Evaluation of Dental Plaque Area with Artificial Intelligence Model.

OBJECTIVES: This study aims to assess the diagnostic accuracy of an artificial intelligence (AI) system employing deep learning for identifying dental plaque, utilizing a dataset comprising photographs of permanent teeth. MATERIALS AND METHODS: In this study, photographs of 168 teeth belonging to 20 patients aged between 10 and 15 years, who met our criteria, were included. Intraoral photographs were taken of the patients in two stages, before and after the application of the plaque staining agent. To train the AI system to identify plaque on teeth with dental plaque that is not discolored, plaque and teeth were marked on photos with exposed dental plaque. One hundred forty teeth were used to construct the training group, while 28 teeth were used to create the test group. Another dentist reviewed images of teeth with dental plaque that was not discolored, and the effectiveness of AI in detecting plaque was evaluated using pertinent performance indicators. To compare the AI model and the dentist's evaluation outcomes, the mean intersection over union (IoU) values were evaluated by the Wilcoxon test. RESULTS: The AI system showed higher performance in our study with a precision of 82% accuracy, 84% sensitivity, 83% F1 score, 87% accuracy, and 89% specificity in plaque detection. The area under the curve (AUC) value was found to be 0.922, and the IoU value was 76%. Subsequently, the dentist's plaque diagnosis performance was also evaluated. The IoU value was 0.71, and the AUC was 0.833. The AI model showed statistically significantly higher performance than the dentist (P < 0.05). CONCLUSIONS: The AI algorithm that we developed has achieved promising results and demonstrated clinically acceptable performance in detecting dental plaque compared to a dentist.

Effect of three different remineralising agents on prevention against acidic erosion of primary teeth: an in vitro study.

PURPOSE: This study aimed to evaluate and compare the protective effect of fluoride varnish (Enamelast™, Ultradent Inc., Cologne, Germany), casein phosphopeptide-amorphous calcium phosphate fluoride/CPP-ACPF (MI Paste Plus, GC Corp., Tokyo, Japan) and self-assembling P11-4 peptide (Curodont™ Protect, Credentis AG, Windisch, Switzerland), against acidic erosion of primary teeth. METHODS: Forty primary anterior teeth were randomly assigned to four groups (n = 10): group 1: control, group 2: fluoride varnish, group 3: CPP-ACPF and group 4: self-assembling P11-4 peptide. After applying remineralising agents, except for the control group, all specimens underwent an erosive challenge of carbonated soft drink and artificial saliva for 15 cycles of 6 s each at 6-h intervals for a day. Groups were compared in terms of surface microhardness, roughness readings, and surface scanning with an extra-oral scanner (D800; 3Shape A/S) before and after the erosive process. RESULTS: All experimental groups showed superior results than the control group regarding microhardness, surface roughness, and substance loss. The fluoride varnish group showed significantly favourable results in microhardness change. There was no significant difference between the experimental groups regarding surface roughness and enamel loss measurements. CONCLUSION: 5% NaF fluoride varnish, CPP-ACPF and self-assembling P11-4 peptide protect the enamel of primary teeth against erosion compared to artificial saliva alone.

Comparison of the applicability of Demirjian and Willems methods for dental age estimation in children from the Thrace region, Turkey.

OBJECTIVES: Dental age (DA) estimation is frequently used in the fields of orthodontics, paediatric dentistry and forensic science. DA estimation methods use radiology, and are reliable and non-destructive according to the literature. The Demirjian method is currently the most frequently used method, but recently, the Willems method was reported to have given results that were more accurate for some regions. The aim of this study was to detect and compare the accuracy of DA estimation methods for children and adolescents from the Thrace region, Turkey. The mean difference between the chronological age (CA) and the DA was selected as the primary outcome measure, and the difference range according to sex and age group was selected as the secondary outcome. MATERIALS AND METHODS: Panoramic radiographs (n=766) from a Thrace region population (380 males and 386 females) ranging in age from 6 to 14.99 years old were evaluated. DA was calculated using both the Demirjian and the Willems methods. RESULTS: The mean CA of the subjects was 11.39±2.34 years (males=11.08±2.42 years and females=11.70±2.23 years). The mean difference values between the CA and the DA (CA-DA) using the Demirjian method and the Willems method were -0.87 and -0.17 for females, respectively, and -1.04 and -0.40 for males, respectively. For the different age groups, the differences between the CA and the DA calculated using the Demirjian method (CA-DA) ranged from -0.53 to -1.46 years for males and from -0.19 to -1.20 years for females, while the mean differences between the CA and the DA calculated by the Willems method (CA-DA) ranged from -0.19 to -0.50 years for males and from 0.20 to -0.49 years for females. CONCLUSION: The results suggest that the Willems method produced more accurate results for almost all age groups of both sexes, and it is better suited for children from the Thrace region of Turkey, than the Demirjian method.

The relationship between migraine and atopic disorders-the contribution of pulmonary function tests and immunological screening.

This cross-sectional clinical study was conducted in order to explore the relationship between atopic disorders and migraine. We evaluated 186 consecutive patients with migraine. Patients with a history of atopic disorders were compared with the others during headache-free intervals, for their headache characteristics, pulmonary test (PFT) performances and immunological screenings, through appropriate statistical methods. Of the patients with migraine, 77 (41.4%) reported at least one atopic disorder. PFT screening showed a general decreased pulmonary capacity and an important correlation between a positive history of atopic disorders and both increased eosinophil and IgE levels in headache-free periods. It should be discussed whether screening with PFT or immunological tests helps in early detection of progressive lung disease which might develop in these patients.