Perceptions and attitudes of dental students and dentists in South Korea toward artificial intelligence: a subgroup analysis based on professional seniority.

BACKGROUND: This study explored dental students' and dentists' perceptions and attitudes toward artificial intelligence (AI) and analyzed differences according to professional seniority. METHODS: In September to November 2022, online surveys using Google Forms were conducted at 2 dental colleges and on 2 dental websites. The questionnaire consisted of general information (8 or 10 items) and participants' perceptions, confidence, predictions, and perceived future prospects regarding AI (17 items). A multivariate logistic regression analysis was performed on 4 questions representing perceptions and attitudes toward AI to identify highly influential factors according to position, age, sex, residence, and self-reported knowledge level about AI of respondents. Participants were reclassified into 2 subgroups based on students' years in school and 4 subgroups based on dentists' years of experience. The chi-square test or Fisher's exact test was used to determine differences between dental students and dentists and between subgroups for all 17 questions. RESULTS: The study included 120 dental students and 96 dentists. Participants with high level of AI knowledge were more likely to be interested in AI compared to those with moderate or low level (adjusted OR 24.345, p < 0.001). Most dental students (60.8%) and dentists (67.7%) predicted that dental AI would complement human limitations. Dental students responded that they would actively use AI in almost all cases (40.8%), while dentists responded that they would use AI only when necessary (44.8%). Dentists with 11-20 years of experience were the most likely to disagree that AI could outperform skilled dentists (50.0%), and respondents with longer careers had higher response rates regarding the need for AI education in schools. CONCLUSIONS: Knowledge level about AI emerged as the factor influencing perceptions and attitudes toward AI, with both dental students and dentists showing similar views on recognizing the potential of AI as an auxiliary tool. However, students' and dentists' willingness to use AI differed. Although dentists differed in their confidence in the abilities of AI, all dentists recognized the need for education on AI. AI adoption is becoming a reality in dentistry, which requires proper awareness, proper use, and comprehensive AI education.

Evaluation of residual dentin thickness using quantitative light-induced fluorescence technology.

This study aimed to determine whether a correlation exists between residual dentin thickness and quantitative light-induced fluorescence (QLF) values and, if so, to analyze its tendencies. Forty extracted sound human molars were assigned to filled and unfilled groups. The teeth were submerged in a mold with clear acrylic resin. Red utility wax was inserted into the pulp chamber space in the filled group to simulate vital pulp. The specimen was sectioned longitudinally to observe the inside of the pulp space. The samples were cut horizontally from the highest point of the pulp space 2 mm apart. QLF images were then taken of 2 mm, 1 mm, and 0.5 mm samples using the QLF-D Biluminator™ 2 + system. Three operators independently evaluated the QLF images, and the statistical analysis was conducted using one-way analysis of variance, Pearson correlation coefficients, and intraclass correlation coefficients. In the filled group, the mean ΔF values for residual dentin thicknesses of 2 mm, 1 mm, and 0.5 mm were - 3.22, - 7.84, and - 11.52, respectively. In the unfilled group, the mean ΔF values were 0, - 6.90, and - 10.14, respectively. A positive correlation was found between residual dentin thickness and ΔF values (P < 0.05). The intraclass correlation coefficients for observations made by the three operators for the filled and unfilled groups were 0.831 and 0.917, respectively (P < 0.05). In conclusion, residual dentin thickness and ΔF values were significantly correlated and had a highly positive correlation regardless of the QLF device operator.

Trend in the Incidence of Severe Partial Edentulism among Adults Using the Korean National Health Insurance Service Claim Data, 2014-2018.

