A Skeleton in a Huff: Insights in Etiologies of Osteosclerosis.

A 30-year-old man developed right lower leg pain and a palpable solid mass. Radiographic imaging revealed a periosteal reaction with an exostotic mass arising from the right distal fibula. Generalized skeletal osteosclerosis with periosteal reaction was discovered on a radiographic skeletal survey. A biopsy of the right fibular mass revealed reactive woven bone. The patient was referred to a metabolic bone disease clinic, where laboratory values were consistent with secondary hyperparathyroidism and increased bone turnover. A DXA bone density scan revealed high bone density, with an L1-4 spine Z-score of +9.3, a left femoral neck Z-score of +8.5, and a total hip Z-score of +6.5. A dental exam revealed generalized gingival inflammation, teeth mobility, generalized horizontal alveolar bone loss and widening of the periodontal ligament space, increased bone density around the teeth, and thickening of the radicular lamina dura. An extensive evaluation was performed, with the result of a single test revealing the diagnosis. The differential diagnoses of osteosclerosis affecting the skeleton, teeth, and oral cavity are discussed.

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.

Optimizing radiation safety in dentistry: Clinical recommendations and regulatory considerations.

BACKGROUND: The value of dental radiographs to oral health care decision making must be balanced with radiation safety to minimize patient exposure and occupational risk of oral health care providers. This review summarizes recommendations and regulatory guidance regarding dental radiography and cone-beam computed tomography. An expert panel presents recommendations on radiation safety, appropriate imaging practices, and reducing radiation exposure. TYPES OF STUDIES REVIEWED: A systematic search run in Ovid MEDLINE, Embase, and Cochrane Database of Systematic Reviews identified relevant topical systematic reviews, organizational guidelines, and regulatory reviews published in the peer-reviewed literature since 2010. A supplemental search of the gray literature (eg, technical reports, standards, and regulations) identified topical nonindexed publications. Inclusion criteria required relevance to primary oral health care (ie, general or pediatric dentistry). RESULTS: A total of 95 articles, guidance documents, and regulations met the inclusion criteria. Resources were characterized as applicable to all modalities, operator and occupational protection, dose reduction and optimization, and quality assurance and control. PRACTICAL IMPLICATIONS: Understanding factors affecting imaging safety and applying fundamental principles of radiation protection consistent with federal, state, and local requirements are essential for limiting patient ionizing radiation exposure, in conjunction with implementing optimal imaging procedures to support prudent use of dental radiographs and cone-beam computed tomographic imaging. The regulatory guidance and best practice recommendations summarized in this article should be followed by dentists and other oral health care providers.

Asymmetry in Class II subdivision malocclusion: Assessment based on 3D surface models.

INTRODUCTION: There is currently no consensus in the literature whether the aetiology of a Class II subdivision is dental, skeletal or both. The aim of this study was to identify and quantify skeletal and dental asymmetries in Class II subdivision malocclusions. METHODS: CBCTs from 33 Class II subdivision malocclusion patients were used to construct 3D volumetric label maps. Eighteen landmarks were identified. The original scan and associated 3D volumetric label map were mirrored. Registration of the original and mirrored images relative to the anterior cranial base, maxilla and mandible were performed. Surface models were generated, and 3D differences were quantified. Statistical analysis was performed. RESULTS: Anterior cranial base registration showed significant differences for fossa vertical difference, fossa roll, mandibular yaw, mandibular lateral displacement and lower midline displacement. Regional registrations showed significant differences for antero-posterior (A-P) mandibular length, maxillary roll, A-P maxillary first molar position, maxillary first molar yaw and maxillary first molar roll. Class II subdivision patients also show an asymmetric mandibular length as well as an asymmetric gonial angle. Moderate correlations were found between the A-P molar relationship and fossa A-P difference, mandibular first molar A-P difference, maxillary first molar A-P difference and maxillary first molar yaw. CONCLUSIONS: This study suggests that Class II subdivisions can result from both significant skeletal and dental factors. Skeletal factors include a shorter mandible as well as posterior and higher displacement of the fossa on the Class II side, resulting in mandibular yaw. Dental factors include maxillary and mandibular first molar antero-posterior asymmetry.

Three-dimensional Evaluation of the Carriere Motion 3D Appliance in the treatment of Class II malocclusion.

