Detection of Dental Caries and Cracks with Quantitative Light-Induced Fluorescence in Comparison to Radiographic and Visual Examination: A Retrospective Case Study

The Potential Role of Ionic Liquid as a Multifunctional Dental Biomaterial

In craniofacial research and routine dental clinical procedures, multifunctional materials with antimicrobial properties are in constant demand. Ionic liquids (ILs) are one such multifunctional intelligent material. Over the last three decades, ILs have been explored for different biomedical applications due to their unique physical and chemical properties, high task specificity, and sustainability. Their stable physical and chemical characteristics and extremely low vapor pressure make them suitable for various applications. Their unique properties, such as density, viscosity, and hydrophilicity/hydrophobicity, may provide higher performance as a potential dental material. ILs have functionalities for optimizing dental implants, infiltrate materials, oral hygiene maintenance products, and restorative materials. They also serve as sensors for dental chairside usage to detect oral cancer, periodontal lesions, breath-based sobriety, and dental hard tissue defects. With further optimization, ILs might also make vital contributions to craniofacial regeneration, oral hygiene maintenance, oral disease prevention, and antimicrobial materials. This review explores the different advantages and properties of ILs as possible dental material.

Quantitative Evaluation of Caries and Calculus with Ultrahigh-Resolution Optical Coherence Tomography

Dental caries on the crown's surface is caused by the interaction of bacteria and carbohydrates, which then gradually alter the tooth's structure. In addition, calculus is the root of periodontal disease. Optical coherence tomography (OCT) has been considered to be a promising tool for identifying dental caries; however, diagnosing dental caries in the early stage still remains challenging. In this study, we proposed an ultrahigh-resolution OCT (UHR-OCT) system with axial and transverse resolutions of 2.6 and 1.8 μm for differentiating the early-stage dental caries and calculus. The same teeth were also scanned by a conventional spectral-domain OCT (SD-OCT) system with an axial resolution of 7 μm. The results indicated that early-stage carious structures such as small cavities can be observed using UHR-OCT; however, the SD-OCT system with a lower resolution had difficulty identifying it. Moreover, the estimated surface roughness and the scattering coefficient of enamel were proposed for quantitatively differentiating the different stages of caries. Furthermore, the thickness of the calculus can be estimated from the UHR-OCT results. The results have demonstrated that UHR-OCT can detect caries and calculus in their early stages, showing that the proposed method for the quantitative evaluation of caries and calculus is potentially promising.

Use of Digital Diagnostic Aids for Initial Caries Detection: A Review

The advance in digital diagnostic technologies has significantly facilitated the detection of dental caries. Despite the increase in clinically available digital diagnostic aids for dental caries, there is yet to be a comprehensive summary of all available technology. This review aims to provide an overview of digital diagnostic aids for the clinical detection of dental caries, particularly those at an initial stage. Currently available digital diagnostic aids for caries detection can be classified into four categories according to the initial source of energy, including radiation-based aids, light-based aids, ultrasound-based aids, and electric-based aids. Radiation-based aids use ionizing radiation, normally X-ray, to produce images of dental structures. Radiation-based aids encompass digital bitewing radiography and cone beam computed tomography. Light-based aids employ light or laser to induce signals for the detection of the changes in the carious dental hard tissue. Common light-based aids include digital transillumination and light/laser-induced fluorescence. Ultrasound-based aids detect the signal of ultrasound waves to assess the acoustic impedance of the carious teeth. The ultrasound caries detector is an available ultrasound-based aid. Electric-based aids assess the changes in the electric current conductance or impedance of the teeth with caries. Available electric-based aids include electrical conductance measurement and alternating current impedance spectroscopy. Except for these clinically available digital diagnostic aids, many digital diagnostic aids for caries detection are still under development with promising results in laboratory settings.

Transforming Dental Caries Diagnosis Through Artificial Intelligence-Based Techniques

Diagnosing dental caries plays a pivotal role in preventing and treating tooth decay. However, traditional methods of diagnosing caries often fall short in accuracy and efficiency. Despite the endorsement of radiography as a diagnostic tool, the identification of dental caries through radiographic images can be influenced by individual interpretation. Incorporating artificial intelligence (AI) into diagnosing dental caries holds significant promise, potentially enhancing the precision and efficiency of diagnoses. This review introduces the fundamental concepts of AI, including machine learning and deep learning algorithms, and emphasizes their relevance and potential contributions to the diagnosis of dental caries. It further explains the process of gathering and pre-processing radiography data for AI examination. Additionally, AI techniques for dental caries diagnosis are explored, focusing on image processing, analysis, and classification models for predicting caries risk and severity. Deep learning applications in dental caries diagnosis using convolutional neural networks are presented. Furthermore, the integration of AI systems into dental practice is discussed, including the challenges and considerations for implementation as well as ethical and legal aspects. The breadth of AI technologies and their prospective utility in clinical scenarios for diagnosing dental caries from dental radiographs is presented. This review outlines the advancements of AI and its potential in revolutionizing dental caries diagnosis, encouraging further research and development in this rapidly evolving field.

Dental diagnosis for inlay restoration using an intraoral optical coherence tomography system: A case report

PATIENTS

The patient was a 32-year-old man who underwent amalgam restoration of the mandibular right second molar. An amalgam restoration fracture was diagnosed by intraoral optical coherence tomography (OCT), and pulp exposure was examined during cavity preparation. Subsequently, a definitive ceramic restoration was fabricated, and the marginal fit in the oral cavity was evaluated using the OCT system.

