Differentiation of submandibular sialadenitis based on apparent diffusion coefficient.

OBJECTIVES: This study aimed to quantify the submandibular gland in suppurative sialadenitis, primary Sjögren's syndrome (pSS) and radiation-induced sialadenitis using the apparent diffusion coefficient (ADC) for differential diagnosis. SUBJECTS AND METHODS: This retrospective study included 16 patients with suppurative sialadenitis (n = 9), pSS (n = 3) and radiation-induced sialadenitis (n = 4) who underwent magnetic resonance imaging between June 2006 and May 2022. The ADC of the submandibular glands in each state was calculated, and the differences were analysed using a one-way analysis of variance and Tukey's post hoc test. Receiver operating characteristic curves were used to assess the ability of the ADC to distinguish each condition. Statistical significance was set at p < 0.05. RESULTS: The mean ADC value (×10-3 mm2/s) ± standard deviation in the control (non-affected side of the suppurative sialadenitis group), suppurative sialadenitis, pSS and radiation-induced groups were 0.94 ± 0.16, 1.24 ± 0.16, 1.33 ± 0.13 and 1.5 ± 0.12, respectively (p < 0.001). The diagnostic value for distinguishing each group was ≥0.75. CONCLUSION: ADC values are useful for quantitatively assessing and distinguishing submandibular glands in suppurative sialadenitis, primary Sjögren's syndrome and radiation-induced sialadenitis.

Graphical user interface-based convolutional neural network models for detecting nasopalatine duct cysts using panoramic radiography.

Nasopalatine duct cysts are difficult to detect on panoramic radiographs due to obstructive shadows and are often overlooked. Therefore, sensitive detection using panoramic radiography is clinically important. This study aimed to create a trained model to detect nasopalatine duct cysts from panoramic radiographs in a graphical user interface-based environment. This study was conducted on panoramic radiographs and CT images of 115 patients with nasopalatine duct cysts. As controls, 230 age- and sex-matched patients without cysts were selected from the same database. The 345 pre-processed panoramic radiographs were divided into 216 training data sets, 54 validation data sets, and 75 test data sets. Deep learning was performed for 400 epochs using pretrained-LeNet and pretrained-VGG16 as the convolutional neural networks to classify the cysts. The deep learning system's accuracy, sensitivity, and specificity using LeNet and VGG16 were calculated. LeNet and VGG16 showed an accuracy rate of 85.3% and 88.0%, respectively. A simple deep learning method using a graphical user interface-based Windows machine was able to create a trained model to detect nasopalatine duct cysts from panoramic radiographs, and may be used to prevent such cysts being overlooked during imaging.

Texture analysis using short-tau inversion recovery magnetic resonance images to differentiate squamous cell carcinoma of the gingiva from medication-related osteonecrosis of the jaw.

OBJECTIVES: Despite the difficulty in distinguishing between squamous cell carcinoma (SCC) and medication-related osteonecrosis of the jaw (MRONJ) on the basis of medical imaging examinations, the two conditions have completely different treatment methods and prognoses. Therefore, differentiation of SCC from MRONJ on imaging examinations is very important. This study aimed to distinguish SCC from MRONJ by performing texture analysis using magnetic resonance imaging (MRI) short-tau inversion recovery images. METHODS: This retrospective case-control study included 14 patients with SCC of the lower gingiva and 35 with MRONJ of the mandible who underwent MRI and computed tomography (CT) for suspected SCC or MRONJ. SCC was identified by histopathological examination of tissues excised during surgery. The radiomics features of SCC and MRONJ were analyzed using the open-access software MaZda version 3.3 (Technical University of Lodz, Institute of Electronics, Poland). CT was used to evaluate the presence or absence of qualitative findings (sclerosis, sequestrum, osteolysis, periosteal reaction, and cellulitis) of SCC and MRONJ. RESULTS: Among the 19 texture features selected using MaZda feature-reduction methods, SCC of the gingiva and MRONJ of the mandible revealed differences in two histogram features, one absolute gradient feature, and 16 Gy level co-occurrence matrix features. In particular, the percentile, angular second moment, entropy, and difference entropy exhibited excellent diagnostic performance. CONCLUSION: Non-contrast-enhanced MRI texture analysis revealed differences in texture parameters between mandibular SCC and mandibular MRONJ. MRI texture analysis can be a new noninvasive quantitative method for distinguishing between SCC and MRONJ.

