A web-based system for statistical shape analysis in temporomandibular joint osteoarthritis

This study presents a web-system repository: Data Storage for Computation and Integration (DSCI) for Osteoarthritis of the temporomandibular joint (TMJ OA). This environment aims to maintain and allow contributions to the database from multi-clinical centers and compute novel statistics for disease classification. For this purpose, imaging datasets stored in the DSCI consisted of three-dimensional (3D) surface meshes of condyles from CBCT, clinical markers and biological markers in healthy and TMJ OA subjects. A clusterpost package was included in the web platform to be able to execute the jobs in remote computing grids. The DSCI application allowed runs of statistical packages, such as the Multivariate Functional Shape Data Analysis to compute global correlations between covariates and the morphological variability, as well as local p-values in the 3D condylar morphology. In conclusion, the DSCI allows interactive advanced statistical tools for non-statistical experts

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

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

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

Osteoarthritis of the Temporomandibular Joint can be diagnosed earlier using biomarkers and machine learning

After chronic low back pain, Temporomandibular Joint (TMJ) disorders are the second most common musculoskeletal condition affecting 5 to 12% of the population, with an annual health cost estimated at $4 billion. Chronic disability in TMJ osteoarthritis (OA) increases with aging, and the main goal is to diagnosis before morphological degeneration occurs. Here, we address this challenge using advanced data science to capture, process and analyze 52 clinical, biological and high-resolution CBCT (radiomics) markers from TMJ OA patients and controls. We tested the diagnostic performance of four machine learning models: Logistic Regression, Random Forest, LightGBM, XGBoost. Headaches, Range of mouth opening without pain, Energy, Haralick Correlation, Entropy and interactions of TGF-β1 in Saliva and Headaches, VE-cadherin in Serum and Angiogenin in Saliva, VE-cadherin in Saliva and Headaches, PA1 in Saliva and Headaches, PA1 in Saliva and Range of mouth opening without pain; Gender and Muscle Soreness; Short Run Low Grey Level Emphasis and Headaches, Inverse Difference Moment and Trabecular Separation accurately diagnose early stages of this clinical condition. Our results show the XGBoost + LightGBM model with these features and interactions achieves the accuracy of 0.823, AUC 0.870, and F1-score 0.823 to diagnose the TMJ OA status. Thus, we expect to boost future studies into osteoarthritis patient-specific therapeutic interventions, and thereby improve the health of articular joints

Shape variation analyzer: A classifier for temporomandibular joint damaged by osteoarthritis

We developed a deep learning neural network, the Shape Variation Analyzer (SVA), that allows disease staging of bony changes in temporomandibular joint (TMJ) osteoarthritis (OA). The sample was composed of 259 TMJ CBCT scans for the training set and 34 for the testing dataset. The 3D meshes had been previously classified in 6 groups by 2 expert clinicians. We improved the robustness of the training data using data augmentation, SMOTE, to alleviate over-fitting and to balance classes. We combined geometrical features and a shape descriptor, heat kernel signature, to describe every shape. The results were compared to nine different supervised machine learning algorithms. The deep learning neural network was the most accurate for classification of TMJ OA. In conclusion, SVA is a 3D Slicer extension that classifies pathology of the temporomandibular joint osteoarthritis cases based on 3D morphology

Morphofunctional analysis of temporomandibular joint after bilateral discectomy and discopexy : preclinical study

