Assessing tooth wear progression in non-human primates: a longitudinal study using intraoral scanning technology.

Intraoral scanners are widely used in a clinical setting for orthodontic treatments and tooth restorations, and are also useful for assessing dental wear and pathology progression. In this study, we assess the utility of using an intraoral scanner and associated software for quantifying dental tissue loss in non-human primates. An upper and lower second molar for 31 captive hamadryas baboons (Papio hamadryas) were assessed for dental tissue loss progression, giving a total sample of 62 teeth. The animals are part of the Southwest National Primate Research Center and were all fed the same monkey-chow diet over their lifetimes. Two molds of each dentition were taken at either two- or three-year intervals, and the associated casts scanned using an intraoral scanner (Medit i700). Tissue loss was calculated in WearCompare by superimposition of the two scans followed by subtraction analysis. Four individuals had dental caries, and were assessed separately. The results demonstrate the reliability of these techniques in capturing tissue loss data, evidenced by the alignment consistency between scans, lack of erroneous tissue gain between scans, and uniformity of tissue loss patterns among individuals (e.g., functional cusps showing the highest degree of wear). The average loss per mm2 per year for all samples combined was 0.05 mm3 (0.04 mm3 for females and 0.08 mm3 for males). There was no significant difference in wear progression between upper and lower molars. Substantial variation in the amount of tissue loss among individuals was found, despite their uniform diet. These findings foster multiple avenues for future research, including the exploration of wear progression across dental crowns and arcades, correlation between different types of tissue loss (e.g., attrition, erosion, fractures, caries), interplay between tissue loss and microwear/topographic analysis, and the genetic underpinnings of tissue loss variation.

Caries lesions diagnosis with deep convolutional neural network in intraoral QLF images by handheld device.

OBJECTIVES: This study investigated the effectiveness of a deep convolutional neural network (CNN) in diagnosing and staging caries lesions in quantitative light-induced fluorescence (QLF) images taken by a self-manufactured handheld device. METHODS: A small toothbrush-like device consisting of a 400 nm UV light-emitting lamp with a 470 nm filter was manufactured for intraoral imaging. A total of 133 cases with 9,478 QLF images of teeth were included for caries lesion evaluation using a CNN model. The database was divided into development, validation, and testing cohorts at a 7:2:1 ratio. The accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC) were calculated for model performance. RESULTS: The overall caries prevalence was 19.59%. The CNN model achieved an AUC of 0.88, an accuracy of 0.88, a specificity of 0.94, and a sensitivity of 0.64 in the validation cohort. They achieved an overall accuracy of 0.92, a sensitivity of 0.95 and a specificity of 0.55 in the testing cohort. The model can distinguish different stages of caries well, with the best performance in detecting deep caries followed by intermediate and superficial lesions. CONCLUSIONS: Caries lesions have typical characteristics in QLF images and can be detected by CNNs. A QLF-based device with CNNs can assist in caries screening in the clinic or at home. TRIAL REGISTRATION: The clinical trial was registered in the Chinese Clinical Trial Registry (No. ChiCTR2300073487, Date: 12/07/2023).

Diagnosis of dental caries based on attenuation coefficients analysis of optical coherence tomography images.

Quantitative analysis of optical attenuation based on optical coherence tomography images will offer an effective method to enhance diagnostic capabilities. In this paper, the optical attenuation in demineralized caries specimens was calculated to distinguish between normal teeth and carious teeth and further to differentiate the severity of caries, and thus come to the half-automated diagnosis of dental caries. Results show that the attenuation coefficient in carious regions is approximately 4.97 mm - 1 ± 0.206 , while that of normal teeth is about 3.69 mm - 1 ± 0.231 . Attenuation coefficient of carious regions is 35% higher than that of normal teeth. Moreover, five classes of caries were qualified and classified based on the optical attenuation coefficient. Compared with the healthy teeth, there is a noticeable disparity in the attenuation coefficients of carious teeth, both on the surface and at the dentinoenamel junction. This study provides a method for accurate caries diagnosis, particularly in detection of early lesions and subtle structural changes.