Efficacy of magnetic resonance imaging texture features of the lateral pterygoid muscle in distinguishing rheumatoid arthritis and osteoarthritis of the temporomandibular joint.

OBJECTIVES: The aim of this study was to assess whether magnetic resonance imaging (MRI) texture features of the lateral pterygoid muscle can distinguish between rheumatoid arthritis (RA) and osteoarthritis (OA) of the temporomandibular joint (TMJ). METHODS: The authors extracted 279 texture features from 36 patients with RA and OA from the region of interest set for the lateral pterygoid muscle on short tau inversion recovery (STIR) images using MaZda Ver.3.3. A total of 10 texture features were selected using Fisher's coefficients, as well as probability of error and average correlation coefficients. Data observed to have a non-normal distribution using the Kolmogorov-Smirnov test were compared using the Mann-Whitney U-test. Receiver operating characteristic (ROC) curves were used to assess the ability of the 10 texture features to distinguish RA and OA of the TMJ. RESULTS: A total of 10 features (5 Correlation, 3 Run Length Nonuniformity, 1 Sigma, and 1 Teta) were selected from 279 texture features. These texture features revealed significant differences between the RA and OA groups (p < 0.01). The sensitivity, specificity, accuracy, and area under the ROC curve of the texture features for distinguishing RA from OA were 0.78-0.94, 0.89-1.0, 0.86-0.92, and 0.89-0.95, respectively. CONCLUSION: MRI texture analysis of the lateral pterygoid muscle may be useful for distinguishing between RA and OA of the TMJ.

Detecting lymphadenopathy affected by peri-implantitis using diffusion-weighted magnetic resonance imaging.

PURPOSE: This study aimed to assess peri-implantitis-induced lymphadenopathy on diffusion-weighted imaging (DWI). METHODS: This retrospective study was conducted from October 2017 to March 2020 in patients with and without peri-implantitis who underwent magnetic resonance imaging (MRI). Patients in the peri-implantitis group had radiographically confirmed loss of alveolar bone > 2.0 mm and clinical findings such as bleeding on probing, suppuration of tissues surrounding the teeth, probing-pocket depth of > 4 mm, pain on implant function, and clinical implant mobility, whereas those without peri-implantitis had none of the abovementioned clinical findings. The Mann-Whitney U test was used to compare groups, using lymph node (LN) short-axis diameters and apparent diffusion coefficients (ADCs) as the criterion variables and presence or absence of peri-implantitis as the explanatory variable. Receiver operating characteristic (ROC) analysis was done to investigate the effectiveness of LN size and ADC use in detecting peri-implantitis-induced lymphadenopathy. Statistical significance was established at P < 0.05. RESULTS: There were 66 lymph nodes from 12 patients analyzed. The mean LN size and ADC were significantly higher in patients with peri-implantitis than in those without (P < 0.01). ROC curve analysis showed cut-off LN sizes of 4.78 and 4.84 mm and cut-off ADCs of 1.12 and 1.09 for lymphadenopathy affected by peri-implantitis corresponding to levels IB and II, respectively. CONCLUSIONS: Cervical lymphadenopathy may be an inflammatory finding associated with peri-implantitis.

Diagnostic Efficacy of Diffusion-weighted Imaging in Distinguishing Chronic Diffuse Sclerosing Osteomyelitis from Suppurative Osteomyelitis of the Mandible.

