3D superimposition and understanding temporomandibular joint arthritis

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/111112/1/ocr12070.pd

SVA: Shape variation analyzer

Temporo-mandibular osteo arthritis (TMJ OA) is characterized by progressive cartilage degradation and subchondral bone remodeling. The causes of this pathology remain unclear. Current research efforts are concentrated in finding new biomarkers that will help us understand disease progression and ultimately improve the treatment of the disease. In this work, we present Shape Variation Analyzer (SVA), the goal is to develop a noninvasive technique to provide information about shape changes in TMJ OA. SVA uses neural networks to classify morphological variations of 3D models of the mandibular condyle. The shape features used for training include normal vectors, curvature and distances to average models of the condyles. The selected features are purely geometric and are shown to favor the classification task into 6 groups generated by consensus between two clinician experts. With this new approach, we were able to accurately classify 3D models of condyles. In this paper, we present the methods used and the results obtained with this new tool

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

Clinical application of SPHARM-PDM to quantify temporomandibular joint osteoarthritis

The severe bone destruction and resorption that can occur in Osteoarthritis of the Temporomandibular Joint (TMJ) is associated with significant pain and limited joint mobility. However, there is no validated method for the quantification of discrete changes in joint morphology in early diagnosis or assessment of disease progression or treatment effects. To achieve this, the objective of this cross-sectional study was to use simulated bone resorption on cone-beam CT (CBCT) to study condylar morphological variation in subjects with temporomandibular joint (TMJ) osteoarthritis (OA). The first part of this study assessed the hypothesis that the agreement between the simulated defects and the shape analysis measurements made of these defects would be within 0.5mm (the image’s spatial resolution). One hundred seventy-nine discrete bony defects measuring 3mm and 6mm were simulated on the surfaces of 3D models derived from CBCT images of asymptomatic patients using ITK-Snap software. SPHARM shape correspondence was used to localize and quantify morphological differences of each resorption model with the original asymptomatic control. The size of each simulated defect was analyzed and the values obtained compared to the true defect size. The statistical analysis revealed very high probabilities that mean shape correspondence measured defects within 0.5mm of the true defect size. 95% confidence intervals (CI) were (2.67,2.92) and (5.99,6.36) and 95% prediction intervals (PI) were (2.22,3.37) and (5.54, 6.82), respectively for 3mm and 6mm simulated defects. The second part of this study applied shape correspondence methods to a longitudinal sample of TMJ OA patients. The mapped longitudinal stages of TMJ OA progression identified morphological variants or subtypes, which may explain the heterogeneity of the clinical presentation. This study validated shape correspondence as a method to precisely and predictably quantify 3D condylar resorption

Cone beam computed tomography-based models versus multislice spiral computed tomography-based models for assessing condylar morphology

To quantitatively compare condylar morphology using CBCT and MSCT virtual 3D surface models

Federating heterogeneous datasets to enhance data sharing and experiment reproducibility

Recent studies have demonstrated the difficulties to replicate scientific findings and/or experiments published in past.1 The effects seen in the replicated experiments were smaller than previously reported. Some of the explanations for these findings include the complexity of the experimental design and the pressure on researches to report positive findings. The International Committee of Medical Journal Editors (ICMJE) suggests that every study considered for publication must submit a plan to share the de-identified patient data no later than 6 months after publication. There is a growing demand to enhance the management of clinical data, facilitate data sharing across institutions and also to keep track of the data from previous experiments. The ultimate goal is to assure the reproducibility of experiments in the future. This paper describes Shiny-tooth, a web based application created to improve clinical data acquisition during the clinical trial; data federation of such data as well as morphological data derived from medical images; Currently, this application is being used to store clinical data from an osteoarthritis (OA) study. This work is submitted to the SPIE Biomedical Applications in Molecular, Structural, and Functional Imaging conference

A 3D Imaging and Biological Marker Analysis of TMJ OA: A New Modeling Technique

Aim: To investigate 3D morphology and biomarker profiles in a population of early onset TMJ Osteoarthritis (TMJ OA) subjects. Methods: Twelve subjects and controls underwent an exam and obtained a Cone beam CT (CBCT), as well as TMJ arthrocentesis and venipuncture. CBCT Datasets were used to construct 3D models of all condyles. Average OA and health models were created. 3D Shape Correspondence determined areas of statistically significant difference between models. Protein microarrays were used to analyze the synovial fluid (SF) and plasma samples. Shape Analysis MANCOVA was used to look for statistical correlations between biomarker levels and variations in surface morphology. Results: The average OA model demonstrated a smaller size with areas of statistically significant difference. 32 biomarkers were measured in the plasma and/or SF samples. Shape Analysis MANCOVA successfully mapped variations in 10 SF and 20 plasma biomarkers to specific regions of anatomic variability in the OA group.Master of Scienc

Morphological Differences of the Articulating Surfaces of Mandibular Condyles in C3H/HeJ and A/J Mice

Characterize the normal variation of the articulating surfaces of mandibular condyle morphologies during periods of growth within and between two strains of mice (A/J and C3H/HeJ) using 3D micro-CT analysis and determine which parts of the microanatomy of the articulating surfaces of the condyle are less susceptible to morphologic variation during skeletal growth. Methods: Cross sectional study utilized micro-CT scans of the condyles of two strains of mice (A/J and C3H/HeJ) at 3-5 wks, 6-8 wks and 9-11 wks of age. Virtual 3D surface models were created, analyzed and computed using shape analysis methods. Results: There is inter-strain variation in condyle morphologies among inbred strains and at each age group. For A/J condylar growth the greatest differences in morphologic change occurs between 3-5 weeks and 6-8 weeks of age with little change thereafter. For the C3H/HeJ strain condylar growth and morphology continued to change beyond 6-8 weeks of age. The anterior and the posterior surfaces of the condyles tended to vary greatest in morphology. Conclusions: Condyles of A/J inbred of mice reach a morphologic plateau around 6-8 weeks of age whereas C3H/HeJ inbred of mice condyles continue morphologic change and growth after 6-8 weeks. Inbred mice despite being isogenic still present shape differences in anatomical structures such as the condyle.Master of Scienc

Three-dimensional regional displacement after surgical-orthodontic correction of Class III malocclusion

To investigate how displacements of maxillo-mandibular structures are associated with each other at splint removal and one year post-surgery following 1-jaw and 2-jaw surgeries for correction of Class III malocclusion

Temporomandibular Joint Condylar Changes Following Maxillomandibular Advancement and Articular Disc Repositioning

To evaluate condylar changes 1 year after bimaxillary surgical advancement with or without articular disc repositioning using longitudinal quantitative measurements in 3-dimensional (3D) temporomandibular joint (TMJ) models