PURPOSE: Missing teeth is one of the most important indicators of oral health behavior and the result of dental caries, periodontal disease, and injuries. This study examined a trend in the incidence of severe partial edentulism (SPE) using the Korean National Health Insurance Service (KNHIS) data. MATERIALS AND METHODS: Data of adults aged ≥20 years were obtained from the KNHIS for the 2014-2018 period. SPE was defined in dental information within a population with a treatment history of dental scaling as having 1 to 8 natural teeth. Crude incidence rates (CIRs) and age-standardized incidence rates (AIRs) with 95% confidence interval were calculated per 100000 persons. The Cochran Armitage trend (CAT) test and average annual percentage change were used to analyze SPE trends. RESULTS: The CIRs among Korean adults were from 346.29 to 391.11 in 2014-2016 and from 391.11 to 354.09 in 2016-2018. The AIRs trend statistically increased by 4.31% from 346.29 to 376.80 and decreased by 4.72% from 376.80 to 342.10. The AIRs in men increased by 4.00% and decreased by 3.01%. The AIRs in women decreased by 2.18% and increased by 2.11% (CAT; p<0.01). The AIRs by region and income also showed trends of increase and decrease. CONCLUSION: The study showed that the incidence trend of SPE increased and decreased from 2014 to 2018. This result would be able to aid in the planning of public oral health, and may also serve as fundamental data for verifying the impact of the public oral health policies implemented.

Evaluation metric of smile classification by peri-oral tissue segmentation for the automation of digital smile design.

OBJECTIVES: This study aimed to develop and validate evaluation metric for an automated smile classification model termed the "smile index." This innovative model uses computational methods to numerically classify and analyze conventional smile types. METHODS: The datasets used in this study consisted of 300 images to verify, 150 images to validate, and 9 images to test the evaluation metric. Images were annotated using Labelme. Computational techniques were used to calculate smile index values for the study datasets, and the resulting values were evaluated in three stages. RESULTS: The smile index successfully classified smile types using cutoff values of 0.0285 and 0.193. High accuracy (0.933) was achieved, along with an F1 score greater than 0.09. The smile index successfully reclassified smiles into six types (low, low-to-medium, medium, medium-to-high, high, and extremely high smiles), thereby providing a clear distinction among different smile characteristics. CONCLUSION: The smile index is a novel dimensionless parameter for classifying smile types. The index acts as a robust evaluation tool for artificial intelligence models that automatically classify smile types, thereby providing a scientific basis for largely subjective aesthetic elements. CLINICAL SIGNIFICANCE: The computational approach employed by the smile index enables quantitative numerical classification of smile types. This fosters the application of computerized methods in quantifying and analyzing real smile characteristics observed in clinical practice, paving the way for a more objective evidence-based approach to aesthetic dentistry.

Validation of the Korean Academy of Geriatric Dentistry screening questionnaire and oral frailty diagnostic criteria in community-dwelling older adults.

OBJECTIVES: This study aimed to establish the validity-specifically, the sensitivity and specificity-of the screening questionnaire and diagnostic criteria for oral frailty proposed by the Korean Academy of Geriatric Dentistry (KAGD) among community-dwelling older adults. METHODS: This study enrolled 100 participants. Among various definitions of oral frailty, this study used the criteria proposed by Tanaka as the reference test. The screening questionnaire consisted of 11 items for screening physical frailty, chewing ability, swallowing difficulties, oral dryness, and tongue and lip motor function. Each question had a different scoring weight, and if the total score was 1 or higher, an oral frailty diagnostic examination proposed by the KAGD would be recommended. The diagnostic test was the oral frailty diagnostic criteria proposed by the KAGD including 6 measures: chewing ability, occlusal force, tongue pressure, oral dryness, swallowing difficulty, and oral hygiene. If a participant exhibited 2 or more positive measures, this participant was classified as "oral frail." The screening questionnaire was analyzed using a cut-off value of 1 or higher, while the diagnostic criteria utilized a cut-off of 2 or more positive measures. Sensitivity and specificity were calculated. RESULTS: The screening questionnaire showed significant power for screening oral frailty (area under the receiver operating characteristic curve, 0.783; sensitivity, 87.8%; specificity, 52.5%). The diagnostic accuracy of the newly proposed diagnostic criteria was acceptable (sensitivity, 95.1%; specificity, 42.4%). CONCLUSIONS: The newly proposed screening questionnaire and diagnostic criteria in Korea appear to be a useful tool to identify oral frailty in community-dwelling older adults.

