Effect of pit and fissure sealants on caries detection by a fluorescent camera system

Fluorescence devices for the detection of dental caries

BACKGROUND

Caries is one of the most prevalent and preventable conditions worldwide. If identified early enough then non-invasive techniques can be applied, and therefore this review focusses on early caries involving the enamel surface of the tooth. The cornerstone of caries detection is a visual and tactile dental examination, however alternative methods of detection are available, and these include fluorescence-based devices. There are three categories of fluorescence-based device each primarily defined by the different wavelengths they exploit; we have labelled these groups as red, blue, and green fluorescence. These devices could support the visual examination for the detection and diagnosis of caries at an early stage of decay.

OBJECTIVES

Our primary objectives were to estimate the diagnostic test accuracy of fluorescence-based devices for the detection and diagnosis of enamel caries in children or adults. We planned to investigate the following potential sources of heterogeneity: tooth surface (occlusal, proximal, smooth surface or adjacent to a restoration); single point measurement devices versus imaging or surface assessment devices; and the prevalence of more severe disease in each study sample, at the level of caries into dentine.

SEARCH METHODS

Cochrane Oral Health's Information Specialist undertook a search of the following databases: MEDLINE Ovid (1946 to 30 May 2019); Embase Ovid (1980 to 30 May 2019); US National Institutes of Health Ongoing Trials Register (ClinicalTrials.gov, to 30 May 2019); and the World Health Organization International Clinical Trials Registry Platform (to 30 May 2019). We studied reference lists as well as published systematic review articles.

SELECTION CRITERIA

We included diagnostic accuracy study designs that compared a fluorescence-based device with a reference standard. This included prospective studies that evaluated the diagnostic accuracy of single index tests and studies that directly compared two or more index tests. Studies that explicitly recruited participants with caries into dentine or frank cavitation were excluded.

DATA COLLECTION AND ANALYSIS

Two review authors extracted data independently using a piloted study data extraction form based on the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). Sensitivity and specificity with 95% confidence intervals (CIs) were reported for each study. This information has been displayed as coupled forest plots and summary receiver operating characteristic (SROC) plots, displaying the sensitivity-specificity points for each study. We estimated diagnostic accuracy using hierarchical summary receiver operating characteristic (HSROC) methods. We reported sensitivities at fixed values of specificity (median 0.78, upper quartile 0.90).

MAIN RESULTS

We included a total of 133 studies, 55 did not report data in the 2 x 2 format and could not be included in the meta-analysis. 79 studies which provided 114 datasets and evaluated 21,283 tooth surfaces were included in the meta-analysis. There was a high risk of bias for the participant selection domain. The index test, reference standard, and flow and timing domains all showed a high proportion of studies to be at low risk of bias. Concerns regarding the applicability of the evidence were high or unclear for all domains, the highest proportion being seen in participant selection. Selective participant recruitment, poorly defined diagnostic thresholds, and in vitro studies being non-generalisable to the clinical scenario of a routine dental examination were the main reasons for these findings. The dominance of in vitro studies also means that the information on how the results of these devices are used to support diagnosis, as opposed to pure detection, was extremely limited. There was substantial variability in the results which could not be explained by the different devices or dentition or other sources of heterogeneity that we investigated. The diagnostic odds ratio (DOR) was 14.12 (95% CI 11.17 to 17.84). The estimated sensitivity, at a fixed median specificity of 0.78, was 0.70 (95% CI 0.64 to 0.75). In a hypothetical cohort of 1000 tooth sites or surfaces, with a prevalence of enamel caries of 57%, obtained from the included studies, the estimated sensitivity of 0.70 and specificity of 0.78 would result in 171 missed tooth sites or surfaces with enamel caries (false negatives) and 95 incorrectly classed as having early caries (false positives). We used meta-regression to compare the accuracy of the different devices for red fluorescence (84 datasets, 14,514 tooth sites), blue fluorescence (21 datasets, 3429 tooth sites), and green fluorescence (9 datasets, 3340 tooth sites) devices. Initially, we allowed threshold, shape, and accuracy to vary according to device type by including covariates in the model. Allowing consistency of shape, removal of the covariates for accuracy had only a negligible effect (Chi2 = 3.91, degrees of freedom (df) = 2, P = 0.14). Despite the relatively large volume of evidence we rated the certainty of the evidence as low, downgraded two levels in total, for risk of bias due to limitations in the design and conduct of the included studies, indirectness arising from the high number of in vitro studies, and inconsistency due to the substantial variability of results.

