Quantification Of Dental Plaque Research Articles

Development of AI Web Service for Quantification of Dental Plaque

Development of AI Web Service for Quantification of Dental Plaque

Semi-Automated Planimetric Quantification of Dental Plaque Using an Intraoral Fluorescence Camera.

Dental plaque accumulation is quantified using clinical indices or, otherwise, the planimetric plaque index (PPI),which measures the relative area of a tooth that is covered by plaque deposits. Compared to clinical indices, the PPI has a higher discriminatory power, but traditional planimetry is a time-consuming analysis, as the plaque-covered and clean tooth areas have to be determined manually for each image using image-processing software. Here, we present a method for the semi-automated planimetric quantification of dental plaque, which allows for the rapid processing of up to 1,000 images simultaneously. The method exploits the enhanced contrast between disclosed plaque, sound tooth surfaces, and soft tissues in fluorescence images acquired with an intraoral camera. Careful execution of the clinical procedures and accurate image acquisition are crucial steps for the successful semi-automated identification of the plaque-covered areas. The method is suitable for planimetry on sound facial and oral tooth surfaces, on most composite resin restorations, and on teeth with orthodontic brackets, but not on metallic restorations. Compared to traditional PPI recordings, semi-automated planimetry considerably reduces the amount of time spent on the analysis, as well as the subjective human input, thus increasing the reproducibility of planimetric measurements.

A fast and reliable method for semi-automated planimetric quantification of dental plaque in clinical trials.

To develop a simple and reproducible method for semi-automated planimetric quantification of dental plaque. Plaque from 20 healthy volunteers was disclosed using erythrosine, and fluorescence images of the first incisors, first premolars, and first molars were recorded after 1, 7, and 14 days of de novo plaque formation. The planimetric plaque index (PPI) was determined using a semi-automated threshold-based image segmentation algorithm and compared with manually determined PPI and the Turesky modification of the Quigley-Hein plaque index (TM-QHPI). The decrease of tooth autofluorescence in plaque-covered areas was quantified as an index of plaque thickness (TI). Data were analysed by analysis of variance (ANOVA) and Pearson correlations. The high contrast between teeth, disclosed plaque, and soft tissues in fluorescence images allowed for a fast threshold-based image segmentation. Semi-automated PPI is strongly correlated with manual planimetry (r=0.92; p < .001) and TM-QHPI recordings (r=0.88; p < .001), and may exhibit a higher discriminatory power than TM-QHPI due to its continuous scale. TI values corresponded to optically perceived plaque thickness, and no differences were observed over time (p > .05, ANOVA). The proposed semi-automated planimetric analysis based on fluorescence images is a simple and efficient method for dental plaque quantification in multiple images with reduced human input.

DenTiUS Plaque, a Web-Based Application for the Quantification of Bacterial Plaque: Development and Usability Study.

BackgroundIn the dentistry field, the analysis of dental plaque is vital because it is the main etiological factor in the 2 most prevalent oral diseases: caries and periodontitis. In most of the papers published in the dental literature, the quantification of dental plaque is carried out using traditional, non-automated, and time-consuming indices. Therefore, the development of an automated plaque quantification tool would be of great value to clinicians and researchers.ObjectiveThis study aimed to develop a web-based tool called DenTiUS and various clinical indices to evaluate dental plaque levels using image analysis techniques.MethodsThe tool was executed as a web-based application to facilitate its use by researchers. Expert users are free to define experiments, including images from either a single patient (to observe an individual plaque growth pattern) or several patients (to perform a group characterization) at a particular moment or over time. A novel approach for detecting visible plaque has been developed as well as a new concept known as nonvisible plaque. This new term implies the classification of the remaining dental area into 3 subregions according to the risk of accumulating plaque in the near future. New metrics have also been created to describe visible and nonvisible plaque levels.ResultsThe system generates results tables of the quantitative analysis with absolute averages obtained in each image (indices about visible plaque) and relative measurements (indices about visible and nonvisible plaque) relating to the reference moment. The clinical indices that can be calculated are the following: plaque index of an area per intensity (API index, a value between 0 and 100), area growth index (growth rate of plaque per unit of time in hours; percentage area/hour), and area time index (the time in days needed to achieve a plaque area of 100% concerning the initial area at the same moment). Images and graphics can be obtained for a moment from a patient in addition to a full report presenting all the processing data. Dentistry experts evaluated the DenTiUS Plaque software through a usability test, with the best-scoring questions those related to the workflow efficiency, value of the online help, attractiveness of the user interface, and overall satisfaction.ConclusionsThe DenTiUS Plaque software allows automatic, reliable, and repeatable quantification of dental plaque levels, providing information about area, intensity, and growth pattern. Dentistry experts recognized that this software is suitable for quantification of dental plaque levels. Consequently, its application in the analysis of plaque evolution patterns associated with different oral conditions, as well as to evaluate the effectiveness of various oral hygiene measures, can represent an improvement in the clinical setting and the methodological quality of research studies.

