PubMed Health⌕ Search
Home/Archive/PubMed

PubMed · 13678458

Photon undulatory non-linear conversion diagnostic method for caries detection: a pilot study.

G Kesler·V Masychev·A Sokolovsky·M Alexandrov·A Kesler·R Koren
View original source ↗Export metadata ↓

Abstract

OBJECTIVE: The objective of this study was to evaluate a new optical method - photon undulatory non-linear conversion (PNC)--for use in different stages of caries detection. BACKGROUND DATA: Caries should be considered an infectious disease managed by risk assessment, early detection, and preventive therapies, rather than simply "drilling and filling." MATERIAL AND METHODS: Fluorescence emission spectroscopy was performed in vitro on 90 extracted teeth, with intact occlusal surfaces. This system differs from the basic Diagnodent unit in its ability to distinguish between different tissue components with respect to their spectrums. Histological analysis served as the gold standard for verification. The teeth sections correspond to the specific point with the highest reading of the detector. The system was compared to visual inspection, probing, and x-ray methods. The system tested (helium-neon [He-Ne], lambda = 633 nm) has a fiber optic device that delivers radiation to the tooth and a spectrophotometer device that detects bacterial porphyrins fluorescence, allowing detection of caries, fillings, and calculus by simultaneous measurement of backscattering and fluorescence intensity. RESULTS: The system tested provides quantitatively reproducible measurements and detection even through sound enamel of more than 1 mm in thickness. CONCLUSION: The PNC method detects different stages of caries lesions in real time, and it exceeds x-rays in sensitivity, without any ionizing radiation. Preliminary results showed a high potential of using the PNC method in clinical practice (98% accuracy) in comparison to the other methods.

Explore related subjects

Dental CariesDental Caries Activity TestsHumansLasersOptics and PhotonicsPilot ProjectsSpectrometry, FluorescenceJournal Article

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

G Kesler, V Masychev, A Sokolovsky, M Alexandrov, A Kesler, R Koren. 2003. Photon undulatory non-linear conversion diagnostic method for caries detection: a pilot study.. https://doi.org/10.1089/104454703768247783

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2026

Artificial intelligence for dental caries detection: An umbrella review.

Artificial intelligence (AI) has been proposed as a tool to improve dental caries detection across imaging modalities; however, its clinical value remains uncertain. This umbrella review aimed to synthesize and critically appraise systematic reviews evaluating AI for caries detection and diagnosis. An umbrella review was conducted following PRIOR guidance (PROSPERO CRD420261340728). Searches were performed in MEDLINE, Embase, Scopus, Web of Science, and Google Scholar up to 15 March 2026. Methodological quality was assessed using AMSTAR 2, and overlap of primary studies was quantified using the corrected covered area (CCA). Seventeen systematic reviews were included, of which five reported diagnostic test accuracy meta-analyses using bivariate or HSROC models. Across these meta-analyses, pooled sensitivity ranged from 0.76 to 0.94 and specificity from 0.85 to 0.91. Most systems were based on deep learning models applied to bitewing radiographs and intraoral photographs. However, substantial heterogeneity was observed in imaging modalities, lesion thresholds, analytical tasks, and evaluation metrics. In addition, a high degree of overlap across reviews and recurrent methodological limitations, including reliance on retrospective datasets, limited external validation, and inconsistent reporting, substantially weaken the reliability of the evidence. Although AI models demonstrate high diagnostic performance under experimental conditions, current evidence does not support their use as stand-alone diagnostic tools. Their clinical applicability remains limited, and implementation should be restricted to decision-support contexts until robust prospective validation demonstrates meaningful impact on clinical decision-making and patient outcomes.

Dental Caries↗
PubMed2007

Hardness, elasticity, and ultrastructure of bonded sound and caries-affected primary tooth dentin.

Biomechanical properties of bonded dentin are important factors for resin restoration. We evaluated the hardness and elastic modulus of bonded sound and caries-affected primary tooth dentin using a one-step adhesive system, and observed the microstructure of the bonded interface. Six sound and six carious primary teeth were used. For sound teeth, flat occlusal dentin surfaces were prepared with a water-cooled high-speed diamond bur. For carious teeth, infected dentin was stained with a caries detector and removed with a water-cooled low-speed round steel bur and hand instruments. The prepared dentin was bonded with One-Up Bond F Plus (Tokuyama Dental Co., Tokyo, Japan). The resin-dentin interface and dentin beneath the interface were measured with a nano-indentation tester and observed with SEM and TEM. For both the carious and sound teeth, there was no significant difference between the hardness of the interfacial dentin and dentin 10-80 microm beneath the interface. However, the Young's modulus of the interfacial dentin was significantly lower than the dentin 40-80 microm (carious teeth) or 50-80 microm (sound teeth) beneath the interface. Both the hardness and Young's modulus of the interfacial dentin were not significantly different between the carious and sound teeth. Compared to the sound dentin, the hybrid layer on the caries-affected dentin was thicker and exhibited more complicated morphologic features. The thickness of the hybrid layers was generally less than 1 microm.

Dental Caries↗
PubMed2006

Arresting caries.

Explore the source record for details and available documents.

Dental Caries↗