Prioritization of research engaged with rare disease stakeholders: a systematic review and thematic analysis.

BACKGROUND: Although rare diseases (RD) are increasingly becoming a priority for healthcare activities and services around the world, developing research policy for investigating RD in public settings proves challenging due to the limited nature of existing evidence. Rare conditions require the involvement of a wide range of stakeholders in order to promote general awareness and garner political support. Consequently, it is critically important to identify trends in the various types of research focusing on rare disease stakeholders, including the specific topics or issues to be included in surveys and studies focused on RD stakeholders. This systematic review and thematic analysis analyses the existing literature based on RD surveys, including the stakeholders involved, and proposes potential research priorities and initiatives for policy-making related to RD. METHODS: Articles were downloaded and analyzed from across five electronic databases (PubMed, EMBASE, Cochrane Central, Web of Science, and CINHAL) and 115 studies were included. RESULTS: Across 115 studies, the main research participants were patients and/or caregivers (n = 77, 67.0%), health professionals (n = 18, 15.7%), and the public (n = 7, 6.1%). The studies discussed RDs in general (n = 46, 40.0%), endocrine, nutritional, and metabolic diseases (n = 20, 17.4%) and other RDs. Experiences with RD were examined by more than half of the selected studies (n = 74, 64.3%), followed by the opinions of stakeholders (n = 24, 20.9%). Most of the studies used surveys in order to collect relevant data (n = 114, 99.1%). Additionally, the majority of the studies were conducted in high-income countries (n = 92, 80.0%) and rarely in middle and low-income countries (n = 12, 13.8%). CONCLUSION: Stakeholder research on RD reveals that there are significant instances of unmet needs and various challenges faced by the medical system in dealing with RDs. Furthermore, public awareness and support is critical to ensuring political feasibility of increasing national-level investments for RDs and development of medical products and treatment.

Deep learning and clustering approaches for dental implant size classification based on periapical radiographs.

This study investigated two artificial intelligence (AI) methods for automatically classifying dental implant diameter and length based on periapical radiographs. The first method, deep learning (DL), involved utilizing the pre-trained VGG16 model and adjusting the fine-tuning degree to analyze image data obtained from periapical radiographs. The second method, clustering analysis, was accomplished by analyzing the implant-specific feature vector derived from three key points coordinates of the dental implant using the k-means++ algorithm and adjusting the weight of the feature vector. DL and clustering model classified dental implant size into nine groups. The performance metrics of AI models were accuracy, sensitivity, specificity, F1-score, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC-ROC). The final DL model yielded performances above 0.994, 0.950, 0.994, 0.974, 0.952, 0.994, and 0.975, respectively, and the final clustering model yielded performances above 0.983, 0.900, 0.988, 0.923, 0.909, 0.988, and 0.947, respectively. When comparing the AI model before tuning and the final AI model, statistically significant performance improvements were observed in six out of nine groups for DL models and four out of nine groups for clustering models based on AUC-ROC. Two AI models showed reliable classification performances. For clinical applications, AI models require validation on various multicenter data.

Anti-biofilm activity of a novel nanoemulsion containing Curcuma xanthorrhiza oil.