Comparison of Quantitative light-induced fluorescence-digital (QLF-D) images and images of disclosed plaque for planimetric quantification of dental plaque in multibracket appliance patients

The purpose of the present cross-sectional clinical study was to check the ability of plaque detection and quantification by QLF-D against conventional digital photographs of disclosed plaque in multibracket appliance (MB) patients. 20 patients were included according to the following criteria: (1) upper and lower jaw treated by MB appliance, (2) patients being 16 years of age or older, (3) all central and lateral incisors as well as canines in situ, (4) absence of developmental defects, carious lesions, surface fillings, prosthetic restorations or recessions greater than 1/3 of root length in central/lateral incisors and canines as well as (5) declaration of consent. QLF-D and conventional photographs were analyzed planimetrically regarding plaque coverage on buccal and oral surfaces of central/lateral incisors and canines. The conventional photographs of stained plaque served as gold standard. On average, in QLF-D pictures 20.7% ± 17.4 of the tooth surfaces were covered with plaque, while the conventional photographs of disclosed plaque presented a mean plaque-covered area of 36.2% ± 23.5. The Bland-Altman plot for both imaging modalities showed a very large inconsistent scattering with both negative and positive deviations. The method discrepancy increased with increasing plaque coverage, thus indicating a systematic method error. On average, the deviation of the methods from the optimal line of accordance was −15.5%. In patients wearing MB appliances, there was no clinical significant agreement regarding the plaque-covered tooth surface depicted by QLF-D respectively conventional images of disclosed plaque. Due to the large method discrepancy, QLF-D is currently not reliable for precise plaque quantification in MB patients.

Clinical validation and assessment of a modular fluorescent imaging system and algorithm for rapid detection and quantification of dental plaque

BackgroundSignificant numbers of adults and children have untreated plaque due to poor oral hygiene and consequently suffer from associate dental and systemic diseases.MethodsA handheld device equipped with 405 nm light-emitting diodes was constructed to examine the prevalence of red fluorescence signatures associated with dental plaque. This device was used for in vivo imaging of all four incisors and all four canines of twenty-eight consenting human subjects. The same areas were further imaged under white light illumination with a commercial image-processing based plaque-imaging device, and evaluated by a hygienist and dentist. A custom computer vision algorithm using pixel information was developed to calculate plaque coverage ratios ranging from 0 (no plaque) to 1 (complete plaque coverage) for images captured by both devices.ResultsThe algorithm calculated red fluorescence-based plaque coverage ratios ranging from 0.011 to 0.211 for the subjects imaged. Clinical assessment and statistical analyses of associated plaque ratios of the 405 nm device images indicated high sensitivity and specificity in detecting dental plaque by the experimental device compared to the commercial reference device.ConclusionsThe low-cost and open source 405 nm device and the associated computer vision algorithm successfully captured red fluorescence signatures associated with dental plaque and demonstrated comparable performance to a commercially available device. Therefore, a proof of concept validation was provided for the construction and application of a sensitive cost-effective plaque-detecting device. A miniaturized mobile adaptable version of the device was also provided, together with and a step-by-step guide for device assembly and webhost the associated software, to facilitate open-source access to a cost-effective at-home, in-clinic oral care technology.Trial registrationClinicalTrials.gov NCT03379337, December 19 2017. Retrospectively registered.

Quantification of dental plaque in oral cavity was enabled by a novel algorithm of image processing

ObjectivesQuantitative analysis of the biofilm has been critical for pathogenicity of oral diseases such as caries and periodontal disease. Currently, the plaque control record (PCR) is used most frequently to evaluate the presence of plaque on teeth, but no quantification methods exist so far. The aim of this study was to establish a method to quantify plaque adhesion on teeth. MethodsA novel algorithm and executing program was developed to calculate the staining volume of biofilm on plastic disks or extracted teeth inoculated by Streptococcus mutans from photographic image data. The biofilm's volume on plastic disks was determined using a confocal microscope, and correlations between image analysis data were analyzed. Subsequently, the amount of plaque in the oral cavity was clinically evaluated using this algorithm. ResultsA strong correlation was observed between the biofilm's volume and the image analysis data. Similar results were also obtained with the biofilm model using extracted teeth. Clinically, it was revealed that an assessment of the amount of plaque adhesion for every tooth was possible, which could not be determined by PCR in the oral cavity. ConclusionsWe successfully developed a novel method, designated “plaque volume ratio,” to quantify the plaque accurately from photographic image data. Our findings indicated that this method may be useful for the evaluation of the amount of plaque on the surfaces of not only teeth but also dental materials in the oral cavity.

Detection and quantification of dental plaque based on laser-induced autofluorescence intensity ratio values.

