Temporomandibular disorders (TMD) are a collection of clinical disorders which involve the temporomandibular joints (TMJ), the muscles of mastication, and associated structures.1
TMD affects approximately 10% of the population and is more prevalent in women.2
The associated pain and limited mouth opening can lead to severe functional impairment and disability.3
TMJ osteoarthritis(OA) is a local inflammatory condition which occurs when the dynamic equilibrium between the breakdown and the repair of joint tissue is compromised. The spectrum of clinical and pathological presentation of TMJ OA range from structural and functional failure of the joint with disc displacement and degeneration, to subchondral bone alterations (erosions), bone overgrowth (osteophytes), loss of articular fibrocartilage, and synovitis._Local inflammatory processes in the TMJ are known to share common pathways with pain and bone resorption.4-9
However, the factors which mitigate the morphological changes and clinical signs and symptoms (such as pain and joint sounds) is unknown.10
Furthermore, the multitude of risk factors, the complex etiopathogenesis, and the heterogeneity of clinical presentation create a challenge for developing novel therapies.11,12
The Research Diagnostic Criteria for Temporomandibular Disorders (RDC/TMD)13
was revised recently to include image analysis criteria for various imaging modalities.14
Reportedly, Computed Tomography (CT) has the best positive percentage agreement (84%) for the diagnosis of TMJ OA. In concordance with these guidelines 42.6% of TMD patients presented with tomographic evidence of TMJ OA changes including bone erosions and osteophytes.15
However, previous studies attempting to correlate two-dimensional (2D) and three-dimensional (3D) cross-sectional radiographic changes of the TMJ to clinical signs and symptoms have yield mixed findings.3,15,16
Refinement in image analysis for accurate visualization by reconstruction of 2D and cross-sectional images into 3D may enable the localization and quantification of previously unidentified condylar resorption patterns and reveal important relationship between the morphological variance and the clinical symptoms.17
Shape Correspondence (SC), a 3D surface mapping technique using CBCT images, was developed for the precise localization and quantification of the extent of resorptive changes in mandibular condyles.18,19
Computer-based methods allow for the development and widespread use of imaging biomarkers (i.e., joint space narrowing and erosions), which may have an impact in clinical decision making, for drug development, and for monitoring of treatment. The transition of OA assessment toward an automatic quantification system minimizes the influence of the reader experience, and thus decreases inter- and intra-reader variability. The automation allows for a remote analysis over the Internet, which is particularly relevant for future multicenter clinical trials that require a consistent assessment of the data. The tracking of individual erosive destructions can lead to a more fundamental understanding of the fine interactions within the disease process, even for large populations, which are difficult to grasp with global scores that are determined manually. This system is already in experimental use. Ongoing research is focused on clinical evaluation in a large population and the integration of follow-up examinations (erosion tracking) in the assessment of the disease progression. This work can play a role in the rapidly evolving field of biomedical imaging research, leading from discrete scales toward continuous imaging biomarkers in musculoskeletal radiology.
With this advanced method, we proposed to investigate the influence of pain and disease duration on the degree of condylar destruction in patients with TMJ OA. Such novel findings will improve the diagnostic yield and consequently, direct the timing and type of therapeutic interventions aimed at preventing further TMJ degradation and pain. Using this technique, the objectives of this study were to: (1) assess the 3D condylar morphology and evaluate the extent of condylar resorption in TMJ OA; (2) determine the difference in location and extent of condylar resorptive changes between osteoarthritic and asymptomatic TMJs; and (3) assess the correlation of the severity of resorption of osteoarthritic condyles with pain intensity and duration.