Analysis of cariogenic biofilms by using a swept-source optical coherence tomography in vitro.

OBJECTIVE: The objective was to measure the thickness of Streptococcus mutans (S. mutans) biofilms forming in an oral biofilm reactor (OBR) by using a noninvasive swept-source optical coherence tomography (SS-OCT) system at every 4 h time interval until 20 h and analyze the correlations with the amounts of biofilms. METHODS: S. mutans biofilms were formed on square-shaped bovine enamel blocks inside an OBR. Biofilms were analyzed at every 4 h stage (4 h, 8 h, 12 h, 16 h and 20 h) using a SS-OCT system and a laser scanning confocal microscope (LSCM). The amounts of biofilms were measured at each stage by separating the water insoluble glucan (WIG) and bacterial cells. Co-relationships between the SS-OCT measured biofilm thickness and the amounts of adhered biofilms were analyzed. RESULTS: The thickness of biofilms detected on SS-OCT images at 4 h stage was 0.059 ± 0.029 (Av ± SD) mm which increased time-dependently in a linear fashion after 8 h stage and reached to 0.435 ± 0.159 mm at 20 h stage and the correlation coefficient was about 0.89. The amounts of biofilms; bacterial optical density (OD) and WIG concentration increased time-dependently were 0.035 ± 0.008 / mm2 and 10.328 ± 2.492 µg/ mm2 respectively at 20 h stage. Correlation coefficients of 0.66 between 'the amounts of bacteria' and 'biofilm thickness on OCT' and 0.67 between 'the amounts of WIG' and 'biofilm thickness on OCT' were obtained, suggesting that there was a relatively positive correlation between them. CONCLUSION: The SS-OCT can be a useful tool to measure time-dependent growth of biofilms. Further studies are needed in order to assess biofilms using SS-OCT more accurately.

Evaluation of the effects of postprocessing settings in digital bitewing radiographs on proximal caries detection.

OBJECTIVE: Radiographs are an integral part of detecting proximal caries. The aim of this study was to evaluate the effect of contrast, brightness, noise, sharpness, and γ adjustment of digital intraoral radiographs on the diagnosis of proximal caries. MATERIALS AND METHODS: In this in vitro study, 40 extracted teeth including 20 premolars and 20 molars with enamel lesions (white spot or dentin discoloration seen through the enamel) were mounted together in groups of eight inside the skull. Bitewing radiographic images of each dental group were obtained by a photostimulable phosphor plate sensor with exposure conditions of 8 mA, 70 kV, and 0.2 s. The images were reconstructed by the built-in software and examined by two oral and maxillofacial radiologists in various settings of contrast, brightness, sharpness, noise, and γ. The teeth were then cut mesiodistally and the presence or absence of caries was confirmed by an oral and maxillofacial pathologist using a stereomicroscope. The data were then analyzed using the κ agreement coefficient, sensitivity, specificity, and accuracy (α = .05). RESULTS: Adjustment of brightness and contrast led to higher diagnostic performance with an accuracy of 82.5% and 83.8 (for observers 1 and 2, respectively) and 82.5% (for both observers), respectively. Noise adjustment was the least helpful approach for diagnosis of proximal dental caries among other adjustments, with an accuracy of 78.8% and 77.5% for observers 1 and 2, respectively. CONCLUSION: Brightness and contrast setting was more efficient in improving the diagnostic potential of bitewing radiographs compared to other adjustments.

Assessment of the efficiency of dental excavation methods using laser speckle imaging.