AUTHORS' CONCLUSIONS

There is considerable variation in the performance of these fluorescence-based devices that could not be explained by the different wavelengths of the devices assessed, participant, or study characteristics. Blue and green fluorescence-based devices appeared to outperform red fluorescence-based devices but this difference was not supported by the results of a formal statistical comparison. The evidence base was considerable, but we were only able to include 79 studies out of 133 in the meta-analysis as estimates of sensitivity or specificity values or both could not be extracted or derived. In terms of applicability, any future studies should be carried out in a clinical setting, where difficulties of caries assessment within the oral cavity include plaque, staining, and restorations. Other considerations include the potential of fluorescence devices to be used in combination with other technologies and comparative diagnostic accuracy studies.

Effect of Er:YAG laser irradiation on deciduous enamel roughness and bacterial adhesion: An in vitro study

Laser irradiation has been proposed as a preventive method against dental caries since it is capable to inhibit enamel demineralization by reducing carbonate and modifying organic matter, yet it can produce significant morphological changes. The purpose of this study was to evaluate the influence of Er:YAG laser irradiation on superficial roughness of deciduous dental enamel and bacterial adhesion. Fifty-four samples of deciduous enamel were divided into three groups (n = 18 each). G1_control (nonirradiated); G2_100 (7.5 J/cm² ) and G3_100 (12.7 J/cm² ) were irradiated with Er:YAG laser at 7.5 and 12.7 J/cm² , respectively, under water irrigation. Surface roughness was measured before and after irradiation using a profilometer. Afterwards, six samples per group were used to measure bacterial growth by XTT cell viability assay. Adhered bacteria were observed using confocal laser scanning microscopy (CLSM) and a scanning electron microscopy (SEM). Paired t-, one-way analysis of variance (ANOVA), Kruskal-Wallis and pairwise Mann-Whitney U tests were performed to analyze statistical differences (p < .05). Before treatment, samples showed homogenous surface roughness, and after Er:YAG laser irradiation, the surfaces showed a significant increase in roughness values (p < .05). G3_100 (12.7 J/cm² ) showed the highest amount of Streptococcus mutans adhered (p < .05). The increase in the roughness of the tooth enamel surfaces was proportional to the energy density used; the increase in surface roughness caused by laser irradiation did not augment the adhesion of Streptococcus sanguinis; only the use of the energy density of 12.7 J/cm² favored significantly the adhesion of S. mutans.

Algorithmic analysis for dental caries detection using an adaptive neural network architecture

Objectives

AI techniques have lifelong impact in biomedics and widely accepted outcomes. The sole objective of the study is to evaluate accurate detection of caries using feature extraction and classification of the dental images along with amalgamation Adaptive Dragonfly algorithm (DA) algorithm and Neural Network (NN) classifier.

Materials and methods

Here proposed caries detection model is designed for detecting the tooth cavities in an accurate manner. This methodology has two main phases; feature extraction and classification. In all total 120 images database is split into three sets, randomly for evaluating the performance. Further, this categorization of the test cases aids in ensuring the enhancement of the performance. In each of the test cases, there are 40 caries images the investigation in the performance of the proposed caries detection model was done in terms of accuracy, sensitivity, specificity, and precision, FPR, FNR, NPV, FDR, F1Score and MCC.

Results

Here MPCA with Nonlinear Programming and Adaptive DA, the proposed model is termed as MNP-ADA. The performance of the proposed MPCA-ADA model is evaluated by comparing it over the other existing feature extraction models. MPCA–ADA over the conventional classifier models like PCA-ADA, LDA-ADA and ICA-ADA in terms of performance parameters and MCC for all the test types and have superior results than the existing ones.

