70 research outputs found

    Diagnostic index: An open-source tool to classify TMJ OA condyles

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    Osteoarthritis (OA) of temporomandibular joints (TMJ) occurs in about 40% of the patients who present TMJ disorders. Despite its prevalence, OA diagnosis and treatment remain controversial since there are no clear symptoms of the disease, especially in early stages. Quantitative tools based on 3D imaging of the TMJ condyle have the potential to help characterize TMJ OA changes. The goals of the tools proposed in this study are to ultimately develop robust imaging markers for diagnosis and assessment of treatment efficacy. This work proposes to identify differences among asymptomatic controls and different clinical phenotypes of TMJ OA by means of Statistical Shape Modeling (SSM), obtained via clinical expert consensus. From three different grouping schemes (with 3, 5 and 7 groups), our best results reveal that that the majority (74.5%) of the classifications occur in agreement with the groups assigned by consensus between our clinical experts. Our findings suggest the existence of different disease-based phenotypic morphologies in TMJ OA. Our preliminary findings with statistical shape modeling based biomarkers may provide a quantitative staging of the disease. The methodology used in this study is included in an open source image analysis toolbox, to ensure reproducibility and appropriate distribution and dissemination of the solution proposed

    Temporomandibular joints’ morphology and osteoarthritic changes in cone-beam computed tomography images in patients with and without reciprocal clicking : a case control study

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    Patients referred for orthodontic treatment often present symptoms of temporomandibular joints’ disorders (TMD), predominantly clicking. The objective was to analyze the morphology of the temporomandibular joints in cone-beam computed tomography (CBCT) images based on the presence of reciprocal clicking before orthodontic treatment. Methods: 105 participants took part in the study. 210 temporomandibular joints (TMJs) were allocated into one of two groups regarding the presence of reciprocal clicking. Morphology of condyle’s head, glenoid fossa, and articular eminence as well as condylar head position in the glenoid fossa and osteoarthritic changes in the area of the condylar head were examined for each TMJ in the CBCT images. Statistical analysis was performed with STATISTICA version 12.0. The following tests were performed: U-Mann Whitney, Kruskal-Wallis, t-Student, and chi-square. The statistical significance level was p = 0.05 for all the measurements included. Results: Significantly smaller condylar A-P dimension (p = 0.040) characterized temporomandibular joints with reciprocal clicking. Condyles were substantially more often positioned posteriorly (p = 0.043) and were significantly more often accompanied by subcortical cysts and pathologic osteoarthritic bone changes (p < 0.001). Conclusions: The early stages of internal derangements stay with alterations in morphology and position of TMJs as well as with the presence of osteoarthritic changes

    A web-based system for neural network based classification in temporomandibular joint osteoarthritis

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    Objective: The purpose of this study is to describe the methodological innovations of a web-based system for storage, integration and computation of biomedical data, using a training imaging dataset to remotely compute a deep neural network classifier of temporomandibular joint osteoarthritis (TMJOA). Methods: This study imaging dataset consisted of three-dimensional (3D) surface meshes of mandibular condyles constructed from cone beam computed tomography (CBCT) scans. The training dataset consisted of 259 condyles, 105 from control subjects and 154 from patients with diagnosis of TMJ OA. For the image analysis classification, 34 right and left condyles from 17 patients (39.9 ± 11.7 years), who experienced signs and symptoms of the disease for less than 5 years, were included as the testing dataset. For the integrative statistical model of clinical, biological and imaging markers, the sample consisted of the same 17 test OA subjects and 17 age and sex matched control subjects (39.4 ± 15.4 years), who did not show any sign or symptom of OA. For these 34 subjects, a standardized clinical questionnaire, blood and saliva samples were also collected. The technological methodologies in this study include a deep neural network classifier of 3D condylar morphology (ShapeVariationAnalyzer, SVA), and a flexible web-based system for data storage, computation and integration (DSCI) of high dimensional imaging, clinical, and biological data. Results: The DSCI system trained and tested the neural network, indicating 5 stages of structural degenerative changes in condylar morphology in the TMJ with 91% close agreement between the clinician consensus and the SVA classifier. The DSCI remotely ran with a novel application of a statistical analysis, the Multivariate Functional Shape Data Analysis, that computed high dimensional correlations between shape 3D coordinates, clinical pain levels and levels of biological markers, and then graphically displayed the computation results. Conclusions: The findings of this study demonstrate a comprehensive phenotypic characterization of TMJ health and disease at clinical, imaging and biological levels, using novel flexible and versatile open-source tools for a web-based system that provides advanced shape statistical analysis and a neural network based classification of temporomandibular joint osteoarthritis

