Caries Classification Research Articles

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

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

Dental Caries Detection Using Score-Based Multi-Input Deep Convolutional Neural Network

Panoramic and periapical radiograph tools help dentists in diagnosing the most common dental diseases, such as dental caries. Generally, dental caries is manually diagnosed by dentists based on panoramic and periapical images. For several reasons, such as carelessness caused by heavy workload and inexperience, manual diagnosis may cause unnoticeable dental caries. Thus, computer-based intelligent vision systems supported by machine learning and image processing techniques are needed to prevent these negativities. This study proposed a novel approach for the automatic diagnosis of dental caries based on periapical images. The proposed procedure used a multi-input deep convolutional neural network ensemble (MI-DCNNE) model. Specifically, a score-based ensemble scheme was employed to increase the achievement of the proposed MI-DCNNE method. The inputs to the proposed approach were both raw periapical images and an enhanced form of it. The score fusion was carried out in the Softmax layer of the proposed multi-input CNN architecture. In the experimental works, a periapical image dataset (340 images) covering both caries and non-caries images were used for the performance evaluation of the proposed method. According to the results, it was seen that the proposed model is quite successful in the diagnosis of dental caries. The reported accuracy score is 99.13%. This result shows that the proposed MI-DCNNE model can effectively contribute to the classification of dental caries.

Generation of Teeth Caries Features for Human Dental Caries Classification

Many dental diseases are experienced by humans, one of which is dental caries, there are three types of human dental caries, namely enamel caries, dentin caries and pulp caries. This study contains the detection of caries disease in human teeth using two-dimensional images and radiological results of x-ray periapical radiographs from a test image dataset that has a number of pixels between 374x288 to 672x514 pixels with an image resolution of 96 DPI. The original data of existing dental images was processed using Matlab language to obtain caries features through three stages of the processes: pre-processing stage which are stages of the preprocessing process that converts data from a two-dimensional color image (row/height, column/width) that is stored using three channels Red, Green and Blue (RGB), into a grayscale image with one channel, the process of extracting dental caries features by performing calculations caries area and calculate the distance of the caries area to the nerve canal (pulp), and the process of building learning or reference data from dental caries using 24 radiograph periapical data on molar tooth images processed using Matlab. Dental caries features extraction process and the features learning process to generate references features from dental caries is the main objective of this research. This study result was references features for human dental caries classification.

Evaluation of VGG-16 deep learning algorithm for dental caries classification

Evaluation of VGG-16 deep learning algorithm for dental caries classification

Understanding dental caries as a non-communicable disease

The recent developments in the science underpinning our knowledge of both the initiation of dental caries and the subsequent behaviour of lesions over time gives us a solid base to understand caries differently. Advances in understanding the human and oral microbiome have come in parallel with the recognition of the importance of balancing protective and pathological risk factors. Caries prevention and management is now about controlling risk factors to maintain a balanced intraoral biofilm ecology that guards against a continuing low pH driven by the frequent consumption of sugars. Thus, caries control is no longer about attempts at eradicating any specific microorganism. Further, the present knowledge leads to the classification of dental caries as a non-communicable disease (NCD), which is vitally important from a policy perspective (both globally and at the country level). Caries shares similar risk factors with other chronic/systemic diseases, which provides opportunities for developing common prevention strategies and promoting health equity through action on the social determinants of health. So, preventing and controlling caries should be integrated across the so-called upstream, midstream and downstream levels and these activities can also help to control other NCDs.

