Salivary Diagnosis of Dental Caries: A Systematic Review.

The activity of dental caries, combined with its multifactorial etiology, alters salivary molecule composition. The present systematic review was developed to answer the following question: "Are salivary biomarkers reliable for diagnosis of dental caries?". Following the "Preferred Reporting Item for Systematic Reviews and Meta-analysis" (PRISMA) guidelines, the review was conducted using multiple database research (Medline, Web of Science, and Scopus). Studies performed on healthy subjects with and without dental caries and providing detailed information concerning the clinical diagnosis of caries (Decayed, Missing, Filled Teeth-DMFT and International Caries Detection and Assessment System-ICDAS criteria) were included. The quality assessment was performed following a modified version of the Joanna Briggs Institute Prevalence Critical Appraisal Checklist. The protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO, ID: CRD42022304505). Sixteen papers were included in the review. All studies reported statistically significant differences in the concentration of salivary molecules between subjects with and without caries (p < 0.05). Proteins were the most investigated molecules, in particular alpha-amylase and mucins. Some studies present a risk of bias, such as identifying confounding factors and clearly defining the source population. Nevertheless, the 16 papers were judged to be of moderate to high quality. There is evidence that some salivary compounds studied in this review could play an important diagnostic role for dental caries, such as salivary mucins, glycoproteins (sCD14), interleukins (IL-2RA, 4,-13), urease, carbonic anhydrase VI, and urea.

Correlation between Matrix Metalloproteinase Presence and Caries Surface Appearance.

INTRODUCTION: Cariogenic bacterial acids dissolve the inorganic elements in dentine, leaving the dentine matrix exposed. Host-derived matrix metalloproteinases (MMPs) play an essential role in caries progression as they are significant regulators of extracellular matrix turnover and can degrade exposed collagen. This paper investigates the expression of MMP2 and MMP9 across various stages of caries in primary human teeth and relate this with a diagnosis recorded by the International Caries Detection and Assessment System (ICDAS). METHODS: Twenty-four sections (150 µm in thickness) from extracted teeth, clinically diagnosed using ICDAS, were immunohistochemically treated with monoclonal anti-MMP2 and anti-MMP9 antibodies. Positive staining was visualised by immunofluorescence using a VectorFluor Duet Double Labeling Kit. Images from triplicate samples for each ICDAS score were analysed using ImageJ software. Collagen degradation in caries lesions was detected using a hydroxyproline assay. RESULTS: MMPs were weakly detected in caries with ICDAS 1-2 scores, and an insignificant increase was detected in ICDAS 3. However, a significant increase in MMP expression was seen in caries with an ICDAS score of 4-6. There was a strong positive correlation between the ICDAS score and MMP2 (r [6] = 0.86, p = 0.002) and between ICDAS and MMP9 (r [6] = 0.82, p = 0.004). Data were analysed using two-way ANOVA followed by Tukey multiple comparison test (*p < 0.05). CONCLUSION: The use of ICDAS to assess the severity of caries lesions and how this correlates with the presence of MMP in these lesions validates the modern approach to caries management with a minimally invasive concept.

Clinical and ex-vivo effect of LASERs on prevention of early-enamel caries: systematic review & meta-analyses.

To investigate the in vivo and in situ effect of different types of lasers in prevention of enamel demineralization in high caries risk cases (around orthodontic brackets, around restoration and in caries susceptible pits and fissures). PubMed was searched using the following keyword sequence; (Laser therapy OR laser irradiation OR laser application) AND (enamel caries prevention OR enamel demineralization OR enamel remineralization OR early enamel caries OR early-enamel caries OR enamel resistance OR enamel decalcification OR white spot lesions WSLs OR incipient lesion OR enamel decay OR enamel Dissolution OR enamel microhardness) AND (clinical trial OR Randomized clinical trial OR In situ study). The latest literature search was ended by "30 January 2023". PubMed was used as a primary data base for study selection. Scopus, EBSCO, and Google scholar are checked in our study after results of systematic search on PubMed. Only duplicates were found. Two meta-analyses were carried out. The first, clinical meta-analysis on incidence of white spot lesions (WSLs) following CO2 laser irradiation of enamel. The second meta-analysis on ex-vivo/in situ effect of CO2 laser on microhardness of enamel. In each meta-analysis three studies were included. Risk of bias was assessed. The search identified eight studies (four ex-vivo and four clinical trials). Regarding the clinical meta-analysis, the overall standardized mean difference was 0.21 [ 95% confidence interval (CI): 0.15-0.30, p < 0.00001]. This indicates that the incidence of new WSLs in patients who received low power CO2 laser treatment was highly significantly lower than placebo groups. The heterogeneity was considerable (I2 = 71%). In the second meta-analysis, the overall standardized mean difference was 49.55 [ 95% confidence interval (CI): 37.74, 61.37, p < 0.00001]. This indicates that microhardness of enamel receiving low power (0.4-5 W) CO2 laser irradiation is highly significantly lower than control untreated enamel. The heterogeneity was substantial (I2 = 48%). Within the limitations of this study, Low level laser therapy concept with CO2 laser seems to be effective in preventing enamel caries.Prospero registration number: CRD42023437379.

