PurposeThe nasopalatine canal is a well-known, important anatomical structure in the anterior maxilla, but this region contains many accessory canals. The canalis sinuosus (CS) is one of these canals; it contains the anterior superior alveolar nerve, along with veins and arteries. The purpose of this study was to evaluate the CS using conebeam computed tomography (CBCT) in patients with maxillary impacted canines.Materials and MethodsA total of 111 patients admitted to the Istanbul Medipol University School of Dentistry for the exposure, orthodontic treatment, and/or extraction of an impacted canine were included in this study. CBCT images were obtained for these patients under standard conditions. Axial, coronal, and sagittal sections were evaluated to assess the prevalence of CS, the direction and diameter of the canal, its relation with the impacted canine, and its distance from the alveolar crest. Further, possible correlations with patient gender and age were analyzed.ResultsThe CS could be detected bilaterally in all the evaluated tomography images. The mean canal diameter was significantly larger in males than in females (P=.001). The CS ran significantly closer to the impacted canine when the canal was located horizontally (P=.03). Variations of the canal, such as accessory canals, were identified in 6 patients.ConclusionCS is an anatomical entity that may resemble periapical lesions and other anatomical structures. Evaluation with CBCT prior to surgical procedures in the anterior maxilla will help to prevent overlooking such anatomical structures and to decrease possible surgical complications.
Objective: This study aimed to examine the association between sleep quality, depression, anxiety and stress levels, and the frequency of temporomandibular disorders in a sample of Turkish dental students during the COVID-19 pandemic. Methods: The current cross-sectional study was conducted with 699 dental university students during the COVID-19 pandemic. Fonseca Anamnestic Index (FAI), Pittsburgh Sleep Quality Index (PSQI), and Depression Anxiety Stress Scale-21 (DASS-21) were used in the present study. Results: The incidence of temporomandibular joint disorders in the present study was found to be 77.5%. Female students' FAI scores were found to be statistically significantly higher than males (p < 0.05). Additionally, higher depression and anxiety and stress levels caused increased PSQI and FAI scores. Conclusion: During the COVID-19 pandemic, increased temporomandibular joint disorders were observed with increased impaired sleep quality and higher depression, anxiety and stress levels among dental university students.
Hygiene habits and attitudes may be affected by gender, but education level and hygiene attitudes may not always present positive correlation. Dentists should thoroughly inform patients about the harmful effects of overnight wearing and motivate to clean metal parts of RPD's and cleansing tablet use in order to minimize the abrasive effect of widely preferred cleaning method of brushing with toothpaste.
Stafne bone defects are asymptomatic lingual bone depressions of the lower jaw. In 1942, Stafne described for the first time 35 asymptomatic, radiolucent cavities, unilaterally located in the posterior region of the mandible, between the mandibular angle and the third molar, below the inferior dental canal and slightly above the basis mandibulae. In this study, the clinical and radiological characteristics of 2 cases of Stafne bone defects were described. Orthopantomograph and CBCT were used for diagnosing the defects. The bone defects of two patients in this study were asymptomatic and any other bone lesions, such as cysts and tumors, were excluded because no signs of inflammatory or tumoral changes were evident Therefore, surgery was not considered and the patients were followed for 1 year. Stafne bone defect was an incidental finding, presenting no evolutionary changes, and as such conservatory therapy based on periodic controls was indicated. Currently, complementary techniques such as CT are sufficient to establish a certain diagnosis.
Purpose The aim of this study was to assess the performance of a deep learning system for permanent tooth germ detection on pediatric panoramic radiographs. Materials and Methods In total, 4518 anonymized panoramic radiographs of children between 5 and 13 years of age were collected. YOLOv4, a convolutional neural network (CNN)-based object detection model, was used to automatically detect permanent tooth germs. Panoramic images of children processed in LabelImg were trained and tested in the YOLOv4 algorithm. True-positive, false-positive, and false-negative rates were calculated. A confusion matrix was used to evaluate the performance of the model. Results The YOLOv4 model, which detected permanent tooth germs on pediatric panoramic radiographs, provided an average precision value of 94.16% and an F1 value of 0.90, indicating a high level of significance. The average YOLOv4 inference time was 90 ms. Conclusion The detection of permanent tooth germs on pediatric panoramic X-rays using a deep learning-based approach may facilitate the early diagnosis of tooth deficiency or supernumerary teeth and help dental practitioners find more accurate treatment options while saving time and effort.
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