From 'ICDAS' to 'CariesCare International': the 20-year journey building international consensus to take caries evidence into clinical practice

This paper charts the 20-year collaborative journey made by international teams of dental researchers, educators and practitioners. Following the initial development of the International Caries Detection and Assessment System (ICDAS) in 2002, the International Caries Classification and Management System (ICCMS) was collaboratively developed between 2010-2017 with several dental research and practice organisations, and influenced by best evidence judged via SIGN methodology, the UNEP Minamata Treaty (and linked phasing down of dental amalgam), three Dental Policy Labs and an international movement in operative dentistry to move towards minimally invasive dentistry. The FDI World Dental Federation publicised and advocated the ICCMS in 2019, when the 'CariesCare International' Consensus Guide and 4D caries management system was published to aid the delivery of ICCMS into practice. This system, which is designed to help practitioners deliver optimal caries care for patients, is now being adapted internationally for post-pandemic use in the 'Caries OUT' study. It is also being used as a vehicle for implementing the updated Delivering better oral health guidance on caries, as part of the minimum intervention oral healthcare delivery framework in the UK.

Application of Selected Biomaterials and Stem Cells in the Regeneration of Hard Dental Tissue in Paediatric Dentistry-Based on the Current Literature.

Currently, the development of the use of biomaterials and their application in medicine is causing rapid changes in the fields of regenerative dentistry. Each year, new research studies allow for the discovery of additional possibilities of dental tissue restoration. The structure and functions of teeth are complex. They consist of several diverse tissues that need to act together to ensure the tooth’s function and durability. The integrity of a tooth’s enamel, dentin, cementum, and pulp tissue allows for successful mastication. Biomaterials that are needed in dentistry must withstand excessive loading forces, be biocompatible with the hosts’ tissues, and stable in the oral cavity environment. Moreover, each tooth’s tissue, as well as aesthetic qualities in most cases, should closely resemble the natural dental tissues. This is why tissue regeneration in dentistry is such a challenge. This scientific research focuses on paediatric dentistry, its classification of caries, and the use of biomaterials in rebuilding hard dental tissues. There are several methods described in the study, including classical conservative methods such as caries infiltration or stainless-steel crowns. Several clinical cases are present, allowing a reader to better understand the described methods. Although the biomaterials mentioned in this work are artificial, there is currently ongoing research regarding clinical stem cell applications, which have a high potential for becoming one of the most common techniques of lost dental-tissue regeneration in the near future. The current state of stem cell development is mentioned, as well as the various methods of its possible application in dentistry.

ICCMS™ root caries lesions stages and their underlying depth towards the pulp: an in vitro study with histologic evaluation.

To examine the relationship between the ICCMS™ (International Caries Classification and Managing System) features of root caries lesions and the underlying depth of the lesion towards the pulp. In order to control for bias, the study followed the tailored document for risk of bias assessment (RoB-tool) recently published. A pilot study showed that the outline of the pulp was much clearer on horizontal compared to vertical sections through the lesions (p = 0.03) and that the histological stereomicroscopical (SM) assessed lesion depth towards the pulp was not influenced by the cutting direction (p = 0.155). A sample of extracted permanent molar teeth (n = 100) were classifiedindependently by two of the authors according to ICCMS™ as no sign of root caries lesion 0 = sound; 1 = initial lesion (non-cavitated); 2 = moderate lesion (cavity depth ≤ 2mm) and 3 = extensive lesion (cavity depth > 2mm). After horizontal sectioning (HS) through the lesion, the depth of the underlying lesion was SM assessed independently by two of the authors as 0 = no lesion; 1 = lesion in outer 1/3; 2 = middle 1/3; and 3 = inner 1/3 of the dentine towards the pulp. Intra- and inter-reproducibility (weighted kappa values ≥ 0.83); the accuracy (Spearman's rho-values) = 0.94 and 0.95; and specificity/sensitivities/AUC values (three different thresholds) were ≥ 0.91, ≥ 0.93, and ≥ 0.96, respectively. Under the umbrella of the RoB-tool, the validity in terms of the reproducibility and accuracy of the ICCMS™ root caries scoring system was high. By means of the ICCMS™ root caries scoring system, the underlying lesion depth can be estimated, which must be considered when managing the lesion.