This paper introduces a novel application of the laser speckle technique in dentistry, focusing on assessing the efficiency of dental excavation methods used to remove decayed tooth structure. The aim is to evaluate the efficiency of two chemo-mechanical agents and the high-speed drill using the laser speckle technique, which offers objective, non-invasive, and real-time evaluation capabilities. Extracted human primary molars with active occlusal carious lesions were sectioned into three parts, with each part allocated to one of three groups: Group 1 (Brix3000®), Group 2 (Papacarie DUO®), and Group 3 (High-speed drill mechanical caries removal). Caries removal was performed using the designated agent or method for each group. After caries excavation, speckle imaging using a 632.8 nm laser was conducted. Additionally, SEM was used to acquire micro-photographs of the surface morphology of the treated samples. The findings reveal insights into the comparative efficiency of the three dental excavation agents and methods using the laser speckle technique. The speckle parameters extracted from speckle patterns generated by treated teeth provide valuable information for evaluating the performance of the excavation methods. The scanning electron microscopy images also offer detailed visual evidence to support the analysis. This paper demonstrates the potential of the laser speckle technique for assessing the efficiency of dental excavation methods. The objective, non-invasive, and real-time evaluation provided offers advantages over subjective visual assessment and manual measurements.

3D intraoral scanning techniques support the effects of crown morphology on dental caries.

BACKGROUND: With the development and utilization of three-dimensional (3D) intraoral scanning (IOS) technology, the morphological characteristics of teeth were quantitatively assessed. In this research, we aimed to explore the prevalence of dental caries in relation to each measurable morphological indicator of the tooth body via 3D intraoral scanning techniques. METHODS: A hospital-based single-centre study was conducted at our hospital from Dec. 2021 to Apr. 2023. A total of 53 patients were involved in the study, providing complete morphological data for 79 teeth. Each patient completed an oral hygiene routine questionnaire and underwent examination by an experienced dentist to evaluate caries conditions before undergoing 3D intraoral scanning to obtain a digital dental model. Geomagic Studio 2014 was used to extract oral morphological data from the models. The acquired data were entered, cleaned and edited using Excel 2016 and subsequently exported to SPSS version 25.0 for analysis. Chi-square analysis and logistic regression analyses were employed to test the associations. RESULTS: Among the participants, 33 (61.1%) were female, with a mean age of 26.52 ± 10.83 years. Significant associations were found between dental caries and the vertical distance between the distal tip and the gum (OR 14.02; 95% CI 1.80-109.07; P = 0.012), the distal lateral horizontal distance of occlusion (OR 0.40; 95% CI 0.18-0.90; P = 0.026), and the mesial horizontal distance of occlusion (OR 2.20; 95% CI 1.12-4.31; P = 0.021). The Hosmer-Lemeshow test indicated a P value of 0.33. CONCLUSIONS: The vertical distance between the distal tip and the gum, the distal lateral horizontal distance of the occlusion and the mesial horizontal distance of the occlusion were the influencing factors for dental caries (identified as independent risk factors). We hypothesize that these factors may be associated with the physiological curvature of teeth and the role of chewing grooves in plaque formation over time. However, further studies involving larger population samples and more detailed age stratification are still needed.

Parental use and acceptance of an accessible, commercially available intraoral camera for teledentistry in their children.

PURPOSE: The potential of combining teledentistry and engaging parents as underutilised resources to monitor paediatric dental health was emphasised during the COVID-19 pandemic and remains underexplored. This study aims to assess parental acceptance and use of a commercially available intraoral camera (IOC) for effective remote monitoring. METHODS: 47 child-parent dyads, where the parent was the main caregiver and the child was treated under general anaesthesia for early childhood caries, were recruited. Caregivers were trained to image their child's teeth on a commercially available IOC. Subsequently, submitted images were reviewed asynchronously by dentists for image quality, presence of dislodged fillings, abscesses, cavitation, and oral hygiene. Post-surgery monitoring was performed using teledentistry at 1 and 2 months and in-person at 4 months. A modified Telehealth Usability Questionnaire (TUQ) was used to record caregiver acceptance for study procedures. RESULTS: A mean TUQ of 6.09 out of 7 was scored by caregivers. Caregiver-reported issues were limited to problems with technique and child uncooperativeness. The number of clear images during the second teledentistry review was improved compared to the first (p = 0.007). 68% of children liked having images of their teeth taken. CONCLUSION: This study supports the feasibility of using an IOC as a clinically appropriate avenue for teledentistry with a high level of caregiver-child acceptance.

