The Brazilian (FRANCO) method for dental age estimation: Willems' model revisited.

OBJECTIVES: This study aimed (I) to test the Willems' dental age estimation method in different geographic samples of the Brazilian population, and (II) to propose a new model combining the geographic samples in a single reference table of Brazilian maturity scores. MATERIALS AND METHODS: The sample consisted of 5017 panoramic radiographs of Brazilian males (n = 2443) and females (n = 2574) between 6 and 15.99 years (mean age = 10.99 ± 2.76 years). The radiographs were collected from the Southeastern (SE) (n = 2920), Central-Western (CW) (n = 1176), and Southern (SO) (n = 921) geographic regions. Demirjian's technique was applied followed by Willems' method and the proposed Brazilian model. RESULTS: Willems' method led to mean absolute errors (MAE) of 0.79 and 0.81 years for males and females, respectively. Root mean squared errors (RMSE) were 1.01 and 1.03 years, respectively. The Brazilian model led to MAE of 0.72 and 0.74 years for males and females, respectively, and RMSE of 0.93 years for both sexes. The MAE was reduced in 70% of the age categories. Differences between regions were statistically (p < 0.05) but not clinically significant. CONCLUSION: The new model based on a combined population had an enhanced performance compared to Willems' model and led to reference outcomes for Brazilians. CLINICAL RELEVANCE: Assessing patients' biological development by means of dental analysis is relevant to plan orthopedic treatments and follow up. Having a combined-region statistic model for dental age estimation of Brazilian children contributes to optimal age estimation practices.

The expression of TNF-α in recurrent aphthous stomatitis: A systematic review and meta-analysis.

OBJECTIVE: The pathogenesis of recurrent aphthous stomatitis (RAS) is related to an increase of pro-inflammatory cytokine, namely tumor necrosis factor α (TNF-α). This cytokine plays an important role in the development of ulcer lesions, both in saliva, tissues and blood. This systematic review analyzed the differences of TNF-α in lesions, salivary and blood and can be used as a reliable method of diagnosis for RAS. METHODS: A comprehensive search of PubMed, Scopus databases, Web of Science, Scielo, Google Scholar and Embase with keywords. The inclusion criteria were studies that assessed the saliva, serum, and RAS lesion, with the outcome reporting the mean of saliva, serum and tissue expression of TNF-α. The risk of bias was also assessed. RESULT: Healthy individuals showed significantly lower TNF-α than RAS (SMD = -1.517, 95% CI [-2.25, -0.78]). Although there is a significant difference between sample (i.e., saliva, serum) and detection type (i.e., cytometry bead array, ELISA), both methods can detect a significant difference in TNF-α between healthy individuals and RAS patients. CONCLUSIONS: The TNF-α is a useful diagnostic marker for RAS. We encourage saliva to detect changes in TNF-α during ulceration as it provides accuracy, reliability, and non-invasive procedure compared to a blood draw.

Towards fully automated third molar development staging in panoramic radiographs.

Staging third molar development is commonly used for age assessment in sub-adults. Current staging techniques are, at most, semi-automated and rely on manual interactions prone to operator variability. The aim of this study was to fully automate the staging process by employing the full potential of deep learning, using convolutional neural networks (CNNs) in every step of the procedure. The dataset used to train the CNNs consisted of 400 panoramic radiographs (OPGs), with 20 OPGs per developmental stage per sex, staged in consensus between three observers. The concepts of transfer learning, using pre-trained CNNs, and data augmentation were used to mitigate the issues when dealing with a limited dataset. In this work, a three-step procedure was proposed and the results were validated using fivefold cross-validation. First, a CNN localized the geometrical center of the lower left third molar, around which a square region of interest (ROI) was extracted. Second, another CNN segmented the third molar within the ROI. Third, a final CNN used both the ROI and the segmentation to classify the third molar into its developmental stage. The geometrical center of the third molar was found with an average Euclidean distance of 63 pixels. Third molars were segmented with an average Dice score of 93%. Finally, the developmental stages were classified with an accuracy of 54%, a mean absolute error of 0.69 stages, and a linear weighted Cohen's kappa coefficient of 0.79. The entire automated workflow on average took 2.72 s to compute, which is substantially faster than manual staging starting from the OPG. Taking into account the limited dataset size, this pilot study shows that the proposed fully automated approach shows promising results compared with manual staging.

The radiographic diversity of dental patterns among 7219 young individuals-a contribution to disaster victim identification.

The diversity of dental patterns is a fundamental topic in disaster victim identification. The current scientific literature, however, is scarce of data regarding young individuals. This study aimed to assess the radiographic diversity of dental patterns, considering missing, unrestored, and filled teeth in young individuals. The sample consisted of 7219 panoramic radiographs of individuals between 12 and 22.9 years. The permanent teeth, except third molars, were coded as missing, unrestored, or filled and odds ratios (OR) were calculated based on sex, dental arch, and age. The sex-combined sample had 1.116 distinctive dental patterns. "All unrestored" teeth was the most common pattern (OR: 0.437) followed by the sequence of unrestored teeth except restored mandibular first molars (OR: 0.021). Females had more distinctive dental patterns than males (p < .001), while males had more unrestored teeth (p < .001). In the age category of 12-12.9 years, the OR for finding a distinctive dental pattern was 11%, while in the age category of 22-22.9 years it increased to 58%. On the other hand, the OR for "all unrestored" gradually decreased according to age (74% in the younger category, and 23% in the older age category). The distinctiveness of dental patterns among young individuals is affected by the predominance of unrestored teeth. However, registering a single filled tooth in a remaining unrestored dentition can reduce exponentially the probability of finding an identical pattern of missing, unrestored and filled teeth.

Accuracy of the third molar maturity index (I3M) for diagnosing the legal majority of young southern Brazilians.

Background: The numerous techniques for identifying adulthood require research testing the accuracy of each method in different populations. This study verified the accuracy of the third molar maturity index (I3M) proposed by Cameriere et al. (2008) for diagnosing the age of majority in a southern Brazilian population sample. Material and Methods: Panoramic radiographs of patients with dental element 38 treated at the School of Dentistry of the University of Passo Fundo (UPF), RS, Brazil, were analyzed. The patients were separated into age groups between 15.00 and 22.99 years. The Cameriere (2008) method was applied to each radiograph. The study sample comprised 671 individuals, with 385 women (mean age 19.67 ± 2.05) and 286 men (mean age 19.5 ± 2.11). Results: The original cut-off value of I3M≤0.08 classified individuals younger and older than 18 years. ROC curve plotting resulted in an overall accuracy of 0.69 and 0.84 for women and men, respectively. The most favorable cut-off value for southern Brazilian men was 0.06, and women showed better results with an I3M adjusted to 0.13. The new cut-off values produced an accuracy of 0.78 for women and 0.84 for men. The original cut-off point to the I3M (0.08) was not the most appropriate for the studied sample. Conclusions: Thus, index adjustments to 0.13 for women and 0.06 for men may improve method performance among southern Brazilian individuals. Key words:Molar, third, radiography, panoramic, forensic dentistry, age groups, imputability.