An optimized process flow for rapid segmentation of cortical bones of the craniofacial skeleton using the level-set method.

Accurate representation of skeletal structures is essential for quantifying structural integrity, for developing accurate models, for improving patient-specific implant design and in image-guided surgery applications. The complex morphology of thin cortical structures of the craniofacial skeleton (CFS) represents a significant challenge with respect to accurate bony segmentation. This technical study presents optimized processing steps to segment the three-dimensional (3D) geometry of thin cortical bone structures from CT images. In this procedure, anoisotropic filtering and a connected components scheme were utilized to isolate and enhance the internal boundaries between craniofacial cortical and trabecular bone. Subsequently, the shell-like nature of cortical bone was exploited using boundary-tracking level-set methods with optimized parameters determined from large-scale sensitivity analysis. The process was applied to clinical CT images acquired from two cadaveric CFSs. The accuracy of the automated segmentations was determined based on their volumetric concurrencies with visually optimized manual segmentations, without statistical appraisal. The full CFSs demonstrated volumetric concurrencies of 0.904 and 0.719; accuracy increased to concurrencies of 0.936 and 0.846 when considering only the maxillary region. The highly automated approach presented here is able to segment the cortical shell and trabecular boundaries of the CFS in clinical CT images. The results indicate that initial scan resolution and cortical-trabecular bone contrast may impact performance. Future application of these steps to larger data sets will enable the determination of the method's sensitivity to differences in image quality and CFS morphology.

Sensitivity analysis of a validated subject-specific finite element model of the human craniofacial skeleton.

Developing a more complete understanding of the mechanical response of the craniofacial skeleton (CFS) to physiological loads is fundamental to improving treatment for traumatic injuries, reconstruction due to neoplasia, and deformities. Characterization of the biomechanics of the CFS is challenging due to its highly complex structure and heterogeneity, motivating the utilization of experimentally validated computational models. As such, the objective of this study was to develop, experimentally validate, and parametrically analyse a patient-specific finite element (FE) model of the CFS to elucidate a better understanding of the factors that are of intrinsic importance to the skeletal structural behaviour of the human CFS. An FE model of a cadaveric craniofacial skeleton was created from subject-specific computed tomography data. The model was validated based on bone strain measurements taken under simulated physiological-like loading through the masseter and temporalis muscles (which are responsible for the majority of craniofacial physiologic loading due to mastication). The baseline subject-specific model using locally defined cortical bone thicknesses produced the strongest correlation to the experimental data (r2 = 0.73). Large effects on strain patterns arising from small parametric changes in cortical thickness suggest that the very thin bony structures present in the CFS are crucial to characterizing the local load distribution in the CFS accurately.

Effects of bone density alterations on strain patterns in the pelvis: application of a finite element model.

Insufficiency fractures occur when physiological loads are applied to bone deficient in mechanical resistance. A better understanding of pelvic mechanics and the effect of bone density alterations could lead to improved diagnosis and treatment of insufficiency fractures. This study aimed to develop and validate a subject-specific three-dimensional (3D) finite element (FE) model of a pelvis, to analyse pelvic strains as a function of interior and cortical surface bone density, and to compare high strain regions with common insufficiency fracture sites. The FE model yielded strong agreement between experimental and model strains. By means of the response surface method, changes to cortical surface bone density using the FE model were found to have a 60 per cent greater influence compared with changes in interior bone density. A small interaction was also found to exist between surface and interior bone densities (< 3 per cent), and a non-linear effect of surface bone density on strain was observed. Areas with greater increases in average principal strains with reductions in density in the FE model corresponded to areas prone to insufficiency fracture. Owing to the influence of cortical surface bone density on strain, it may be considered a strong global (non-linear) indicator for insufficiency fracture risk.