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.

Visualising cervical lymph nodes in jaw osteonecrosis using diffusion-weighted imaging.

OBJECTIVES: This study aimed to apply diffusion-weighted imaging to the evaluation of cervical lymph nodes affected by medication-related osteonecrosis of the jaw (MRONJ). METHODS: This retrospective study analysed the diffusion-weighted imaging data of 70 patients with or without MRONJ (Stages 0-3). The mean apparent diffusion coefficient (ADC) values of the submandibular (level IB) and superior internal jugular (level IIA) nodes in the control and MRONJ groups were calculated, and differences were analysed using the Mann-Whitney test. Moreover, receiver operating characteristic (ROC) curve analysis was performed to evaluate the ability of ADC values to predict lymph nodes that were affected by MRONJ. p < 0.05 was considered statistically significant. RESULTS: The median [interquartile range] (×10-3 mm2/s) of level IB was 0.74 [0.7-0.81] and 0.93 [0.84-1.09] and that of level IIA was 0.79 [0.76-0.85] and 0.97 [0.84-1.06] in the control and MRONJ groups respectively. ROC analysis revealed that the ADC value had excellent ability to discriminate between the control and MRONJ groups. CONCLUSIONS: The study findings indicate that diffusion-weighted imaging can contribute to differentiation of MRONJ from other cervical lymph node diseases and facilitate early detection of MRONJ.

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.

Central vascular malformations of the mandible: characteristic findings in computed tomography and magnetic resonance imaging.

Central vascular malformations (CVMs) of the mandible are rare and can have varied clinical and radiological characteristics, thus making differential diagnosis difficult. We retrospectively reviewed 5 patients with proven CVM who underwent computed tomography (CT) and magnetic resonance imaging (MRI), including diffusion-weighted imaging (DWI) (and magnetic resonance angiography (MRA) for one patient), to assess the characteristic imaging findings of this lesion. CT revealed multilocularity in 3 lesions. All CVMs produced fine, irregular borders and low-to-intermediate density. Lesion continuity with the mandibular canal was discovered in 4 cases and enlarged feeding and outflow vessels in 3 lesions. Bone overgrowth was observed in 2 patients. CT values ranged from 30.84 to 52.87 Hounsfield units (HU). MRI exhibited low to intermediate signals on T1-weighted imaging (T1WI), signals ranging from low to intermediate-to-high on T2WI, and low to high signal intensity on short-tau inversion recovery (STIR) images, with flow voids in all patients and no inflammation in surrounding tissues. As calculated with DWI, the apparent diffusion coefficient (ADC) ranged from 0.69 to 1.74 × 10-3 mm2/s. MRA showed the presence of feeding vessels in 1 lesion. Interexaminer agreement on image interpretation ranged from moderate to excellent. These typical CVM imaging findings may aid in the differential diagnosis of this lesion.

Differential diagnosis of parotid gland tumors using apparent diffusion coefficient, texture features, and their combination.

OBJECTIVES: Warthin's tumors (WT) and pleomorphic adenomas (PA) are the commonest parotid gland tumors; however, their differentiation remains difficult. This study aimed to investigate the utility of the apparent diffusion coefficient (ADC) value, texture features, and their combination for the differential diagnosis of parotid gland tumors. METHODS: Patients who underwent magnetic resonance imaging (MRI) between April 2008 and March 2021 for parotid gland tumors were included and divided into two groups according to the tumor type: WT and PA. The tumor types were used as predictor variables, while the ADC value, texture features, and their combination were the outcome variables. Texture features were measured on short tau inversion recovery (STIR) images and selected using the Fisher's coefficient method and probability of error, and average correlation coefficients. The Mann-Whitney U-test was used to analyze bivariate statistics. Receiver operating characteristic curve analysis was used to assess the ability of the ADC value, texture features, and their combination to distinguishing between the two tumor types. RESULTS: A total of 22 patients were included, 11 in each group. The ADC value, 10 texture features, and their combination were significantly different between the two groups (p < .001). Moreover, all three variables had high area under the curve values of 0.93-0.96. CONCLUSION: The ADC value, texture features, and their combination demonstrated good diagnostic ability to distinguish between WTs and PAs. This method may be used to aid the differential diagnosis of parotid gland tumors, thereby promoting timely and adequate treatment.

Diagnostic efficacy of apparent diffusion coefficient, texture features, and their combination for differential diagnosis of odontogenic cysts and tumors.

OBJECTIVE: This study assessed the diagnostic efficacy of apparent diffusion coefficient (ADC), texture features, and their combination for the differential diagnosis of odontogenic cysts and tumors with cyst-like features. STUDY DESIGN: In total, 14 dentigerous cysts (DCs), 12 odontogenic keratocysts (OKCs), and 6 unicystic ameloblastomas (UABs) were used as predictor variables in 32 outpatients who underwent magnetic resonance imaging. The outcome variables were ADC, texture features, and their combination for each lesion. Texture features including histogram and gray-level co-occurrence matrix (GLCM) were measured on ADC maps. Ten features were selected by using the Fisher coefficient method. The Kruskal-Wallis test and post hoc Mann-Whitney test with Bonferroni adjustment were used to analyze trivariate statistics. Statistical significance was established at P < .05. Receiver operating characteristic analysis was used to evaluate the diagnostic effect of ADC, texture features, and their combination in distinguishing the lesions from each other. RESULTS: Apparent diffusion coefficient, 1 histogram feature, 9 GLCM features, and their combination demonstrated significant differences between DC, OKC, and UAB (P ≤ .01). Receiver operating characteristic analysis revealed a high area under the curve of .95 to 1.00 for ADC, 10 texture features, and their combination. Sensitivity, specificity, and accuracy ranged from .86 to 1.00. CONCLUSIONS: Apparent diffusion coefficient and texture features, alone or in combination, can be clinically important in facilitating the distinction between these odontogenic lesions.

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.