PURPOSE: Chronic diffuse sclerosing osteomyelitis (CDSO) is a non-suppurative inflammatory bone disease diagnosed based on combined clinical, histopathological, and radiological findings. Accurate diagnosis is important since CDSO is more refractory to treatment than suppurative osteomyelitis. The purpose of this study was to determine the diagnostic efficacy of diffusion-weighted imaging (DWI) in the quantitative assessment of CDSO to distinguish it from acute suppurative osteomyelitis (ASO) and chronic suppurative osteomyelitis (CSO) of the mandible. METHODS: Using a retrospective cohort study design, we analyzed MRI data of 6 patients with CDSO and 34 patients with ASO and CSO. The mean apparent diffusion coefficient (ADC) values of the three groups (CDSO, ASO, and CSO groups) were calculated, and differences were analyzed using Kruskal-Wallis and post-hoc Mann-Whitney tests with Bonferroni adjustments. We performed a receiver operating characteristic (ROC) curve analysis to evaluate the ability of the ADC to predict CDSO. P < 0.05 was considered statistically significant. RESULTS: The mean ADCs in the CDSO, ASO, and CSO groups were 1.22 ± 0.04 × 10-3 mm2/s, 1.28 ± 0.08 × 10-3 mm2/s, and 1.06 ± 0.09 × 10-3 mm2/s, respectively. Significant differences were observed between the ASO and CSO groups (P < 0.001) and CSO and CDSO groups (P < 0.01). However, there was no significant difference between the ASO and CDSO groups (P = 0.21). The ROC analysis revealed a cut-off ADC value of 1.19 for distinguishing the CSO group from the CDSO group. Sensitivity, specificity, accuracy, and area under the ROC curve were 1.0, 0.92, 0, 95, and 0.94, respectively. CONCLUSION: The results suggest that ADC may be useful in distinguishing CDSO from mandibular suppurative osteomyelitis.

Risk assessment of external apical root resorption associated with orthodontic treatment using computed tomography texture analysis.

OBJECTIVES: This study aimed to quantitatively assess maxillary central incisor roots using pre-orthodontics computed tomography (CT) texture analysis as part of a radiomics quantitative analysis. METHODS: This retrospective case-control study included 16 patients with external apical root resorption (EARR) and 16 age- and sex-matched patients without EARR, after orthodontic treatment who underwent pre-orthodontics CT for jaw deformities. All patients were treated with a fixed orthodontic appliance before and after surgical orthodontic treatment. EARR was defined as root resorption ≥ 2 mm of the left and right maxillary central incisors on CT images more than 2 years after the start of orthodontic treatment. Texture features of the maxillary central incisor with and without EARR after orthodontic treatment were analyzed using the open-access software, MaZda Ver. 3.3. Ten texture features were selected using the Fisher method in MaZda from 279 original parameters, which were calculated for each of the maxillary central incisors with and without EARR. The results were tested using the Student's t test, Welch's t test, or Mann-Whitney U test. RESULTS: Four gray-level run length matrix features and six gray-level co-occurrence matrix features displayed significant differences between both the groups (p < 0.01). CONCLUSIONS: CT texture analysis was able to quantitatively assess maxillary central incisor roots and distinguish between maxillary central incisor roots with and without EARR. CT texture analysis may be a useful method for predicting EARR after orthodontic treatment.

Magnetic resonance image texture analysis of the lateral pterygoid muscle in patients with rheumatoid arthritis: a preliminary report.

OBJECTIVES: Magnetic resonance imaging (MRI) is useful for assessing temporomandibular disorders (TMDs). However, few studies have attempted texture analysis of the lateral pterygoid muscle in patients with rheumatoid arthritis (RA). This study aims to investigate the usefulness of MRI texture analysis of the lateral pterygoid muscle of patients with RA of the temporomandibular joint (TMJ). METHODS: We analyzed the data from 36 patients (18 non-RA patients and 18 RA patients) who complained of pain and underwent MRI between April 2008 and August 2021. From the MRI scans of these patients, 279 radiomics features were extracted using STIR image data of the ROIs on the lateral pterygoid muscle of patients with RA and analyzed using MaZda ver. 3.3. Seven gray-level co-occurrence matrix features (Sum entropy, Sum variance) were picked up using the Fisher coefficient, for comparison between the RA and non-RA groups. Data analysis was performed using the Mann-Whitney U test A P value of < 0.05 was considered as statistically significant. RESULTS: All seven lateral pterygoid muscle radiomic features indicated significant differences between the non-RA and RA groups (P < 0.05). CONCLUSION: MRI texture analysis shows potential for application in radiomics diagnosis of RA in TMJ.

Quantitative analysis of masticatory muscle changes by Eichner index using diffusion-weighted imaging.

