Relationship of Malocclusions with Disorders of the Temporomandibular Joint in Children of CALI—Colombia

Objective The aim of this study was to determine the relationship of malocclusion with the presence and severity of temporomandibular disorders (TMDs) in children. Materials and Methods A clinical examination was performed in 87 patients (from 4 to 14 years of age) who attended the dentistry clinics of Universidad del Valle. Results The 77 patients studied had malocclusions; 55 patients had TMD and 67.3% were female. The most frequent symptom of TMD was articular unilateral noise with 33.8%, followed by pain in at least one masticatory muscle with 26%. TMJ pain was observed in 24.7% of the patients. There was a statistically significant relationship between the presence and severity of TMD with type of dentition and transverse malocclusion, respectively. Conclusion The presence of TMD in children with malocclusion presented in a high frequency. TMD depends on the type of dentition and its severity is dependent on transverse malocclusion.

Automated segmentation of articular disc of the temporomandibular joint on magnetic resonance images using deep learning

Temporomandibular disorders are typically accompanied by a number of clinical manifestations that involve pain and dysfunction of the masticatory muscles and temporomandibular joint. The most important subgroup of articular abnormalities in patients with temporomandibular disorders includes patients with different forms of articular disc displacement and deformation. Here, we propose a fully automated articular disc detection and segmentation system to support the diagnosis of temporomandibular disorder on magnetic resonance imaging. This system uses deep learning-based semantic segmentation approaches. The study included a total of 217 magnetic resonance images from 10 patients with anterior displacement of the articular disc and 10 healthy control subjects with normal articular discs. These images were used to evaluate three deep learning-based semantic segmentation approaches: our proposed convolutional neural network encoder-decoder named 3DiscNet (Detection for Displaced articular DISC using convolutional neural NETwork), U-Net, and SegNet-Basic. Of the three algorithms, 3DiscNet and SegNet-Basic showed comparably good metrics (Dice coefficient, sensitivity, and positive predictive value). This study provides a proof-of-concept for a fully automated deep learning-based segmentation methodology for articular discs on magnetic resonance images, and obtained promising initial results, indicating that the method could potentially be used in clinical practice for the assessment of temporomandibular disorders.

The Importance of Type D Personality in the Development of Temporomandibular Disorders (TMDs) and Depression in Students during the COVID-19 Pandemic

Background: a type D personality is a factor in a person’s susceptibility to general mental stress, especially during the COVID-19 pandemic. Although many studies were conducted on the relationships among stressful situations, an individual’s personality, depression, and the occurrence of various diseases, e.g., cardiovascular disease or cancer, there are no analogous data on people with temporomandibular disorders (TMDs). Aim: the assessment of TMDs and depression symptoms in students with type D personality. Material and Methods: the research was carried out with the participation of 240 physiotherapy students. The study group (G1) consisted of 120 participants with type D personalities, the control group (G2) consisted of the same number of participants, without “stress” personalities. All subjects were assessed for the occurrence of TMD symptoms, as well as for depression and anxiety symptoms, using the Beck Depression Inventory (BDI), based on the proprietary questionnaire. Results: in students with type D personality symptoms, TMDs occurred significantly more often and in greater number (p = 0.00) than in those without stress personalities. The exception was the symptom of increased muscle tension, which showed no statistical difference (p = 0.22). Among the 240 respondents, depression was found in 128 people (53.3%). In the group of students with type D personalities, depression was significantly more frequent than in the group without type D personalities (p = 0.00). In participants with depression, TMD symptoms were more common, i.e., headaches, neck, and shoulder girdle pain, TMJ acoustic symptoms, increased masticatory muscle tension, teeth clenching, and teeth grinding. There was no significant difference between the incidence of depression and TMJ pain and jaw locking. There was a significant interaction between the occurrence of headaches and acoustic symptoms and the occurrence of depression. For headache and depression interactions, the OR was >1; based on the results, we may assume that a headache depends more on the occurrence of depression rather than it being a symptom of a TMJ disorder in people with type D personalities. Conclusion: type D personality and depression may contribute to the development of TMD symptoms.