DISCUSSION

The existing OCT system cannot acquire images inside the oral cavity because of the large probe size. However, the proposed intraoral OCT system can access the prostheses in the mandibular right second molar. Therefore, dental diagnosis for restoration treatment with dental prosthesis fracture, marginal gap, and pulp exposure after tooth preparation is possible using the proposed intraoral OCT system.

CONCLUSIONS

The use of the intraoral OCT system improved dental diagnosis by allowing the dentist to confirm quantitative values through cross-sectional images, rather than that by determining a treatment plan after visual dental diagnosis.

Development of a Visualisation Approach for Analysing Incipient and Clinically Unrecorded Enamel Fissure Caries Using Laser-Induced Contrast Imaging, MicroRaman Spectroscopy and Biomimetic Composites: A Pilot Study

This pilot study presents a practical approach to detecting and visualising the initial forms of caries that are not clinically registered. The use of a laser-induced contrast visualisation (LICV) technique was shown to provide detection of the originating caries based on the separation of emissions from sound tissue, areas with destroyed tissue and regions of bacterial invasion. Adding microRaman spectroscopy to the measuring system enables reliable detection of the transformation of the organic–mineral component in the dental tissue and the spread of bacterial microflora in the affected region. Further laboratory and clinical studies of the comprehensive use of LICV and microRaman spectroscopy enable data extension on the application of this approach for accurate determination of the boundaries in the changed dental tissue as a result of initial caries. The obtained data has the potential to develop an effective preventive medical diagnostic approach and as a result, further personalised medical treatment can be specified.

Evaluation of dental caries detection with quantitative light-induced fluorescence in comparison to different field of view devices

This study evaluated dental caries detection ability between the Qraycam and Qraypen on the same dental caries lesions. A total of 178teeth from 61patients were imaged using Qraypen C®(QC) and Qraycam Pro®(QP) devices and evaluated using analysis software (QA2). Occlusal, secondary, and proximal dental caries were evaluated and scored according to International Caries Detection and Assessment System(ICDAS II) and X-ray criteria. Bland–Altman plots were used to compare quantitative light-induced fluorescence(QLF) parameters obtained from the different QLF devices. Sensitivity, specificity, and area under the receiver operating characteristic curve(AUROC) were calculated. The ΔF_aver. of the QLF-parameters showed that the mean difference between the two different QLF devices was close to zero and that the ± 5 error value was included in the mean ± 1.96SD range for the detection of dental caries. The accuracies for diagnosing occlusal dental caries were 0.83–0.96 and 0.81–0.82 and the accuracies for diagnosing proximal dental caries were 0.52–0.62 and 0.52–0.71 for the QC and QP devices, respectively. In conclusion, the ΔF_aver. obtained from the QP showed diagnostic value mainly for screening of demineralized teeth. For teeth selected through screening, the depth of the lesion must be precisely evaluated using additional QP and radiographic imaging.

The Effectiveness of a Quantitative Light-induced Fluorescent Device for the Diagnosis of a Cracked Tooth: A Case Report

Diagnosing a cracked tooth is a challenge for dental clinicians. This report describes the use of a quantitative light-induced fluorescent (QLF) device that detects fluorescence reactions with visible light (405 nm) to visually identify microscopic tooth cracks during the diagnosis and treatment of cracked teeth that caused pulp disease. Fluorescence images of the occlusal surface, before and after removal of the restoration, and inside of the access cavity for root canal treatment were obtained using an intraoral capture-type QLF device (Q-ray penC; AIOBIO, Seoul, Korea). The device provided visual information such as enhanced magnification and fluorescent images to identify cracks on the exterior of the tooth, around restorations, and inside the cavity after removal of the restoration by a simple image capture process. The device was able to demonstrate the existence of the crack line and to predict the depth of cracks during treatment.The QLF device showed a potential benefit in the diagnosis and characterization, including the location and depth, of tooth cracks.

Microbiome of Saliva and Plaque in Children According to Age and Dental Caries Experience

Dental caries are one of the chronic diseases caused by organic acids made from oral microbes. However, there was a lack of knowledge about the oral microbiome of Korean children. The aim of this study was to analyze the metagenome data of the oral microbiome obtained from Korean children and to discover bacteria highly related to dental caries with machine learning models. Saliva and plaque samples from 120 Korean children aged below 12 years were collected. Bacterial composition was identified using Illumina HiSeq sequencing based on the V3–V4 hypervariable region of the 16S rRNA gene. Ten major genera accounted for approximately 70% of the samples on average, including Streptococcus, Neisseria, Corynebacterium, and Fusobacterium. Differential abundant analyses revealed that Scardovia wiggsiae and Leptotrichia wadei were enriched in the caries samples, while Neisseria oralis was abundant in the non-caries samples of children aged below 6 years. The caries and non-caries samples of children aged 6–12 years were enriched in Streptococcus mutans and Corynebacterium durum, respectively. The machine learning models based on these differentially enriched taxa showed accuracies of up to 83%. These results confirmed significant alterations in the oral microbiome according to dental caries and age, and these differences can be used as diagnostic biomarkers.