OBJECTIVES: We aimed to solubilize Curcuma xanthorrhiza oil (CXO) using nanoemulsification and evaluate its inhibitory effects against biofilm formation. METHODS: The components of CXO were evaluated through high-performance liquid chromatography (HPLC) analysis. Healthy human saliva was inoculated onto hydroxyapatite discs to form microcosm biofilms for four days and treated six times with each antimicrobial agent: distilled water (DW), CXO emulsion (EM), CXO nanoemulsion (NE), and positive controls (Listerine and chlorhexidine). Biofilm fluorescence imaging was performed using quantitative light-induced fluorescence, and cell viability and dry-weight measurements were obtained. We compared the bacterial cell and extracellular polysaccharide (EPS) biovolume and thickness using confocal laser scanning microscopy (CLSM). RESULTS: HPLC analysis revealed that CXO was composed of approximately 47% xanthorrhizol. Compared with DW, NE exhibited significantly lower red fluorescence intensity and area (42% and 37%, p < 0.001 and p < 0.001, respectively), and reduced total and aciduric bacterial cell viability (7.3% and 3.9%, p < 0.001, p = 0.01, respectively). Furthermore, the bacterial cell and EPS biovolume and thickness in NE decreased by 40-80% compared to DW, similar to chlorhexidine. Conversely, EM showed a significant difference only in cell viability against total bacteria when compared with DW (p = 0.003), with EPS biovolume and thickness exhibiting higher values than DW. CONCLUSIONS: Nanoemulsification successfully solubilized CXO and demonstrated superior anti-biofilm effects compared to the emulsion form. CLINICAL SIGNIFICANCE: These findings suggest the potential use of NE as a novel antimicrobial agent for preventing oral diseases.

Oral characteristics and dietary habits of preterm children: A retrospective study using National Health Screening Program for Infants and Children.

The rate of preterm birth is increasing worldwide and preterm infants are susceptible to oral health problems. Hence, this study aimed to investigate the effect of premature birth on dietary and oral characteristics as well as dental treatment experiences of preterm infants using a nationwide cohort study. Data was retrospectively analyzed from National Health Screening Program for Infants and Children (NHSIC) of the National Health Insurance Service of Korea. 5% sample of children born between 2008 and 2012 who completed first or second infant health screening were included and divided into full-term and preterm-birth groups. Clinical data variables such as dietary habits, oral characteristics, and dental treatment experiences were investigated and comparatively analyzed. Preterm infants showed significantly lower rates of breastfeeding at 4-6 months (p<0.001), delayed start of weaning food at 9-12 months (p<0.001), higher rates of bottle feeding at 18-24 months (p<0.001), poor appetite at 30-36 months (p<0.001) and higher rates of improper swallowing and chewing function at 42-53 months (p = 0.023) than full-term infants. Preterm infants also had eating habits leading to poor oral conditions and higher percentage of absence of dental visit compared to full-term infants (p = 0.036). However, dental treatments including 1-visit pulpectomy (p = 0.007) and 2-visit pulpectomy (p = 0.042) significantly decreased when oral health screening was completed at least once. The NHSIC can be an effective policy for oral health management in preterm infants.

Effectiveness of an Oral Health Education Program Using a Smart Toothbrush with Quantitative Light-Induced Fluorescence Technology in Children.

This randomized controlled trial aimed to educate patients and manage oral hygiene remotely via a smart toothbrush (ST) by using mobile applications and to improve oral hygiene and habits by evaluating the plaque state via images from a Q-ray cam, which is a quantitative light-induced fluorescence (QLF) digital imaging device. In total, 68 children (aged 6-12 years) were randomly divided into three groups. Group I was assigned an electro-toothbrush (ET), group II was assigned a smart toothbrush (ST), and group III used a manual toothbrush (MT). Each group used an assigned toothbrush and was checked after 1 and 3 months. Oral hygiene status was evaluated using the patient hygiene performance (PHP) index and fluorescent plaque index (FPI), which are presented in the QLF program. In addition, questionnaires on oral health behaviors and attitudes were also evaluated. There was a 0.24 decrease in the PHP index and a 1.40 decrease in the simple hygiene score three months later compared with the baseline in the ST group, with no significant difference between the three methods (p = 0.518, p = 0.626). Many group II participants said that ST helped with oral hygiene, and they were willing to use it continuously. In addition, all participants' brushing times and attitudes toward oral hygiene improved after oral hygiene education using a Q-ray cam. Therefore, the use of STs provided good dental health education and a plaque-decreasing effect to children aged 6-12 years old. Furthermore, the QLF device can be used as a useful tool for maintaining good oral hygiene in children.

Evaluation of the clinical efficacy of quantitative light-induced fluorescence technology in diagnosing cracked teeth.

