Comparison of ultrasonography-based masticatory muscle thickness between temporomandibular disorders bruxers and temporomandibular disorders non-bruxers

The study aimed to compare the morphometric and morphologic analyses of the bone structures of temporomandibular joint and masticatory muscles on Cone beam computed tomography (CBCT) in 62 healthy subjects and 33 subjects with temporomandibular dysfunction (TMDS) aged between 18 and 56 years. In addition, a machine learning (ML) pipeline involving the Random Forest classifier was used to automatically detect TMDS. Thirty parameters (including age and gender) associated with the condylar process, articular tubercle, mandibular fossa, ramus mandible, joint space, and masticatory muscles were examined using CBCT. Well-known steps including scaling, feature selection, and feature extension are used to build the ML pipeline. Among 30 parameters, angle between mediolateral axes of both the head of mandible, medial pterygoid muscle thickness (PMT), distance between the most superior point of head of the mandible and the mandibular fossa bone surface opposite, medial joint space, lateral joint space, articular tubercle inclination, mandibular fossa depth head of the mandible’s length, and angle between the ramus mandible long axis and the coronal plane values showed significant differences between healthy subjects and TMDS. Additionally, from the above measurements, all parameters (except PMT) were significantly lower in TMDS than in healthy subjects. Moreover, the results show that it is possible to automatically detect temporomandibular dysfunction with an f1-score of 0.967 when arming our ML pipeline with feature selection and extension. The reference values of the condylar process, articular tubercle, mandibular fossa, ramus of mandible, and joint space may play a key role in increasing of the success of the surgical procedure, or the assessment/differentiating of the TMD. ML is capable of detecting TMD in an automatic and highly accurate way. Hence, it is also concluded that ML can be useful for cases requiring making automatic and highly correct predictions.

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Comparison of the Cone Beam Computed Tomography-Based Analysis of the Masseter Muscle Between Epilepsy Patients and Healthy Subjects

Polat,

Yüksel,

Evlice

et al. 2024

Journal of Craniofacial Surgery

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It is important to investigate the changes in the masseter muscle, one of the chewing muscles, in epilepsy patients and to determine whether epilepsy can be effectively predicted on muscle. The aim of this study is to measure masseter muscle thickness, circumference and cross-sectional area in individuals with epilepsy and healthy individuals. This study was performed with 128 individuals (64 epilepsy patients and 64 healthy subjects) aged between 18 to 59 years. The mean cross-sectional area, thickness and circumference determined by measuring both of the masseter muscles were using cone beam computed tomography. The mean right masseter muscle cross-sectional area varied across age groups in epilepsy individuals (P=0.020). Significant differences were observed in the right masseter muscle circumference among age groups in epilepsy individuals (P=0.003). Significant differences were observed in the mean among age groups in epilepsy individuals (P=0.004). Statistically significant differences were observed in the mean right masseter muscle cross-sectional area between sexes in healthy individuals (P<0.001). Similarly, significant differences were observed in the mean right masseter muscle thickness between sexes in healthy individuals (P<0.001). Significant differences were observed in the mean left masseter muscle cross-sectional area between sexes in healthy individuals (P<0.001). Although jaw joint’s muscular dislocations are common, the masseter muscle, which has a very strong function in masticatory movements, is very important in terms of location, neighbourhood and clinical aspects. For this reason, our study examining the masseter muscle morphometric measurements in the epileptic and healthy population using cone beam computed tomography provides important information and normative data.

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Comparison of ultrasonography-based masticatory muscle thickness between temporomandibular disorders bruxers and temporomandibular disorders non-bruxers

Cited by 4 publications

References 69 publications

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The influence of service quality, Guanxi, value co-creation and corporate image in building developers apartments loyalty toward contractors in apartment construction industry

Temporomandibular joint and masticatory muscles morphometry and morphology in healthy subjects and individuals with temporomandibular dysfunction: An anatomical, radiological, and machine learning application study

Comparison of the Cone Beam Computed Tomography-Based Analysis of the Masseter Muscle Between Epilepsy Patients and Healthy Subjects

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