Two-year clinical and radiographic evaluation of ACTIVA BioACTIVE versus Compomer (Dyract® eXtra) in the restoration of class-2 cavities of primary molars: a non-inferior split-mouth randomised clinical trial.

OBJECTIVES: The trial aimed to compare the clinical performance and radiographic success of ACTIVA BioACTIVE versus Compomer in restoring class-II cavities of primary molars. MATERIALS AND METHODS: A non-inferior split-mouth design was considered. A pre-calculated sample size of 96 molars (48 per group) with class-2 cavities of twenty-one children whose ages ranged from 5 to 10 years were randomly included in the trial. Pre-operative Plaque Index (PI), DMFT/dmft scores and the time required to fill the cavity were recorded. Over 24 months, the teeth were clinically evaluated every six months and radiographically every 12 months by two calibrated and blinded evaluators using the United States public health service (USPHS)-Ryge criteria. The two-sided 95% confidence interval (CI) for the difference in success rate was considered to assess non-inferiority, and the margin was set at -18%. The linear mixed model and Firth's logistic regression model were used for data analysis (P < 0.05). RESULTS: After 24 months, 86 teeth (43 per group) were evaluated. The mean PI score was 1.1(± 0.9), while DMFT/dmft was 0.35 (± 0.74) and 6.55 (± 2.25) respectively. The clinical and radiographic success rate of Dyract vs. ACTIVA was 95.3% and 88.3% vs. 93% and 86%, respectively. The two-sided 95% CI for the difference in success rate (-2.3%) was - 3.2 to 1.3% and didn't reach the predetermined margin of -18% which had been anticipated as the non-inferiority margin. Clinically, ACTIVA had a significantly better colour match (P = 0.002) but worse marginal discolouration (P = 0.0143). There were no significant differences regarding other clinical or radiographic criteria (P > 0.05). ACTIVA took significantly less placement time than Dyract, with a mean difference of 2.37 (± 0.63) minutes (P < 0.001). CONCLUSION: The performance of ACTIVA was not inferior to Dyract and both materials had a comparable high clinical and radiographic performance in children with high-caries experience. ACTIVA had a significantly better colour match but more marginal discolouration. It took significantly less time to be placed in the oral cavity. TRIAL REGISTRATION: The study was registered at ClinicalTrials.gov on 4 May 2018 (#NCT03516838).

Comparison of near-infrared imaging with cone-beam computed tomography for proximal caries detection in permanent dentition: An in vivo study.

OBJECTIVES: This study aimed to evaluate the diagnostic performance of near-infrared imaging (NIRI) and unaided visual examination (UVE) in detecting proximal caries in permanent dentition in comparison with cone-beam computed tomography (CBCT). METHODS: Patients who underwent NIRI, UVE, and CBCT imaging within 1 week were enrolled. Using CBCT as the reference test, the positive percent agreement (PPA), negative percent agreement (NPA), and overall percent agreement (OPA) of NIRI, UVE, and a combination of the two for detecting proximal caries at different depths and in different tooth locations were assessed. Additionally, the consistency of these diagnostic methods with CBCT was evaluated. RESULTS: We evaluated 6,084 proximal surfaces and identified 177 CBCT-positive sites. NIRI had a PPA, NPA, and OPA of 68.93 %, 99.09 %, and 98.21 %, respectively, with a substantial agreement with CBCT. When combined with UVE, the PPA increased by approximately 50 % compared with that of UVE alone. Regarding caries at different depths, NIRI outperformed UVE in detecting initial caries (ICDAS 1-2) over moderate-to-advanced caries (ICDAS 3-6). However, the combined use of NIRI and UVE improved the detection of moderate-to-advanced caries. In the anterior teeth region, NIRI exhibited excellent agreement with CBCT, surpassing its performance in the posterior region. CONCLUSIONS: Although NIRI cannot fully replace radiographic methods, the substantial agreement of NIRI with CBCT in detecting proximal caries highlights its potential as a complementary tool in routine caries screening, especially when combined with UVE. CLINICAL SIGNIFICANCE: This study highlights the potential of NIRI as a radiation-free method for detecting proximal caries in permanent teeth. Early detection through regular NIRI scanning can lead to timely intervention, improved patient outcomes, and reduced overall disease burden.

