Diffusion-Tensor Imaging Versus Digitization in Reconstructing the Masseter Architecture

Accurate characterization of the craniomaxillofacial (CMF) skeleton using finite element (FE) modeling requires representation of complex geometries, heterogeneous material distributions, and physiological loading. Musculature in CMF FE models are often modeled with simple link elements that do not account for fiber bundles (FBs) and their differential activation. Magnetic resonance (MR) diffusion-tensor imaging (DTI) enables reconstruction of the three-dimensional (3D) FB arrangement within a muscle. However, 3D quantitative validation of DTI-generated FBs is limited. This study compares 3D FB arrangement in terms of pennation angle (PA) and fiber bundle length (FBL) generated through DTI in a human masseter to manual digitization. CT, MR-proton density, and MR-DTI images were acquired from a single cadaveric specimen. Bone and masseter surfaces were reconstructed from CT and MR-proton density images, respectively. PA and FBL were estimated from FBs reconstructed from MR-DTI images using a streamline tracking (STT) algorithm (n = 193) and FBs identified through manual digitization (n = 181) and compared using the Mann-Whitney test. DTI-derived PAs did not differ from the digitized data (p = 0.411), suggesting that MR-DTI can be used to simulate FB orientation and the directionality of transmitted forces. Conversely, a significant difference was observed in FBL (p < 0.01) which may have resulted due to the tractography stopping criterion leading to early tract termination and greater length variability. Overall, this study demonstrated that DTI can yield muscle FB orientation data suitable to representative directionality of physiologic muscle loading in patient-specific CMF FE modeling.