    Minimally Invasive Approach for Diagnosing TMJ Osteoarthritis

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    This study’s objectives were to test correlations among groups of biomarkers that are associated with condylar morphology and to apply artificial intelligence to test shape analysis features in a neural network (NN) to stage condylar morphology in temporomandibular joint osteoarthritis (TMJOA). Seventeen TMJOA patients (39.9 ± 11.7 y) experiencing signs and symptoms of the disease for less than 10 y and 17 age- and sex-matched control subjects (39.4 ± 15.2 y) completed a questionnaire, had a temporomandibular joint clinical exam, had blood and saliva samples drawn, and had high-resolution cone beam computed tomography scans taken. Serum and salivary levels of 17 inflammatory biomarkers were quantified using protein microarrays. A NN was trained with 259 other condyles to detect and classify the stage of TMJOA and then compared to repeated clinical experts’ classifications. Levels of the salivary biomarkers MMP-3, VE-cadherin, 6Ckine, and PAI-1 were correlated to each other in TMJOA patients and were significantly correlated with condylar morphological variability on the posterior surface of the condyle. In serum, VE-cadherin and VEGF were correlated with one another and with significant morphological variability on the anterior surface of the condyle, while MMP-3 and CXCL16 presented statistically significant associations with variability on the anterior surface, lateral pole, and superior-posterior surface of the condyle. The range of mouth opening variables were the clinical markers with the most significant associations with morphological variability at the medial and lateral condylar poles. The repeated clinician consensus classification had 97.8% agreement on degree of degeneration within 1 group difference. Predictive analytics of the NN’s staging of TMJOA compared to the repeated clinicians’ consensus revealed 73.5% and 91.2% accuracy. This study demonstrated significant correlations among variations in protein expression levels, clinical symptoms, and condylar surface morphology. The results suggest that 3-dimensional variability in TMJOA condylar morphology can be comprehensively phenotyped by the NN

    Temporomandibular Joint Anatomy Assessed by CBCT Images

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    Osteoarthritis of the Temporomandibular Joint: Clinical and Imagenological Diagnosis, Pathogenic Role of the Immuno- Inflammatory Response, and Immunotherapeutic Strategies Based on T Regulatory Lymphocytes

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    Osteoarthritis is a degenerative disease affecting the TMJ. It is the most common TMJ disorder and shows a higher prevalence in women and older people. TMJ osteoarthritis (TMJ-OA) is characterized by variable degrees of inflammation, destruction of the articular cartilage, and sub-chondral bone resorption. In this context, diverse pro-inflammatory cytokines, chemokines, enzymes, and bone-resorptive associated factors have been considered as possible markers of active TMJ-OA. The molecular balance is determinant not only for initiation and progression, but also for the clinical expression of the disease. Recent advances in the biochemical analysis of synovial fluid from affected patients have provided new insights into the patho-physiology of the TMJ-OA; however, its molecular pathogenesis still remains unclear. Recently, a Th1 and Th17-dominated immune response has been associated with the inflammatory and destructive events characteristic of TMJ-OA and, in particular, the Th17 lymphocyte pathway has a pivotal role in the increased production of RANKL, which is involved in osteoclast activation and subsequent sub-chondral bone resorption. Understanding the TMJ physiology and pathogenesis of the TMJ-OA, together with the key molecular determinants of the TMJ tissue destruction, will enable the development of new chair-side point of care diagnostics and more conservative treatment modalities with minimal complications

    Association between condylar asymmetry and temporo-mandibular disorders using 3D-CT