INTRODUCTION: This study aimed to quantify the outcomes of adolescent patients with Class II malocclusion treated with the Carriere Motion 3D Appliance (CMA) combined with full fixed appliances. METHODS: Cone-beam computed tomography scans of 22 patients were available before orthodontic treatment (T1), at removal of the CMA (T2), and posttreatment (T3). The average age of the patients was 13.5 ± 1.6 years at T1, 14.1 ± 0.2 years at T2, and 15.6 ± 0.5 years at T3. The 3-dimensional image analysis procedures were performed using ITK-SNAP (version 3.6.0; www.itksnap.org, Hatfield, Pa) and SlicerCMF (version 4.11.0; http://www.slicer.org, Cambridge, Mass); skeletal and dentoalveolar changes relative to cranial base, maxillary, and mandibular regional superimpositions were evaluated. RESULTS: Changes were analyzed with 1 sample t tests using the mean differences during the CMA phase (T1 to T2) and total treatment time (T1 to T3). Significant skeletal changes included a slight reduction of ANB from T1 to T3, mandibular growth (Co-Gn increment of 1.2 mm and 3.3 mm from T1 to T2 and T1 to T3, respectively), inferior displacement of point A, and anterior and inferior displacement of point B. The mandibular plane did not change significantly during treatment. During the CMA treatment, posterior tipping and distal rotation of the maxillary molars, tip back and inferior displacement of the maxillary canines, significant mesial rotation, and superior displacement of the mandibular molars were observed. These movements rebounded during the full fixed appliance phase except for the molar and canine vertical displacements. Clinically significant dental changes during treatment included a reduction in overjet and overbite, Class II correction of the molar and canine relationship, and proclination of the mandibular incisors. CONCLUSIONS: The CMA is an effective treatment modality for Class II correction in growing patients because of a combination of mesial movement of the mandibular molar, distal rotation of the maxillary molar, and anterior displacement of the mandible.

Patient shielding during dentomaxillofacial radiography: Recommendations from the American Academy of Oral and Maxillofacial Radiology.

BACKGROUND: The American Academy of Oral and Maxillofacial Radiology established an ad hoc committee to draft evidence-based recommendations and clinical guidance for the application of patient contact shielding during dentomaxillofacial imaging. TYPES OF STUDIES REVIEWED: The committee reviewed monographs and reports from radiation protection organizations and studies that reported radiation dose to gonads, breasts, and thyroid gland from dentomaxillofacial imaging. RESULTS: Considering the absence of radiation-induced heritable effects in humans and the negligible dose to the gonads and fetus from dentomaxillofacial imaging, the committee recommends discontinuing shielding of the gonads, pelvic structures, and fetuses during all dentomaxillofacial radiographic imaging procedures. On the basis of radiation doses from contemporaneous maxillofacial imaging, the committee considered that the risks from thyroid cancer are negligible and recommends that thyroid shielding not be used during intraoral, panoramic, cephalometric, and cone-beam computed tomographic imaging. PRACTICAL IMPLICATIONS: This position statement informs and educates the reader on evolving radiation protection practices and provides simple, unequivocal guidance to dental personnel to implement these guidelines. State and local authorities should be contacted to update regulations to reflect these recommendations.

Clear aligner mandibular advancement in growing patients with Class II malocclusion.

Treatment effects occurring during Class II malocclusion treatment with the clear aligner mandibular advancement protocol were evaluated in two growing patients: one male (12 years, 3 months) and one female (11 years, 9 months). Both patients presented with full cusp Class II molar and canine relationships. Intraoral scans and cone-beam computed tomography were acquired before treatment and after mandibular advancement. Three-dimensional skeletal and dental long-axis changes were quantified, in which the dental long axis was determined by registering the dental crowns obtained from intraoral scans to the root canals in cone-beam computed tomography scans obtained at the same time points. Class II correction was achieved by a combination of mandibular skeletal and dental changes. A similar direction of skeletal and dental changes was observed in both patients, with downward and forward displacement of the mandible resulting from the growth of the mandibular condyle and ramus. Dental changes in both patients included mesialization of the mandibular posterior teeth with flaring of mandibular anterior teeth. In these two patients, clear aligner mandibular advancement was an effective treatment modality for Class II malocclusion correction with skeletal and dental effects and facial profile improvement.