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.

Automatic caries detection in bitewing radiographs-Part II: experimental comparison.

OBJECTIVE: The objective of this study was to compare the detection of caries in bitewing radiographs by multiple dentists with an automatic method and to evaluate the detection performance in the absence of a reliable ground truth. MATERIALS AND METHODS: Four experts and three novices marked caries using bounding boxes in 100 bitewing radiographs. The same dataset was processed by an automatic object detection deep learning method. All annotators were compared in terms of the number of errors and intersection over union (IoU) using pairwise comparisons, with respect to the consensus standard, and with respect to the annotator of the training dataset of the automatic method. RESULTS: The number of lesions marked by experts in 100 images varied between 241 and 425. Pairwise comparisons showed that the automatic method outperformed all dentists except the original annotator in the mean number of errors, while being among the best in terms of IoU. With respect to a consensus standard, the performance of the automatic method was best in terms of the number of errors and slightly below average in terms of IoU. Compared with the original annotator, the automatic method had the highest IoU and only one expert made fewer errors. CONCLUSIONS: The automatic method consistently outperformed novices and performed as well as highly experienced dentists. CLINICAL SIGNIFICANCE: The consensus in caries detection between experts is low. An automatic method based on deep learning can improve both the accuracy and repeatability of caries detection, providing a useful second opinion even for very experienced dentists.

Accuracy of an intraoral scanner with near-infrared imaging feature in detection of interproximal caries of permanent teeth: An in vivo validation.

OBJECTIVE: This study aimed to evaluate the accuracy of an intraoral scanner with near-infrared imaging (NIRI) feature in the diagnosis of interproximal caries and to compare it with the visual-tactile method (VTM), bitewing radiography (BWR), and panoramic radiography (PR). MATERIALS AND METHODS: Six hundred thirty-nine interproximal surfaces (mesial-distal) of posterior teeth from 22 volunteers were examined. Results were scored by VTM, BWR, PR, and NIRI. Lesions were scored as 0 for no-caries, 1 for early-enamel lesion (EEL), and 2 for lesions involving dentino-enamel junction (DEJ). McNemar, Kappa, and Fleis Kappa tests were used to evaluate the agreement levels. Pearson's Chi-square test was used to determine the matching rates after validation. RESULTS: A good level of agreement was observed between examination methods (Ƙ = 0.613; p < 0.001). In pairwise comparisons, a moderate agreement was seen between all the methods for lesions with DEJ involvement, while a statistically good agreement was observed between BWR and NIRI (Ƙ = 0.675; p < 0.001). As a result of validation, the accuracy of NIRI for molars was considered 85.2% and 75.7% for premolars in EELs, 85.2% for molars, and 70% for premolars regarding the lesions involving DEJ. CONCLUSIONS: Intraoral scanners with the NIRI feature may be used for diagnosing interproximal caries, especially for permanent molars. CLINICAL SIGNIFICANCE: Early detection of proximal caries is one of the most essential topics forming the basis of preventive dentistry. This study investigates a caries diagnostic tool integrated into intraoral scanners to diagnose interproximal caries. A caries diagnostic tool integrated into an intraoral scanner may prevent the harmful effects of ionizing radiation in early caries diagnosis and may improve the patient's oral health status.

Evaluation of near-infrared digital imaging transillumination compared with bitewing radiography for proximal caries detection in children.