BACKGROUND: This retrospective study evaluated the clinical efficacy of quantitative light-induced fluorescence (QLF) technology for crack detection and the diagnosis of cracked teeth and assessed the possibility of a quantitative evaluation of cracks using QLF technology. METHODS: Patients who were clinically diagnosed with cracked teeth over a 1-year period were included. The QLF images of the corresponding symptomatic cracked teeth and asymptomatic contralateral teeth with crack lines were taken with Qraypen C (AIOBIO, Seoul, Korea). Fluorescence loss (ΔF), maximum fluorescence loss (ΔFmax), red fluorescence (ΔR), and maximum red fluorescence (ΔRmax) of the crack line were analyzed. The correlation between these parameters and sex, age, tooth position (1st premolar, 2nd premolar, 1st molar, 2nd molar), spontaneous pain (+/-), percussion test (+/-), cold test (++/+/-), and bite test (+/-) were statistically analyzed. RESULTS: A total of 66 patients were included. Twenty-four patients had asymptomatic contralateral teeth with apparent crack lines; thus, 90 teeth were analyzed. The crack lines in 84 teeth observed as red fluorescent lines on the QLF images showed ΔR values higher than the cut-off value set by the analysis program used. The patient's age and the ∣ΔF∣ and ΔR values were positively correlated. However, there was no statistically significant difference in the QLF parameters between the same patient's symptomatic tooth and the contralateral tooth. CONCLUSIONS: QLF technology is a useful assistive diagnostic device for diagnosing cracked teeth.

Incidence of edentulism among older adults using the Korean National Health Insurance Service database, 2013-2018.

OBJECTIVES: Population aging is rapidly accelerating worldwide. Oral diseases related to aging are also on the rise. This study examined trends in the incidence of edentulism among the older Korean population using data from the Korean National Health Insurance Service (KNHIS). METHODS: Data on older adults, aged ≥75 years of age, were obtained from the KNHIS for the period 2013-2018. Edentulism was defined as a treatment history of complete dentures in the KNHIS database. The exclusion criteria consisted of both disease codes and treatment codes related to conservative dental treatment, including periodontal and extraction treatment afterward. Crude incidence rates (CIRs) and age-standardized incidence rates (AIRs) with 95% confidence intervals were calculated and reported per 100,000 person-years by the direct method. Trends were tested by Cochrane Armitage models. RESULTS: Statistically significant increasing trends in both CIRs and AIRs were found among the older Korean population registered in the KNHIS (CIRs, 707.92 to 895.92; AIRs, 705.11 to 889.68; p<0.01). The incidence tended to increase in both genders (p<0.01). Both CIRs and AIRs in specific regions also showed slight but significant annual increases except for Jeju Island (p<0.01 or <0.05). The incidence showed increasing trends (p<0.01) in all income quintiles apart from the highest quintile. The edentulism incidence was highest in the lowest income group (the first quintile). CONCLUSIONS: Our data showed that the incidence of edentulism among the elderly showed an increasing trend from 2013 to 2018. This result provides a basis for future epidemiological studies on the incidence of edentulism in the older Korean population.

Periodontal disease and cancer risk: A nationwide population-based cohort study.