Three-dimensional decision support system for treatment of canine impaction.

INTRODUCTION: This study aimed to develop a 3-dimensional (3D) characterization of the severity of maxillary impacted canines and to test the clinical performance of this characterization as a treatment decision support tool. METHODS: Cone-beam computed tomography images obtained from 83 patients with 120 impacted maxillary canines were included. Quantitative information on the canine 3D position and qualitative assessment of root damage of adjacent teeth were evaluated. A severity index was constructed on the basis of the quantitative findings. Clinical applicability was tested by comparing clinical diagnosis and treatment planning for conventional records vs the 3D characterization via a 2-part survey. RESULTS: The average quantitative assessments of impacted maxillary canine position were 6.4 ± 3.6 mm from the midsagittal plane, 11.6 ± 3.1 mm in height relative to the occlusal plane, 31.5° ± 18° of roll, and 48.8° ± 14.3° of pitch. The severity index ranged from 0-13 with a mean score of 4.5 ± 2.2. Overlap with adjacent teeth was the greatest contributor (33%) to the index. Bicortically impacted canines caused the most severe root damage. Cone-beam computed tomography was preferred for assessing root damage and overall severity, whereas conventional imaging was sufficient for height and angulation assessment. The 3D report was very important or important for evaluating root damage, canine position, overall severity, and overlap. The 3D report changed most of the decisions relating to biomechanics, patient education, and treatment time estimate. The decision of exposure and traction vs extraction was changed 22% of the time after the presentation of the 3D report. CONCLUSIONS: The overlap with adjacent teeth frequently contributes the most to the severity index. The 3D report provided relevant clinical information regarding the canine position, damage to adjacent teeth, and the severity index, with a profound impact on the decisions of the clinicians regarding biomechanics, patient education, and treatment time estimate.

Student learning of head and neck anatomy using cone beam computed tomography and immersive virtual reality.

OBJECTIVES: The purpose of this study was to evaluate the efficacy of student learning of anatomy and 3D imaging concepts using cone beam computed tomography (CBCT) and immersive virtual reality (VR) technology. METHODOLOGY: Ninety (n = 90) first year dental students with no previous experience in 3D imaging were recruited. All participants completed a 10-item, multiple-choice questionnaire (MCQ) and a pre-survey prior to the educational intervention. Following a brief video orientation on CBCT and anatomy, each participant underwent a one-on-one educational intervention using immersive VR with calibrated instructors to identify head and neck anatomic structures using a VR/CBCT educational tool. Immediately following the intervention, all participants completed a postsurvey, a second MCQ, NASA task load index and presence questionnaires. Participants completed a third MCQ 2 weeks following the intervention. Analysis of objective measures of performance on MCQ's (p < 0.05) and subjective data from the questionnaires was completed. RESULTS: The students doubled their mean test scores 2.45 ± 1.274 to 5.99 ± 1.576 on MCQ's immediately following the educational intervention (p < 0.05). The significant increase in the MCQ test scores was maintained after 2 weeks, 5.73 ± 1.721 (p < 0.05). There were no gender differences in student test performance. Students rated the immersive VR/CBCT educational intervention experience highly for control, sensory, and realism factors with minimal distraction and frustration factors. CONCLUSION: Results from this study show that immersive VR/CBCT educational intervention improved test performance and contributed to information recall in students. Further benefits reported by participants include the sense of presence and increased engagement using immersive VR.

Three-Dimensional Assessment of Radiographic Changes after Indirect Pulp Capping Using Silver Diamine Fluoride with or without Potassium Iodide in Young Permanent Teeth (12-Month RCT).

