Image-based Modelling of Craniomaxillofacial Structures: A Finite Element Study

Hanieh Arjmand 1, 2 ;  Cristina Falcinelli 2 ;  Cari Whyne 1, 2

1. Institute of Biomaterials and Biomedical Engineering, University of Toronto; 2. Orthopaedic Biomechanics Laboratory, Sunnybrook Research Institute

Background: Subject-specific finite element (FE) models can be used to better understand the mechanical behaviour (e.g. stress, strain) of the craniomaxillofacial skeleton (CMFS) and to represent physiological loads and boundary conditions (i.e. during mastication). Clinical computed tomography (CT) imaging provides excellent visualization of bone and has been used widely to develop skeletal FE models. However, CT imaging data alone has been unable to provide sufficient soft tissue visualization to adequately depict musculature key to physiological loading. In vivo muscle loading is complex due to the non-uniform stretching and activation patterns of muscles generated, which is dependent on fibre bundle architecture. Magnetic resonance (MR) diffusion tensor imaging (DTI) can be used to visualize the fibre structure within muscles.

Objective: To characterize physiologic loading patterns in CMFS through specimen-specific FE modeling utilizing data generated from multimodal imaging techniques (CT, MRI and DTI).

Methods: To generate physiologically relevant subject-specific FE models of the CMFS, we will combine deblurred CT images (to yield accurate bone geometry and density) with co-registered MR T2 imaging (for gross modelling of soft tissues) and DTI (for obtaining muscle fibre architecture) (N=6). Experimental validation of these FE models will be conducted using simple loading applied to the associated cadaveric specimens. Complex muscle loading will be then applied to the validated models to simulate more complex physiologic loading scenarios.

Anticipated Results/Conclusion: We expect the integration of the muscles fibres to yield improved skeletal strain estimates (higher coefficient of determination between experimental measures and FE-based strain results) compared to models using simplified spring representations of muscle loading. The developed validated FE models incorporating accurate representation of the musculature will then be used to study CMFS load transmission during mastication. These novel FE models developed from multimodal imaging will yield an improved understanding of the physiological behaviour of the CMFS.