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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., (© 2022. The Author(s) under exclusive licence to Japanese Society for Oral and Maxillofacial Radiology.)

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.

Purpose: Magnetic resonance imaging can detect soft- and hard-tissue abnormalities and has become the primary imaging modality for temporomandibular joints. However, few studies have quantitatively evaluated rheumatoid arthritis (RA) in temporomandibular joints using diffusion-weighted imaging. The purpose of this study was to assess the apparent diffusion coefficient (ADC) values of the inflammatory connective tissue around the mandibular condyle in RA., Methods: This was a retrospective cohort study. We analyzed the magnetic resonance imaging studies of patients with suspected temporomandibular joint disorders performed between April 2008 and August 2020. The predictor variable was disease status (RA-y/n). The primary outcome variable was the mean of ADC values of the connective tissue around the mandibular condyle. The other variables were age and sex. Furthermore, the ADC values were compared between the 2 groups. Data were analyzed using a Mann-Whitney U test, Spearman's correlation coefficient, and a receiver operating characteristic curve. P < .05 was considered to indicate statistical significance., Results: In total, 35 patients (18 normal patients and 17 patients with RA) were included. The mean ADC values were 1.26 ± 0.11 × 10 -3  mm 2 /s and 1.60 ± 0.19 × 10 -3  mm 2 /s in the control and RA groups, respectively (P < .001). Receiver operating characteristic analysis revealed that a cutoff of 1.37 for ADC values for RA provided an accuracy of 0.86. The sensitivity and specificity of ADC values were 0.94 and 0.83, respectively., Conclusions: ADC values of the inflammatory connective tissue around the mandibular condyle in RA were significantly higher in the RA group than those in the control group. This parameter might be useful for the quantitative evaluation of RA., (Copyright © 2021 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.)

Purpose: The purpose of this study was to quantitatively assess the mandibular condyle in patients with rheumatoid arthritis (RA) using the apparent diffusion coefficient (ADC) on diffusion-weighted imaging (DWI)., Patients and Methods: Thirty-one patients with RA 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. Twenty-one patients with normal TMJs who underwent MRI examination at our hospital between August 2006 and March 2020 were included as controls. The MRI findings were compared between the 2 groups., Results: The mean ADC values of the mandibular condyle in patients with RA were 1.20 ± 0.17 × 10 -3  mm 2 /second. The mean ADC values of the mandibular condyle in patients with RA were significantly greater than the controls (P < .01). Receiver operating characteristic curve analysis revealed a cutoff of 0.89 for the ADC values of the mandibular condyle in patients with RA. The receiver operating characteristic curve analysis revealed areas under the curve for maximum ADC values of 0.98., Conclusions: Our study found that the ADC on DWI could be used for the quantitative assessment of the mandibular condyle in patients with RA, which indicated that the ADC on DWI could be useful for predicting RA., (Copyright © 2020 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.)