Evaluation of masticatory muscles in temporomandibular joint disorder patients using quantitative MRI fat fraction analysis-Could it be a biomarker?

Temporomandibular joint disorders (TMDs) are closely related to the masticatory muscles, but objective and quantitative methods to evaluate muscle are lacking. IDEAL-IQ, a type of chemical shift-encoded magnetic resonance imaging (CSE-MRI), can quantify the fat fraction (FF). The purpose of this study was to develop an MR IDEAL-IQ-based method for quantitative muscle diagnosis in TMD patients. A total of 65 patients who underwent 3 T MRI scans, including CSE-MRI sequences, were retrospectively included. MRI diagnoses and clinical data were reviewed. There were 19 patients in the normal group and 46 patients in the TMD group with unilateral disc displacement. The TMD group was subdivided into those with and without clenching. The right and left FF values of the masseter, medial, and lateral pterygoid muscles were measured twice by two oral radiologists on CSE-MRI, and the average value was used. FF measurements using CSE-MRI showed excellent intra- and inter-observer agreement (ICC > 0.889 for both). There were no statistically significant differences between the right and left FF values in the masseter, medial pterygoid, and lateral pterygoid of the normal group (p > 0.05). A statistically significant difference was found in the TMD group without clenching, in which the masseter muscle had a statistically significantly lower FF value on the disc displacement side (3.94 ± 1.61) than on the normal side (4.52 ± 2.24) (p < 0.05). CSE-MRI, which can reproducibly quantify muscle FF values, is expected to be a biomarker for objective muscle evaluation in TMD patients. The masseter muscle is expected to be particularly useful compared to other masticatory muscles, but further research is needed.

CT and MR imaging findings of head and neck chondrosarcoma.

OBJECTIVES: This study investigated the imaging features of head and neck chondrosarcoma (HNCS) according to its origin and pathologic subtype. METHODS: Patients who were pathologically diagnosed with HNCS between January 2000 and April 2022 were retrospectively reviewed. Lesions were classified based on their origin and pathologic subtype. The size and margin were evaluated on the image. Internal calcification and the effects on adjacent bone were assessed using computed tomography (CT) images, while signal intensity and contrast enhancement patterns were analyzed using magnetic resonance (MR) imaging. RESULTS: Thirteen HNCSs were included in this study: 8 bone tumors (61.5%) and 5 soft tissue tumors (38.5%). The bone tumors were pathologically diagnosed as conventional (n = 5) and mesenchymal type (n = 3). Soft tissue tumors were defined as myxoid type. The main symptoms were swelling (90.9%) and pain (72.7%). The lesions measured 4.5 cm on average. The margins showed benign and well-defined except for the mesenchymal type. On CT, most bone tumors (75%) showed internal calcification with remodeling or destruction of the adjacent bone. No soft tissue tumors, except one case, showed internal calcification or destruction of the adjacent bone. MR imaging features were non-specific (T2 high signal intensity and contrast enhancement). CONCLUSIONS: HCNS showed various imaging findings according to their origin and pathologic subtype. HNCS should be differentiated if a bone tumor shows internal calcification and affects the adjacent bone. When diagnosing slow-growing soft tissue tumors, even if low possibility, HNCS should be considered.

Development and accuracy validation of a fat fraction imaging biomarker for sialadenitis in the parotid gland.

