A Three-Dimensional Exploration of the Facial Musculature: Unraveling facial dynamics

In this thesis, the convergence of facial aesthetics and facial surgery was elaborated. It created 3D average facial models, explored upon facial expressions, and created methods for imaging and assessment of facial musculature. The creation of these models and atlases provides valuable reference materials for clinicians, aiding in surgical planning and assessment of facial morphology and dynamics.

The research highlights the importance of 3D imaging over traditional 2D methods, offering more consistent and comprehensive analysis. The dynamic analysis of facial expressions provides insights into normal and abnormal facial movements, which is crucial for both diagnosis and treatment planning.

The innovative use of 7 Tesla MRI technology represents a substantial improvement in visualizing and understanding facial musculature, which can enhance surgical precision and outcomes.

Based on the results of this thesis, future steps can be taken to enable automatic segmentation of the entire facial musculature. The ultimate goal is to develop reliable, automated methods for muscle segmentation, making the process faster and more applicable in clinical settings. This is of great importance in the evolvement of facial surgery, as it allows for individualized surgical planning and, potentially, better prediction of surgical outcomes. For the maxillofacial surgeon, one of the potential implications lies within orthognathic surgery. For example le Fort I osteotomies, where predictions on soft tissue outcomes are still challenging. Moreover, it could aid in assessment of cleft surgery, where modelling the muscles prior to surgery indicates how they must be repositioned, or after surgery to evaluate correct repositioning. Other implications are facial reanimation after facial paralysis, or face lift procedures. In these types of surgery, information of anatomy of facial muscles might aid in perioperative assessment to improve outcomes.