The aim of this study was to conduct a three-dimensional (3D) evaluation of radiographic changes after indirect pulp capping (IPC) with silver diamine fluoride (SDF) with or without potassium iodide (KI) and resin-modified glass ionomer cement (RMGIC) in deep carious young permanent molars using cone-beam computed tomography (CBCT). 108 first permanent molars with deep occlusal cavitated caries lesions, in forty-nine 6- to 9-year-old children, were randomly allocated to one of 3 groups (n = 36) and treated with SDF+KI, SDF, and RMGIC as IPC materials. CBCT scans were taken at 0 and 12 months to assess tertiary dentin formation (volume and grey level intensity), increase in root length, and pathological changes such as secondary caries, periapical radiolucency, internal resorption, and obliteration of the pulp. The 3D image analysis procedures were performed using ITK-SNAP and 3D Slicer CMF. Comparisons were made using analysis of variance with a fixed effect for treatment and random effects for patient and patient-by-treatment to account for within-patient correlations. A two-sided 5% significance level was used. There were no significant differences among the three groups regarding tertiary dentin volume (p = 0.712) and grey level intensity (p = 0.660), increase in root length (p = 0.365), prevention of secondary caries (p = 0.63), and periapical radiolucency (p = 0.80) in the analysed 69 CBCT scans. The study did not find differences among the groups regarding quality and quantity of tertiary dentin formed, increase in root length, absence of secondary caries, and other signs of failure as shown by CBCT. Clinical Significance: The results show no significant differences in radiographic outcomes (quality and quantity of tertiary dentin formed, increase in root length, absence of secondary caries, and other signs of failure) when using SDF+KI, SDF, and RMGIC in IPC. The results of this study can help guide treatment decision-making regarding use of SDF and SDF+KI as IPC materials in deep cavitated lesions.

Quantitative bone imaging biomarkers and joint space analysis of the articular Fossa in temporomandibular joint osteoarthritis using artificial intelligence models.

Temporomandibular joint osteoarthritis (TMJ OA) is a disease with a multifactorial etiology, involving many pathophysiological processes, and requiring comprehensive assessments to characterize progressive cartilage degradation, subchondral bone remodeling, and chronic pain. This study aimed to integrate quantitative biomarkers of bone texture and morphometry of the articular fossa and joint space to advance the role of imaging phenotypes for diagnosis of Temporomandibular Joint Osteoarthritis (TMJ OA) in early to moderate stages by improving the performance of machine-learning algorithms to detect TMJ OA status. Ninety-two patients were prospectively enrolled (184 h-CBCT scans of the right and left mandibular condyles), divided into two groups: 46 control and 46 TMJ OA subjects. No significant difference in the articular fossa radiomic biomarkers was found between TMJ OA and control patients. The superior condyle-to-fossa distance (p < 0.05) was significantly smaller in diseased patients. The interaction effects of the articular fossa radiomic biomarkers enhanced the performance of machine-learning algorithms to detect TMJ OA status. The LightGBM model achieved an AUC 0.842 to diagnose the TMJ OA status with Headaches and Range of Mouth Opening Without Pain ranked as top features, and top interactions of VE-cadherin in Serum and Angiogenin in Saliva, TGF-ß1 in Saliva and Headaches, Gender and Muscle Soreness, PA1 in Saliva and Range of Mouth Opening Without Pain, Lateral Condyle Grey Level Non-Uniformity and Lateral Fossa Short Run Emphasis, TGF-ß1 in Serum and Lateral Fossa Trabeculae number, MMP3 in Serum and VEGF in Serum, Headaches and Lateral Fossa Trabecular spacing, Headaches and PA1 in Saliva, and Headaches and BDNF in Saliva. Our preliminary results indicate that condyle imaging features may be more important in regards to main effects, but the fossa imaging features may have a larger contribution in terms of interaction effects. More studies are needed to optimize and further enhance machine-learning algorithms to detect early markers of disease, improve prediction of disease progression and severity to ultimately better serve clinical decision support systems in the treatment of patients with TMJ OA.

Automatic multi-anatomical skull structure segmentation of cone-beam computed tomography scans using 3D UNETR.

The segmentation of medical and dental images is a fundamental step in automated clinical decision support systems. It supports the entire clinical workflow from diagnosis, therapy planning, intervention, and follow-up. In this paper, we propose a novel tool to accurately process a full-face segmentation in about 5 minutes that would otherwise require an average of 7h of manual work by experienced clinicians. This work focuses on the integration of the state-of-the-art UNEt TRansformers (UNETR) of the Medical Open Network for Artificial Intelligence (MONAI) framework. We trained and tested our models using 618 de-identified Cone-Beam Computed Tomography (CBCT) volumetric images of the head acquired with several parameters from different centers for a generalized clinical application. Our results on a 5-fold cross-validation showed high accuracy and robustness with a Dice score up to 0.962±0.02. Our code is available on our public GitHub repository.

Patterns of radiograph use in a population of commercially insured children.