OBJECTIVES: Diffusion-weighted imaging (DWI) provides quantitative functional information about the microscopic movement of water at the cellular level. However, few reports have quantitatively evaluated histological changes in masticatory muscles due to changes in occlusal relationships using DWI. This study aimed to assess the changes in masticatory muscles by Eichner index using DWI. METHODS: We analyzed magnetic resonance imaging (MRI) studies of 201 patients from November 2017 to April 2018. Each Eichner index group, age, and sex were used as criterion variables, and the average apparent diffusion coefficient (ADC) values of the masticatory muscles were the explanatory variable. The mean ADC value differences were analyzed in each Eichner index group. We analyzed the data using the Kruskal-Wallis test and post hoc Mann-Whitney test with Bonferroni adjustment multiple regression analysis with Shapiro-Wilk test and Spearman's correlation coefficients. P < 0.05 was considered statistically significant. RESULTS: The mean ADC values of each Eichner classification group were significantly different, with the lowest value in group C (P < 0.001). There was a negative correlation between the ADC value of the masseter, lateral pterygoid muscle, and age (P < 0.001). There were significant differences between the sex groups (P < 0.001). CONCLUSIONS: ADC values of masticatory muscles were significantly different in the Eichner index groups. The ADC values of masticatory muscles may be useful for the quantitative evaluation of the masticatory muscles affected by the occlusal state.

Texture analysis of low-flow vascular malformations in the oral and maxillofacial region: venous malformation vs. lymphatic malformation.

Purpose: It is challenging for radiologists to distinguish between venous malformations (VMs) and lymphatic malformations (LMs) using magnetic resonance imaging (MRI). Thus, this study aimed to differentiate VMs from LMs using non-contrast-enhanced MRI texture analysis. Material and methods: This retrospective case-control study included 12 LM patients (6 men and 6 women; mean age 43.58, range 7-85 years) and 29 VM patients (7 men and 22 women; mean age 53.10, range 19-76 years) who underwent MRI for suspected vascular malformations. LM and VM patients were identified by histopathological examination of tissues excised during surgery. The texture features of VM and LM were analysed using the open-access software MaZda version 3.3. Seventeen texture features were selected using the Fisher and probability of error and average correlation coefficient methods in MaZda from 279 original parameters calculated for VM and LM. Results: Among 17 selected texture features, the patients with LM and VM revealed significant differences in 1 histogram feature, 8 grey-level co-occurrence matrix (GLCM) features, and 1 grey-level run-length matrix feature. At the cut-off values of the histogram feature [skewness ≤ -0.131], and the GLCM features [S(0, 2) correlation ≥ 0.667, S(0, 3) correlation ≥ 0.451, S(0, 4) correlation ≥ 0.276, S(0, 5) correlation ≥ 0.389, S(1, 1) correlation ≥ 0.739, S(2, 2) correlation ≥ 0.446, S(2, -2) correlation ≥ 0.299, S(3, -3) correlation ≥ 0.091] had area under the curves of 0.724, 0.764, 0.773, 0.747, 0.733, 0.759, 0.730, 0.744 and 0.727, respectively. Conclusions: Non-contrast-enhanced MRI texture analysis allows us to differentiate between LMs and VMs.

Normal Variants of the Oral and Maxillofacial Region: Mimics and Pitfalls.

A normal variant is defined as an incidental, often asymptomatic, imaging finding that mimics a true pathologic condition. Given the complex anatomy and wide variety of normal variants in the oral and maxillofacial region, a thorough understanding of commonly encountered normal variants in this region is essential to avoid misinterpretation and unnecessary further imaging or interventions. Moreover, familiarity with normal variants that are known to become symptomatic at times is necessary to facilitate further workup and guide the treatment plan. Intraoral radiography and panoramic radiography, which are unique to oral and maxillofacial radiology, provide two-dimensional (2D) images. Hence, the overlapping of structures or the displacement of the tomographic layer on images can confuse radiologists. It is crucial to understand the principle of 2D imaging to avoid being confused by ghost images or optical illusions. In addition, understanding the normal development of the maxillofacial region is essential when interpreting maxillofacial images in children or young adults because the anatomy may be quite different from that of mature adults. Knowledge of changes in the jaw bone marrow and each tissue's growth rate is essential. It is also necessary to know when the tooth germ begins to calcify and the tooth erupts for diagnostic imaging of the maxillofacial region. The authors describe imaging findings and clinical manifestations of common normal variants in the oral and maxillofacial region, divided into four parts: the maxilla, mandible, tooth, and temporomandibular joint, and discuss the imaging approach used to differentiate normal variants from true pathologic conditions. Online supplemental material is available for this article. ©RSNA, 2022.

Diagnostic utility of magnetic resonance imaging texture analysis in suppurative osteomyelitis of the mandible.