Automatic Blob Detection for Dental Caries

Dental Caries are one of the most prevalent chronic diseases around the globe. Detecting carious lesions is a challenging task. Conventional computer aided diagnosis and detection methods in the past have heavily relied on the visual inspection of teeth. These methods are only effective on large and clearly visible caries on affected teeth. Conventional methods have been limited in performance due to the complex visual characteristics of dental caries images, which consist of hidden or inaccessible lesions. The early detection of dental caries is an important determinant for treatment and benefits much from the introduction of new tools, such as dental radiography. In this paper, we propose a deep learning-based technique for dental caries detection namely: blob detection. The proposed technique automatically detects hidden and inaccessible dental caries lesions in bitewing radio-graphs. The approach employs data augmentation to increase the number of images in the data set to have a total of 11,114 dental images. Image pre-processing on the data set was through the use of Gaussian blur filters. Image segmentation was handled through thresholding, erosion and dilation morphology, while image boundary detection was achieved through active contours method. Furthermore, the deep learning based network through the sequential model in Keras extracts features from the images through blob detection. Finally, a convexity threshold value of 0.9 is introduced to aid in the classification of caries as either present or not present. The process of detection and classifying dental caries achieved the results of 97% and 96% for the precision and recall values, respectively.

Needs-led human resource planning for Sierra Leone in support of oral health

BackgroundIn Sierra Leone (SL), a low-income country in West Africa, dental care is very limited, largely private, and with services focused in the capital Freetown. There is no formal dental education. Ten dentists supported by a similar number of dental care professionals (DCPs) serve a population of over 7.5 million people. The objective of this research was to estimate needs-led requirements for dental care and human resources for oral health to inform capacity building, based on a national survey of oral health in SL.MethodsA dedicated operational research (OR) decision tool was constructed in Microsoft Excel to support this project. First, total treatment needs were estimated from our national epidemiological survey data for three key ages (6, 12 and 15 years), collected using the ‘International Caries Classification and Management System (ICCMS)’ tool. Second, oral health needs were extrapolated to whole population levels for each year-group, based on census demographic data. Third, full time equivalent (FTE) workforce capacity needs were estimated for mid-level providers in the form of Dental Therapists (DTs) and non-dental personnel based on current oral disease management approaches and clinical timings for treatment procedures. Fourth, informed by an expert panel, three oral disease management scenarios were explored for the national population: (1) Conventional care (CC): comprising oral health promotion (including prevention), restorations and tooth extraction; (2) Surgical and Preventive care (S5&6P and S6P): comprising oral health promotion (inc. prevention) and tooth extraction (D5 and D6 together, & at D6 level only); and (3) Prevention only (P): consisting of oral health promotion (inc. prevention). Fifth, the findings were extrapolated to the whole population based on demography, assuming similar levels of treatment need.ResultsTo meet the needs of a single year-group of childrens’ needs, an average of 163 DTs (range: 133–188) would be required to deliver Conventional care (CC); 39 DTs (range: 30–45) to deliver basic Surgical and Preventive care (S6P); 54 DTs for more extended Surgical and Preventive care (S5&6P) (range 38–68); and 27 DTs (range: 25–32) to deliver Prevention only (P). When scaled up to the total population, an estimated 6,147 DTs (range: 5,565–6,870) would be required to deliver Conventional care (CC); 1,413 DTs (range: 1255–1438 DTs) to deliver basic Surgical and Preventive care (S6P); 2,000 DTs (range 1590–2236) for more extended Surgical and Preventive care (S5&6P) (range 1590–2236); and 1,028 DTs to deliver Prevention only (P) (range: 1016–1046). Furthermore, if oral health promotion activities, including individualised prevention, could be delivered by non-dental personnel, then the remaining surgical care could be delivered by 385 DTs (range: 251–488) for the S6P scenario which was deemed as the minimum basic baseline service involving extracting all teeth with extensive caries into dentine. More realistically, 972 DTs (range: 586–1179) would be needed for the S5&6P scenario in which all teeth with distinctive and extensive caries into dentine are extracted.ConclusionThe study demonstrates the huge dental workforce needs required to deliver even minimal oral health care to the Sierra Leone population. The gap between the current workforce and the oral health needs of the population is stark and requires urgent action. The study also demonstrates the potential for contemporary epidemiological tools to predict dental treatment needs and inform workforce capacity building in a low-income country, exploring a range of solutions involving mid-level providers and non-dental personnel.