BACKGROUND: The diagnosis of sialadenitis, the most frequent disease of the salivary glands, is challenging when the symptoms are mild. In such cases, biomarkers can be used as definitive diagnostic indicators. Recently, biomarkers have been developed by extracting and analyzing pathological and morphological features from medical imaging. This study aimed to establish a diagnostic reference for sialadenitis based on the quantitative magnetic resonance imaging (MRI) biomarker IDEAL-IQ and assess its accuracy. METHODS: Patients with sialadenitis (n = 46) and control subjects (n = 90) that underwent MRI were selected. Considering that the IDEAL-IQ value is a sensitive fat fractional marker to the body mass index (BMI), all subjects were also categorized as under-, normal-, and overweight. The fat fraction of parotid gland in the control and sialadenitis groups were obtained using IDEAL-IQ map. The values from the subjects in the control and sialadenitis groups were compared in each BMI category. For comparison, t-tests and receiver operating characteristic (ROC) curve analyses were performed. RESULTS: The IDEAL-IQ fat faction of the control and sialadenitis glands were 38.57% and 23.69%, respectively, and the differences were significant. The values were significantly lower in the sialadenitis group (P), regardless of the BMI types. The area under the ROC curve (AUC) was 0.83 (cut-off value: 28.72) in patients with sialadenitis. The AUC for under-, normal-, and overweight individuals were 0.78, 0.81, and 0.92, respectively. CONCLUSIONS: The fat fraction marker based on the IDEAL-IQ method was useful as an objective indicator for diagnosing sialadenitis. This marker would aid less-experienced clinicians in diagnosing sialadenitis.

Radiomics-based sialadenitis staging in contrast-enhanced computed tomography and ultrasonography: a preliminary rat model study.

OBJECTIVE: The aim of this study was to measure the ability of radiomics analysis to diagnose different stages of sialadenitis, compare the diagnostic accuracy of computed tomography (CT) and ultrasonography (US), and suggest radiomics features selected through 3 machine learning algorithms that would be helpful in discriminating between stages of sialadenitis with both imaging systems. STUDY DESIGN: Wistar rats were treated to induce acute and chronic sialadenitis in the left and right submandibular glands, respectively. Contrast-enhanced CT and US of the glands were performed, followed by extirpation and histopathologic confirmation. Radiomics feature values of the glands were obtained from all images. Based on 3 feature selection methods, an optimal feature set was defined after a comparison of the receiver operating characteristic area under the curve (AUC) of each combination of 3 deep learning algorithms and 3 classification models. RESULTS: The attribute features for the CT model were 2 gray-level run length matrices and 2 gray-level zone length matrices. In the US model, there were 2 gray-level co-occurrence matrices and 2 gray-level zone length matrices. The most accurate diagnostic models of CT and US yielded outstanding (AUC = 1.000) and excellent (AUC = 0.879) discrimination, respectively. CONCLUSIONS: The radiomics diagnostic model using gray-level zone length matrices-based features conferred clinically outstanding discriminating ability among stages of sialadenitis using CT and excellent discrimination with US in almost all combinations of machine learning feature selections and classification models.

Refinement of image quality in panoramic radiography using a generative adversarial network.

OBJECTIVE: We aimed to develop and assess the clinical usefulness of a generative adversarial network (GAN) model for improving image quality in panoramic radiography. METHODS: Panoramic radiographs obtained at Yonsei University Dental Hospital were randomly selected for study inclusion (n = 100). Datasets with degraded image quality (n = 400) were prepared using four different processing methods: blur, noise, blur with noise, and blur in the anterior teeth region. The images were distributed to the training and test datasets in a ratio of 9:1 for each group. The Pix2Pix GAN model was trained using pairs of the original and degraded image datasets for 100 epochs. The peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) were obtained for the test dataset, and two oral and maxillofacial radiologists rated the quality of clinical images. RESULTS: Among the degraded images, the GAN model enabled the greatest improvement in those with blur in the region of the anterior teeth but was least effective in improving images exhibiting blur with noise (PSNR, 36.27 > 32.74; SSIM, 0.90 > 0.82). While the mean clinical image quality score of the original radiographs was 44.6 out of 46.0, the highest and lowest predicted scores were observed in the blur (45.2) and noise (36.0) groups. CONCLUSION: The GAN model developed in this study has the potential to improve panoramic radiographs with degraded image quality, both quantitatively and qualitatively. As the model performs better in refining blurred images, further research is required to identify the most effective methods for handling noisy images.

