To investigate the 3D morphological variations in 169 temporomandibular ioint (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 seven healthy controls (mean age 43 ± 12.4 years).Materials and 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.