BACKGROUND: The objective of this study was to evaluate differences in number and type of radiographs used among 3 age groups (0-5, 6-12, 13-18 years) by general dentists, pediatric dentists, and other specialists, and to determine the association between number and type of radiographs and clinical need. METHODS: A retrospective analysis of insurance claims by age group and oral health care provider type included children aged 0 through 8 years in 2005 who had a minimum of 10 years of continuous eligibility. Indicator claim variables were calculated to identify high-risk, high-need patients. RESULTS: A total of 6,712,155 records from 105,010 patients and 34,406 providers were analyzed. There was a significant effect (P < .001) of age on the number of radiographs obtained per visit. The estimated rates of radiographs per visit for ages 0 through 5, 6 through 12, and 13 through 18 were 0.373, 0.492, and 0.393, respectively. There was a significant interaction effect between age and provider type. For patients younger than 13 years, general dentists had lower rates of obtaining radiographs than did pediatric dentists, with no significant difference between providers for the 13- through 18-year age group. Treatments received, except for extractions and prosthodontics, were significantly associated with rate of radiographs per visit, with "number of restorations" as an indicator of increased risk, need, or both showing an inverse association with radiograph use. CONCLUSIONS: Child age and provider type had an effect on number of radiographs obtained per visit. Lack of caries diagnostic codes and uncommon use of risk codes hindered interpretation of whether use, frequency, or both is associated with need. PRACTICAL IMPLICATIONS: Radiograph use should follow existing guidelines or recommendations based on clinical need.

Temporomandibular Joint Osteoarthritis Diagnosis Using Privileged Learning of Protein Markers.

Diagnosis of temporomandibular joint (TMJ) Osteoarthritis (OA) before serious degradation of cartilage and subchondral bone occurs can help prevent chronic pain and disability. Clinical, radiomic, and protein markers collected from TMJ OA patients have been shown to be predictive of OA onset. Since protein data can often be unavailable for clinical diagnosis, we harnessed the learning using privileged information (LUPI) paradigm to make use of protein markers only during classifier training. Three different LUPI algorithms are compared with traditional machine learning models on a dataset extracted from 92 unique OA patients and controls. The best classifier performance of 0.80 AUC and 75.6 accuracy was obtained from the KRVFL+ model using privileged protein features. Results show that LUPI-based algorithms using privileged protein data can improve final diagnostic performance of TMJ OA classifiers without needing protein microarray data during classifier diagnosis.

Automatic Segmentation of Dental Root Canal and Merging with Crown Shape.

In this paper, machine learning approaches are proposed to support dental researchers and clinicians to study the shape and position of dental crowns and roots, by implementing a Patient Specific Classification and Prediction tool that includes RootCanalSeg and DentalModelSeg algorithms and then merges the output of these tools for intraoral scanning and volumetric dental imaging. RootCanalSeg combines image processing and machine learning approaches to automatically segment the root canals of the lower and upper jaws from large datasets, providing clinical information on tooth long axis for orthodontics, endodontics, prosthodontic and restorative dentistry procedures. DentalModelSeg includes segmenting the teeth from the crown shape to provide clinical information on each individual tooth. The merging algorithm then allows users to integrate dental models for quantitative assessments. Precision in dentistry has been mainly driven by dental crown surface characteristics, but information on tooth root morphology and position is important for successful root canal preparation, pulp regeneration, planning of orthodontic movement, restorative and implant dentistry. In this paper we propose a patient specific classification and prediction of dental root canal and crown shape analysis workflow that employs image processing and machine learning methods to analyze crown surfaces, obtained by intraoral scanners, and three-dimensional volumetric images of the jaws and teeth root canals, obtained by cone beam computed tomography (CBCT).

Automatic Segmentation of Mandibular Ramus and Condyles.