Automatic diagnosis of retention pseudocyst in the maxillary sinus on panoramic radiographs using a convolutional neural network algorithm.

The evaluation of the maxillary sinus is very important in dental practice such as tooth extraction and implantation because of its proximity to the teeth, but it is not easy to evaluate because of the overlapping structures such as the maxilla and the zygoma on panoramic radiographs. When doom-shaped retention pseudocysts are observed in sinus on panoramic radiographs, they are often misdiagnosed as cysts or tumors, and additional computed tomography is performed, resulting in unnecessary radiation exposure and cost. The purpose of this study was to develop a deep learning model that automatically classifies retention pseudocysts in the maxillary sinuses on panoramic radiographs. A total of 426 maxillary sinuses from panoramic radiographs of 213 patients were included in this study. These maxillary sinuses included 86 sinuses with retention pseudocysts, 261 healthy sinuses, and 79 sinuses with cysts or tumors. An EfficientDet model first introduced by Tan for detecting and classifying the maxillary sinuses was developed. The developed model was trained for 200 times on the training and validation datasets (342 sinuses), and the model performance was evaluated in terms of accuracy, sensitivity, and specificity on the test dataset (21 retention pseudocysts, 43 healthy sinuses, and 20 cysts or tumors). The accuracy of the model for classifying retention pseudocysts was 81%, and the model also showed higher accuracy for classifying healthy sinuses and cysts or tumors (98% and 90%, respectively). One of the 21 retention pseudocysts in the test dataset was misdiagnosed as a cyst or tumor. The proposed model for automatically classifying retention pseudocysts in the maxillary sinuses on panoramic radiographs showed excellent diagnostic performance. This model could help clinicians automatically diagnose the maxillary sinuses on panoramic radiographs.

Unemployment risk of all employed working-age cancer survivors after cancer diagnosis in South Korea: a retrospective cohort analysis of population-based administrative data.

PURPOSE: As the cancer survival rate increases, discussions on the employment status of cancer survivors should be actively carried out worldwide. This study examined patients' working status changes after cancer diagnosis to provide the basis for cancer survivors' return to work. METHODS: We established a nationwide cohort to determine long-term work changes after cancer diagnosis. All patients aged 19 to 50 years who were newly diagnosed with cancer while working for the previous 3 years were considered as the case group in 2010. Using propensity score matching (PSM), the cases were matched by sex and age at a ratio of 1:3 with the control group. Kaplan-Meier curve and Cox hazard model analyses were performed to determine the occurrence of unemployment and return to work in the case and control groups on a yearly basis. RESULTS: According to the 6-year follow-up after cancer diagnosis, 26.5% of cancer patients and 23.2% of controls had lost their jobs by the end of the follow-up (P < .0001). Meanwhile, 50.5% of cancer patients and 57.4% of controls had returned to work after unemployment (P < .0001). Subsequently, based on the Cox hazard model, the unemployment risk of cancer patients was 1.42 times higher than that of the general population, while the proportion of those who returned to work was 1.15 times lower. CONCLUSION: Employment is very closely related to the quality of life of cancer survivors. These results highlight the need for a system that can support cancer survivors' work maintenance and return to work after unemployment during the treatment period and the fact that awareness of this must be improved.

Impact of physiological parameters on the parotid gland fat fraction in a normal population.