PURPOSE: This study aimed to determine the diagnostic utility of magnetic resonance imaging (MRI) texture analysis for evaluating mandibular suppurative osteomyelitis (OM). MATERIALS AND METHODS: In this retrospective cohort study, we analyzed the records of 50 patients with and without OM who underwent MRI between April 2019 and March 2021. The presence or absence of OM served as a predictor variable. The outcome variables were the texture features of the region of interest, which were analyzed. Quantitative parameters based on histogram features (90th percentile) and gray-level co-occurrence matrix (GLCM) features (Sum Averg) were calculated using short-tau inversion-recovery data with a region of interest. These six features out of 279 parameters were selected using Fisher, probability of error, and average correlation coefficient methods in MaZda. For the analysis of trivariate statistics, the post-Mann-Whitney test of the Kruskal-Wallis test with Bonferroni adjustment was used, and the p value was set to 0.05. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic effect of texture function to distinguish between acute and chronic diseases. RESULTS: One histogram feature and five GLCM features showed differences among the non-OM patients, acute OM patients, and chronic OM patients (p < 0.05). The ROC analysis revealed a high area under the curve ranging from 0.91 to 0.96 for six texture features. CONCLUSION: The six texture features of the mandibular bone marrow demonstrated differences among patients without and with acute and chronic OM. MRI texture analysis may facilitate accurate assessment of the mandibular OM stage.

Quantitative assessment of the mandibular condyle in patients with diabetes mellitus using diffusion-weighted magnetic resonance imaging.

OBJECTIVE: The purpose of this study was to quantitatively assess the mandibular condyle in patients with diabetes mellitus (DM) using the apparent diffusion coefficient (ADC) on diffusion-weighted magnetic resonance imaging (DWI). STUDY DESIGN: 102 patients with DM and temporomandibular joint (TMJ) pain who underwent magnetic resonance imaging (MRI) examination of the TMJs at our hospital between August 2006 and March 2020 were included in this study. 112 patients with temporomandibular disorders (TMD) who underwent MRI examination at our hospital between April 2019 and March 2020 were included as controls. The MRI findings were compared between the two groups. RESULTS: The mean ADC values of the mandibular condyle in patients with DM were significantly greater than the controls (P < 0.01). Receiver operating characteristic (ROC) curve analysis revealed a cutoff of 0.98 for the ADC values of the mandibular condyle in patients with DM. CONCLUSION: This study found that the ADC on DWI could be used for the quantitative assessment of the mandibular condyle in patients with DM. DWI might serve as a new and noninvasive method to assess the presence of DM.

Quantitative assessment of age-related changes in the mandibular bone marrow using apparent coefficient value.

PURPOSE: The purpose of this study was to investigate the age-related changes in apparent diffusion coefficient (ADC) values of the mandibular bone marrow using diffusion-weighted imaging (DWI). MATERIALS AND METHODS: This retrospective cohort study comprised all patients who underwent pantomography and magnetic resonance imaging (MRI) between April 2018 and November 2020 at our institution. A total of 351 participants (140 men, 211 women), aged 15-89 years (mean age 46.01 years), were included in the study. Spearman's correlation coefficients were calculated using age groups as the criterion variable and the ADC values as the explanatory variables. P < 0.05 was considered statistically significant. RESULTS: The mean ADC value for all age groups was 0.91 ± 0.18 in men and 0.86 ± 0.16 in women (p = 0.016). There was a significant negative correlation between age and the ADC values in each sex group (p < 0.001). CONCLUSION: This study demonstrates that the normal ADC values of the mandibular bone marrow show significant negative correlation with increasing age. These findings will be useful in the diagnosis of bone marrow diseases.

Magnetic resonance imaging texture analysis in the quantitative evaluation of acute osteomyelitis of the mandibular bone.

OBJECTIVES: Accurate assessment of radiological images can help in early diagnosis and therapy of suppurative osteomyelitis (OM). The purpose of this study was to apply texture analysis to MRI as a means of quantitatively evaluating acute OM of the mandible. METHODS: We analyzed the data from 38 patients who complained of pain and underwent MRI between April 2017 and March 2019. From the MRIs of these patients, with (n = 19) and without OM (n = 19), 279 radiomics features were extracted using short tau inversion recovery, data of the regions of interest and analyzed with MaZda v. 3.3. 10 features, including one histogram feature (90th percentile), eight gray-level co-occurrence matrix features (Sum Averg), and one gray-level run-length matrix feature (Horzl_RLNonUni), were selected using Fisher coefficient and compared between the acute OM and non-OM groups. The two groups were compared using Mann-Whitney U test with p value set at 0.05. RESULTS: All 10 radiomics features showed significant differences between the acute OM and non-OM groups (p < 0.05). CONCLUSIONS: MRI texture analysis has potential application in radiomics diagnosis of acute OM of the mandible.