Knowledge and Practice of ICDAS and ICCMS in Young Children: A Cross-sectional Study among Final-year Dental Students in Malaysia.

BackgroundTo evaluate the association of sex, type of institution, and satisfaction of educational activities with dental students’ knowledge of International Caries Detection and Assessment System (ICDAS) and International Caries Classification and Management System (ICCMS) in young children.Materials and methodsThis was a cross-sectional study involving final-year dental students from all accredited dental institutions across Malaysia. A self-constructed questionnaire was given through an identified personal contact from each school. The students’ responses on the association of sex and institution type with the satisfaction of education activities and ICDAS and ICCMS knowledge were tested using the independent t-test. The relationship between satisfaction of educational activities and knowledge of ICDAS and ICCMS among dental students was evaluated using Spearman's correlation analysis. Statistical significance was set at p < 0.05.ResultsA total of 440 responses were obtained. Out of this, 312 (70.9%) were female and 126 (28.6%) were male respondents, and 2 with unknown sex. There were 231 responses (52.5%) from the private institution and 209 responses (47.5%) from the government institution. Males had a higher level of satisfaction toward the education activities. No significant difference was observed between the knowledge of ICCMS and ICDAS and sex or institution type.ConclusionMale dental students felt more satisfied with pediatric lectures conducted during preclinical years and were more prepared to treat patients independently upon graduation. Sex and type of institution did not play a role in the knowledge and dental students were more knowledgeable in ICDAS compared to ICCMS.How to cite this articleYin LS, Tamilselvam K, Abdulla AM, et al. Knowledge and Practice of ICDAS and ICCMS in Young Children: A Cross-sectional Study among Final-year Dental Students in Malaysia. Int J Clin Pediatr Dent 2021;14(2):278–285.

The performance of SoproLIFE for early detection of coronal caries using the International Caries Classification and Management System - A preliminary laboratory-based study

The aim of this laboratory-based study is to evaluate performance of the Light-Induced Fluorescence Evaluator (SoproLIFE) for early detection of coronal caries and to validate the findings using the International Caries Classification and Management System (ICCMS). A total of 56 freshly extracted teeth with coronal carious lesions were included. 74 regions of interest were identified. Visual assessments with International Caries Detection and Assessment Systems (ICDAS), radiographic information and SoproLIFE images were used to classify each region of interest according to the ICCMS as a reference standard. SoproLIFE specificity and sensitivity were calculated at the sound-enamel and dentine lesion levels. Inter and intra reproducibility of ICDAS were analysed and showed a moderate agreement (0.52) and (0.58) respectively. At the sound-initial caries level, the sensitivity and specificity for the SoproLIFE were 90.0%, 95.8% respectively, whilst for the dentine caries level, sensitivity was 100% with specificity of 53.8%. A low proportion of teeth with dental caries were classified as caries-free using the SoproLIFE (false negative=10%). As a conclusion, the performance of SoproLIFE was promising in distinguishing between early enamel carious lesions and sound surfaces. This detection tool could be suggested to be used with ICCMS to assist in the clinical decision-making process.