Conclusion

The research work emphasizes the prospective efficacy of IP and NN algorithms for the detection and diagnosis of dental caries. A novel and improved model shows substantially worthy performance in distinguishing dental caries using image processing techniques.

Adhesion of Streptococcus mutans and Streptococcus sanguinis on Er:YAG Laser-Irradiated Dental Enamel: Effect of Surface Roughness

Objective: To determine surface roughness caused by Er:YAG laser irradiation and its effect on the increase in bacterial adhesion. Background: Er:YAG laser was proposed as a strategic device to reduce caries by its ability to generate chemical and structural changes in tooth enamel; in turn, it produces undesirable effects on the tooth surface that could increase its roughness and allow a greater accumulation of microorganisms. Methods: Eighty-four samples of human enamel were divided into seven groups (n = 12): G1_control (no laser irradiation); G2_100/H₂O, G3_200/H₂O, and G4_300/H₂O were irradiated with Er:YAG laser (12.7, 25.5, and 38.2 J/cm², respectively) under water irrigation. In addition, G5_100, G6_200, and G7_300 were irradiated with the energy densities described above and no water irrigation. Surface roughness measurements were recorded before and after treatment using a profilometer. Afterward, three samples per group were incubated in a microorganism suspension for the tetrazolium salt (XTT) assay. Biofilm morphology was observed using scanning electron microscopy and confocal laser scanning microscope. One-way analysis of variance and t-tests were performed for statistical analysis (p < 0.05). Results: There were no statistically significant differences in roughness values in the G5_100 group before and after treatment, but there were statistically significant differences observed in the other groups evaluated (p < 0.05). No significant differences in adhesion of both strains were detected in irradiated groups compared with G1_control. Conclusions: The increase in roughness on dental enamel surfaces was proportional to the irradiation conditions. However, the increase in surface roughness caused by Er:YAG laser irradiation did not affect Streptococcus mutans and S. sanguinis adhesion.

Detection of Caries Around Resin-Modified Glass Ionomer and Compomer Restorations Using Four Different Modalities In Vitro

The aim of this study was to evaluate the ability of visual examination (International Caries Detection and Assessment System—ICDAS II), light-emitting diodes (LED) fluorescence (SPECTRA), laser fluorescence (DIAGNODent, DD), photothermal radiometry and modulated luminescence (PTR-LUM, The Canary System, CS) to detect natural decay beneath resin-modified glass ionomer (RMGIC) and compomer restorations in vitro. Twenty-seven extracted human molars and premolars, consisting of 2 control teeth, 10 visually healthy/sound and 15 teeth with natural cavitated lesions, were selected. For the carious teeth, caries was removed leaving some carious tissue on one wall of the preparation. For the sound teeth, 3 mm deep cavity preparations were made. All cavities were restored with RMGIC or compomer restorative materials. Sixty-eight sites (4 sites on sound unrestored teeth, 21 sound sites and 43 carious sites with restorations) were selected. CS and DD triplicate measurements were done at 2, 1.5, 0.5, and 0 mm away from the margin of the restoration (MOR). SPECTRA images were taken, and two dentists provided ICDAS II scoring for the restored surfaces. The SPECTRA data and images were inconclusive due to signal interference from the restorations. Visual examinations of the restored tooth surfaces were able to identify 5 of the 15 teeth with caries. In these situations, the teeth were ranked as having ICDAS II 1 or 2 rankings, but they could not identify the location of the caries or depth of the lesion. CS and DD were able to differentiate between sound and carious tissue at the MOR, but larger variation in measurement, and poorer accuracy, was observed for DD. It was concluded that the CS has the potential to detect secondary caries around RMGIC and compomer restorations more accurately than the other modalities used in this study.

Influence of 2 caries-detecting devices on clinical decision making and lesion depth for suspicious occlusal lesions: A randomized trial from The National Dental Practice-Based Research Network

BACKGROUND

A suspicious occlusal carious lesion (SOCL) can be defined as a lesion with no cavitation and no radiographic radiolucency but for which caries is suspected. The authors evaluated whether using a device changed the percentage of SOCLs that were opened surgically and, among those SOCLs that were opened, the proportion that had penetrated into dentin.

