Sex‐related differences in symptoms of temporomandibular disorders and structural changes in the lateral pterygoid muscle after whiplash injury

Auh

2021

Preprint

Self Cite

Objective: To investigate the change in volume and signal in the masticatory muscles and temporomandibular joint (TMJ) of patients with temporomandibular disorder (TMD) after whiplash injury based on magnetic resonance imaging (MRI) and to correlate them with other clinical parameters. Methods: Ninety patients (64 women, 26 men; mean age: 39.36±15.40 years), including 45 patients with symptoms of TMD after whiplash injury (wTMD), and 45 age- and sex-matched controls with TMD due to idiopathic causes (iTMD) were included. TMD was diagnosed using the study diagnostic criteria for TMD Axis I, and MRI findings of the TMJ and masticatory muscles were investigated. To evaluate the severity of TMD pain and muscle tenderness, we used a visual analog scale (VAS), palpation index (PI), and neck PI. Results: TMD indexes, including VAS, PI, and neck PI were significantly higher in the wTMD group. In the wTMD group, muscle tenderness was highest in the masseter muscle (71.1%), and muscle tenderness in the temporalis (60.0%), lateral pterygoid muscle (LPM) (22.2%), and medial pterygoid muscle (15.6%) was significantly more frequent than that in the iTMD group (all p<0.05). The most noticeable structural changes in the masticatory muscles occurred in the LPM with whiplash injury. Volume (57.8% vs. 17.8%) and signal changes (42.2% vs. 15.6%) of LPM were significantly more frequent in the wTMD group than in the iTMD group. The presence of signal changes in the LPM was positively correlated with the increased VAS scores only in the wTMD group (r=0.346, p=0.020). The prevalence of anterior disc displacement without reduction (ADDWoR) (53.3% vs. 28.9%) and disc deformity (57.8% vs. 40.0%) were significantly higher in the wTMD group (p<0.05). The presence of headache, sleep problems, and psychological distress was significantly higher in the wTMD group than in the iTMD group. Conclusion: Abnormal MRI findings and their correlations with clinical characteristics of the wTMD group were different from those of the iTMD group. The underlying neuropathophysiology may differ depending on the cause of TMD, raising the need for a treatment strategy accordingly.

Section: Introductionmentioning

confidence: 93%

“…The detailed procedure of validation has been described in our previous papers. 6,13 The disc position in the oblique sagittal plane was determined in the closed and open-mouth positions. In addition, disc position was classi ed as anterior disc displacement with reduction (ADDWR) or without reduction (ADDWoR) (Fig.…”

Section: Validation Of Mri Ndingsmentioning

confidence: 99%

MRI-based Assessment of Masticatory Muscle Changes in TMD Patients After Whiplash Injury 

Auh

2021

Preprint

Self Cite

“…High-resolution MRI images were obtained on a 3T MRI system (Signa™ Genesis, GE Healthcare, Chicago, IL, USA) with a 6-cm × 8-cm diameter surface coil. MRI examination was dependent on the MR sequences and protocol of Kyung Hee University Medical Center, and the details has also been revealed in our previous studies [13,27]: All scans involved sagittal oblique sections (section thickness, 3 mm or less,; eld of view, 15-cm; matrix dimensions, 256 × 224 matrix) and spin-echo sagittal MR images were obtained on the axial localizer images. T1-weighted images (T1WIs) and T2-weighted images (T2WIs) were obtained using a 650/14 TR/TE sequence and 2,650/82 TR/TE sequence, respectively.…”

Section: Mri Acquisition and Analysismentioning

confidence: 99%

“…In addition, the huge tensile force throughout the whiplash injury exerted on a muscle may lead to excessive stretching of the muscle bers and consequently a tear, and impair the muscle-tendon junction [22]. According to our previous MRIbased studies, patients with TMD due to whiplash injury suffered more distortion of the disc-condyle relationship and LPM changes [6,13]. TMJ disc displacement leads to degenerative changes in the disc deformity and condylar degeneration, [23] and the symptoms of TMD might become chronic.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

MRI-Based Assessment of Masticatory Muscle Changes in TMD Patients After Whiplash Injury