Quantifying physiological fat tissue in the organs is important to further assess the organ's pathologic status. This study aimed to investigate the impact of body mass index (BMI), age, and sex on the fat fraction of normal parotid glands. Patients undergoing magnetic resonance imaging (MRI) of iterative decomposition of water and fat with echo asymmetry and least squares estimation (IDEAL-IQ) due to non-salivary gland-related disease were reviewed. Clinical information of individual patients was categorized into groups based on BMI (under/normal/overweight), age (age I/age II/age III), and sex (female/male) and an inter-group comparison of the fat fraction values of both parotid glands was conducted. Overall, in the 626 parotid glands analyzed, the fat fraction of the gland was 35.80%. The mean fat fraction value increased with BMI (30.23%, 35.74%, and 46.61% in the underweight, normal and overweight groups, respectively [p < 0.01]) and age (32.42%, 36.20%, and 41.94% in the age I, II, and III groups, respectively [p < 0.01]). The fat content of normal parotid glands varies significantly depending on the body mass and age regardless of sex. Therefore, the patient's age and body mass should be considered when evaluating fatty change in the parotid glands in imaging results.

Parotid gland evaluation of menopausal women with xerostomia using the iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL-IQ) method of MRI: a pilot study.

OBJECTIVES: This study aimed to analyze the quantitative fat fraction (FF) of the parotid gland in menopausal females with xerostomia using the iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL-IQ) method. METHODS: A total 138 parotid glands of 69 menopausal females were enrolled in our study and participants were divided into normal group and xerostomia group. The xerostomia group was divided into those with or without Sjögren's syndrome. Participants underwent IDEAL-IQ sequences of MRI and the stimulated salivary flow test (s-SFR). The unpaired t-test was used to compare the FFs between the normal and xerostomia groups and between the subgroups with and without Sjögren's syndrome. The correlation between FF and s-SFR was analyzed by Pearson's correlation. RESULTS: Excellent intra- and interobserver agreement during the measurement of FFs by IDEAL-IQ method (ICC>0.99, respectively). FF value in the xerostomia group was statistically significantly higher than the value in the normal group (p < 0.05). Within the xerostomia group, the average FF value of females with Sjögren's syndrome was higher than that of females without Sjögren's syndrome. However, the difference was not statistically significant (p > 0.05). Within the xerostomia group, FF value correlated negatively with s-SFR (p < 0.05). CONCLUSIONS: The FF of the parotid gland was higher in the xerostomia group than in the normal group and FF value and s-SFR showed a negative correlation. Analyses of the FF using IDEAL-IQ in menopausal females can be helpful for the quantitative diagnosis of xerostomia.

Harmonization of robust radiomic features in the submandibular gland using multi-ultrasound systems: a preliminary study.

OBJECTIVE: This study aimed to identify robust radiomic features in multiultrasonography of the submandibular gland and normalize the interdevice discrepancies by applying a machine-learning-based harmonization method. METHODS: Ultrasonographic images of normal submandibular gland of young healthy adults, aged between 20 and 40 years, were selected from two different devices. In a total of 30 images, the region of interest was determined along the border of gland parenchyma, and 103 radiomic features were extracted using A-VIEW. The coefficient of variation (CV) was obtained for individual features, and the features showing CV less than 10% were selected. For the selected features, the interdevice discrepancy was normalized using machine-learning method, called the ComBat harmonization. Median differences of the features between the two scanners, before and after harmonization, were compared using Mann-Whitney U-test; confidence interval of 95%. RESULTS: Among total 103 radiomic features, 17 features were selected as robust, showing CV less than 10% in both scanners. All values of selected features, except two, showed a statistical difference between the two devices. After applying the ComBat harmonization method, the median and distribution of the 16 features were harmonized to show no significant difference between the two scanners (p > 0.05). One feature remained different (p ≤ 0.05). CONCLUSION: On ultrasonographic examination, robust radiomic features for normal submandibular gland were obtained and interdevice normalization was efficiently conducted using ComBat harmonization. Our findings would be useful for multidevices or multicenter studies based on clinical ultrasonographic imaging data to improve the accuracy of the overall diagnostic model.

Imaging feature of cosmetic fillers in cone-beam computed tomography and its dental consideration.

