Medial sigmoid depression prevalence and association with a sigmoid notch: cone beam computed tomography and panoramic image study.

This study aims to determine whether and how the data of the medial sigmoid depression (MSD) area via cone beam computed tomography (CBCT) differs from panoramic radiography. This study also aims to evaluate various sigmoid notch types and assess the relationship between sigmoid depression and notch morphology. A total of 129 individuals consisting of 258 sides were evaluated. Chi-Square/Fisher Exact tests were used to assess parameters on a categorical scale between two or more groups. McNemar's test compared the findings detected on panoramic and CBCT images. MSD was more prevalent in females than males in both techniques, but this difference was not statistically significant. There was no association between the prevalence of MSD and the morphology of the sigmoid notch. The incidence of MSD shape was not significantly different between both imaging modalities. In both panoramic and CBCT, we found a high and similar prevalence of MSD. While the MSD prevalence was 66.7% for CBCT, it was 58.1% for panoramic. The shape or prevalence of MSDs in either approach did not correlate with sigmoid notch morphology. The two approaches' identical prevalence indicates that the panoramic image has adequately defines MSD. The high prevalence of MSD demonstrated how important it is for clinicians to characterize this anatomical variation accurately for the surgical treatment.

Machine learning assessment of dental age classification based on cone-beam CT images: a different approach.

OBJECTIVES: Machine learning (ML) algorithms are a portion of artificial intelligence that may be used to create more accurate algorithmic procedures for estimating an individual's dental age or defining an age classification. This study aims to use ML algorithms to evaluate the efficacy of pulp/tooth area ratio (PTR) in cone-beam CT (CBCT) images to predict dental age classification in adults. METHODS: CBCT images of 236 Turkish individuals (121 males and 115 females) from 18 to 70 years of age were included. PTRs were calculated for six teeth in each individual, and a total of 1416 PTRs encompassed the study dataset. Support vector machine, classification and regression tree, and random forest (RF) models for dental age classification were employed. The accuracy of these techniques was compared. To facilitate this evaluation process, the available data were partitioned into training and test datasets, maintaining a proportion of 70% for training and 30% for testing across the spectrum of ML algorithms employed. The correct classification performances of the trained models were evaluated. RESULTS: The models' performances were found to be low. The models' highest accuracy and confidence intervals were found to belong to the RF algorithm. CONCLUSIONS: According to our results, models were found to be low in performance but were considered as a different approach. We suggest examining the different parameters derived from different measuring techniques in the data obtained from CBCT images in order to develop ML algorithms for age classification in forensic situations.

Application of the Kvaal method to CBCT reconstructed panoramic images for age estimation.

As the teeth are more durable than other parts of the skeleton, they provide valuable data for age estimation. Age estimation from adult teeth is mainly based on secondary dentin production. The present study aimed to devise a regression formula for age estimation specific to the Anatolian population using the Kvaal method on CBCT reconstructed panoramic images. In total, 201 individuals aged between 20 and 69 were divided into two groups: data from the study group (n = 101) were used to create the regression formulae, and data from the control group (n = 100) were used to test the formulae. Pearson's correlation coefficients and linear regression analyses were performed. Maxillary teeth provided more accurate age estimates than mandibular teeth. The regression formulae derived in this study are found to be statistically applicable and reasonably accurate. However, these results should be interpreted with caution.

Assessment of dental anxiety levels among dental emergency patients during the COVID­19 pandemic through the Modified Dental Anxiety Scale.

BACKGROUND: Coronavirus disease 2019 (COVID­19) continues to affect dental emergency services worldwide. Dental anxiety (DA) is described as a common and distressing problem in terms of oral health maintenance. OBJECTIVES: The present study aimed to evaluate DA levels as well as the COVID­19 fear and perception of control (COVID­19 FPC) in patients attending dental emergency clinics during the COVID­19 pandemic. MATERIAL AND METHODS: Sociodemographic, dental and medical data was obtained from the participants. A face-to-face questionnaire with questions referring to the reasons for the emergency dental visit, the visual pain scale, the Modified Dental Anxiety Scale (MDAS), and the COVID­19 Fear and Perception of Control Scale (COVID­19 FPCS) as well as additional questions concerning bruxism and a previous diagnosis of anxiety/panic attacks or depression was administered. The χ2 test was used to analyze the data. RESULTS: A total of 1,439 patients were included in the study. The most common reason for the dental visit was pain (47.5%). The prevalence of DA was 5.1% (74/1,439). A significant association was found between DA and gender (p = 0.020). The incidence of severe pain was higher in patients with DA than in those without DA (p = 0.002). No significant differences in the MDAS scores were found between patients with and without a chronic disease (p = 0.804), with regard to the educational status (p = 0.364), or between the age groups (p = 0.600). The prevalence of a 'strongly agree' response to all questions in COVID­19 FPCS was higher in patients with DA as compared to those without DA. CONCLUSIONS: Females and patients with severe pain were more likely to exhibit DA. In general, patients with DA strongly agreed with the statements of COVID­19 FPCS, which may indicate a correlation between the 2 scales.

Invasive squamous cell carcinoma arising in an inverted papilloma involving oral cavity.

Inverted papilloma (IP) is a benign tumour characterized by the growth of epithelial cells downward into the underlying supportive tissue. The tumour derives from the lining mucosa of the nasal cavity and paranasal sinuses. IP typically arises as a unilateral lesion from the lateral wall of the nasal cavity and extends secondarily to the paranasal sinuses. The aggressive behaviour of IP causing local invasion, its tendency for local recurrence, and its propensity to be associated with carcinoma constitute serious complications. This paper describes a very rare case of IP associated with squamous cell carcinoma, extending into paranasal sinuses, causing destruction of the bony wall of maxillary sinus and involvement of the oral cavity.

Accuracy of the use of radiographic visibility of root pulp in the mandibular third molar as a maturity marker at age thresholds of 18 and 21.

Evaluation of the radiographic visibility of root pulp in mandibular third molars has been suggested as an alternative method for estimation of legal age threshold in living individuals when the root apices are mature. Here, we assessed the accuracy of this method for age thresholds of 18 and 21 years. A sample of 463 panoramic radiographs of individuals aged between 16 and 34 years was examined. The root pulp visibility of the mandibular third molars was scored; the stages ranged from 0 to 3. A receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC) were used to select optimal cut-offs for 18- and 21-year-old thresholds. As prognostic predictors, the selected cut-offs were stages 1 and 2 for the 18- and 21-year-old thresholds of both sexes, respectively. For the 18-year-old threshold, the AUC, sensitivity and specificity were 0.829, 83.1% and 66.7% in females; and 0.930, 89.4% and 90.9% in males, respectively. For the 21-year-old threshold, the AUC, sensitivity and specificity were 0.874, 72.8% and 92.0% in females; and 0.906, 85.5% and 88.2% in males, respectively. The accuracy of the method for estimating the 18- and 21-year-old thresholds ranged from moderate to high. Therefore, the method must be used in conjunction with other age estimation methods, especially to predict whether a female has reached 18 years of age.