A mobile-phone-based diagnostic tool, which most of the population can easily access, could be a game changer in increasing the number of examinations of people with dental caries. This study aimed to apply a deep learning algorithm in diagnosing the stages of smooth surface caries via smartphone images. Materials and methods: A training dataset consisting of 1902 photos of the smooth surface of teeth taken with an iPhone 7 from 695 people was used. Four deep learning models, consisting of Faster Region-Based Convolutional Neural Networks (Faster R-CNNs), You Only Look Once version 3 (YOLOv3), RetinaNet, and Single-Shot Multi-Box Detector (SSD), were tested to detect initial caries lesions and cavities. The reference standard was the diagnosis of a dentist based on image examination according to the International Caries Classification and Management System (ICCMS) classification. Results: For cavitated caries, YOLOv3 and Faster R-CNN showed the highest sensitivity among the four tested models, at 87.4% and 71.4%, respectively. The sensitivity levels of these two models were only 36.9 % and 26% for visually non-cavitated (VNC). The specificity of the four models reached above 86% for cavitated caries and above 71% for VNC. Conclusion: The clinical application of YOLOv3 and Faster R-CNN models for diagnosing dental caries via smartphone images was promising. The current study provides a preliminary insight into the potential translation of AI from the laboratory to clinical practice.

Although bruxism is a common issue with a high prevalence, there has been a lack of epidemiological data about bruxism in Vietnam. This cross-sectional study aimed to determine the prevalence and associated factors of bruxism and its impact on oral health-related quality of life among Vietnamese medical students. Bruxism was assessed by the Bruxism Assessment Questionnaire. Temporomandibular disorders were clinically examined followed by the Diagnostic Criteria for Temporomandibular Disorders Axis I. Perceived stress, educational stress, and oral health-related quality of life were assessed using the Vietnamese version of Perceived Stress Scale 10, the Vietnamese version of the Educational Stress Scale for Adolescents, and the Vietnamese version of the 14-item Oral Health Impact Profile, respectively. The prevalence of bruxism, sleep bruxism, awake bruxism, and both conditions in Vietnamese medical students were 51.2%, 38.2%, 23.4%, and 10.4% respectively. Stress, temporomandibular joint pain, masticatory muscle pain, and tooth attrition were associated with the presence of bruxism. Vietnamese medical students were negatively affected by bruxism in terms of oral health-related quality of life.

This systematic review and meta-analysis aimed to investigate the efficacy of fluorescence-based methods, visual inspections, and photographic visual examinations in initial caries detection. A literature search was undertaken in the PubMed and Cochrane databases. Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines were followed, and eligible articles published from 1 January 2009 to 30 October 2019 were included if they met the following criteria: they (1) assessed the accuracy of methods of detecting initial tooth caries lesions on occlusal, proximal, or smooth surfaces in both primary and permanent teeth (in clinical); (2) used a reference standard; (3) reported data regarding the sample size, prevalence of initial tooth caries, and accuracy of the methods. Data collection and extraction, quality assessment, and data analysis were conducted according to Cochrane standards Quality Assessment of Diagnostic Accuracy Studies-2. Statistical analyses were performed using Review Manager 5.3 and STATA 14.0. A total of 12 eligible articles were included in the meta-analysis. The results showed that the sensitivity and specificity of fluorescence-based methods were 80% and 80%, respectively; visual inspection was measured at 80% and 75%, respectively; photographic visual examination was measured at 67% and 79%, respectively. We found that the visual method and the fluorescence method were reliable for laboratory use to detect early-stage caries with equivalent accuracy.

Tra Thu Nguyen, DDS/Phanomporn Vanichanon, DDS, MSc/Kanokporn Bhalang, DDS, PhD/Suknipa Vongthongsri, DDS: Aims: To investigate the relationships between three pain parameters (duration, intensity, and frequency), the number of pain sites and comorbidities, and the risk of having coexisting pain and/or comorbidities in patients with temporomandibular disorder (TMD) pain. Methods: The sample consisted of 198 outpatients attending the Dental Hospital of Chulalongkorn University. TMD pain was determined using the Diagnostic Criteria for TMD. Pain lasting 3 months or longer was defined as chronic pain. Pain intensity was reflected using a 0- to 10-point numeric rating scale, and pain frequency was assessed with the percentage of pain days over a 2-week period. The number of pain sites was evaluated using the Widespread Pain Index. The presence of comorbidities was assessed with a validated diagnostic questionnaire. The associations were analyzed using Spearman rho test, multiple linear regression, and logistic regression, with a significance level of P ≤ .05. Age and gender were analyzed as confounders. Results: The number of pain sites was related to pain duration, pain intensity, and age. The number of comorbidities was associated with pain duration. Neither pain frequency nor gender were related to the number of pain sites or comorbidities. When the pain duration reached 1 month, patients had a 1.045-times higher probability of pain beyond the orofacial area (odds ratio [OR] = 1.045; 95% confidence interval [CI] = 1.024 to 1.066; P = .001) and a 1.028-times higher probability of comorbidities (OR = 1.028; 95% CI = 1.005 to 1.05; P = .008). For an increase of 1 score on the numeric rating scale, patients had a 1.206-times higher probability of pain presence beyond the orofacial area (OR = 1.206; 95% CI = 1.068 to 1.344; P = .026). Conclusion: High pain intensity and long pain duration increase the probability of having coexisting pain and comorbidities in TMD pain patients.