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    Objectives: Using reconstructed three-dimensional computed tomography (3D-CT) models, the purpose of this study was to analyze and compare mandibular condyle morphology in patients with and without temporomandibular disorder (TMD). Study Design: Thirty-two patients were divided into two groups: the first comprised those with TMD (n=18), and the second those who did not have TMD (n=14). A CT of each patient was obtained and reconstructed as a 3D model. The 64 resulting 3D condylar models were evaluated for possible TMD-associated length, width and height asymmetries of the condylar process. Descriptive statistics were used to assess the results and student?s t tests applied to compare the two groups. Results: Statistically significant (p<0.05) vertical, mediolateral and sagittal asymmetries of the condylar process were observed between TMD and non-TMD groups. TMD patients showed less condylar height (p<0.05) in comparison with their asymptomatic counterparts. Conclusions: Using 3D-CT, it was shown that condylar width, height and length asymmetries were a common feature of TM

    Association of Condylar Bone Quality with TMJ Osteoarthritis

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    The etiology and treatment of temporomandibular joint (TMJ) osteoarthritis (TMJOA) remain complex and unclear. Based on clinical observations, we hypothesized that low condylar bone quality is significantly correlated with TMJOA and explored this association in a cross-sectional study with human patients. A total of 254 postmenopausal female participants were included in this study. Radiographic findings from cone beam computed tomography (CBCT) and clinical symptoms were used to classify each TMJ data sample as healthy control ( n = 124) or TMJOA ( n = 130). Condylar bone mineral density (BMD) (computed tomography Hounsfield unit [CT HU]) and bone volume fraction (BV/TV) were measured and modeled as predictors of healthy control versus TMJOA status in multilevel logistic regression analyses. Both CT HU (adjusted odds ratio [AOR] = 0.9989, interquartile odds ratio [IOR] = 0.4206) and BV/TV (AOR= 0.8096, IOR = 0.1769) were negatively associated with TMJOA ( P = 0.049, 0.011, respectively). To assess the diagnostic performance of CT HU and BV/TV for identification of TMJOA, receiver operating characteristic (ROC) curves were plotted. The estimated areas under the curve (AUC) were 0.6622 for BV/TV alone, 0.6074 for CT HU alone, and 0.7136 for CT HU and BV/TV together. The model incorporating CT HU and BV/TV together had a significantly higher AUC than the models using BV/TV alone ( P = 0.038) or HU alone ( P = 0.021). In conclusion, we found that low condylar bone quality was significantly correlated with TMJOA development and that condylar CT HU and BV/TV can be used together as a potential diagnostic tool for TMJOA. Careful clinical evaluation of the condyle coupled with appropriate radiographic interpretation would thus be critical for the early detection of TMJOA.ope

    Relationship between posterior permanent dentition pattern and radiographic changes of the mandibular condyle

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    This study assessed the relationship between posterior permanent dentition and radiographic changes of the mandibular condyle. This descriptive, cross-sectional study was conducted on 300 panoramic radiographs of patients over 40 years of age (188 females and 112 males). Panoramic radiographs were evaluated for condylar changes such as flattening, subcortical sclerosis, subcortical cyst, erosion, osteophytes, and generalized sclerosis. Presence of muscle pain and temporomandibular joint (TMJ) pain and sounds, and history of TMJ trauma were also assessed. The occlusal scheme of posterior teeth was analyzed according to the Eichner’s index. The frequency of condylar changes was calculated in the right and left sides, and their association with posterior permanent dentition was analyzed by the Chi-square test (alpha = 0.05). The frequency of flattening, muscle pain, TMJ sounds, and erosion was 11.7%, 9.7%, 5.7%, and 3.7% in the right side, respectively. The frequency of flattening, muscle pain, erosion, and subcortical cyst was 12%, 9.3%, 5%, and 5% in the left side, respectively. The frequency of bilateral muscle pain, flattening, TMJ sounds, and TMJ pain was 18%, 16.7%, 11.7%, and 9.3%, respectively. Cases with TMJ trauma, generalized sclerosis, and osteophytes were few. According to the Eichner’s index, most patients with condylar changes had classes A and B, and a smaller percentage had class C. No significant difference was noted between healthy individuals and those with condylar changes regarding dentition patterns. No relationship existed between condylar changes and posterior permanent dentition pattern
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