Comparing modified USPHS and FDI criteria for the assessment of glass ionomer restorations in primary molars utilising clinical and photographic evaluation.

PURPOSE: To compare the applicability of modified US Public Health Service (USPHS) and FDI criteria for evaluating glass ionomer cement (GIC) restorations in primary posterior teeth through digital image analysis. METHODS: This comparative analytic study was conducted at the Children's Dental Clinic RSKGM FKG UI, involving 40 GIC restorations on lower first primary molars in children aged 4-9 years. After cleaning, the restorations were assessed clinically using modified USPHS and FDI criteria before taking digital images, then the collected images were re-evaluated using both sets of criteria, and the clinical assessment results were compared to the digital image assessment results. RESULTS: Statistical analysis revealed significant differences between the clinical evaluation of GIC restorations in primary teeth and their corresponding digital photographs when using the modified USPHS criteria, and although the use of FDI criteria yielded different results, these differences were not statistically significant. CONCLUSION: The assessment of GIC restorations through digital images aligns more closely with clinical assessments using the FDI criteria compared to the modified USPHS criteria.

Progression of proximal caries in primary molars using the radiographic ICDAS: a retrospective cohort study.

PURPOSE: To evaluate the proximal caries progression in primary molars using the radiographic International Caries Detection and Assessment System (ICDAS). METHODS: A study was conducted on 196 children aged 3-9 years old who underwent the clinical examination and bitewing radiography during baseline and 6-month (and over) follow-up visits. The primary molars bitewing radiographs with initial enamel caries (RA1 and RA2) or outer dentine caries (RA3) of proximal surfaces were included. Caries advancement was scored using ICDAS criteria and statistical analyses with the chi-square test. Median survival time was evaluated using Kaplan-Meier survival curves and log-rank tests. RESULTS: A total of 439 surfaces of primary molars were included in this study and an averaged follow-up period of enamel and dentine caries group were 18.3 ± 9.6 months and 16.5 ± 9.5 months respectively. The progression of proximal enamel lesions significantly differed between primary maxillary and mandibular molars (p = 0.002) and among each patient's primary mandibular second molar and the others (p = 0.002). On the contrary, the outer dentine caries of each group of primary molars was not different. The median survival time of the initial enamel proximal caries (23.30 months) was non-significantly longer than that of the dentine (20.80 months). CONCLUSIONS: Progressions of the initial enamel proximal caries were significantly different among primary molars at the average 18.3-month follow-up. The median survival period of the enamel proximal caries was more extended than that of dentine but without statistical difference. These results provide essential information for dentists regarding an appropriate appointment for bitewing examinations.

Comparative evaluation and patient satisfaction with an electrical impedance-based device versus digital radiography in the estimation of remaining dentin thickness in carious posterior permanent teeth: (Diagnostic accuracy study).