Background: Although emerging evidence suggests that periodontitis might increase the risk of cancer, comorbidity and lifestyle behaviors, such as smoking and body mass index (BMI), may have confounded this reported association. This study aimed to investigate whether chronic periodontitis is associated with cancer risk using a large, nationwide database. Methods: We conducted a population-based, retrospective cohort study using data from the Korean National Health Insurance Cohort Database obtained between January 2003 and December 2015. We included 713,201 individuals without a history of cancer who were followed up to 10 years. Confounding factors included demographic factors (age, sex, income, and residential area), lifestyle behaviors (smoking history and BMI), and comorbidities, such as hypertension, diabetes, heart failure, and pulmonary disease, using the Charlson Comorbidity Index. Multivariable Cox regression analysis was applied to estimate the adjusted hazard ratio (aHR) for cancer risk. Results: Of the 713,201 participants, 53,075 had periodontitis and were placed in the periodontitis group; the remaining 660,126 individuals were included as the control group. Overall, the cumulative incidence of cancer in the periodontitis group was 2.2 times higher than that in the control group. The periodontitis group had an increased risk of total cancer compared to the control group after adjusting for age, sex, comorbidities, BMI, and smoking history (aHR, 1.129; 95% confidence interval [CI], 1.089-1.171; P<0.0001). When examining specific cancer types, significant associations were also observed between periodontitis and stomach cancer (aHR, 1.136; 95% CI, 1.042-1.239; P=0.0037), colon cancer (aHR, 1.129; 95% CI, 1.029-1.239; P=0.0105), lung cancer (aHR, 1.127; 95% CI, 1.008-1.260; P=0.0353), bladder cancer (aHR, 1.307; 95% CI, 1.071-1.595; P=0.0085), thyroid cancer (aHR, 1.191; 95% CI, 1.085-1.308; P=0.0002), and leukemia (aHR, 1.394; 95% CI, 1.039-1.872; P=0.0270). There was no significant association between the development of secondary malignancy and periodontitis in cancer survivors who were alive 5 years after they were diagnosed with the primary malignancy. Conclusions: Periodontal disease, including periodontitis, was associated with increased risk of cancer, which persisted after controlling for confounding factors. Further prospective research is warranted to establish a causal relationship.

Effect of Silver Diamine Fluoride and Potassium Iodide Solution on Enamel Remineralization and Discoloration in Artificial Caries.

Silver diamine fluoride (SDF) is a strong fluoride agent for caries control, remineralization, and reducing the incidence of dental caries. This study used 38% SDF with potassium iodide (KI) on enamel remineralization and compared it with the currently used 38% SDF and 5% sodium fluoride (NaF) varnish to treat artificial caries. Bovine incisors were demineralized for 120 h and randomly distributed for treatment by the remineralization agents for 120 h as follows: control (n = 15), SDF/KI (n = 15), SDF (n = 15), and NaF (n = 15). Colorimetric analysis was performed using the ΔE value. The Vickers microhardness (VHN) was determined to evaluate the enamel remineralization of the specimens. Polarized light microscopy (PLM) and scanning electron microscopy (SEM) were performed to confirm the surfaces precisely and histologically. SDF/KI caused no significant difference in discoloration between the control and NaF groups. There was also no significant difference in the VHN after remineralization, but SDF/KI exhibited the highest mean microhardness. PLM revealed that SDF/KI had the greatest remineralization ability. In conclusion, SDF/KI is effective for dental enamel remineralization even with KI, which reduces discoloration.

Optical detection of oral biofilm in hospitalized geriatric patients using quantitative light-induced fluorescence technology.

Detection and removal of pathological oral biofilm are essential in hospitalized geriatric patients as the biofilm can lead to lung infection. However, as elderly patients often have cognitive and physical impairments, general oral examination is complicated and detection of pathological biofilms is challenging. Quantitative light-induced fluorescence (QLF) technology, which is currently actively used to detect bacterial structures in the oral cavity, is used to detect dental biofilm and to identify various oral bacterial infections. We confirmed the applicability of QLF technology to oral hygiene assessment and evaluation of hospitalized geriatric patients using the QLF technology to detect and remove the pathological oral biofilm in a hospitalized geriatric patient. The oral biofilm attached to the oral mucosa was difficult to observe with the naked eye. However, it was detected with red fluorescence on QLF images, which helped us observe the to detect pathological oral biofilm and evaluate the effectiveness of oral hygiene care (OHC). After OHC, the strong red fluorescence expressed in the oral mucosa was no longer observed. This change in the clinical aspect of red fluorescence suggests that QLF can be used to detect pathological oral biofilm accumulated on the oral mucous membrane and evaluate the effectiveness of OHC in hospitalized patients with extremely poor oral hygiene.