Classification of caries in third molars on panoramic radiographs using deep learning

The objective of this study is to assess the classification accuracy of dental caries on panoramic radiographs using deep-learning algorithms. A convolutional neural network (CNN) was trained on a reference data set consisted of 400 cropped panoramic images in the classification of carious lesions in mandibular and maxillary third molars, based on the CNN MobileNet V2. For this pilot study, the trained MobileNet V2 was applied on a test set consisting of 100 cropped PR(s). The classification accuracy and the area-under-the-curve (AUC) were calculated. The proposed method achieved an accuracy of 0.87, a sensitivity of 0.86, a specificity of 0.88 and an AUC of 0.90 for the classification of carious lesions of third molars on PR(s). A high accuracy was achieved in caries classification in third molars based on the MobileNet V2 algorithm as presented. This is beneficial for the further development of a deep-learning based automated third molar removal assessment in future.

Metagenomic analysis of black-stained plaques in permanent dentition

ObjectivesWe aimed to determine the aetiologic agent responsible for black staining of permanent dentition using next-generation sequencing and determine the relationship between caries and black stains. Materials and methodsA total of 52 systemically healthy patients with black-stained and caries-free (n = 13), black-stained and carious (n = 13), black stain-free and caries-free (n = 13), and black stain-free and carious (n = 13) teeth were enrolled in the study. The International Caries Detection and Assessment System (ICDAS II) was used for caries classification. Between 08:00 and 10:00, supragingival plaque samples were collected after a minimum of 8–12 h of accumulation and DNA samples were isolated. The samples were processed using the ZymoBIOMICS™ Service. Bioinformatics analysis was performed using mothur at usegalaxy.org. Data were analysed statistically using the Pearson chi-square and Fisher tests. ResultsThe number of caries-free teeth (ICDAS 0, 1, and 2) was significantly higher in patients with black stains (p = 0.007).Capnocytophaga (4.8 %), Corynebacterium (3.9 %), and Neisseria (5.4 %) species were the most abundant among all black-stained plaques (carious and caries-free) (p < 0.05). Capnocytophaga (10.8 %), Cardiobacterium (3.6 %), and Rothia (1.72 %) species were detected in the black-stained plaques of caries-free patients (p < 0.05). ConclusionThis study is one of the first studies examining the microbial composition of dental plaques with black staining in carious and caries-free adult patients using next generation sequencing technology. In the presence of black staining, plaques have an ultimate complex microbial structure. A lower caries burden was noted in the presence of black staining.

Evaluating the Performance of Dental Students with Different Levels of Clinical Experience in Learning ICDAS

This study aimed to evaluate the dental students' performance in ICDAS (International Caries Detection and Assessment System) coding with different levels of clinical experience. Dental students (n = 122) in their clinical years, year 3 (n = 37), year 4 (n = 44), and year 5 (n = 41) received training (two-hour introductory lecture on ICDAS, followed by a 90 min e-learning video, and practice sessions using extracted teeth and photographs) from a calibrated expert. After training, the students examined a prevalidated set of extracted teeth and assigned scores in two sessions. The intra- and inter-examiner agreement between students was analyzed using weighted kappa statistics and a focus group discussion was conducted for qualitative feedback. The range of kappa values for intra-examiner agreement among the year 3, 4, and 5 students for ICDAS caries code (0.611-0.879, 0.633-0.848, and 0.645-1.000) and restoration code (0.615-0.942, 0.612-0.923, 0.653-1.000), respectively. The range of kappa values for inter-examiner agreement for year 3, 4, and 5 students with a trained expert for ICDAS caries code (0.526-0.713, 0.467-0.810, and 0.525-0.842) and restoration code (0.531-0.816, 0.682-0.842, and 0.645-0.928), respectively. The ICDAS system is a promising tool for caries detection and its implementation in the curriculum was perceived by dental students as an effective method. In general, there was moderate to substantial agreement for ICDAS caries and restoration code between students of different academic year groups and with a trained ICDAS expert. ICDAS is a simple, logical, and evidence-based system for the detection and classification of caries. Introducing ICDAS to dental students enables them to detect caries in a reliable and reproducible manner irrespective of their past clinical experience and also significantly improves their caries detection skills.

