Temporomandibular Joint Space Dimensions among Saudi Patients with Temporomandibular Disorders: MRI-Based Retrospective Study

Relationships between functional temporomandibular joint space and disc morphology, position, and condylar osseous condition in patients with temporomandibular disorder

OBJECTIVE

To investigate the correlations between joint space and temporomandibular joint (TMJ) components and the compressive states of the disc and condyle subsequent to joint space changes.

MATERIALS AND METHODS

A total of 240 TMJs were categorized according to disc morphology, disc position, and condylar osseous condition. The two-dimensional (2D) and three-dimensional (3D) measurements were compared. The functional joint space (FJS) and disc areas on closed- and open-mouth images (DA-C and DA-O) were also calculated, and the joint space was measured in five directions. Different groups of TMJ components were compared. A spring model was used to simulate the effect of condylar displacement on the disc and condyle.

RESULTS

Disc morphology was strongly correlated with its position. The measurements were equivalent between 2D and 3D methods. DA-C and FJS differed significantly between groups. The DA-C to FJS ratio differed between the Class 2 and Class 3 groups and between disc displacement groups with and without reduction. Altered disc morphology and position were correlated with significant changes in joint space in the 60°, 90°, and 120° directions. Despite minor discrepancies among condylar osseous conditions, reduced joint space was correlated with bone destruction at the corresponding site. The spring model stimulation revealed that condylar displacement caused elevated stresses on the disc and condyle.

CONCLUSIONS

Condylar displacement causes joint space alterations while exerting compressive pressure on both the disc and condyle.

CLINICAL RELEVANCE

Proper condylar positioning within the fossa is recommended to ensure sufficient articular disc accommodation.

A comprehensive patient-specific prediction model for temporomandibular joint osteoarthritis progression

Temporomandibular joint osteoarthritis (TMJ OA) is a prevalent degenerative disease characterized by chronic pain and impaired jaw function. The complexity of TMJ OA has hindered the development of prognostic tools, posing a significant challenge in timely, patient-specific management. Addressing this gap, our research employs a comprehensive, multidimensional approach to advance TMJ OA prognostication. We conducted a prospective study with 106 subjects, 74 of whom were followed up after 2 to 3 y of conservative treatment. Central to our methodology is the development of an innovative, open-source predictive modeling framework, the Ensemble via Hierarchical Predictions through Nested cross-validation tool (EHPN). This framework synergistically integrates 18 feature selection, statistical, and machine learning methods to yield an accuracy of 0.87, with an area under the ROC curve of 0.72 and an F1 score of 0.82. Our study, beyond technical advancements, emphasizes the global impact of TMJ OA, recognizing its unique demographic occurrence. We highlight key factors influencing TMJ OA progression. Using SHAP analysis, we identified personalized prognostic predictors: lower values of headache, lower back pain, restless sleep, condyle high gray level-GL-run emphasis, articular fossa GL nonuniformity, and long-run low GL emphasis; and higher values of superior joint space, mouth opening, saliva Vascular-endothelium-growth-factor, Matrix-metalloproteinase-7, serum Epithelial-neutrophil-activating-peptide, and age indicate recovery likelihood. Our multidimensional and multimodal EHPN tool enhances clinicians' decision-making, offering a transformative translational infrastructure. The EHPN model stands as a significant contribution to precision medicine, offering a paradigm shift in the management of temporomandibular disorders and potentially influencing broader applications in personalized healthcare.