BACKGROUND: Limitations in traditional caries detection tools have driven the development of alternatives methods, focused on the early lesion detection such as near-infrared digital imaging transillumination (NIDIT). AIM: The aim of this study was to evaluate the performance of NIDIT compared with bitewing radiography (BWR) in the detection of interproximal carious lesions in children. DESIGN: A retrospective audit of data from children who had NIDIT, BWR and intraoral photographs was conducted. Carious lesions were scored on a tooth surface level with BWR acting as the primary reference for comparison. Accuracy was determined using multi-class area under the curve (AUC), and correlation was determined using Fleiss' Kappa. RESULTS: Data from 499 tooth surfaces involving 44 children were included in this study. The average age across the participants was 86 months (~7 years) with an average dmft (decayed, missing and filled teeth in primary dentition) of 5.29. Multi-class AUC comparing NIDIT to BWR was 0.70. The correlation between NIDIT and BWR was moderate (0.43), whereas the correlation between photographic examination and BWR was 0.30, which is fair. CONCLUSION: When compared to BWR, NIDIT showed a high specificity but a low sensitivity for proximal caries detection in primary teeth.

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.

Clinical SWIR and CP-OCT imaging of interproximal lesions.

BACKGROUND: Enamel is highly transparent at short wavelength infrared imaging (SWIR) wavelengths allowing the detection of dental decay without the need for ionizing radiation. The purpose of this study was to use SWIR imaging methods including cross polarization optical coherence tomography (CP-OCT), occlusal transillumination (SWIR-OT), proximal transillumination (SWIR-PT), and occlusal reflectance (SWIR-R) to image interproximal lesions in vivo and compare the sensitivity with radiography. METHODS: Participants (n = 30) aged 18-80 each with a radiopositive interproximal lesion scheduled for restoration were enrolled in the study. Studies have shown that the opposing proximal surfaces across the contact will likely also have lesions. SWIR images were acquired of the adjoining teeth at each contact with an interproximal lesion scheduled for restoration. Lesion presence and depth were assessed on each side of the contact for radiography and each SWIR imaging method. Lesions on radiographs and in CP-OCT images were identified by a single examiner while lesions in SWIR images were identified by a contrast threshold via semi-automatic image segmentation. RESULTS: All SWIR imaging methods had significantly higher sensitivity (P < 0.05) than radiographs for the detection of interproximal lesions on the teeth opposite those restored. CP-OCT and SWIR-R imaging methods had significantly higher sensitivity than the other methods. SWIR imaging methods showed significantly higher lesion contrast than radiography. CONCLUSIONS: SWIR imaging methods can be used to detect interproximal lesions on posterior teeth with higher diagnostic performance than radiographs. CP-OCT appears well suited as a potential gold standard for the detection of interproximal lesions and assessment of their severity in vivo.

A Tele-detection and referral pAthways model for early childhood cariEs control- a protocol for a randomized factorial study: the TRACE study.

BACKGROUND: Early childhood caries (ECC) is one of the most common childhood diseases affecting the primary teeth of children younger than 6 years of age. ECC progression can be reversed in the early stages although these lesions often go undetected. New approaches are needed to detect oral diseases at an early stage when they can be better controlled. The aim of the study is to assess the effectiveness of ECC tele-detection methods combined with referral pathways with and without user fee removal in controlling ECC. METHODS: A randomized factorial trial will be used to compare two tele-dentistry detection methods for ECC (intraoral camera and smartphone camera) and two referral pathways (user fee removal versus conventional care). The study will recruit children younger than 6 years of age in marginalized communities in Alexandria, Egypt. The primary outcome is the percentage of teeth receiving indicated care, while the secondary outcomes are the oral health-related quality of life, acceptance of teledentistry by dentists, procedure time, and child cooperation. Two-way analysis of variance will be used to assess the effect of the two factors as between group variables on the outcomes after 6 and 12 months. The interaction between detection methods and referral pathways will also be assessed, and the effect of confounders will be controlled in a multivariable linear regression model. DISCUSSION: The findings of this study have the potential to inform clinical practice and oral healthcare policies for ECC management. Successful tele-detection and referral pathways could be integrated into oral healthcare systems, leading to improved oral health outcomes for children. TRIAL REGISTRATION: The trial has been registered on ClinicalTrials.gov in August 2023 (initial release) ID: NCT06019884.

Monitoring lesion activity on primary teeth with CP-OCT and SWIR reflectance imaging.