Learning compact and discriminative hybrid neural network for dental caries classification

Dental caries, alternatively called tooth decay is considered as the most general and rapidly increasing diseases. According to the statistics, nearly 90% of the adults confront the issue of dental caries. Hence for proper dental care and health, early detection and diagnosis concerning the caries lesion plays a mandatory role. To achieve this, technique of Imaging Processing is being adopted which further helps the specialists to carry out precise diagnosis. Dental Caries can be categorized into different types depending on its position as well as seriousness. This categorization holds significant to carry out diagnosis and plan for the treatment of dental disease. The paper recommends the new HNN (Hybrid Neural Network) technique for detecting dental caries depending on, its type and therefore precisely classify the caries affected layer. HNN is a blend of ANN (Artificial Neural Network and DNN (Deep neural network) techniques. To obtain image classification, deep neural network relies upon the stacked sparse auto-encoder. Thereafter authentic information can be fetched from data via supervised fine-tuning and unsupervised pre-training. On the other hand ANN (Artificial neural network) relies upon the logistic regression for classifying the dental caries affected layer. Various processes involved in dental input image are as following: l. Pre-Processing, 2. Segmentation, 3. Feature Extraction and 4.Classification. Caries are categorized into 4 different layers by the HNN, namely: Enamel, Dentin, Pulp and root lesions. The proposed system yield in effective output against the input image provided and precisely categorizes the caries level. Hybrid neural network is the innovative technique which is giving good result in terms of accuracy and processing time.

Topographic Distribution of Proximal Cavitated Lesions on Primary Mandibular Molars

Introduction: Increased prevalence of proximal caries in primary teeth and its difficult diagnosis makes it necessary to develop newer diagnostic tools for accurate detection of these lesions. International Caries Detection and Assessment System (ICDAS) and its associated International Caries Classification and Management System (ICCMS) is a newer system that uses ICDAS for clinical staging of caries and ICDAS Radiographic score for radiographic staging of carious lesion. Aim: To the topographical distribution of proximal cavitated lesions on the mandibular arch and on primary mandibular molar tooth surface and to determine the extent of the agreement between clinical and radiographic examination in identifying proximal cavitated lesions involving primary mandibular molars. Materials and Methods: An observational study between July 2018-August 2019 in a total of 100 (60 first and 40 second primary molars) primary mandibular molars (D or E) was conducted. Proximal cavitation involving primary mandibular molars were examined both clinically (ICCMS caries merged category scores) and radiographically (ICDAS Radiographic scoring system) and the correlation between both scores were also analysed. Results: First primary molar was observed to have statistically significant prevalence of proximal cavitation (p-value ≤0.001) both clinically and radiographically as compared to second primary molar. Distal surface was observed to have more carious lesions as compared to mesial surface (p-value=0.003). Also, a statistically significant correlation was observed between the clinical and radiographic scores (p-value ≤0.001). Conclusion: Mandibular first primary molar is more prone to proximal cavitation along with chances of distal surface cavitations being higher.

Restorative thresholds for carious lesions in primary molars: French dentist's decisions.