Comparison of the bite force and occlusal contact area of the deviated and non-deviated sides after intraoral vertical ramus osteotomy in skeletal Class III patients with mandibular asymmetry: Two-year follow-up.

Objective: The objectives of this study were to compare the time-dependent changes in occlusal contact area (OCA) and bite force (BF) of the deviated and non-deviated sides in mandibular prognathic patients with mandibular asymmetry before and after orthognathic surgery and investigate the factors associated with the changes in OCA and BF on each side. Methods: The sample consisted of 67 patients (33 men and 34 women; age range 15-36 years) with facial asymmetry who underwent 2-jaw orthognathic surgery. OCA and BF were taken before presurgical orthodontic treatment, within 1 month before surgery, and 1 month, 3 months, 6 months, 1 year, and 2 years after surgery. OCA and BF were measured using the Dental Prescale System. Results: The OCA and BF decreased gradually before surgery and increased after surgery on both sides. The OCA and BF were significantly greater on the deviated side than on the non-deviated side before surgery, and there was no difference after surgery. According to the linear mixed-effect model, only the changes in the mandibular plane angle had a significant effect on BF (p < 0.05). Conclusions: There was a difference in the amount of the OCA and BF between the deviated and non-deviated sides before surgery. The change in mandibular plane angle affects the change, especially on the non-deviated side, during the observation period.

Anti-biofilm activity of chlorhexidine-releasing elastomerics against dental microcosm biofilms.

OBJECTIVE: To evaluate the anti-biofilm activity of chlorhexidine-releasing elastomerics (CRE) developed to prevent biofilm-related diseases in orthodontic patients, using dental microcosm biofilms. METHODS: Elastomerics coated with one of two solutions (CRE 1 and 2) were attached to bovine enamel specimens. Uncoated elastomerics were used for negative (distilled water [DW]) and positive (0.1% chlorhexidine [CHX]) control groups. After saliva inoculation on the surface of the specimen for biofilm formation, DW and CRE groups were treated with DW, and the positive control group was treated with CHX twice a day for 5 min. After 7 days of biofilm formation, colony-forming units (CFUs, total and aciduric bacteria), red/green (R/G) ratio, biofilm thickness, live/dead cell ratio, and bacterial morphology in the biofilms were evaluated. Enamel demineralization was evaluated by fluorescence loss (ΔF). RESULTS: The CFUs of total and aciduric bacteria and R/G ratios in the CRE groups were significantly lower than those in the DW group with a reduction by 13%, 13%, and 19%, respectively (p < 0.05). The CFUs of total bacteria was significantly lower in the CRE groups than in the 0.1% CHX group (p < 0.05). Among the CRE groups, only CRE 1 exhibited a significantly reduced biofilm thickness of 54% compared to the DW group (p < 0.05) and apparent changes in bacterial morphology. ΔF in the CRE groups was significantly higher by 36% compared to that in the DW group (p < 0.05). CONCLUSIONS: CREs exhibited anti-biofilm and demineralization-inhibiting effect. Particularly, CRE 1 using dichloromethane as the solvent was most effective against biofilms. CLINICAL SIGNIFICANCE: Chlorhexidine-releasing elastomerics exhibited increased anti-biofilm and demineralization-inhibiting effect compared to 0.1% chlorhexidine mouthwash. Therefore, it is possible to prevent biofilm-related diseases simply and effectively by applying chlorhexidine-releasing elastomerics to orthodontic patients.

A novel model to predict tooth bleaching efficacy using autofluorescence of the tooth.