OBJECTIVE: The purpose of this study was to use cross polarization optical coherence tomography (CP-OCT) and short wavelength infrared imaging (SWIR) reflectance imaging to monitor changes in the structure and activity of early occlusal caries on primary teeth over a period of 6 months during intervention with fluoride. METHODS: Participants (n = 29) aged 6-10 each with two suspected active occlusal lesions on primary teeth completed the study. Fluoride varnish was applied to tooth surfaces every 3-months and participants were instructed to brush twice daily with a fluoride toothpaste. Images were acquired using CP-OCT every 3 months for 6 months. SWIR reflectance images were acquired during forced air-drying of the lesions for 30 s at 0 and 6-months. RESULTS: Most of the 42 lesions appeared initially active at baseline. Only 6 lesions appeared arrested at baseline based on the presence of a highly mineralized transparent surface layer (TSL) in CP-OCT images. At 6 months, 14 of the lesions appeared arrested including the 6 initially arrested lesions and the TSL thickness increased significantly (p < 0.0001). The mean lesion depth (Ld) and the integrated reflectivity over the lesion depth (ΔR) increased significantly (p < 0.05) after 6 months for the 42 lesions analyzed. SWIR reflectance images showed that there was a significantly higher (p < 0.05) delay before changes in intensity were measured for active lesions versus arrested lesions during lesion drying. CONCLUSION: CP-OCT was able to monitor changes in lesion structure and activity including the formation of a highly mineralized TSL indicative of lesion arrest during nonsurgical intervention. Time-resolved SWIR reflectance imaging also shows that there are differences in the dehydration kinetics between active and arrested lesions. This study demonstrates two independent imaging methods that can be used to monitor changes in lesion activity over time.

Accuracy of Two Visual Criteria for the Assessment of Caries around Restorations: A Delayed-Type Cross-Sectional Study.

The aim of this study was to compare the performance of two visual criteria used for the detection of caries around restorations in permanent teeth. In this delayed-type cross-sectional study, the study sample was randomly allocated to one of two visual criteria for the assessment of restorations as follows: (a) International Dental Federation (FDI) criteria, considers marginal staining, marginal adaptation, and caries recurrence and (b) Caries Associated with Restorations or Sealants (CARS) criteria, defined by the International Caries Classification and Management System. A calibrated examiner assessed the restorations using two reference standards as follows: (i) for restorations requiring operative interventions (repair/replacement), the restoration was partially or totally removed and the presence or absence of carious tissue was assessed; and (ii) for restorations requiring nonoperative intervention, follow-up for a period of 1 year was recommended to allow identification of the presence of new lesions not detected at baseline. The sensitivity, specificity, area under receiver operating characteristic curve (Az), and accuracy of the criteria were assessed. The study included 305 restorations. The FDI marginal staining parameter had the lowest Az value (Az = 0.501), while similar sensitivity was observed between the CARS (62.0%), FDI presence of caries (65.0%), and FDI marginal adaptation (74.0%) parameters. CARS exhibited the highest specificity (88.3%) and accuracy (85.6%). The CARS criteria exhibited better specificity and accuracy in detecting caries around restorations, followed by the FDI criteria for caries recurrence and marginal adaptation. Considering marginal staining or combining multiple marginal features to assess secondary caries resulted in an increased risk of false-positive outcomes and overtreatment.

Secondary Caries Detection and Treatment Decision according to Two Criteria and the Impact of a Three-Dimensional Intraoral Scanner on Gap Evaluation.