BACKGROUND: As the application of cone-beam computed tomography (CBCT) in head and neck area increases for dental treatment purposes, cosmetic filler materials are incidentally observed. Since the materials are very diverse, unnecessary referrals or additional examination may be performed when clinicians are unfamiliar with the imaging findings. Thus, this study aimed to introduce the imaging characteristics of cosmetic fillers and grafts shown in dental CBCT with dental considerations that the clinician should be aware of. METHODS: CBCT obtained for dental purpose presenting cosmetic material were selected. The location of the material was identified as buccal, retroantral, parotid space, nose, zygoma, and symphysis. The material was classified as single or multiple, and grouped according to morphology: speckle, round, eggshell, linear, and amorphous. The radiopacity was classified as similar to soft tissue, between soft and hard tissue, similar to hard tissue, and metal. RESULTS: Twenty-one patients were reviewed, and all patients were female with mean age of 50.5 years. The buccal space was the most frequent location for multiple filler materials. The symphysis was the next frequent location and only single material were shown in this location. Cases having multiple filler showed diverse shapes while all single materials showed round shape. Fillers showing radiopacity of hard tissue were similar to diseases producing soft tissue calcifications. Metal-density material distributed in spaces induced white and dark streak artifacts in the CBCT image. All single materials presented radiopacity between soft and hard tissue and attached to the bone surface causing mandibular bone resorption. CONCLUSIONS: Cosmetic materials displayed various imaging features in CBCT acquired during dental procedure. Clinicians should consider that cosmetic material may cause mandibular bone resorption and imaging artifacts on CBCT. Knowledge of the imaging characteristics of cosmetic fillers may help correct diagnosis.

Efficacy of corticosteroid ductal irrigation in acute salivary gland inflammation induced in a rat model.

Purpose: This study aimed to compare the therapeutic effects of corticosteroid irrigations and normal saline irrigations in the early inflammatory state of the salivary gland. Materials and Methods: Adult male Wistar rats were divided into experimental (n=6) and control (n=3) groups. Inflammation was induced in the experimental subjects on both sides of the submandibular gland with ligation. After 14 days, both sides of the glands were de-ligated and retroductal irrigation using saline (n=3) and a corticosteroid (n=3) was performed on the left sides only. The controls (n=3) were used to normalize the gland state for the effects of diet and aging. Magnetic resonance imaging was performed to confirm inflammation and post-irrigation gland recovery by measuring relative signal intensity (SI). The glands were excised for histological examination. Results: All experimental animals showed inflamed glands with increased SI and subsequent recovery of the gland with decreased SI to varying degrees. The SI of the controls showed no significant changes during the overall period. The mean SI change of the irrigated gland was higher than that of the non-irrigated side, without a significant difference. The corticosteroid-irrigated glands showed a greater change in SI than that of the saline-irrigated glands. Histology revealed that inflammation was not observed in most of the irrigated glands, while mild to moderate quantities inflammatory cells were found in non-irrigated glands. Conclusion: Corticosteroid irrigation mitigated the early stages of salivary gland inflammation more effectively than normal saline.

Canal configuration and root morphology of mandibular premolars using cone-beam computed tomography in a Korean population.

OBJECTIVES: This study aimed to investigate the anatomy of mandibular premolars from two perspectives-the canal configuration and radicular grooves-using cone-beam computed tomography (CBCT) in a large Korean population. MATERIALS AND METHODS: CBCT images of mandibles acquired from March 2018 to December 2019 for dental treatment were randomly selected. In each image, the root canal of premolars was classified into 8 types according to the canal merging or diverging pattern and the number of apical foramens. The presence and the location of radicular grooves were also assessed. Statistical analysis was performed. RESULTS: A total of 1463 first and 1448 s premolars from 732 patients (390 males, 342 females, mean age of 36.1 years) were evaluated. A single canal with one foramen predominated in both first (85.7%) and second (99.5%) premolars, while complete or partial multi-canals accounted for 14.3% and 0.5% of first and second premolars, respectively. The prevalence of radicular grooves was significantly higher in first premolars (13.2%) than in second premolars (0.5%) and in males (4.3%, n = 119) than in females (2.5%, n = 73). CONCLUSIONS: Although most premolars were complete single canals, the first premolars showed a relatively higher number of complex canals compared to the second premolar. In addition, radicular grooves in mandibular premolars were significantly more common in male patients. CLINICAL RELEVANCE: When planning the endodontic treatment of mandibular premolars, clinicians should be aware of their morphologic complexity, especially in the first premolar of male patients.

