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The use of 3D intraoral scanners (IOS) and software that can support automated detection and objective monitoring of oral diseases such as caries, tooth wear or periodontal diseases, is increasingly receiving attention from researchers and industry. This study clinically validates an automated caries scoring system for occlusal caries detection and classification, previously defined for an IOS system featuring fluorescence (TRIOS 4, 3Shape TRIOS A/S, Denmark). Four algorithms ( ALG1, ALG2, ALG3, ALG4 ) are assessed for the IOS; the first three are based only on fluorescence information, while ALG4 also takes into account the tooth color information. The diagnostic performance of these automated algorithms is compared with the diagnostic performance of the clinical visual examination, while histological assessment is used as reference. Additionally, possible differences between in vitro and in vivo diagnostic performance of the IOS system are investigated. The algorithms show comparable in vivo diagnostic performance to the visual examination with no significant difference in the area under the ROC curves ( p > 0.05 ). Only minor differences between their in vitro and in vivo diagnostic performance are noted but no significant differences in the area under the ROC curves, ( p > 0.05 ). This novel IOS system exhibits encouraging performance for clinical application on occlusal caries detection and classification. Different approaches can be investigated for possible optimization of the system.

Aim This systematic review and meta-analysis aimed to assess the diagnostic accuracy and reliability of commonly used caries detection methods for proximal caries diagnostics. Visual examination (VE), bitewing radiography (BWR), laser fluorescence (LF), and fibre-optic transillumination (FOTI) were considered in detail. Material and methods PRISMA guidelines for the reporting of systematic reviews and meta-analyses were applied. The mnemonic PIRDS (problem, index test, reference test, diagnostic and study type) concept was used to guide the literature search. Next, studies that met the inclusion criteria were stepwise selected and evaluated for their quality with a risk of bias (RoB) assessment tool. Studies with low/moderate bias and sufficient reporting were considered for meta-analysis. The pooled sensitivity (SE), specificity (SP), diagnostic odds ratio (DOR), and area under the ROC curve (AUC) were calculated. Results From 129 studies meeting the selection criteria, 31 in vitro studies and five clinical studies were finally included in the meta-analysis. The AUC values for in vitro VE amounted to 0.84 (caries detection) and 0.85 (dentin caries detection). BWR ranged in vitro from 0.55 to 0.82 (caries detection) and 0.81–0.92 (dentin caries detection). LF showed higher AUC values for overall caries detection (0.91) and dentin caries detection (0.83) than did other methods. Clinical data are limited. Conclusion The number of diagnostic studies with low/moderate RoB was found to be low and indicates a need for high-quality, well-designed caries diagnostic studies. Clinical relevance BWR and LF showed good diagnostic performance on proximal surfaces. However, because of the low number of includable clinical studies, these data should be interpreted with caution.

Background: Model alignment in cases of erosive tooth wear can be challenging, and no method has been reported to outweigh the others. Methods: Extracted human teeth were mounted on two models and scanned at different times, from 1 h to 2 weeks, with an intraoral scanner (3Shape TRIOS 4) before and after immersion in Monster® energy drink and tap water. The scans were superimposed (3Shape TRIOS Patient Monitoring, Version 2.2.3.3, 3Shape A/S, Copengagen, Denmark). Best fit, best-fit tooth comparison, reference best fit using fillings, and palatal rugae as reference points were used for alignment. Surface profile differences were calculated in a cross-section view. The nonparametric Bland–Altman and Kruskal–Wallis tests were used. Results: First, statistically significant differences were marked after 4 days of immersion. The measurements obtained after 2 weeks of immersion were statistically significantly different from the measurements obtained at the different time points until 1 week. No statistically significant differences (p < 0.05) were observed among the alignment methods at any time. Conclusion: In comparison to the best-fit model, both palatal rugae and fillings can be used. The best-fit tooth comparison method is a reliable option; however, it should be used with caution in cases of major surface loss.

