Functional Changes of the Lateral Pterygoid Muscle in Patients with Temporomandibular Disorders: A Pilot Magnetic Resonance Images Texture Study
Temporomandibular disorders (TMDs) are a common clinical syndrome characterized by pain in the temporomandibular joint (TMJ) or its associated tissues. TMDs affect a significant portion of the adult population, with one-third of adults reporting symptoms. The management of TMDs has become a costly endeavor, with expenses reaching up to $4 billion annually in the past decade. Despite their prevalence, the etiology of TMDs remains unclear and is likely multifactorial. One of the most common causes of TMDs is TMJ disc displacement, which is often associated with pathological changes in the lateral pterygoid muscle (LPM). However, these functional changes in the LPM are often subtle and cannot be detected by conventional imaging techniques alone.
This study aimed to evaluate the functional changes of the LPM in patients with TMDs using texture analysis of magnetic resonance (MR) images. Texture features, which are intrinsic properties of human tissues, were employed to detect these subtle changes. The study utilized the gray-level co-occurrence matrix (GLCM) method to analyze the texture of the LPM on axial T2-weighted imaging (T2WI). The texture features examined included angular second moment (ASM), contrast, correlation, inverse different moment (IDM), and entropy.
The study included 29 patients with TMD who underwent MR imaging on a 3.0T MR scanner. The patients were classified into three groups based on the type of disc displacement: disc without displacement (DWoD), disc displacement with reduction (DDWR), and disc displacement without reduction (DDWoR). The MR imaging protocol included axial T2WI and oblique sagittal proton density-weighted imaging (PDWI) with both closed and open mouth positions. The imaging parameters for T2WI were as follows: repetition time (TR) = 3600 ms, echo time (TE) = 92.5 ms, field of view (FOV) = 21 cm x 21 cm, matrix size = 320 x 288, number of acquisitions (NEX) = 2, slice thickness = 3 mm, and slice gap = 4 mm. For PDWI, the parameters were: TR = 2423 ms, TE = 30 ms, FOV = 14 cm x 14 cm, matrix size = 288 x 192, NEX = 2, slice thickness = 2 mm, and slice gap = 1 mm.
The texture analysis was performed on the superior belly of the LPM using the GLCM method. The GLCM plugin in ImageJ software was used to measure the texture features, with the step size set to 1 pixel and the direction set to 0 degrees. The region of interest (ROI) was drawn on the LPM slice with the maximal area, avoiding adjacent fat and bone components. Each ROI was measured three times, and the mean value of the texture parameter was used for analysis.
The results revealed significant differences in texture contrast and entropy among the three groups. Texture contrast was significantly lower in the DDWoR group (46.30 [35.03, 94.48]) compared to the DWoD group (123.85 [105.06, 143.23]; test statistic = 23.05; P < 0.001). Texture entropy also showed significant differences among the groups, with values of 7.62 ± 0.33 in the DWoD group, 6.76 ± 0.35 in the DDWR group, and 6.46 ± 0.39 in the DDWoR group (F value = 60.352, PDWoD-DDWR < 0.001, PDWoD-DDWoR < 0.001, and PDDWR-DDWoR = 0.014). The area under the receiver operating characteristics (ROC) curve (AUC) demonstrated that texture entropy had an excellent diagnostic accuracy for distinguishing DWoD from DDWR (AUC = 0.96) and DWoD from DDWoR (AUC = 0.98). Texture contrast also showed good diagnostic accuracy for distinguishing DWoD from DDWoR (AUC = 0.88).
The findings suggest that texture contrast and entropy can effectively identify altered functional status of the LPM in patients with TMD. These texture features could serve as imaging biomarkers for evaluating the functional changes of the LPM in TMD. The study highlights the potential of texture analysis in detecting subtle changes in the LPM that are not visible on conventional MR images. This approach could provide valuable insights into the pathomechanism of disc displacement and inform treatment strategies for TMD patients.
The study also discussed the limitations of the current research. First, the GLCM measurement could be expanded to include more parameters, such as different step sizes and directions. Second, other texture analysis techniques, such as histogram analysis, gray-level run-length matrix, and local binary patterns, could be explored in future studies. Additionally, texture analysis was performed only on T2WI images, and future research could investigate other imaging sequences, such as T1-weighted imaging (T1WI), diffusion-weighted imaging (DWI), and PDWI.
In conclusion, this study demonstrates that texture analysis of MR images can effectively detect functional changes in the LPM of patients with TMD. The texture features of contrast and entropy were found to be particularly useful in distinguishing between different types of disc displacement. These findings suggest that texture analysis could be a valuable tool in the diagnosis and management of TMD, providing a more detailed understanding of the underlying pathomechanisms and guiding therapeutic interventions. Future research should aim to validate these findings in larger cohorts and explore additional texture analysis techniques to further enhance the diagnostic accuracy and clinical utility of this approach.
doi.org/10.1097/CM9.0000000000000658
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