BACKGROUND: Accurate assessment of remaining dentin thickness (RDT) is paramount for restorative decisions and treatment planning of vital teeth to avoid any pulpal injury. This diagnostic accuracy study compared the validity and patient satisfaction of an electrical impedance based device Prepometer™ (Hager & Werken, Duisburg, Germany) versus intraoral digital radiography for the estimation of remaining dentin thickness in carious posterior permanent teeth. METHODS: Seventy patients aged 12-25 years with carious occlusal or proximal permanent vital posterior teeth were recruited. Tooth preparation was performed to receive an adhesive restoration. Pre- and post-excavation RDT were measured radiographically by two calibrated raters using the paralleling periapical technique. Prepometer™ measurements were performed by the operator. Patients rated their satisfaction level with each tool on a 4-point Likert scale and 100 mm visual analog scale (VAS). Inter and intragroup comparisons were analyzed using signed rank test, while agreement between devices and observations was tested using weight kappa (WK) coefficient. RESULTS: the intergroup comparisons showed that, before and after excavation, there was a significant difference between measurements made by both techniques (p < 0.001). After excavation, there was a weak agreement between measurements (WK = 0.2, p < 0.001), whereas before excavation, the agreement was not statistically significant (p = 0.407). Patients were significantly more satisfied with Prepometer™ based on scales and VAS (p < 0.001). CONCLUSION: Prepometer™ could be a viable clinical tool for determining RDT with high patient satisfaction, while radiographs tended to overestimate RDT in relation to the Prepometer™.

Eligibility of a novel BW + technology and comparison of sensitivity and specificity of different imaging methods for radiological caries detection.

OBJECTIVES: Bitewing radiography is considered to be of high diagnostic value in caries detection, but owing to projections, lesions may remain undetected. The novel bitewing plus (BW +) technology enables scrolling through radiographs in different directions and angles. The present study aimed at comparing BW + with other 2D and 3D imaging methods in terms of sensitivity, specificity, and user reliability. MATERIALS AND METHODS: Five human cadavers were used in this study. In three cadavers, natural teeth were transplanted post-mortem. BW + , two-dimensional (digital sensors, imaging plates, 2D and 3D bitewing radiographs) and 3D methods (high and low dose CBCT) were taken. Carious lesions were evaluated on 96 teeth at three positions (mesial, distal, and occlusal) and scored according to their level of demineralization by ten observers, resulting in 35,799 possible lesions across all observers and settings. For reference, µCT scans of all teeth were performed. RESULTS: Overall, radiographic evaluations showed a high rate of false-negative diagnoses, with around 70% of lesions remaining undetected, especially enamel lesions. BW + showed the highest sensitivity for dentinal caries and had comparatively high specificity overall. CONCLUSIONS: Within the limits of the study, BW + showed great potential for added diagnostic value, especially for dentinal caries. However, the tradeoff of diagnostic benefit and radiation exposure must be considered according to each patient's age and risk.

Current Applications of Artificial Intelligence for Pediatric Dentistry: A Systematic Review and Meta-Analysis.

Purpose: To systematically evaluate artificial intelligence applications for diagnostic and treatment planning possibilities in pediatric dentistry. Methods: PubMed®, EMBASE®, Scopus, Web of Science™, IEEE, medRxiv, arXiv, and Google Scholar were searched using specific search queries. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) checklist was used to assess the risk of bias assessment of the included studies. Results: Based on the initial screening, 33 eligible studies were included (among 3,542). Eleven studies appeared to have low bias risk across all QUADAS-2 domains. Most applications focused on early childhood caries diagnosis and prediction, tooth identification, oral health evaluation, and supernumerary tooth identification. Six studies evaluated AI tools for mesiodens or supernumerary tooth identification on radigraphs, four for primary tooth identification and/or numbering, seven studies to detect caries on radiographs, and 12 to predict early childhood caries. For these four tasks, the reported accuracy of AI varied from 60 percent to 99 percent, sensitivity was from 20 percent to 100 percent, specificity was from 49 percent to 100 percent, F1-score was from 60 percent to 97 percent, and the area-under-the-curve varied from 87 percent to 100 percent. Conclusions: The overall body of evidence regarding artificial intelligence applications in pediatric dentistry does not allow for firm conclusions. For a wide range of applications, AI shows promising accuracy. Future studies should focus on a comparison of AI against the standard of care and employ a set of standardized outcomes and metrics to allow comparison across studies.