Synthesis of T2-weighted images from proton density images using a generative adversarial network in a temporomandibular joint magnetic resonance imaging protocol.

Purpose: This study proposed a generative adversarial network (GAN) model for T2-weighted image (WI) synthesis from proton density (PD)-WI in a temporomandibular joint (TMJ) magnetic resonance imaging (MRI) protocol. Materials and Methods: From January to November 2019, MRI scans for TMJ were reviewed and 308 imaging sets were collected. For training, 277 pairs of PD- and T2-WI sagittal TMJ images were used. Transfer learning of the pix2pix GAN model was utilized to generate T2-WI from PD-WI. Model performance was evaluated with the structural similarity index map (SSIM) and peak signal-to-noise ratio (PSNR) indices for 31 predicted T2-WI (pT2). The disc position was clinically diagnosed as anterior disc displacement with or without reduction, and joint effusion as present or absent. The true T2-WI-based diagnosis was regarded as the gold standard, to which pT2-based diagnoses were compared using Cohen's ĸ coefficient. Results: The mean SSIM and PSNR values were 0.4781(±0.0522) and 21.30(±1.51) dB, respectively. The pT2 protocol showed almost perfect agreement (ĸ=0.81) with the gold standard for disc position. The number of discordant cases was higher for normal disc position (17%) than for anterior displacement with reduction (2%) or without reduction (10%). The effusion diagnosis also showed almost perfect agreement (ĸ=0.88), with higher concordance for the presence (85%) than for the absence (77%) of effusion. Conclusion: The application of pT2 images for a TMJ MRI protocol useful for diagnosis, although the image quality of pT2 was not fully satisfactory. Further research is expected to enhance pT2 quality.

Analysis of the mandibular canal course using unsupervised machine learning algorithm.

OBJECTIVES: Anatomical structure classification is necessary task in medical field, but the inevitable variability of interpretation among experts makes reliable classification difficult. This study aims to introduce cluster analysis, unsupervised machine learning method, for classification of three-dimensional (3D) mandibular canal (MC) courses, and to visualize standard MC courses derived from cluster analysis in the Korean population. MATERIALS AND METHODS: A total of 429 cone-beam computed tomography images were used. Four sites in the mandible were selected for the measurement of the MC course and four parameters, two vertical and two horizontal parameters were measured per site. Cluster analysis was carried out as follows: parameter measurement, parameter normalization, cluster tendency evaluation, optimal number of clusters determination, and k-means cluster analysis. The 3D MC courses were classified into three types with statistically significant mean differences by cluster analysis. RESULTS: Cluster 1 showed a smooth line running towards the lingual side in the axial view and a steep slope in the sagittal view. Cluster 2 ran in an almost straight line closest to the lingual and inferior border of mandible. Cluster 3 showed the pathway with a bent buccally in the axial view and an increasing slope in the sagittal view in the posterior area. Cluster 2 showed the highest distribution (42.1%), and males were more widely distributed (57.1%) than the females (42.9%). Cluster 3 comprised similar ratio of male and female cases and accounted for 31.9% of the total distribution. Cluster 1 had the least distribution (26.0%) Distributions of the right and left sides did not show a statistically significant difference. CONCLUSION: The MC courses were automatically classified as three types through cluster analysis. Cluster analysis enables the unbiased classification of the anatomical structures by reducing observer variability and can present representative standard information for each classified group.