Aim This systematic review and meta-analysis aimed to assess the diagnostic performance of commonly used methods for occlusal caries diagnostics, such as visual examination (VE), bitewing radiography (BW) and laser fluorescence (LF), in relation to their ability to detect (dentin) caries under clinical and laboratory conditions. Materials and methods A systematic search of the literature was performed to identify studies meeting the inclusion criteria using the PIRDS concept ( N  = 1090). A risk of bias (RoB) assessment tool was used for quality evaluation. Reports with low/moderate RoB, well-matching thresholds for index and reference tests and appropriate reporting were included in the meta-analysis ( N  = 37; 29 in vivo/8 in vitro). The pooled sensitivity (SE), specificity (SP), diagnostic odds ratio (DOR) and areas under ROC curves (AUCs) were computed. Results SP ranged from 0.50 (fibre-optic transillumination/caries detection level) to 0.97 (conventional BW/dentine detection level) in vitro. AUCs were typically higher for BW or LF than for VE. The highest AUC of 0.89 was observed for VE at the 1/3 dentin caries detection level; SE (0.70) was registered to be higher than SP (0.47) for VE at the caries detection level in vivo. Conclusion The number of included studies was found to be low. This underlines the need for high-quality caries diagnostic studies that further provide data in relation to multiple caries thresholds. Clinical relevance VE, BW and LF provide acceptable measures for their diagnostic performance on occlusal surfaces, but the results should be interpreted with caution due to the limited data in many categories.

Background: Early detection of secondary caries near dental restorations is essential to prevent further complications. This systematic review seeks to evaluate the sensitivity of fluorescence and near-infrared (NIR) imaging techniques for detecting secondary caries and to provide insight into their clinical utility. Methods: A comprehensive search strategy was used to select studies from seven databases, emphasizing diagnostic accuracy studies of secondary caries detection using fluorescence and NIR imaging techniques. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) instrument assessed bias risk and practicality. Two evaluators performed data extraction, screening, and quality assessment independently. Results: From 3110 initial recordings, nine studies were selected for full-text analysis. Wide variations in sensitivity (SE) and specificity (SP) values were reported across the studies. These studies exhibited variable SE and SP values, and the findings highlighted the importance of method selection based on clinical context. This systematic review underlines the potential for fluorescence and NIR imaging to detect secondary caries. However, results from different studies vary, indicating the need to consider additional variables such as restoration materials. Conclusions: Although these technologies exhibit potential for detecting caries, our research underscores the complex procedure of identifying secondary caries lesions. It is a continuous necessity for progress in dental diagnostics to promptly identify secondary caries lesions, particularly those in proximity to tooth-colored ones.

Abstract AimThe aim of this paper is to present recommendations from an international workshop which evaluated the methodology and reporting of caries diagnostic studies. As a unique feature, this type of studies is focused on caries lesion detection and assessment, and many of them are carried out in vitro, because of the possibility of histological validation of the whole caries spectrum. This feature is not well covered in the existing reporting STARD guideline within the EQUATOR Network.Participants and methodsAn international working group of 13 cariology researchers was formed. The STARD checklist was reviewed and modified for caries detection and diagnosis purposes, in a three-step process of evaluation, consensual modification, and delivery during three 2-day workshops over 18 months. Special attention was paid to reporting requirements of caries studies that solely focus on reliability.ResultsThe STARD checklist was modified in 14/30 items, with an emphasis on issues of sample selection (tooth selection in in vitro studies), blinding, and detailed reporting of results.ConclusionFollowing STARCARDDS (STAndard Reporting of CAries Detection and Diagnostic Studies) is expected to result in complete reporting of study design and methodology in future caries diagnosis and detection experiments both in vivo and in vitro, thus allowing for better comparability of studies and higher quality of systematic reviews.Clinical relevanceStandardization of caries diagnostic studies leads to a better comparability among future studies, both in vivo and in vitro.

