Laser induced fluorescence with 2-D Hilbert transform edge detection algorithm and 3D fluorescence images for white spot early recognition

Non-invasive caries detection and delineation via novel laser-induced fluorescence with hyperspectral imaging

Carious is a global chronic disease; 2 billion people and 520 million children suffer from permanent and primary teeth caries respectively. Early caries detection via precise, non-invasive, non-ionizing radiation is highly appreciated. Carious deteriorate the chemical structure of sound tooth tissues, with variation in its optical properties. In this study, customized laser-induced fluorescence system consists of non-ionizing laser light source and hyperspectral camera was developed for early caries detection. Tested tooth sample was illuminated with laser source of 385 nm and 5 mW power. The emitted spectrum signature for main tooth elements including enamel, dentin, stain, and caries were captured. Logarithmic scale of spectrum signature was applied in an attempt to enhance system sensitivity to fluorescent signal. Fluorescence signature at 500 nm secured the maximum fluorescence intensity difference for different tooth elements. Consequently 2D hyperspectral image at 500 nm was constructed. Enhanced 2D image was accomplished via nonlinear filter to enhance contrast. Segmentation via K mean clustering was adopted for precise caries delineation. This narrative, facile, non-invasive, non-ionizing technique experienced precise and accurate delineation of different caries stages (normal, moderate, and severe).

Fluorescence spectrometry based chromaticity mapping, characterization, and quantitative assessment of dental caries

PURPOSE

Dental caries detection, especially the accurate detection of early caries, facilitates prompt interventions. It is reasonably common to use fluorescence imaging for classification and evaluation of caries, but lacks a quantitative, precise and easy-to-use characterization for practical applications. In this study a quantitative approach for caries stage detection by correlating caries spectral and chromatic features was examined.

METHODS

A 405 nm LED light source was used as the excitation source. A hyperspectral imaging camera is employed to collect 336 spectral data of different caries stages. Four critical intervals for different stages of caries were extracted by fluorescence spectral features. The mapping relationship between caries spectral and chromatic features was established by Fast Formula Fitting (FFF) and Neural Network Fitting (NNF) methods.

RESULTS

The 470-780 nm spectral power distribution was proved to be the best matching color waveband guiding the selection of filters in future instrument development. The correlation coefficients for the two fitting methods were 0.990 and 0.999, respectively. Both methods achieved caries stage prediction at the pixel level with high accuracy using color information. The visualization region in the chromaticity diagram was created.

CONCLUSIONS

This quantitative method enables accurate prediction of caries on the entire tooth surface and facilitates the development of portable and low-cost caries detection instruments.

Automated caries detection in vivo using a 3D intraoral scanner

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 (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p>0.05$$\end{document}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, (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p>0.05$$\end{document}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.

Intraoral scanner featuring transillumination for proximal caries detection. An in vitro validation study on permanent posterior teeth

OBJECTIVES

To assess the validity of an intraoral scanner system featuring near-infrared (NIR) transillumination to aid the detection of proximal caries lesions, and to compare the diagnostic performance of this system with that of conventional caries detection methods and with that of an intraoral camera featuring NIR transillumination (DIAGNOcam).

METHODS

Ninety-five permanent posterior teeth were examined using a prototype tip functioning with TRIOS 4 intraoral scanner system (3Shape TRIOS A/S, Denmark) and emitting NIR light, DIAGNOcam, and visual and radiographic examination employing ICDAS criteria. One or two approximal surfaces per tooth, sound or with caries lesions at different stages, were examined (N₁=158). Histological assessment was used as the reference standard.

RESULTS

All methods showed excellent intra-examiner reliability (κ_intra ≥0.80). Two independent examiners assessed the NIR images obtained with both devices. The first examiner, who obtained and assessed the images, showed improved diagnostic performance than the second examiner, who only had access to the images. The inter-examiner agreement between the two examiners assessing the NIR images was substantial (κ_inter 0.57-0.72). The intraoral scanner and DIAGNOcam showed similar diagnostic performance. Regarding initial caries lesions, the NIR image assessment resulted in equal or improved sensitivity (SE 0.50-0.89) compared to radiographic assessment (SE 0.49-0.51) and higher than visual examination (SE 0.28-0.39). Radiographic and NIR image assessment resulted in similar SE in detecting moderate-extensive dentin caries lesions (SE 0.59-0.70), while visual examination showed an inferior value (SE 0.30).

CONCLUSIONS

The intraoral scanner system featuring NIR transillumination and DIAGNOcam showed an overall good diagnostic performance. The conventional caries detection methods showed inferior sensitivity at initial caries lesion stages.

CLINICAL SIGNIFICANCE

Considering the promising diagnostic performance of the intraoral scanner featuring transillumination and the advantages offered by combining the NIR images with the 3D models of the teeth, this system has the potential to contribute towards more reliable caries detection and monitoring in clinical practice without the use of ionizing radiation.