scholarly journals Caries Diagnosis in Dental Practices: Results From Dentists in a Brazilian Community

2019 ◽  
Vol 44 (1) ◽  
pp. E23-E31 ◽  
Author(s):  
EPS Tagliaferro ◽  
A Valsecki Junior ◽  
FL Rosell ◽  
SRC Silva ◽  
JL Riley ◽  
...  
Keyword(s):  
Dental Caries ◽  
Diagnostic Methods ◽  
Laser Fluorescence ◽  
Dental School ◽  
Research Network ◽  
Advanced Degree ◽  
Occlusal Caries ◽  
Caries Diagnosis ◽  
Air Jet ◽  
School Graduation

SUMMARY The aim of this study was to assess practices related to diagnosis of dental caries among dentists (n=217) from Araraquara, São Paulo State, Brazil. Data on sociodemographic information and practitioner characteristics were collected using a pretested questionnaire, and data on practices related to caries diagnosis were gathered by using a translated and culturally adapted questionnaire from the US National Dental Practice-Based Research Network. Descriptive statistics and regression analyses were used for data analysis. Respondents reported using in most of their patients radiographs (Rx) to diagnose proximal caries (59%), explorer (Ex) for the diagnosis of occlusal caries (64%) and on the margins of existing restorations (79%), as well as air jet (AJ) with drying (92%). Magnification (M) (25%), fiber optic transillumination (FOTI; 14%), and laser fluorescence (LF) (3%) were used in the minority of patients. Regression analysis revealed that the following dentists' characteristics were significantly associated (p<0.05) with the use of diagnostic methods on a greater percentage of their patients: advanced degree (Rx, FOTI), higher percentage of patients with individualized caries prevention (Rx, FOTI, M), more years since dental school graduation (Ex, M), and work in an exclusively private practice model (LF). In conclusion, most Brazilian dentists from Araraquara reported they most commonly use visual, tactile, and radiographic imaging for the diagnosis of dental caries. Some dentists' characteristics, such as time from dental school graduation and having a postgraduation course, were associated with the use of certain diagnostic methods.

Reliability and validity issues of laser fluorescence measurements in occlusal caries diagnosis

2002 ◽  
Vol 30 (4) ◽  
pp. 129-134 ◽  
Author(s):  
Hanna M Alwas-Danowska ◽  
Alphons J.M Plasschaert ◽  
Stanislaw Suliborski ◽  
Emiel H Verdonschot
Keyword(s):  
Reliability And Validity ◽  
Laser Fluorescence ◽  
Occlusal Caries ◽  
Caries Diagnosis ◽  
Fluorescence Measurements

scholarly journals The Effect of Distance and Tooth Structure on Laser Fluorescence Caries Detection

2012 ◽  
Vol 37 (2) ◽  
pp. 150-160 ◽  
Author(s):  
K Markowitz ◽  
RM Stenvall ◽  
M Graye
Keyword(s):  
Clinical Relevance ◽  
Laser Fluorescence ◽  
Caries Detection ◽  
Carious Lesion ◽  
Occlusal Caries ◽  
Caries Diagnosis ◽  
Tooth Structure

Clinical RelevanceDevices used to aid occlusal caries diagnosis are supposed to detect small lesions deep in the pit and fissure system. In detecting small occlusal caries, distance and tooth structure may separate the instrument and the carious lesion. In this study distance and tooth structure were found to reduce the ability of the DIAGNOdent to detect caries.

scholarly journals Comparison of novel and established caries diagnostic methods: a clinical study on occlusal surfaces

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Friederike Litzenburger ◽  
Gerrit Schäfer ◽  
Reinhard Hickel ◽  
Jan Kühnisch ◽  
Katrin Heck
Keyword(s):  
Diagnostic Performance ◽  
Diagnostic Methods ◽  
Laser Fluorescence ◽  
The Other ◽  
Caries Detection ◽  
Reference Standard ◽  
Occlusal Caries ◽  
Enamel Caries ◽  
Dentin Caries ◽  
Occlusal Caries Detection

Abstract Background The purpose of this prospective clinical diagnostic study with validation was to compare the diagnostic accuracy of near-infrared transillumination (NIRT), laser fluorescence measurement (LF), alternating current impedance spectroscopy (ACIS) and their combinations as adjunct methods to visual examination (VE) for occlusal caries detection using a hybrid reference standard. Methods Ninety-six first and second non-cavitated permanent molars from 76 individuals (mean age 24.2) were investigated using (VE) (ICDAS) and bitewing radiography (BWR), as well as NIRT, LF and ACIS. The findings of BWR and NIRT were evaluated by two examiners while the other examinations were conducted by one calibrated dentist. The hybrid reference standard consisted of non-operative validation based on the results of VE and BWR and operative validation. Statistical analysis included cross-tabulations, calculation of sensitivity, specificity and area under the receiver operating characteristic curve at three diagnostic thresholds: caries in general, enamel caries and dentin caries. Results NIRT, LF and ACIS exhibited high sensitivity for caries in general [1.00 (1.00–1.00), 0.77 (0.65–0.88), 0.75 (0.63–0.87)) and for dentin caries (0.97 (0.91–1.03), 0.76 (0.76–0.90), 0.64 (0.47–0.80)]. Sensitivity values for enamel caries were weak (0.21, 0.11, 0.37). Specificity values did not fall below 0.65 (NIRT) for all categories and methods, except for NIRT at the caries detection threshold (0.27). A combination of LF and ACIS with VE improved the diagnostic performance at the overall and the enamel caries threshold. The other methods showed fair to excellent discrimination at the overall caries threshold (NIRT 0.64, LF 0.89 and ACIS 0.86) and acceptable discrimination at the dentin caries threshold (NIRT 0.82, LF 0.81 and ACIS 0.79). AUROC for enamel caries exhibited the weakest discrimination. Accuracy was 65.6% for VE, 69.8% for BWR, 50.0% for NIRT, 53.1% for LF and 74.0% for ACIS. Reliability assessment for BWR and NIRT showed at least substantial agreements for all analyses. Conclusions The methods, NIRT, LF and ACIS, revealed different potential but no impeccable performance for occlusal caries detection. All are suitable instruments to detect hidden carious lesion in dentin. As auxiliaries to VE, LF and ACIS showed an increase in diagnostic performance.