This study aimed to evaluate the in vitro performance in detecting caries around composite restorations in permanent posterior teeth and the impact of treatment decisions of two visual criteria: International Dental Federation (FDI) criteria and the Caries Associated with Restorations and Sealants (CARS) system. The correlation among secondary caries and the presence of gap measured with a three-dimensional (3D) intraoral scanner was also aimed. One hundred sixteen teeth were assessed by a trained and calibrated examiner according to the FDI criteria or CARS system. A second examiner measured the gap on the 3D models using specific software. The reference standard was the histological examination performed by a third examiner blind to the other evaluations. Other 30 extracted permanent teeth were used only to assess the reproducibility of the methods. The same random sample was selected for re-examination by all three methods, and there were 7 days between the examinations. Unweighted and weighted kappa tests were conducted to assess intra-examiner reproducibility. Spearman's correlation coefficient (Rho) and 95% confidence intervals (95% CI) were calculated between the histological examination and scores obtained with FDI criteria, CARS system, and treatment decisions. Spearman's correlation between the visual and scanner evaluation with the reference standard was performed. Spearman's rank correlation analyses were conducted independently between the gap evaluated and measured by the visual inspection with the gap assessed using the scanner. The reproducibility of the visual score systems reached high values. Spearman's correlation coefficients (Rho; 95% CI) between the following variables versus histology were the FDI presence of caries (0.65; 0.53-0.74); CARS scores (0.65; 0.52-0.74); FDI treatment decision (0.46; 0.31-0.59); and CARS treatment decision (0.62; 0.49-0.72). Rho (95% CI) between histology and the gap assessment by the visual inspection was 0.59 (0.45-0.70), the gap measurement by the visual inspection was 0.49 (0.33-0.62), and the gap measured by the scanner was 0.37 (0.18-0.53). Both visual criteria present similar performance in detecting caries. The correlation among treatment decisions is moderate for the FDI and CARS criteria, and both are moderately correlated with lesion depth, with a slight CARS superiority. However, visual examination presents better performance than the 3D intraoral scanner on gap size assessment.

Assessment of YOLOv3 for caries detection in bitewing radiographs based on the ICCMS™ radiographic scoring system.

OBJECTIVES: To assess the feasibility of the YOLOv3 model under the intersection over union (IoU) thresholds of 0.5 (IoU50) and 0.75 (IoU75) for caries detection in bitewing radiographs based on the International Caries Classification and Management System (ICCMS™). MATERIALS AND METHODS: We trained the YOLOv3 model by feeding 994 annotated radiographs with the IoU50 and IoU75 thresholds. The testing procedure (n = 175) was subsequently conducted to evaluate the model's prediction metrics on caries classification based on the ICCMS™ radiographic scoring system. RESULTS: Regarding the 4-class classification representing caries severity, YOLOv3 could accurately detect and classify enamel caries and initial dentin caries (class RA) (IoU50 vs IoU75: precision, 0.75 vs 0.71; recall, 0.67 vs 0.64). Concerning the 7-class classification signifying specific caries depth (class 0, healthy tooth; classes RA1-3, initial caries affecting outer half, inner half of enamel, and the outer 1/3 of dentin; class RB4, caries extending to the middle 1/3 of dentin; classes RC5-6, extensively cavitated caries affecting the inner 1/3 of dentin and involving the pulp chamber), YOLOv3 could accurately detect and classify caries with pulpal exposure (class RC6) (IoU50 vs IoU75: precision, 0.77 vs 0.73; recall, 0.61 vs 0.57) but it failed to predict the outer half of enamel caries (class RA1) (IoU50 vs IoU75: precision, 0.35 vs 0.32; recall, 0.23 vs 0.21). CONCLUSIONS: YOLOv3 yielded acceptable performances in both IoU50 and IoU75. Although the performance metrics decreased in the 7-class detection, the two thresholds revealed comparable results. However, the model could not consistently detect initial-stage caries affecting the outermost surface of the enamel. CLINICAL RELEVANCE: YOLOv3 could be implemented to detect and classify dental caries according to the ICCMS™ classification with acceptable performances to assist dentists in making treatment decisions.

Automatic caries detection in bitewing radiographs: part I-deep learning.

OBJECTIVE: The aim of this work was to assemble a large annotated dataset of bitewing radiographs and to use convolutional neural networks to automate the detection of dental caries in bitewing radiographs with human-level performance. MATERIALS AND METHODS: A dataset of 3989 bitewing radiographs was created, and 7257 carious lesions were annotated using minimal bounding boxes. The dataset was then divided into 3 parts for the training (70%), validation (15%), and testing (15%) of multiple object detection convolutional neural networks (CNN). The tested CNN architectures included YOLOv5, Faster R-CNN, RetinaNet, and EfficientDet. To further improve the detection performance, model ensembling was used, and nested predictions were removed during post-processing. The models were compared in terms of the [Formula: see text] score and average precision (AP) with various thresholds of the intersection over union (IoU). RESULTS: The twelve tested architectures had [Formula: see text] scores of 0.72-0.76. Their performance was improved by ensembling which increased the [Formula: see text] score to 0.79-0.80. The best-performing ensemble detected caries with the precision of 0.83, recall of 0.77, [Formula: see text], and AP of 0.86 at IoU=0.5. Small carious lesions were predicted with slightly lower accuracy (AP 0.82) than medium or large lesions (AP 0.88). CONCLUSIONS: The trained ensemble of object detection CNNs detected caries with satisfactory accuracy and performed at least as well as experienced dentists (see companion paper, Part II). The performance on small lesions was likely limited by inconsistencies in the training dataset. CLINICAL SIGNIFICANCE: Caries can be automatically detected using convolutional neural networks. However, detecting incipient carious lesions remains challenging.