Computed tomography and magnetic resonance imaging characteristics of giant cell tumors in the temporomandibular joint complex.

PURPOSE: This study aimed to investigate the computed tomography and magnetic resonance imaging features of giant cell tumors in the temporomandibular joint region to facilitate accurate diagnoses. MATERIALS AND METHODS: From October 2007 to June 2020, 6 patients (2 men and 4 women) at Yonsei University Dental Hospital had histopathologically proven giant cell tumors in the temporomandibular joint. Their computed tomography and magnetic resonance imaging findings were reviewed retrospectively, and the cases were classified into 3 types based on the tumor center and growth pattern observed on the radiologic findings. RESULTS: The age of the 6 patients ranged from 25 to 53 years. Trismus was found in 5 of the 6 cases. One case recurred. The mean size of the tumors, defined based on their greatest diameter, was 32 mm (range, 15-41 mm). The characteristic features of all cases were a heterogeneously-enhancing tumorous mass with a lobulated margin on computed tomographic images and internal multiplicity of signal intensity on T2-weighted magnetic resonance images. According to the site of origin, 3 tumors were bone-centered, 2 were soft tissue-centered, and 1 was peri-articular. CONCLUSION: Computed tomography and magnetic resonance imaging yielded a tripartite classification of giant cell tumors of the temporomandibular joint according to their location on imaging. This study could help clinicians in the differential diagnosis of giant cell tumors and assist in proper treatment planning for tumorous diseases of the temporomandibular joint.

Analysis of three-dimensional imaging findings and clinical symptoms in patients with temporomandibular joint disorders.

BACKGROUND: The purpose of this study was to analyze cone-beam computed tomography (CBCT) and magnetic resonance imaging (MRI) findings in temporomandibular joint disorder (TMD) patients and to comprehensively assess the relationships between these imaging findings and clinical symptoms. METHODS: A total of 754 temporomandibular joints (TMJs) in 377 patients with clinical symptoms of TMD who underwent both CBCT and MRI examinations were retrospectively reviewed. Clinical symptoms included TMJ pain, TMJ sound, and limitation of mouth opening. Oral radiologists evaluated osseous changes of the condylar head on CBCT, as well as the disc configuration, internal derangement, and joint effusion on MRI. The frequency of CBCT and MRI findings and the mean and standard deviation of age were analyzed. Logistic regression analysis was used to identify associations between these imaging findings and clinical symptoms using SPSS version 25.0 for Windows (IBM Corp., Armonk, NY, USA). The model fit was evaluated using the Hosmer and Lemeshow test. RESULTS: TMD patients consisted of 294 females and 83 males, and the age group of 20-39 accounted for 47.2% of the patients. Normal findings regarding osseous changes of the condylar head on CBCT were found in 65.1% of the patients. On MRI, a change in disc configuration was found in 54.9% of the patients, internal derangement in 62.6%, and joint effusion in 46.0%. TMJ pain was significantly associated with sclerosis [odds ratio (OR): 3.81], disc displacement without reduction (DDWOR) (OR: 3.22), grade 2 joint effusion (OR: 2.33), and grade 3 joint effusion (OR: 5.54). TMJ sound was significantly associated with disc displacement with reduction (DDWR) (OR: 3.04), DDWOR (OR: 2.50), grade 2 joint effusion (OR: 2.37), and grade 3 joint effusion (OR: 3.23). Limitation of mouth opening was significantly associated with flattened disc configuration (OR: 2.08), folded disc configuration (OR: 2.30), and grade 3 joint effusion (OR: 2.85). CONCLUSIONS: CBCT findings had little to do with clinical symptoms. In contrast, MRI findings, including disc configuration, internal derangement, and joint effusion, were associated with clinical symptoms. These results suggest that MRI should be recommended over CBCT for the proper diagnosis of TMD patients.

Accuracy of digital model generated from CT data with metal artifact reduction algorithm.

