Effectiveness of Different Methods in Removing Dentin Caries of Primary Teeth: Micro-CT and SEM Evaluation.

OBJECTIVES: With the recent improvements in technology, the expectation of minimal invasion and maximal comfort in caries removal techniques is increasing. This study aims to examine the effectiveness of six caries removal methods in primary teeth. STUDY DESIGN: Sixty primary molars (10 teeth in each groups) were used. The groups were: Group I (Tungsten Carbide Bur), Group II (Sono abrasion), Group III (Air abrasion), Group IV (Carisolv), Group V (Er:YAG Laser), Group VI (ART). In micro-CT scanning, mineral density at the cavity floor was examined before and after caries removal. After caries removal, the patency of the dentinal tubules was examined in two teeth from each group on SEM images. Statistical analyses were performed using Kruskal-Wallis, Wilcoxon tests. RESULTS: For six different caries removal methods, tooth mineral (inorganic, total) densities at cavity floors were compared among the groups after the procedures, and no statistically significant difference was found (p>0.05). On the SEM images, it was seen that the dentinal tubules were exposed and no smear layer was formed in the Carisolv group. Significant rough surfaces were exposed in the laser group. CONCLUSION: It was observed that alternative caries removal methods are at least as effective as the traditional method in primary teeth for clinical applications.

Clinical validation of a novel bioluminescence imaging technology for aiding the assessment of carious lesion activity status.

OBJECTIVES: Clinical validation of a bioluminescence imaging system (Cis) as measured by the level of agreement between clinician visual and tactile assessment of carious lesion presence and activity and the presence/absence of elevated luminescence on a tooth surface determined from intraoral image mapping. MATERIALS AND METHODS: This was a regulatory clinical study designed in consultation with the FDA. The design was a prospective, five-investigator, nonrandomized, post-approval, clinical study utilizing the Cis to provide images of elevated calcium ion concentration (indicative of active demineralization) on tooth surfaces via use of a photoprotein. Imaged teeth were identified as "sound" or having "active lesions." Images were scored independently for luminescence. RESULTS: A total of 110 participants aged 7-74 years were imaged. Of the 90 teeth assessed as "sound," 88 were deemed to show no luminescence by the reviewing investigator, a negative percentage agreement of 97.8% (significantly >50% agreement [p < .0001]; one-sided 97.5% confidence interval [CI]: 0.9220). Of the 86 teeth initially assessed as having an "active lesion," 78 were deemed to show luminescence by the reviewing investigator, a positive percentage agreement of 90.7% (significantly >50% agreement [p < .0001]; 97.5% CI: 0.8249). There were no patient-related adverse events. CONCLUSIONS: Results show, with a high level of agreement, that Cis can differentiate tooth surfaces clinically identified as involving active enamel lesions (ICDAS code 2/3), from sound sites (biochemically equivalent to inactive lesions) and that the system is safe for clinical use.

Classification of Approximal Caries in Bitewing Radiographs Using Convolutional Neural Networks.

Dental caries is an extremely common problem in dentistry that affects a significant part of the population. Approximal caries are especially difficult to identify because their position makes clinical analysis difficult. Radiographic evaluation-more specifically, bitewing images-are mostly used in such cases. However, incorrect interpretations may interfere with the diagnostic process. To aid dentists in caries evaluation, computational methods and tools can be used. In this work, we propose a new method that combines image processing techniques and convolutional neural networks to identify approximal dental caries in bitewing radiographic images and classify them according to lesion severity. For this study, we acquired 112 bitewing radiographs. From these exams, we extracted individual tooth images from each exam, applied a data augmentation process, and used the resulting images to train CNN classification models. The tooth images were previously labeled by experts to denote the defined classes. We evaluated classification models based on the Inception and ResNet architectures using three different learning rates: 0.1, 0.01, and 0.001. The training process included 2000 iterations, and the best results were achieved by the Inception model with a 0.001 learning rate, whose accuracy on the test set was 73.3%. The results can be considered promising and suggest that the proposed method could be used to assist dentists in the evaluation of bitewing images, and the definition of lesion severity and appropriate treatments.

The relationship between COVID-19 and the dental damage stage determined by radiological examination.

OBJECTIVE: COVID-19 causes severe complications particularly in respiratory system especially in the elderly and those with poor general health. General and oral health are closely related to the course of such viral diseases. This study aims to reveal the relationship between the Dental Damage Stage (DD Stg) and the severity of COVID-19 disease. MATERIALS AND METHODS: The study included 137 patients (20-65 years) based on oral examination records and panoramic X-rays of 1516 COVID-19 patients diagnosed through real time PCR tests. DD Stg were determined according to data of Apical Periodontitis Grading Scale, Radiologic Alveolar Bone Loss and Pathophysiological Process of Dental Caries obtained from dental radiological images. DD Stg were determined according to the severity of dental pathology and compared in terms of age, gender, numbers of dental caries (NDC), dental implants (NDI), root canal treatment (NRCT), tooth fillings (NTF), missing teeth (NMT) and hospitalization due to COVID-19 (NHC), presence of chronic disease (CD), and symptom associated with COVID-19 (SAC) RESULTS: Patients in DD Stg 3 had significantly higher age and mortality. CD, NDC and NHC values were higher in DD Stg 2 and 3 than in DD Stg 0 and 1. NHCs were higher in DD Stg 3 than in DD Stg 2. NMTs were higher in DD Stg 3 than other stages. SACs were significantly lower in DD Stg 0 than in DD Stg 1, 2 and 3. NDC, NHC, SAC and CD were effective on DD staging; they were moderately positively related. CONCLUSIONS: The relationship detected between DD stage and the severity and prognosis of viral disease such as COVID-19 was found to be remerkable for extensive studies.