Tese de doutoramento, Medicina (Cirurgia Maxilofacial), Universidade de Lisboa, Faculdade de Medicina, 2018INTRODUCTION The temporomandibular joint (TMJ) is the most used joint in the human body, with over 2000 movements per day, being essential for everyday functions (e.g. mastication, speech, deglution and yawning). The TMJ is responsible for the relation between the mandibular condyle and glenoid fossa of temporal bone. This joint contains an articular disc, an important functional unit interposed between the bony structures, contributing for a congruent movement of this joint. TMJ disorders (TMD) have a prevalence of 34% and represent the main non-tooth origin cause of orofacial pain, leading to high morbidity in severe cases (category 3-5 Dimitroulis classification). In those cases, the treatment is mostly surgical, being the common surgical options discopexy or discectomy. The outcomes of these interventions are a topic of debate, namely in discectomy, once TMJ is left without the TMJ disc. Moreover, in the available scientific literature it is not possible to state any randomized study, blind and with control group, both in human or animals, evaluating the effect of those interventions in TMJ. OBJECTIVES The main goal of this dissertation was evaluating the effect of TMJ discectomy and discopexy in animal model (Black Merino sheep), examining their impact in histologic, imaging and kinematic outcomes. Specific goals: 1. Characterisation of the adequate animal model for preclinical studies in the TMJ. 2. Characterize the anatomy and biomechanics of the native TMJ disc of Black Merino sheep. 3. Develop a study design for preclinical investigation in the TMJ, according to the ARRIVE guidelines 4. Application of the proposed study design on the Black Merino animal model. 5. Propose and test pilot outcomes on the kinematic mastication for preclinical studies in the TMJ and evaluating their impact on bilateral discectomy and bilateral discopexy in Black Merino sheep. 6. Evaluating the histologic and imaging impact of bilateral discectomy and bilateral discopexy in Black Merino sheep. METHODS To achieve the define goals, the following activities were developed and proposed: 1) Characterisation of the adequate animal model for preclinical studies in the TMJ: 15 female Black Merino sheep heads of healthy animals with 40-50 Kg were used to describe the surgical, topographic and histologic anatomy of the TMJ, comparing with the human joint. In a second phase, histologic and biomechanical analysis of the disc were performed. For the anatomical characterisation, a surgical dissection was performed exposing and identifying the TMJ structures. To analyse the TMJ disc, a microsurgical dissection was performed and the TMJ discs were submersed in an impregnated solution (Colorbond), allowing a 3D scanning preserving the morphology of the native disc. To the histologic analysis, the TMJ was removed in block, decalcified in formic acid, included in paraffin and stained with hematoxilin & eosin and orcein. For the biomechanical evaluation, 9 discs were randomized (3 were tested to compression, 3 to anteroposterior strain and 3 to mesiolateral strain). 2) Characterize the anatomy and biomechanics of the native TMJ disc of Black Merino sheep: a microsurgical extraction of 6 discs was completed, removing all the muscular attachments. The discs were submersed in an impregnate solution to preserve their native morphology. A white light system scanner was used, replicating a 3D virtual model with high precision. 3) Develop a study design for preclinical investigation in the TMJ, according to the ARRIVE guidelines: a randomized preclinical trial with 10 sheep was proposed with allocation in 3 intervention groups: bilateral discectomy, bilateral discopexy, sham surgery and one reserve sheep was allocated in a reserve group. A baseline pre-intervention record of body mass, mastication time for 150gr of pellets and rumination kinetics was included. In addition, imaging by computed tomography (CT) was suggested before surgical intervention. It was proposed that the animals would be submitted to surgical intervention and evaluated every 6 months, being posteriorly sacrificed. After sacrifice, a new CT should be done for imaging scoring and discs ought to be prepared for the histologic evaluation. 4) Application of the proposed study design on the Black Merino animal model: the study started in December 2015, the baseline records occurred in January 2016, and the surgical interventions took place in February 2016. According to the established protocol, the animals were monitored for 6 months (with various assessments being performed in specific time points) and were sacrificed in August 2016. 5) Propose and test pilot outcomes on the kinematic mastication for preclinical studies in the TMJ and evaluating their impact on bilateral discectomy and bilateral discopexy in Black Merino sheep: nine specific cages were constructed with a frontal window where all the animals were placed at 08:30 am. The time to eat 150gr of dry pellets Rico Gado A3® was assessed by a chronometer. Following, the animals were placed in their natural habitat and around 01:00 pm they returned to the boxes to record the kinetic rumination of 15 cycles. With adequate software, the trajectory of the jaw was designed during rumination and the time for each cycle was calculated, as well as the ruminant area. Next, the body mass was obtained in a certified balance. 6) Evaluating the histologic and imaging impact of bilateral discectomy and bilateral discopexy in Black Merino sheep: after sacrifice, a cranium CT was performed and the TMJ block was removed. Each block was prepared for histology. In occultation, the different evaluators scored the joint using appropriate scales. 1) The obtained surgical anatomy was similar to the human, with a direct access to TMJ through a pre-auricular incision. The size of the anatomic structures (e.g. temporal fossa, mandibular condyle, inter-articular space and TMJ disc) were also similar to the human. In addition, high similarity was also obtained in the disc histology and biomechanics. A slight concave mandibular condyle was noticed, which is convex in humans. 2) With the proposed method, it was possible to accurately replicate the morphology of the native TMJ disc of Black Merino sheep. The average size was 20.93±1.33mm in the mesiolateral orientation and 11.2±0.78mm in anteroposterior orientation. The thickness of the anterior band was 1.03±0.06mm, the central zone 0.76±0.08mm and the posterior band 1.23±0.07mm. The morphology of the fresh disc showed a slight convexity of the inferior surface, consistent to an adaptive outline to the mandibular condyle. 3) The randomized and blinded study design, with allocation in 3 different bilateral interventions, respecting the ARRIVE guidelines was executed with accuracy and proved to be feasible in Black Merino sheep. The video caption of 15 rumination cycles was achievable, showing this animal the ability to stand still during the rumination. 4) Various histologic changes were noticed in the discectomy and discopexy groups. As expected, the control group presented the main characteristics of the normal TMJ. In the discectomy group, fibrillation and loss of typical laminar structure, with an increased population of proteoglycan stain in all layers and vascular invasion, were observed. In some cases, osteochondral changes were also noticed. The blinded scoring showed statistical significance for the discectomy group only. While no statistical significance, with no loss of the laminar surface, was detected in the discopexy group, a marked proteoglycan increase was noticed. 5) The blinded evaluation of CT images showed statistical significance only for the discectomy group (R2 corresponding to 92.9% of degeneration for global appreciation). In the discopexy group, slight differences were noticed without reaching statistical significance. 6) For both surgical techniques, significant changes were noticed for mastication time in the first month post-operative. Those changes gradually returned to normal and 6 months after surgery no changes were observed. No rumination movements were detected in T1 a T2 after surgery in the discectomy group. In rumination evaluation, a significant difference was stated in T5 for discopexy group with an increased time per cycle. No other changes occurred, neither for rumination time or area. 7) In the first month after surgery, discectomy and discopexy groups loss body mass. However, with the progress of the study, those animals were capable to increase body mass; discectomy group was only capable to return to original weight, and discopexy groups could follow the control group increasing 8% and 8.2% respectively. No significant changes were noticed in the different groups. CONCLUSIONS The Black Merino sheep has proven to be an adequate animal model to conduct TMJ preclinical trials, considering the surgical anatomy, biomechanics and histology like human. Because it is a ruminant animal, it may have an increased value in further studies, examining interposal biomaterials or TMJ prosthesis, and allowing to accurately test the material stress. The proposed randomized, blinded, with bilateral interventions study was feasible and reproducible for TMJ investigation in Black Merino sheep. Discectomy promoted a severe degenerative process in histologic and radiologic analysis, with a repercussion in mastication (only in the first month post-surgery). Discopexy did not induce significant degenerative changes in the TMJ. With a significant role in tissue regeneration, bioengineering and regenerative medicine will be critical to increase and optimize the current surgical techniques, mostly discectomy.Fundação para a Ciência e a Tecnologia (PTDC/EMS-SIS/7032/2014