Questionnaire surveys have been undertaken worldwide to investigate practices and knowledge related to carious lesion management, particularly in adults. The primary objective of this cross-sectional survey was to investigate restorative thresholds (RTs) used for carious lesions in primary molars by dentists practising paediatric dentistry in France. Dentists were surveyed by a specifically developed questionnaire based on clinical and radiographic caries classifications. The secondary objective was to explore restorative management strategies in primary molars. A structured questionnaire assessing RTs and management strategies for occlusal and approximal carious lesions of primary molars was anonymously and electronically administered via SurveyMonkey® to dentists who were members of the Société Française d'Odontologie Pédiatrique. Descriptive analyses, Chi-square test, McNemar test, and logistic regression analyses considering dependent RT variables for occlusal and approximal carious lesions were performed. Among 250 dentists surveyed, 201 responded (response rate 80.4%). Overall, 43% (n = 87) and 75% (n = 151) of respondents would place their RTs in enamel for occlusal and approximal lesions, respectively. Dentists with an exclusive practice of paediatric dentistry more frequently would choose a RT in dentine for approximal lesions than did other dentists (p = 0.010). A preparation technique including sound dental tissues was less frequent for occlusal than approximal lesions (n = 31; 15% vs n = 60; 30%). Overall, 75% (n = 151) of respondents used the same restorative material for occlusal and approximal lesions. In general, dentists practising paediatric dentistry in France overtreated lesions on primary molars, which contradicts minimal intervention recommendations. RTs are too often indicated for enamel-confined carious lesions.

GENERAL FEATURES OF CARIES PATHOGENESIS IN THIRD MOLARS AND AUTOIMMUNE DISEASES

This article presents a literature review, the results of the analysis of random samples of third molars removed for various clinical indications (11 samples). The teeth samples were analyzed visually, then their coronal parts were treated with epoxy plastination technique and prepared polished sections were studied microscopically. The analyzed data demonstrate the pathogenesis of fissure caries in our samples studied can be explained in terms of the direct virulent effect of pathogenic bacteria on the organic matter in the superficial dentin and basal enamel with the formation of auto antigens, which, as a result of sensitization of the local immune system, become the initial source of the carious process spreading to other teeth. This gives grounds to identify it with the pathogenesis of autoimmune pathology. It has been established that carious damage to hard tissues on the smooth surfaces of the dental crown begins with the pulp, when it is vital, and stops as a result of its tissue degeneration. It has been shown that a single latent damage to the hard dental tissues is the initial manifestation of the latent stage of the carious process, while multiple defects indicate its further progression. As for the generally accepted classification of caries, according to which superficial, medium and deep caries are distinguished, then, in our opinion, they should be considered as stages of the further process of carious destruction of hard dental tissues. We can suggest the study of the pathogenesis of carious lesions of third molars is necessary in order to prevent the occurrence of autoimmune diseases and increase the effectiveness of their treatment.

Study protocol for a diagnostic randomized clinical trial to evaluate the effect of the use of two clinical criteria in the assessment of caries lesions around restorations in adults: the Caries Cognition and Identification in Adults (CaCIA) trial

BackgroundThe assessment of restored teeth in dentistry remains a challenge, mainly related to the detection of caries around restorations. There is a diversity of clinical criteria available to assess the caries lesions, resulting in differences in the dentists’ diagnosis and treatment decisions. In addition, there is a lack of evidence regarding the best criteria to detect caries lesions around the restorations. Thus, the present protocol aims to evaluate the effect of using 2 visual criteria to assess restored teeth on the outcomes related to oral health in adults.MethodsThe design protocol of the Caries Cognition and Identification in Adults trial correspond to a triple-blind randomized, controlled clinical trial with parallel-groups. Two groups will be compared: patients who will receive the diagnosis and treatment decision according to FDI (World Dental Federation) criteria—FDI group; and patients who will receive diagnosis and treatment decision according to the “Caries Associated with Restorations or Sealants” criteria defined by the International Caries Classification and Management System (ICCMS group). The participants will be followed up after 6, 12, 18, 24, and 60 months, and the restoration failure will be the primary outcome. The analysis will be conducted through Cox regression with shared frailty. The impact of oral health on quality of life and the cost-effectiveness of the methods used will be the secondary outcomes. Two-tailed analyzes will be used, considering a level of significance of 5%.DiscussionThis is the first clinical trial to assess the effect of using two visual methods to detect caries lesions around restorations on the outcomes related to oral health in adults. The findings of this study will define what is the best diagnostic strategy for the assessment of caries around restorations in permanent teeth.Trial registration NCT03108586 (registered 11 April 2017).