In order to diagnose TMJ pathologies, we developed and tested a novel algorithm, MandSeg, that combines image processing and machine learning approaches for automatically segmenting the mandibular condyles and ramus. A deep neural network based on the U-Net architecture was trained for this task, using 109 cone-beam computed tomography (CBCT) scans. The ground truth label maps were manually segmented by clinicians. The U-Net takes 2D slices extracted from the 3D volumetric images. All the 3D scans were cropped depending on their size in order to keep only the mandibular region of interest. The same anatomic cropping region was used for every scan in the dataset. The scans were acquired at different centers with different resolutions. Therefore, we resized all scans to 512×512 in the pre-processing step where we also performed contrast adjustment as the original scans had low contrast. After the pre-processing, around 350 slices were extracted from each scan, and used to train the U-Net model. For the cross-validation, the dataset was divided into 10 folds. The training was performed with 60 epochs, a batch size of 8 and a learning rate of 2×10-5. The average performance of the models on the test set presented 0.95 ± 0.05 AUC, 0.93 ± 0.06 sensitivity, 0.9998 ± 0.0001 specificity, 0.9996 ± 0.0003 accuracy, and 0.91 ± 0.03 F1 score. This study findings suggest that fast and efficient CBCT image segmentation of the mandibular condyles and ramus from different clinical data sets and centers can be analyzed effectively. Future studies can now extract radiomic and imaging features as potentially relevant objective diagnostic criteria for TMJ pathologies, such as osteoarthritis (OA). The proposed segmentation will allow large datasets to be analyzed more efficiently for disease classification.

Mandibular condylar remodeling characteristics after simultaneous condylectomy and orthognathic surgery.

INTRODUCTION: The objectives of this study were to evaluate postsurgical condylar remodeling using a radiographical interpretation, quantify condylar volumetric asymmetry, and assess soft tissue symmetry after simultaneous unilateral high condylectomy and bimaxillary osteotomies. METHODS: Sixteen patients diagnosed with unilateral condylar hyperplasia underwent unilateral high condylectomy and orthognathic surgery to correct skeletal and facial asymmetries. Cone-beam computed tomography scans were acquired before and 1-year after surgery. A radiographic consensus was evaluated for signs of reparative or degenerative changes. The condyles were mirrored and registered for assessment of volumetric and morphologic asymmetry. Soft tissue symmetry was evaluated by measurement of the distance of soft tissue pogonion from the skeletal midsagittal plane. RESULTS: Patients who undergo unilateral high condylectomy and orthognathic surgery present radiographic signs suggestive of degenerative changes, including sclerosis, osteophytes, flattening, and erosion in both the surgical and nonsurgical condyles (P ≤0.01). There was an average volumetric improvement of 531.9 ± 662.3 mm3 1-year postsurgery (P = 0.006). Soft tissue symmetry improved in all patients, with an average improvement of 65.8% (4.0 mm ± 2.6 mm, P ≤ 0.01). There was no correlation between the change in condylar volumetric asymmetry and the stability of the soft tissue correction. CONCLUSIONS: High condylectomy for the correction of a skeletal asymmetry in patients with condylar hyperplasia successfully reduces the volumetric asymmetry between the condyles. Postsurgical dysmorphic remodeling and degenerative changes were noted in both the surgical and nonsurgical condyles. Despite remarkable changes and remaining joint asymmetry, the soft tissue correction is stable 1-year postsurgery.

Radiographic interpretation using high-resolution Cbct to diagnose degenerative temporomandibular joint disease.

The objective of this study was to use high-resolution cone-beam computed images (hr- CBCT) to diagnose degenerative joint disease in asymptomatic and symptomatic subjects using the Diagnostic Criteria for Temporomandibular Disorders DC/TMD imaging criteria. This observational study comprised of 92 subjects age-sex matched and divided into two groups: clinical degenerative joint disease (c-DJD, n = 46) and asymptomatic control group (n = 46). Clinical assessment of the DJD and high-resolution CBCT images (isotropic voxel size of 0.08mm) of the temporomandibular joints were performed for each participant. An American Board of Oral and Maxillofacial Radiology certified radiologist and a maxillofacial radiologist used the DC/TMD imaging criteria to evaluate the radiographic findings, followed by a consensus of the radiographic evaluation. The two radiologists presented a high agreement (Cohen's Kappa ranging from 0.80 to 0.87) for all radiographic findings (osteophyte, erosion, cysts, flattening, and sclerosis). Five patients from the c- DJD group did not present radiographic findings, being then classified as arthralgia. In the asymptomatic control group, 82.6% of the patients presented radiographic findings determinant of DJD and were then classified as osteoarthrosis or overdiagnosis. In conclusion, our results showed a high number of radiographic findings in the asymptomatic control group, and for this reason, we suggest that there is a need for additional imaging criteria to classify DJD properly in hr-CBCT images.