Enhancing Caries Detection in Bitewing Radiographs Using YOLOv7.

The study aimed to evaluate the impact of image size, area of detection (IoU) thresholds and confidence thresholds on the performance of the YOLO models in the detection of dental caries in bitewing radiographs. A total of 2575 bitewing radiographs were annotated with seven classes according to the ICCMS™ radiographic scoring system. YOLOv3 and YOLOv7 models were employed with different configurations, and their performances were evaluated based on precision, recall, F1-score and mean average precision (mAP). Results showed that YOLOv7 with 640 × 640 pixel images exhibited significantly superior performance compared to YOLOv3 in terms of precision (0.557 vs. 0.268), F1-score (0.555 vs. 0.375) and mAP (0.562 vs. 0.458), while the recall was significantly lower (0.552 vs. 0.697). The following experiment found that the overall mAPs did not significantly differ between 640 × 640 pixel and 1280 × 1280 pixel images, for YOLOv7 with an IoU of 50% and a confidence threshold of 0.001 (p = 0.866). The last experiment revealed that the precision significantly increased from 0.570 to 0.593 for YOLOv7 with an IoU of 75% and a confidence threshold of 0.5, but the mean-recall significantly decreased and led to lower mAPs in both IoUs. In conclusion, YOLOv7 outperformed YOLOv3 in caries detection and increasing the image size did not enhance the model's performance. Elevating the IoU from 50% to 75% and confidence threshold from 0.001 to 0.5 led to a reduction of the model's performance, while simultaneously improving precision and reducing recall (minimizing false positives and negatives) for carious lesion detection in bitewing radiographs.

Effect of resin composite shade on digital fiber-optic transillumination imaging in vitro.

Digital imaging fiber-optic transillumination (DIFOTI) devices have been used to detect caries, a technique without using X-rays. However, the effects of resin composites (RCs) shades on the images acquired with DIFOTI devices have not been investigated. Thus, this study aimed to elucidate the influence of RC shade on the images obtained with DIFOTI technique. Three shades (A1, A3, and Opaque) for each of four flowable RCs were filled on a cavity prepared in a left mandibular first premolar obtained from a donated body. Then, transmission images with a DIFOTI device (DIAGNOcam; KaVo, Biberach, Germany) were acquired, and the average lightness values of the images in the RC and enamel were used to calculate differences between those areas. To clarify the influence of the optical translucency and color on DIFOTI images, the color parameters (L*, a* and b*) of each RC were obtained with black and white backgrounds. The color differences between the backgrounds were calculated as transparency parameter (TP) values. The number of repetitions was set to 10. Differences in the lightness value of the shades varied in each RC. The difference in lightness was significantly associated with the TP value and color parameters of L* (p < 0.01), with negative (R = - 0.81) and positive (R = 0.84) correlations, respectively. In conclusion, DIFOTI images of RCs with high optical translucency resembled those of the natural tooth structure.

Sensitivity and specificity of the ICDAS II system and bitewing radiographs for detecting occlusal caries using the Spectra™ caries detection system as the reference test in children.

BACKGROUND: Most studies assessing the sensitivity and specificity of caries detection methods have been performed in vitro using the histological method as the gold standard showing inconsistent values. The aim of this study was to compare the sensitivity and specificity in detecting occlusal caries using the International Caries Detection and Assessment System (ICDAS II) with the radiographic method (RM), while using the Spectra™ Caries Detection System (SCDS) as the reference test. METHODS: One hundred sixty children, ages 7-12 years, participated in the study. Five zones in the occlusal surfaces of 859 primary and 632 first permanent molars were examined visually using ICDAS-II, the RM using bitewing radiographs and SCDS. The descriptive statistics of sensitivity and specificity were calculated and compared. RESULTS: For all molars combined and for primary molars only, the sensitivity of ICDAS II was higher for detecting total caries (p < 0.001), caries in enamel (p < 0.001), and caries in dentin (p = 0.016), but it was not different for detecting caries in the dentin of permanent first molars (p = 0.214), and primary second molars (p = 0.761). The specificity of RM was higher for detecting total caries, caries in enamel for all molars combined and for permanent first molars (p < 0.001). For caries in dentin, the specificity of ICDAS II was higher for all molars combined and for primary molars only (p < 0.001). For total caries in primary molars only, and caries in dentin of permanent first molars only, the specificity was not different (p = 0.156 and p = 0.181 respectively). CONCLUSIONS: The sensitivity and specificity of ICDAS II and RM changes depending on whether the carious lesion compromises the enamel or dentin, and if the caries detection is performed in the primary molars or permanent first molars.