OBJECTIVES: We aimed to confirm whether autofluorescence emitted from teeth can predict tooth bleaching efficacy and establish a novel model combining natural color parameters and tooth autofluorescence data to improve the predictability of tooth bleaching. METHODS: A total of 61 tooth specimens were prepared from extracted human molars/premolars and immersed in 35% hydrogen peroxide for 1 h for tooth bleaching. The changes in laser-induced fluorescence (∆LIF) were assessed using Raman spectrometry. Tooth color and autofluorescence data were obtained using quantitative light-induced fluorescence (QLF) technology. Pearson correlation analyses were used to confirm the relationship between ∆LIF and autofluorescence. Intraclass correlation coefficients (ICC) were calculated to compare the conventional and new prediction models. Decision tree analysis was performed to evaluate clinical applicability. RESULTS: The yellowness-to-blueness value from fluorescence imaging showed a moderate correlation with ∆LIF (r= -0.409, p = 0.001). The degree of agreement between the actual efficacy and that predicted by our novel model was high (ICC=0.933, p = 0.002). Decision tree analysis suggested that tooth autofluorescence could be a key factor in prediction of tooth bleaching outcomes. CONCLUSIONS: Our findings showed that autofluorescence detected from QLF images may be used to predict tooth bleaching efficacy. Our proposed model appeared to improve the predictability of tooth bleaching.

Analysis of the mandibular canal course using unsupervised machine learning algorithm.

OBJECTIVES: Anatomical structure classification is necessary task in medical field, but the inevitable variability of interpretation among experts makes reliable classification difficult. This study aims to introduce cluster analysis, unsupervised machine learning method, for classification of three-dimensional (3D) mandibular canal (MC) courses, and to visualize standard MC courses derived from cluster analysis in the Korean population. MATERIALS AND METHODS: A total of 429 cone-beam computed tomography images were used. Four sites in the mandible were selected for the measurement of the MC course and four parameters, two vertical and two horizontal parameters were measured per site. Cluster analysis was carried out as follows: parameter measurement, parameter normalization, cluster tendency evaluation, optimal number of clusters determination, and k-means cluster analysis. The 3D MC courses were classified into three types with statistically significant mean differences by cluster analysis. RESULTS: Cluster 1 showed a smooth line running towards the lingual side in the axial view and a steep slope in the sagittal view. Cluster 2 ran in an almost straight line closest to the lingual and inferior border of mandible. Cluster 3 showed the pathway with a bent buccally in the axial view and an increasing slope in the sagittal view in the posterior area. Cluster 2 showed the highest distribution (42.1%), and males were more widely distributed (57.1%) than the females (42.9%). Cluster 3 comprised similar ratio of male and female cases and accounted for 31.9% of the total distribution. Cluster 1 had the least distribution (26.0%) Distributions of the right and left sides did not show a statistically significant difference. CONCLUSION: The MC courses were automatically classified as three types through cluster analysis. Cluster analysis enables the unbiased classification of the anatomical structures by reducing observer variability and can present representative standard information for each classified group.

The diagnostic efficacy of quantitative light-induced fluorescence in detection of dental caries of primary teeth.

OBJECTIVES: To evaluate a quantitative light-induced fluorescence (QLF) caries detection method using a portable device under clinical conditions and present a QLF scoring index (QS-index) for primary teeth. METHODS: A total of 878 tooth surfaces (proximal and occlusal) of 44 children were studied. After visual inspection and radiographic examination, images of dental caries captured with the QLF device were classified according to caries progression stages and analyzed with a specialized software. Cut-off values, sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC) were calculated for the QLF parameters: fluorescence loss (ΔF) and bacterial activity (ΔR). The reliability of logistic regression model to combine ΔF and ΔR was evaluated by the AUROC. RESULTS: QLF parameters showed a good sensitivity (0.72-0.91), specificity (0.74-0.96), and AUROC (0.861-0.940). The AUROC of logistic regression model (0.90-0.957) was higher than ΔF or ΔR average alone in all types of carious lesions. Every level of the QS-index was properly defined to represent the progression of dental caries with corresponding statistical significance. CONCLUSIONS: The reliability of QLF for dental caries detection in primary teeth was similar to or slightly higher than that of the traditional diagnostic methods of visual inspection or radiographic examination in clinical conditions. CLINICAL SIGNIFICANCE: The results of QLF were reliable in detecting all types of dental caries in primary teeth. The QLF method can provide visual images as well as quantitatively analyze the carious lesion.