Performance comparison of multifarious deep networks on caries detection with tooth X-ray images.

OBJECTIVES: Deep networks have been preliminarily studied in caries diagnosis based on clinical X-ray images. However, the performance of different deep networks on caries detection is still unclear. This study aims to comprehensively compare the caries detection performances of recent multifarious deep networks with clinical dentist level as a bridge. METHODS: Based on the self-collected periapical radiograph dataset in clinic, four most popular deep networks in two types, namely YOLOv5 and DETR object detection networks, and UNet and Trans-UNet segmentation networks, were included in the comparison study. Five dentists carried out the caries detection on the same testing dataset for reference. Key tooth-level metrics, including precision, sensitivity, specificity, F1-score and Youden index, were obtained, based on which statistical analysis was conducted. RESULTS: The F1-score order of deep networks is YOLOv5 (0.87), Trans-UNet (0.86), DETR (0.82) and UNet (0.80) in caries detection. A same ranking order is found using the Youden index combining sensitivity and specificity, which are 0.76, 0.73, 0.69 and 0.64 respectively. A moderate level of concordance was observed between all networks and the gold standard. No significant difference (p > 0.05) was found between deep networks and between the well-trained network and dentists in caries detection. CONCLUSIONS: Among investigated deep networks, YOLOv5 is recommended to be priority for caries detection in terms of its high metrics. The well-trained deep network could be used as a good assistance for dentists to detect and diagnose caries. CLINICAL SIGNIFICANCE: The well-trained deep network shows a promising potential clinical application prospect. It can provide valuable support to healthcare professionals in facilitating detection and diagnosis of dental caries.

AI-Dentify: deep learning for proximal caries detection on bitewing x-ray - HUNT4 Oral Health Study.

BACKGROUND: Dental caries diagnosis requires the manual inspection of diagnostic bitewing images of the patient, followed by a visual inspection and probing of the identified dental pieces with potential lesions. Yet the use of artificial intelligence, and in particular deep-learning, has the potential to aid in the diagnosis by providing a quick and informative analysis of the bitewing images. METHODS: A dataset of 13,887 bitewings from the HUNT4 Oral Health Study were annotated individually by six different experts, and used to train three different object detection deep-learning architectures: RetinaNet (ResNet50), YOLOv5 (M size), and EfficientDet (D0 and D1 sizes). A consensus dataset of 197 images, annotated jointly by the same six dental clinicians, was used for evaluation. A five-fold cross validation scheme was used to evaluate the performance of the AI models. RESULTS: The trained models show an increase in average precision and F1-score, and decrease of false negative rate, with respect to the dental clinicians. When compared against the dental clinicians, the YOLOv5 model shows the largest improvement, reporting 0.647 mean average precision, 0.548 mean F1-score, and 0.149 mean false negative rate. Whereas the best annotators on each of these metrics reported 0.299, 0.495, and 0.164 respectively. CONCLUSION: Deep-learning models have shown the potential to assist dental professionals in the diagnosis of caries. Yet, the task remains challenging due to the artifacts natural to the bitewing images.

ORCA-EFCD consensus report on clinical recommendation for caries diagnosis. Paper I: caries lesion detection and depth assessment.