The diagnostic utility of size and apparent diffusion coefficient values for cervical lymph nodes in patients with osteomyelitis of the jaw bone.

PURPOSE: The purpose of this study was to (1) clarify the size and apparent diffusion coefficient (ADC) value of lymph nodes (LN) in each state in their quantitative evaluation diffusion-weighted imaging, and (2) to determine the diagnostic utility of size and ADC values in the quantitative evaluation of LNs using diffusion-weighted imaging. METHODS: This was a retrospective cohort study at our hospital conducted between April 2017 and March 2019. A total of 50 patients (20 men, 30 women) with 118 LNs, aged 34-90 years (mean age 61.18 years), undergoing magnetic resonance imaging examination were included in the study. The predictor variable was disease status. The primary outcome variable was the mean size and ADC values of the LNs. The other variables were age and sex. Data were analyzed using a Kruskal-Wallis test, and hoc Mann-Whitney tests with Bonferroni adjustment and a receiver operating characteristic (ROC) curve. P < 0.05 was considered to indicate statistical significance. RESULTS: We analyzed the records of 50 patients (118 LNs) with and without osteomyelitis. Of these, 21 had acute osteomyelitis, and 16 had chronic osteomyelitis. The size and ADC values of LNs in the osteomyelitis group were significantly greater and higher, respectively, than those in the non-myelitis group (P < 0.01). ROC analysis revealed a cutoff short-axis size of 4.42 and 4.04 mm for lymphadenopathy caused by osteomyelitis, corresponding to levels IB and level II, respectively. Moreover, the ADC cutoff values for the same were 0.85 and 0.86, respectively. CONCLUSION: The results suggest that size and ADC values are useful parameters for the quantitative evaluation of lymphadenopathy caused by osteomyelitis.

Detection of posterior superior alveolar artery using multi-detector row CT: a retrospective study focused on age-related changes.

PURPOSE: The posterior superior alveolar artery (PSAA) is a branch of the maxillary artery that supplies the lateral sinus wall and overlying membrane. This artery is one among several arteries in which arterial damage during surgery can cause massive and fatal bleeding. The purpose of this study was to detect the PSAA using multi-detector row computed tomography (MDCT) by age. MATERIALS AND METHODS: The present study was approved by our university ethics committee (EC19-010). The study included 230 patients (110 males, 120 females; ages 5-91 years, average age 42.5 years) who underwent MDCT of the jaw. The subjects were divided into two groups, one group in which the PSAA was observable and another in which the PSAA was not observable, to perform the Mann-Whitney U test. To perform the Tukey-Kramer multiple comparison test, the subjects were divided into the following ten groups depending on their age: 5-9 years, 10-19 years, 20-29 years, 30-39 years, 40-49 years, 50-59 years, 60-69 years, 70-79 years, 80-89 years, and 90-91 years. RESULTS: The PSAA was identified in 74.5% (5-91 years) of the maxillary sinuses. The average age of subjects in whom the PSAA was observable was 33.4 years, and the average age of subjects in whom the PSAA was not observable was 11.3 years, indicating a significant difference between these two groups (p < 0.01). A comparison by age group showed a significant difference (p < 0.05). CONCLUSIONS: The detection ratio for the PSAA using MDCT increased with increasing age of the subject, reaching a high detection ratio of 94% in adults. This study has shown that MDCT is a very useful tool to observe the PSAA.

Quantitative assessment of the maxillary sinusitis using computed tomography texture analysis: odontogenic vs non-odontogenic etiology.

