Introduction the aim of this study was to evaluate the differences between 2 regions of maxillary voxel-based registration and to test the reproducibility of the registration. Methods 3D models were built for before treatment (T1) and after treatment (T2) Cone Beam CTs for 16 growing subjects. Landmarks were labeled in all T2 models of the maxilla, and voxel-based registration was performed independently by two observers, at two different times, using two different reference regions: 1) the Maxilla region (MAX) included the maxillary bone clipped inferiorly at the dentoalveolar processes, superiorly at the plane passing through the right and left orbitale points, laterally at the zygomatic processes through the orbitale point, and posteriorly at a plane passing through the distal surface of the second molars. 2) the Palate and Infra-zygomatic region (PIZ) had different posterior and anterior limits (at the plane passing through the distal of the first molar and distal of the canines, respectively). The differences between the registration regions were measured by comparing the distances between corresponding landmarks in the T2 registered models and comparing corresponding x,y,z coordinates from corresponding landmarks. Statistical analysis of the differences between T2 surface models was performed by evaluating the means and standard deviations of the distances between landmarks and by testing the agreement between coordinates from corresponding landmarks (ICC and Bland-Altman method). Results The means of the differences between landmarks from PIZ to MAX 3D T2 surface models for all of the regions of reference, times of registrations and observers combinations were smaller than 0.5 mm. The ICC and the Bland-Altman plots indicated adequate concordance. Conclusions Both regions of regional maxillary registration (MAX and PIZ) showed similar results and adequate intra- and inter-observer reproducibility.

This study investigated predictive risk factors of condylar remodeling changes after counterclockwise maxillomandibular advancement (CCW-MMA) and disc repositioning surgery. Forty-one female patients (75 condyles) treated with CCW-MMA and disc repositioning had cone beam computed tomography (CBCT) scans taken pre-surgery, immediately after surgery, and at an average 16 months post-surgery. Pre- and post-surgical three-dimensional models were superimposed using automated voxel-based registration on the cranial base to evaluate condylar displacements after surgery. Regional registration was performed to assess condylar remodeling in the follow-up period. Three-dimensional cephalometrics, shape correspondence (SPHARM-PDM), and volume measurements were applied to quantify changes. Pearson product-moment correlations and multiple regression analysis were performed. Highly statistically significant correlation showed that older patients were more susceptible to overall condylar volume reduction following CCW-MMA and disc repositioning (P ≤ 0.001). Weak but statistically significant correlations were observed between condylar remodeling changes in the follow-up period and pre-surgical facial characteristics, magnitude of the surgical procedure, and condylar displacement changes. After CCW-MMA and disc repositioning, the condyles moved mostly downwards and medially, and were rotated medially and counterclockwise; displacements in the opposite direction were correlated with a greater risk of condylar resorption. Moreover, positional changes with surgery were only weakly associated with remodeling in the follow-up period, suggesting that other risk factors may play a role in condylar resorption.

This study aimed to investigate imaging statistical approaches for classifying three-dimensional (3-D) osteoarthritic morphological variations among 169 temporomandibular joint (TMJ) condyles. Cone-beam computed tomography scans were acquired from 69 subjects with long-term TMJ osteoarthritis (OA), 15 subjects at initial diagnosis of OA, and 7 healthy controls. Three-dimensional surface models of the condyles were constructed and SPHARM-PDM established correspondent points on each model. Multivariate analysis of covariance and direction-projection-permutation (DiProPerm) were used for testing statistical significance of the differences between the groups determined by clinical and radiographic diagnoses. Unsupervised classification using hierarchical agglomerative clustering was then conducted. Compared with healthy controls, OA average condyle was significantly smaller in all dimensions except its anterior surface. Significant flattening of the lateral pole was noticed at initial diagnosis. We observed areas of 3.88-mm bone resorption at the superior surface and 3.10-mm bone apposition at the anterior aspect of the long-term OA average model. DiProPerm supported a significant difference between the healthy control and OA group ([Formula: see text]). Clinically meaningful unsupervised classification of TMJ condylar morphology determined a preliminary diagnostic index of 3-D osteoarthritic changes, which may be the first step towards a more targeted diagnosis of this condition.

Objectives To investigate the 3D morphological variations in 169 Temporomandibular Joint (TMJ) condyles, using novel imaging statistical modeling approaches. Setting and Sample Population The Department of Orthodontics and Pediatric Dentistry at the University of Michigan. Cone beam CT scans were acquired from 69 subjects with long-term TMJ osteoarthritis (OA, mean age 39.1 ± 15.7 years), 15 subjects at initial consult diagnosis of OA (mean age 44.9 ± 14.8 years) and 7 healthy controls (mean age 43 ± 12.4 years). Material & Methods 3D surface models of the condyles were constructed and homologous correspondent points on each model were established. The statistical framework included Direction-Projection-Permutation (DiProPerm) for testing statistical significance of the differences between healthy controls and the OA groups determined by clinical and radiographic diagnoses. Results Condylar morphology in OA and healthy subjects varied widely with categorization from mild to severe bone degeneration or overgrowth. DiProPerm statistics supported a significant difference between the healthy control group and the initial diagnosis of OA group (t=6.6, empirical p-value = 0.006), and between healthy and long term-diagnosis of OA group (t = 7.2, empirical p-value = 0). Compared with healthy controls, the average condyle in OA subjects was significantly smaller in all dimensions, except its anterior surface, even in subjects with initial diagnosis of OA. Conclusion This new statistical modeling of condylar morphology allows the development of more targeted classifications of this condition than previously possible.