Abstract

Orthognathic surgery belongs to the scope of maxillofacial surgery. It treats dentofacial deformities consisting in discrepancy between the facial bones (upper and lower jaws). Such impairment affects chewing, talking, and breathing and can ultimately result in the loss of teeth. Orthognathic surgery restores facial harmony and dental occlusion through bone cutting, repositioning, and fixation. However, in routine practice, we face the limitations of conventional tools and the lack of intraoperative assistance. These limitations occur at every step of the surgical workflow: preoperative planning, simulation, and intraoperative navigation. The aim of this research was to provide novel tools to improve simulation and navigation. We first developed a semiautomated segmentation pipeline allowing accurate and time-efficient patient-specific 3D modeling from computed tomography scans mandatory to achieve surgical planning. This step allowed an improvement of processing time by a factor of 6 compared with interactive segmentation, with a 1.5-mm distance error. Next, we developed a software to simulate the postoperative outcome on facial soft tissues. Volume meshes were processed from segmented DICOM images, and the Bullet open source mechanical engine was used together with a mass-spring model to reach a postoperative simulation accuracy <1 mm. Our toolset was completed by the development of a real-time navigation system using minimally invasive electromagnetic sensors. This navigation system featured a novel user-friendly interface based on augmented virtuality that improved surgical accuracy and operative time especially for trainee surgeons, therefore demonstrating its educational benefits. The resulting software suite could enhance operative accuracy and surgeon education for improved patient care.

Full Text
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