Auh

2021

Preprint

Self Cite

Objective To investigate the change in volume and signal in the masticatory muscles and temporomandibular joint (TMJ) of patients with temporomandibular disorder (TMD) after whiplash injury based on magnetic resonance imaging (MRI) and to correlate them with other clinical parameters. Methods Ninety patients (64 women, 26 men; mean age: 39.36 ± 15.40 years), including 45 patients with symptoms of TMD after whiplash injury (wTMD), and 45 age- and sex-matched controls with TMD due to idiopathic causes (iTMD) were included. TMD was diagnosed using the study diagnostic criteria for TMD Axis I, and MRI findings of the TMJ and masticatory muscles were investigated. To evaluate the severity of TMD pain and muscle tenderness, we used a visual analog scale (VAS), palpation index (PI), and neck PI. Results TMD indexes, including VAS, PI, and neck PI were significantly higher in the wTMD group. In the wTMD group, muscle tenderness was highest in the masseter muscle (71.1%), and muscle tenderness in the temporalis (60.0%), lateral pterygoid muscle (LPM) (22.2%), and medial pterygoid muscle (15.6%) was significantly more frequent than that in the iTMD group (all p < 0.05). The most noticeable structural changes in the masticatory muscles occurred in the LPM with whiplash injury. Volume (57.8% vs. 17.8%) and signal changes (42.2% vs. 15.6%) of LPM were significantly more frequent in the wTMD group than in the iTMD group. The presence of signal changes in the LPM was positively correlated with the increased VAS scores only in the wTMD group (r = 0.346, p = 0.020). The prevalence of anterior disc displacement without reduction (ADDWoR) (53.3% vs. 28.9%) and disc deformity (57.8% vs. 40.0%) were significantly higher in the wTMD group (p < 0.05). The presence of headache, sleep problems, and psychological distress was significantly higher in the wTMD group than in the iTMD group. Conclusion Abnormal MRI findings and their correlations with clinical characteristics of the wTMD group were different from those of the iTMD group. The underlying neuropathophysiology may differ depending on the cause of TMD, raising the need for a treatment strategy accordingly.

Advantages of deep learning with convolutional neural network in detecting disc displacement of the temporomandibular joint in magnetic resonance imaging

Won

Kim

et al. 2022

Sci Rep

This study investigated the usefulness of deep learning-based automatic detection of anterior disc displacement (ADD) from magnetic resonance imaging (MRI) of patients with temporomandibular joint disorder (TMD). Sagittal MRI images of 2520 TMJs were collected from 861 men and 399 women (average age 37.33 ± 18.83 years). A deep learning algorithm with a convolutional neural network was developed. Data augmentation and the Adam optimizer were applied to reduce the risk of overfitting the deep-learning model. The prediction performances were compared between the models and human experts based on areas under the curve (AUCs). The fine-tuning model showed excellent prediction performance (AUC = 0.8775) and acceptable accuracy (approximately 77%). Comparing the AUC values of the from-scratch (0.8269) and freeze models (0.5858) showed lower performances of the other models compared to the fine-tuning model. In Grad-CAM visualizations, the fine-tuning scheme focused more on the TMJ disc when judging ADD, and the sparsity was higher than that of the from-scratch scheme (84.69% vs. 55.61%, p < 0.05). The three fine-tuned ensemble models using different data augmentation techniques showed a prediction accuracy of 83%. Moreover, the AUC values of ADD were higher when patients with TMD were divided by age (0.8549–0.9275) and sex (male: 0.8483, female: 0.9276). While the accuracy of the ensemble model was higher than that of human experts, the difference was not significant (p = 0.1987–0.0671). Learning from pre-trained weights allowed the fine-tuning model to outperform the from-scratch model. Another benefit of the fine-tuning model for diagnosing ADD of TMJ in Grad-CAM analysis was the deactivation of unwanted gradient values to provide clearer visualizations compared to the from-scratch model. The Grad-CAM visualizations also agreed with the model learned through important features in the joint disc area. The accuracy was further improved by an ensemble of three fine-tuning models using diversified data. The main benefits of this model were the higher specificity compared to human experts, which may be useful for preventing true negative cases, and the maintenance of its prediction accuracy across sexes and ages, suggesting a generalized prediction.