OBJECTIVES: The purpose of this study was to investigate computed tomography (CT) texture features of mucosal thickening of maxillary sinus mucosa to differentiate odontogenic maxillary sinusitis (OMS) from non-odontogenic maxillary sinusitis (NOMS). METHODS: Eighteen OMS patients and age- and gender-matched 18 NOMS patients who underwent sinus CT were retrospectively reviewed. OMS patients were identified by histopathological examination of tissues excised at surgery combined with CT imaging findings. Patients with mucosal thickening in the maxillary sinus without apical periodontitis or advanced periodontal bone loss near the maxillary sinus on CT were defined as NOMS. Patients with thin mucosal thickening (< 10 mm), cyst, tumor, post-operative deformity, severe metal artifact precluding visualization of the maxillary sinus, and age younger than 20 years were excluded. CT texture features of the mucosal thickening were analyzed using an in-house developed Matlab-based texture analysis program. Forty-five texture features were extracted from each segmented volume. The results were tested with the Mann-Whitney U test. RESULTS: Six histogram features (mean, median, standard deviation, entropy, geometric mean, harmonic mean) and two gray-level co-occurrence matrix features (entropy, correlation) showed significant differences between OMS and NOMS patients. CONCLUSIONS: CT texture analysis revealed the quantitative differences between OMS and NOMS. The texture features can serve as a quantitative indicator of maxillary sinusitis to differentiate between OMS and NOMS and help prevent incorrect treatment choices.

Risk assessment of lacunar infarct associated with oral conditions: A case control study focused on radiographic bone loss and Eichner classification.

PURPOSE: This study aimed to evaluate whether lacunar infarcts can be predicted from occlusal support and periodontal stage on images. METHODS: Seventy patients with lacunar infarcts and 300 participants without lacunar infarcts who underwent cerebral checkups at our university hospital were retrospectively reviewed. Lacunar infarcts were assessed using magnetic resonance images by a neuroradiologist. The number of teeth, occlusal support, and severity of radiographic bone loss (RBL) were evaluated using computed tomography. Occlusal support was classified according to the Eichner classification. Additionally, patient characteristics were investigated using medical charts and blood test reports. Records of clinical periodontal parameters, such as clinical attachment loss and bleeding on probing, were also evaluated. RESULTS: The severity of RBL and Eichner classification in patients with lacunar infarcts was significantly higher than that in individuals without lacunar infarcts (P<.01). Receiver operating characteristic analysis revealed that the cut-off values for predicting lacunar infarct were ≥ III in the severity of RBL and ≥B1 in the Eichner classification. The corresponding areas under the curve were 0.75 and 0.70, respectively. In multivariate analysis, the factors affecting the severity of RBL (≥ III) (odds ratio [OR], 8.1; 95% confidence interval [CI], 4.1-16.3; P<.001), and Eichner classification (≥B1) (OR, 1.9; 95% CI, 0.86-4.1; P<.05) were significantly associated with the occurrence of lacunar infarcts. CONCLUSION: The severity of RBL and the Eichner classification may be helpful in predicting lacunar infarcts. Therefore, proper periodontal treatment and prosthodontic rehabilitation of missing teeth may prevent lacunar infarcts.

Quantitative assessment of the mandibular bone marrow of diabetes mellitus patients using diffusion-weighted magnetic resonance imaging.

PURPOSE: The purpose of this study was to assess quantitatively the mandibular bone marrow of patients with and without diabetes mellitus (DM) using the apparent diffusion coefficient (ADC) values on diffusion-weighted imaging (DWI). METHODS: 65 DM patients (28 men, 37 women, 29-84 years of age, mean age 55.7 ± 15.7 years) and age-, sex- and periodontitis stage-matched 65 non-DM patients who had underwent MRI between April 2006 and March 2018 were included in this study. The ADC was calculated using the ADC visualization tool implemented in a dedicated off-line workstation. The regions of interest (ROI) were manually placed on the ADC map on which the mandibular bone marrow from the lower first molar to the lower second molar was observed in patients with and without DM. Statistical analysis was performed using the Mann-Whitney U test and receiver operating characteristic (ROC) curve analysis. P values < 0.05 were considered statistically significant. RESULTS: The mean ADC values of the mandibular bone marrow of patients with and without DM were 1.18 ± 0.21 × 10-3 mm2/s and 0.83 ± 0.14 × 10-3 mm2/s, respectively. The ADC values of DM patients were significantly higher than those of patients without DM. CONCLUSION: The ADC values allowed the quantitative evaluation of the mandibular bone marrow of DM patients. DWI might serve as a new and noninvasive method to assess the presence of DM.