OBJECTIVES: The aim of the present consensus paper was to provide recommendations for clinical practice considering the use of visual examination, dental radiography and adjunct methods for primary caries detection. MATERIALS AND METHODS: The executive councils of the European Organisation for Caries Research (ORCA) and the European Federation of Conservative Dentistry (EFCD) nominated ten experts each to join the expert panel. The steering committee formed three work groups that were asked to provide recommendations on (1) caries detection and diagnostic methods, (2) caries activity assessment and (3) forming individualised caries diagnoses. The experts responsible for "caries detection and diagnostic methods" searched and evaluated the relevant literature, drafted this manuscript and made provisional consensus recommendations. These recommendations were discussed and refined during the structured process in the whole work group. Finally, the agreement for each recommendation was determined using an anonymous Delphi survey. RESULTS: Recommendations (N = 8) were approved and agreed upon by the whole expert panel: visual examination (N = 3), dental radiography (N = 3) and additional diagnostic methods (N = 2). While the quality of evidence was found to be heterogeneous, all recommendations were agreed upon by the expert panel. CONCLUSION: Visual examination is recommended as the first-choice method for the detection and assessment of caries lesions on accessible surfaces. Intraoral radiography, preferably bitewing, is recommended as an additional method. Adjunct, non-ionising radiation methods might also be useful in certain clinical situations. CLINICAL RELEVANCE: The expert panel merged evidence from the scientific literature with practical considerations and provided recommendations for their use in daily dental practice.

Effect of composite radiopacity and margin location of the restoration on the diagnosis of secondary caries.

This research aimed to evaluate the effect of the radiopacity of a Bulk-Fill composite (X-TraFil, VOCO, Germany) and a Conventional composite (P60, 3M ESPE, USA) and assessment of the margin location in the enamel and dentin on the diagnosis of secondary caries. 76 intact premolars with MOD preparation were divided into two equal groups and filled with the conventional and bulk-fill composite. Four regions were considered to simulate carious lesions (two regions in enamel and two regions in dentin). In each group, half of the regions in the dentin and half in the enamel were randomly selected for secondary caries simulation and filled with a wax-plaster combination while the remaining regions stayed intact. Bitewing imaging was done using the PSP digital sensor. Five examiners reviewed the images, and lesions were recorded. Caries diagnosis indicators and paired-sample t-test were used for statistical analysis. The reproducibility and accuracy of the examiners' responses were evaluated using the kappa and agreement coefficient (α=0.05). The sensitivity, specificity, and accuracy of diagnosing secondary carious lesions in enamel were significantly better under conventional than bulk-fill composite. Similarly, the sensitivity and accuracy of diagnosing secondary caries in dentin were significantly higher under conventional composite than bulk-fill composite (p<0.05). No significant differences were found in the agreement and kappa coefficient between conventional and bulk-fill composites in the enamel and dentin (p>0.05). The diagnostic accuracy of carious lesions was higher under conventional composite than bulk-fill composite. However, the location of the secondary was ineffective in caries diagnosis.

Artificial intelligence for caries detection: a novel diagnostic tool using deep learning algorithms.

OBJECTIVES: The aim of this study was to develop an assessment tool for automatic detection of dental caries in periapical radiographs using convolutional neural network (CNN) architecture. METHODS: A novel diagnostic model named ResNet + SAM was established using numerous periapical radiographs (4278 images) annotated by medical experts to automatically detect dental caries. The performance of the model was compared to the traditional CNNs (VGG19, ResNet-50), and the dentists. The Gradient-weighted Class Activation Mapping (Grad-CAM) technique shows the region of interest in the image for the CNNs. RESULTS: ResNet + SAM demonstrated significantly improved performance compared to the modified ResNet-50 model, with an average F1 score of 0.886 (95% CI 0.855-0.918), accuracy of 0.885 (95% CI 0.862-0.901) and AUC of 0.954 (95% CI 0.924-0.980). The comparison between the performance of the model and the dentists revealed that the model achieved higher accuracy than that of the junior dentists. With the assist of the tool, the dentists achieved superior metrics with a mean F1 score of 0.827 and the interobserver agreement for dental caries is enhanced from 0.592/0.610 to 0.706/0.723. CONCLUSIONS: According to the results obtained from the experiments, the automatic assessment tool using the ResNet + SAM model shows remarkable performance and has excellent possibilities in identifying dental caries. The use of the assessment tool in clinical practice can be of great benefit as a clinical decision-making support in dentistry and reduce the workload of dentists.