Cone beam computed tomography in the assessment of TMJ deformity in children with JIA: repeatability of a novel scoring system

Background The temporomandibular joint (TMJ) is frequently involved in juvenile idiopathic arthritis (JIA). Diagnostic imaging is necessary to correctly diagnose and evaluate TMJ involvement, however, hitherto little has been published on the accuracy of the applied scoring systems and measurements. The present study aims to investigate the precision of 20 imaging features and five measurements based on cone beam computed tomography (CBCT). Methods Imaging and clinical data from 84 participants in the Norwegian study on juvenile idiopathic arthritis, the NorJIA study, were collected. Altogether 20 imaging features and five measurements were evaluated independently by three experienced radiologists for intra- and interobserver agreement. Agreement of categorical variables was assessed by Fleiss’, Cohen’s simple or weighted Kappa as appropriate. Agreement of continuous variables was assessed with 95% limits of agreement as advised by Bland and Altman. Results “Overall impression of TMJ deformity” showed almost perfect intraobserver agreement with a kappa coefficient of 0.81 (95% CI 0.69–0.92), and substantial interobserver agreement (Fleiss’ kappa 0.70 (0.61–0.78)). Moreover, both “flattening” and “irregularities” of the eminence/fossa and condyle performed well, with intra- and interobserver agreements of 0.66–0.82 and 0.55–0.76, respectively. “Reduced condylar volume” and “continuity” of the fossa/eminence had moderate intra- and interobserver Kappa values, whereas continuity of the condyle had Kappa values above 0.55. Measurements of distances and angles had limits of agreement of more than 15% of the sample mean. Conclusions We propose a CBCT-based scoring system of nine precise imaging features suggestive of TMJ deformity in JIA. Their clinical validity must be tested.publishedVersio

Cone beam computed tomography in the assessment of TMJ deformity in children with JIA: repeatability of a novel scoring system

Background The temporomandibular joint (TMJ) is frequently involved in juvenile idiopathic arthritis (JIA). Diag‑ nostic imaging is necessary to correctly diagnose and evaluate TMJ involvement, however, hitherto little has been published on the accuracy of the applied scoring systems and measurements. The present study aims to investigate the precision of 20 imaging features and fve measurements based on cone beam computed tomography (CBCT). Methods Imaging and clinical data from 84 participants in the Norwegian study on juvenile idiopathic arthritis, the NorJIA study, were collected. Altogether 20 imaging features and fve measurements were evaluated indepen‑ dently by three experienced radiologists for intra- and interobserver agreement. Agreement of categorical variables was assessed by Fleiss’, Cohen’s simple or weighted Kappa as appropriate. Agreement of continuous variables was assessed with 95% limits of agreement as advised by Bland and Altman. Results “Overall impression of TMJ deformity” showed almost perfect intraobserver agreement with a kappa coef‑ fcient of 0.81 (95% CI 0.69–0.92), and substantial interobserver agreement (Fleiss’ kappa 0.70 (0.61–0.78)). Moreover, both “fattening” and “irregularities” of the eminence/fossa and condyle performed well, with intra- and interobserver agreements of 0.66–0.82 and 0.55–0.76, respectively. “Reduced condylar volume” and “continuity” of the fossa/emi‑ nence had moderate intra- and interobserver Kappa values, whereas continuity of the condyle had Kappa values above 0.55. Measurements of distances and angles had limits of agreement of more than 15% of the sample mean. Conclusions We propose a CBCT-based scoring system of nine precise imaging features suggestive of TMJ deformity in JIA. Their clinical validity must be tested