Dental caries is a common chronic disease in children. Digital tools such as intraoral scanners (IOSs) may offer an efficient, scalable alternative to conventional visual examination for dental caries detection. IOSs are handheld devices that generate 3-dimensional (3D) models of the teeth and surrounding structures. Recent advances incorporating fluorescence technology into scanner hardware offer the potential for supporting dental caries detection. However, the performance of digital caries detection methods using 3D models that include both color and fluorescence in children's teeth remains unknown. This study aimed to assess the diagnostic agreement between visual examination and on-screen assessment of 3D models generated by an IOS in color and supplemented with fluorescence for caries detection in primary teeth. Children participating in a clinical trial (n=216, mean age 5.6, SD 0.4 y) underwent visual examination using the International Caries Detection and Assessment System (ICDAS) and intraoral scanning using the TRIOS 4 IOS. Four trained registered dental practitioners independently assessed each participant's 3D models in color and then supplemented with fluorescence, using a previously validated ICDAS index modified for on-screen assessments of 3D models. All 3D models were assessed again after 4 weeks. The time taken for intraoral scanning and on-screen assessment was recorded. Multilevel logistic regression was used to estimate and compare the likelihood of detecting caries between methods, and Bland-Altman plots were used to visualize agreement. Analyses were performed at the initial (ICDAS ≥01), moderate (ICDAS ≥03), and extensive (ICDAS ≥05) dental caries thresholds. Intraclass correlation coefficient (ICC) estimated method agreement and examiner reliability. Of 219 children enrolled, 216 completed dental assessments. A total of 9470 visible primary tooth surfaces were included in the analysis. The average time taken for on-screen assessment of each 3D model (color with fluorescence) was 3.5 (SD 2.3) minutes. The likelihood of detecting caries using color assessment of 3D models was similar to visual examination at all disease thresholds: initial (odds ratio [OR] 1.1, 95% CI 1.0-1.3), moderate (OR 0.9, 95% CI 0.7-1.1), and extensive (OR 1.0, 95% CI 0.7-1.3). When color assessments were supplemented with fluorescence, the likelihood of detecting caries was 30% higher at the initial threshold relative to visual examination (OR 1.3, 95% CI 1.1-1.5) and similar at the moderate (OR 0.9, 95% CI 0.7-1.1) and extensive thresholds (OR 0.9, 95% CI 0.7-1.3). Bland-Altman plots showed a high level of agreement at both moderate and extensive thresholds. Agreement between methods was high (ICC 0.9, 95% CI 0.9-1.0). Intra- and inter-examiner reliability using intraoral scans ranged from good to excellent (ICC 0.8-1.0). On-screen assessment of 3D models in color demonstrated the highest agreement with visual examination for caries detection across all disease thresholds.

Digital methods that enable early caries identification can streamline data collection in research and optimize dental examinations for young children. Intraoral scanners are devices used for creating 3D models of teeth in dentistry and are being rapidly adopted into clinical workflows. Integrating fluorescence technology into scanner hardware can support early caries detection. However, the performance of caries detection methods using 3D models featuring color and fluorescence in primary teeth is unknown. This study aims to assess the diagnostic agreement between visual examination (VE), on-screen assessment of 3D models in approximate natural colors with and without fluorescence, and application of an automated caries scoring system to the 3D models with fluorescence for caries detection in primary teeth. The study sample will be drawn from eligible participants in a randomized controlled trial at the Royal Children's Hospital, Melbourne, Australia, where a dental assessment was conducted, including VE using the International Caries Detection and Assessment System (ICDAS) and intraoral scan using the TRIOS 4 (3Shape TRIOS A/S). Participant clinical records will be collected, and all records meeting eligibility criteria will be subject to an on-screen assessment of 3D models by 4 dental practitioners. First, all primary tooth surfaces will be examined for caries based on 3D geometry and color, using a merged ICDAS index. Second, the on-screen assessment of 3D models will include fluorescence, where caries will be classified using a merged ICDAS index that has been modified to incorporate fluorescence criteria. After 4 weeks, all examiners will repeat the on-screen assessment for all 3D models. Finally, an automated caries scoring system will be used to classify caries on primary occlusal surfaces. The agreement in the total number of caries detected per person between methods will be assessed using a Bland-Altman analysis and intraclass correlation coefficients. At a tooth surface level, agreement between methods will be estimated using multilevel models to account for the clustering of dental data. Automated caries scoring of 3D models was completed as of October 2023, with the publication of results expected by July 2024. On-screen assessment has commenced, with the expected completion of scoring and data analysis by March 2024. Results will be disseminated by the end of 2024. The study outcomes may inform new practices that use digital models to facilitate dental assessments. Novel approaches that enable remote dental examination without compromising the accuracy of VE have wide applications in the research environment, clinical practice, and the provision of teledentistry. Australian New Zealand Clinical Trials Registry ACTRN12622001237774; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=384632. DERR1-10.2196/51578.