scholarly journals Occlusal caries diagnosis in permanent teeth: an in vitro study

2005 ◽  
Vol 19 (4) ◽  
pp. 243-248 ◽  
Author(s):  
Gisele Angnes ◽  
Vivian Angnes ◽  
Rosa Helena Miranda Grande ◽  
Márcio Battistella ◽  
Alessandro Dourado Loguercio ◽  
...  
Keyword(s):  
Visual System ◽  
Roc Curve ◽  
In Vitro Study ◽  
Laser Fluorescence ◽  
Permanent Teeth ◽  
Occlusal Caries ◽  
Caries Diagnosis ◽  
Occlusal Surfaces ◽  
Sensitivity Specificity

The reduction in caries prevalence has not occurred uniformly for all dental surfaces. As the occlusal surfaces are still the most likely sites for the development of lesions, new methods of diagnosis are still being evaluated. This study compared a laser fluorescence (LF) system (DIAGNOdent) with the Ekstrand’s visual system for in vitro detection of occlusal caries. A total of 57 extracted molars with macroscopically intact occlusal surfaces were selected. Two-examiners assessed 110 sites by visual inspection (VI) and LF. After ten days from the first measurement, all teeth were re-evaluated through the same methods by each examiner. Caries extension was histologically assessed (X 40). The methods were compared by means of sensitivity, specificity, intra- and inter-examiner reproducibility and area under the ROC curve. The kappa’s test showed good intra- and inter-examiner reproducibility for both methods. VI and LF showed similar sensitivities for both examiners, however, VI showed higher specificities than LF. The overall analysis, as demonstrated by the area under the ROC curve, showed that VI had a better performance than the LF device. It was concluded that the Ekstrand’s visual system is more reliable than the LF device. LF should be considered only as an adjuvant for occlusal caries diagnosis.

scholarly journals Caries Diagnosis using a Laser Fluorescence System. Observation of Autofluorescence of Dental Caries.

2003 ◽  
Vol 22 (1) ◽  
pp. 56-65 ◽  
Author(s):  
Yoshimi SHIGETANI ◽  
Akira OKAMOTO ◽  
Neamat ABU-BAKR ◽  
Keita TANABE ◽  
Suginari KONDO ◽  
...  
Keyword(s):  
Dental Caries ◽  
Laser Fluorescence ◽  
Caries Diagnosis

scholarly journals Methods Used by Dental Practice-based Research Network (DPBRN) Dentists to Diagnose Dental Caries

2011 ◽  
Vol 36 (1) ◽  
pp. 2-11 ◽  
Author(s):  
V. V. Gordan ◽  
J. L. Riley ◽  
R. M. Carvalho ◽  
J. Snyder ◽  
J. L. Sanderson ◽  
...  
Keyword(s):  
Dental Caries ◽  
Clinical Relevance ◽  
Diagnostic Methods ◽  
Research Network ◽  
Dental Practice ◽  
Practice Based Research

Clinical RelevanceDentists' use of specific diagnostic methods vary substantially. Overall, the dental explorer and radiographs are still the main diagnostic methods to diagnose dental caries.

scholarly journals Proof-of-Concept Study on an Automatic Computational System in Detecting and Classifying Occlusal Caries Lesions from Smartphone Color Images of Unrestored Extracted Teeth

Diagnostics ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1136
Author(s):  
Duc Long Duong ◽  
Quoc Duy Nam Nguyen ◽  
Minh Son Tong ◽  
Manh Tuan Vu ◽  
Joseph Dy Lim ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Dental Caries ◽  
Sensitivity And Specificity ◽  
Color Images ◽  
Caries Detection ◽  
Support Vector ◽  
Proof Of Concept ◽  
Computational System ◽  
Occlusal Caries ◽  
Concept Study

Dental caries has been considered the heaviest worldwide oral health burden affecting a significant proportion of the population. To prevent dental caries, an appropriate and accurate early detection method is demanded. This proof-of-concept study aims to develop a two-stage computational system that can detect early occlusal caries from smartphone color images of unrestored extracted teeth according to modified International Caries Detection and Assessment System (ICDAS) criteria (3 classes: Code 0; Code 1-2; Code 3-6): in the first stage, carious lesion areas were identified and extracted from sound tooth regions. Then, five characteristic features of these areas were intendedly selected and calculated to be inputted into the classification stage, where five classifiers (Support Vector Machine, Random Forests, K-Nearest Neighbors, Gradient Boosted Tree, Logistic Regression) were evaluated to determine the best one among them. On a set of 587 smartphone images of extracted teeth, our system achieved accuracy, sensitivity, and specificity that were 87.39%, 89.88%, and 68.86% in the detection stage when compared to modified visual and image-based ICDAS criteria. For the classification stage, the Support Vector Machine model was recorded as the best model with accuracy, sensitivity, and specificity at 88.76%, 92.31%, and 85.21%. As the first step in developing the technology, our present findings confirm the feasibility of using smartphone color images to employ Artificial Intelligence algorithms in caries detection. To improve the performance of the proposed system, there is a need for further development in both in vitro and in vivo modeling. Besides that, an applicable system for accurately taking intra-oral images that can capture entire dental arches including the occlusal surfaces of premolars and molars also needs to be developed.

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