planning tools that combine imaging, statistical modelling, and 3D printing to shorten case planning time and improve functional/aesthetic outcomes.