METHODS

Eighty-two dentists participated. In phase 1 of the study, dentists identified approximately 20 SOCLs, obtained patient consent, and recorded information about the lesion, treatment or treatments, and depth, if opened. Dentists were then randomly assigned into 1 of 3 groups: no device, DIAGNOdent (KaVo), and Spectra (Air Techniques). In phase 2, dentists enrolled approximately 20 additional patients and recorded the same phase 1 information while using the assigned device to help make their treatment decisions. A mixed-model logistic regression was used to determine any differences after randomization in the proportion of lesions opened and, if opened, the proportion of lesions that penetrated into dentin.

RESULTS

A total of 1,500 SOCLs were enrolled in each phase. No statistically significant difference was found in the change in proportion of lesions receiving invasive treatment from phase 1 to phase 2 across the 3 groups (P = .33) or in the change in proportion of percentage of opened lesions that extended into dentin (P = .31).

CONCLUSION

Caries-detecting devices in the study did not change substantially dentists' decisions to intervene or the accuracy of the intervention decision in predicting lesion penetration into dentin.

PRACTICAL IMPLICATIONS

The caries-detecting devices tested may not improve dentists' clinical decision making for SOCLs.

In Vitro Detection of Caries Around Amalgam Restorations Using Four Different Modalities

Objective:

The aim of this study was to evaluate the ability of PTR-LUM (The Canary System, CS), laser fluorescence (DIAGNOdent, DD), LED fluorescence (Spectra), and visual inspection (ICDAS II) to detect natural decay around bonded amalgam restorations in vitro.

Methods:

Seventeen extracted human molars and premolars, consisting of visually healthy (n=5) and natural cavitated (n=12) teeth were selected. For the carious teeth, caries was removed leaving some decayed tissue on the floor and or wall of the preparation. For sound teeth, 3 mm. deep cavity preparations were made and teeth were restored with bonded-amalgam restorations. Thirty-six sites (13 sound sites; 23 carious sites) were selected. CS and DD scans were performed in triplicate at 2, 1.5, 0.5, and 0 mm away from the margin of the restoration (MOR). Spectra images were captured for the entire surface, and dentists blinded to the samples provided ICDAS II scoring.

Results:

Canary Numbers (Mean±SE) for healthy and carious sites at 2, 1.5, 0.5, and 0 mm from the MOR ranged from 12.9±0.9 to 15.4±0.9 and 56.1±4.0 to 56.3±2.0, respectively. DD peak values for healthy and carious sites ranged from 4.7±0.5 to 13.5±2.99, and 16.7±3.7 to 24.5±4.4, respectively. For CS and DD, sensitivity/specificity for sites at 2.0, 1.5, 0.5, 0 mm ranged from 0.95-1.0/0.85-1.0, and 0.45-0.74/0.54-1.0, respectively. For ICDAS II, sensitivity and specificity were 1.0 and 0.17, respectively. For Spectra, data and images were inconclusive due to signal intereference from the amalgam restoration.

Conclusions:

Using this in-vitro model, CS and DD were able to differentiate between sound and carious tissue at the MOR, but larger variation, less reliability, and poorer accuracy was observed for DD. Therefore, CS has the potential to detect secondary caries around amalgam restorations more accurately than the other investigated modalities.

Detecting Short-Term Changes in the Activity of Caries Lesions with the Aid of New Technologies

This paper discusses the use of new technologies for the assessment of caries and more in particular changes in caries activity. Over the past decades, we have seen a shift from restorative treatment caries to a prevention-driven approach. Also there is a need for shorter and less expensive caries clinical trials. These demand earlier detection of lesions and the monitoring of lesion changes longitudinally in time, which has led to the development of new technologies to aid clinical visual examination. Also clinical visual inspection indices have been refined to fit this purpose. There is a constant flow of technologies emerging and disappearing. This review discusses the merits of recent developments regarding their respective uses for research purposes in testing new caries prevention strategies as well as in clinical caries management in dental private practice. Which technique to choose highly depends on the needed resolution of information.