This study investigated whether metal artifact reduction (MAR) applied computed tomography (CT) scans could be used to generate precise digital models and explored possible correlations between the amount of metal artifact and model accuracy. Thirty maxillofacial CT scans were randomly selected and a MAR algorithm was applied. By subtracting the original and MAR-applied CT images, the amount of metal artifact was quantified. Digital models were generated from the original and the MAR-applied CT data. Paired digital models were superimposed and shape deviation in planar surface was measured at 10 points in 4 planes. Statistical analyses were performed to compare deviations and to assess correlations between the amount of artifact and deviation. The MAR algorithm reduced metal artifact in all cases. The overall mean deviation of the MAR-applied models was 0.0868 mm, with no significant difference according to the reference plane. The amount of artifact did not significantly influence the accuracy of the digital models. MAR-applied CT is a convenient source for digital modeling with clinically acceptable accuracy. The MAR algorithm can be used regardless of the amount of metal artifact, which are generated by dental prostheses, for the quick and convenient manipulation of dental digital models.

Effects of Community-Based Interventions on Medication Adherence and Hospitalization for Elderly Patients with Type 2 Diabetes at Primary Care Clinics in South Korea.

Korean Disease Control and Prevention Agency launched Control and Prevention Community-based Registration and Management for Hypertension and Diabetes mellitus Project (CRMHDP) in Gwangmyeong city, 2009. This project has provided incentives on both patient and physician and has made private clinics and Public Health Center (PHC) in a community collaborate for effective chronic disease management among elderly people. This study aimed to evaluate the effects of CRMHDP on medication compliance and hospitalization due to diabetes-specific complications. The retrospective cohort study design was based on data of Korean National Health Insurance (KNHI) with 2 control areas (A & B) with usual primary care service similar to Gwangmyeong city regarding community health resources. The data on the study subjects were examined for the following 5 years since the baseline point. Medication adherence rates of CRMHDP-enrollees after the project was significantly higher than two control groups. For the hospitalization due to any complications, adjusted hazard ratio in the intervention group, compared to the control group A and B, were 0.76 (95% Confidence Interval: 0.65-0.78) and 0.52 (95% Confidence Interval 0.41-0.78), respectively. CRMHDP could successful in improving the management of type 2 diabetes mellitus among elderly people in South Korean primary care settings.

Synthetic magnetic resonance imaging for quantitative parameter evaluation of temporomandibular joint disorders.

OBJECTIVE: This study investigated the usefulness of quantitative parameters [longitudinal relaxation (T1), transverse relaxation (T2), and proton density (PD)] obtained with synthetic magnetic resonance imaging (MRI) in assessing the progression of temporomandibular joint (TMJ) disorders. METHODS: For individual TMJ disorder diagnoses, the presence of disc displacement in MRI and the osseous change in cone-beam CT were investigated. Joints were classified into three stages: (1) silent stage, no disc displacement or osseous change; (2) incipient stage, presence of disc displacement and absence of osseous change; and (3) progressed stage, both disc displacement and osseous change. In synthetic MRI, the T1, T2, and PD values of the condyle bone marrow were measured simultaneously. The median T1, T2, and PD values were analyzed according to disc displacement, osseous changes, and joint stage. RESULTS: Significant differences were observed in the T1 and PD values of joints with disc displacement or condylar osseous change compared to normal joints. The T1 and PD values also differed between the silent and progressed stages. The PD value differed between the silent and incipient groups, while the T2 value did not differ significantly among the three groups. CONCLUSION: The PD and T1 values of condylar bone marrow obtained from synthetic MRI can be used as sensitive indicators of TMJ disorder progression. The PD value of the bone marrow showed potential as a useful biomarker for recognizing the initial stages of TMJ disorders. Synthetic MRI is useful for the simultaneous acquisition of effective MRI parameters for evaluating TMJ disorders.