[Assessment of carious dental lesions and treatment options: comparison of the knowledge of dental students and orthodontic assistants]. / Einschätzung von kariösen Zahnläsionen und Therapieoptionen: Vergleich der Kenntnisse von Studierenden der Zahnmedizin und AssistenzzahnärztInnen für Kieferorthopädie.

In order to optimize dental education, established procedures for caries diagnosis and therapy, such as the International Caries Classification and Management System (ICCMS), should be integrated into the curriculum. In preparation, the level of knowledge of dental students on caries detection and management was surveyed in order to specifically address deficits in dental teaching. In addition, the data were compared with the knowledge of clinically experienced dentists. The results are presented in this report and possible consequences for dental teaching are discussed.Twenty-six sixth semester dental students and six assistant dentists at the Department of Orthodontics (Philipps University of Marburg, Germany) were available for the written survey during the winter semester 2018/2019. For 12 anonymized orthodontic patient cases, the clinical findings, caries risk, and adequate treatment were to be determined for each defined tooth. The consensus decision of two experienced dentists served as the reference value. As a result, agreement with the reference ranged from 40.7% to 51.3% for students and from 56.9% to 75.0% for assistant dentists. The extent of caries and the resulting necessary treatment were mostly underestimated.In addition to theoretical knowledge, clinical experience is another prerequisite for adequate caries diagnosis and its management. The underestimation of caries extent and necessary treatment should be taken into account when teaching content. Procedures such as the ICCMS should be integrated into the dental curriculum at an early stage, so that orthodontic patients can also receive effective care.

Performance of the caries diagnosis feature of intraoral scanners and near-infrared imaging technology-A narrative review.

PURPOSE: To describe and discuss the benefits and drawbacks of various dental caries diagnostic techniques, including the use of intraoral scanners for caries diagnosis based on near-infrared imaging (NIR) technology. MATERIAL AND METHODS: A MEDLINE search from 1980-2023 focused on dental caries diagnostic techniques, emphasizing intraoral scanners using NIR technology. Alternative caries detection methods were also evaluated for their advantages and limitations, enabling a comparison with NIR. The review included traditional caries tools, the latest detection methods, and NIR's role in intraoral scanners, drawing from case reports and both in vivo and in vitro studies. Keywords like "caries detection," "intraoral scanners," and "Near Infrared Imaging (NIRI)" guided the search. After screening titles and abstracts for relevance, full texts with valuable insights were thoroughly analyzed. The data was grouped into three: traditional diagnostics, advanced digital methods, and intraoral scanner-based detection. RESULTS: This comprehensive narrative review described and discussed the current state of dental caries diagnostic methods, given the insufficient number of clinical investigations suitable for a systematic review. Traditional caries diagnosis techniques have shown variable accuracy dependent on a dentist's experience and the potential over-removal of healthy tooth structures. Intraoral scanners have emerged as a novel caries detection method, because of their integration of NIR technology. Various studies have confirmed the efficacy of NIR in detecting interproximal caries and in the early diagnosis of non-cavitated caries. Specifically, intraoral scanners have demonstrated promising results, proving comparable to established diagnostic methods like bitewing radiography. Nevertheless, while the integration of NIR into intraoral scanners seems promising, the technology still faces challenges, notably its accuracy in detecting secondary and subgingival cavities. However, with anticipated integrations of AI, NIR in intraoral scanners could revolutionize early caries detection. CONCLUSIONS: Intraoral scanners with NIR technology offer non-destructive imaging, real-time lesion visuals, and enhanced patient communication. Although comparable to bitewing radiography in some studies, a universally accepted diagnostic tool is lacking. Future research should compare them with existing methods, focusing on clinical outcomes, cost-effectiveness, and patient acceptance.