The aim of this study was to evaluate the applicability of laser-induced autofluorescence (LIAF) spectroscopy to detect and quantify dental plaque. LIAF spectra were recorded in situ from dental plaque (0–3 grades of plaque index) in 300 patients with 404 nm diode laser excitation. The fluorescence intensity ratio of the emission peaks was calculated from the LIAF spectral data following which their scatter plots were drawn and the area under the receiver operating characteristics were calculated. The LIAF spectrum of clinically invisible grade-1 plaque showed a prominent emission peak at 510 nm with a satellite peak around 630 nm in contrast to grade 0 that has a single peak around 500 nm. The fluorescence intensity ratio (F510/F630) has a decreasing trend with increase in plaque grade and the ratio values show statistically significant differences (p<0.01) between different grades. An overall sensitivity and specificity of 100% each was achieved for discrimination between grade-0 and grade-1 plaque. The clinical significance of this study is that the diagnostic algorithm developed based on fluorescence spectral intensity ratio (F510/F630) would be useful to precisely identify minute amounts of plaque without the need for disclosing solutions and to convince patients of the need for proper oral hygiene and homecare practices.

Reliability and discriminatory power of methods for dental plaque quantification

ObjectiveThis in situ study evaluated the discriminatory power and reliability of methods of dental plaque quantification and the relationship between visual indices (VI) and fluorescence camera (FC) to detect plaque.Material and MethodsSix volunteers used palatal appliances with six bovine enamel blocks presenting different stages of plaque accumulation. The presence of plaque with and without disclosing was assessed using VI. Images were obtained with FC and digital camera in both conditions. The area covered by plaque was assessed. Examinations were done by two independent examiners. Data were analyzed by Kruskal-Wallis and Kappa tests to compare different conditions of samples and to assess the inter-examiner reproducibility.ResultsSome methods presented adequate reproducibility. The Turesky index and the assessment of area covered by disclosed plaque in the FC images presented the highest discriminatory powers.ConclusionsThe Turesky index and images with FC with disclosing present good reliability and discriminatory power in quantifying dental plaque.

Novel modified fuzzy c-means algorithm with applications

Fuzzy c-means (FCM) clustering algorithm has been widely used in many medical image segmentations. However, the conventionally standard FCM algorithm is noise sensitive because of not taking into account the spatial information. To overcome the above problem, a novel modified FCM algorithm (called FCM-AWA later) for image segmentation is presented in this paper. The algorithm is realized by modifying the objective function in the conventional FCM algorithm, i.e., by incorporating the spatial neighborhood information into the standard FCM algorithm. An adaptive weighted averaging (AWA) filter is given to indicate the spatial influence of the neighboring pixels on the central pixel. The parameters (weighting coefficients) of control template (neighboring widow) are automatically determined in the implementation of the weighted averaging image by a predefined nonlinear function. The presented algorithm is applied to both artificial synthesized image and real image. Furthermore, the quantifications of dental plaque using proposed algorithm-based segmentation were conducted. Experimental results show that the presented algorithm performs more robust to noise than the standard FCM algorithm and another FCM algorithm (proposed by Ahmed) do. Furthermore, the results of dental plaque quantification using proposed method indicate the FCM-AWA provides a quantitative, objective and efficient analysis of dental plaque, and possesses great promise.

Validation of a New Dental Plaque Quantification Method in Dogs

Current methods for the quantification of plaque accumulation in cats and dogs are well-accepted adaptations of traditional human models, but have required substantial modifications in order to compensate for the inherent differences in compliance, cooperation, and temperament between animals and humans. While these modifications have sought to maintain or improve upon the accuracy and reproducibility of the original methods, they also have increased the complexity of the technique and have required additional scorer time and animal cooperation, which leads to increased cost of trials. Therefore, research was directed toward the development and validation of a new substrate scoring system that reduces resources while maintaining or increasing the reproducibility attributed to the more traditional methods. This new gingival contour plaque index was shown to be accurate and reproducible, but used fewer animals, required less time, and eliminated the need for many of the specialized procedures required by traditional methods.

Quantification of dental plaque in the research environment

To review the established and novel methods of plaque quantification employed in dental research, including a discussion of their merits and to present a new method of planimetrically measuring plaque using light induced fluorescence. Quantitative light-fluorescence (QLF) images were acquired from the buccal surfaces of an individual who had refrained from oral hygiene both with and without traditional plaque disclosure. Digital photographs were also taken. Images were analysed using a novel method and a percentage plaque index produced. Traditional plaque indices are problematic due to their integral nature and their failure to detect small, but potentially clinically relevant changes in plaque area. The use of a fluorescent technique demonstrated good reliability although there was no correlation between red fluorescent plaque and total disclosed plaque suggesting that the auto-fluorescing plaque is not a good measure of total plaque volume. The use of planimetric techniques can increase the power of plaque studies, potentially reducing the number of subjects and time required to separate therapies or products. Fluorescent methods of quantification have potential as they enable clear separation of the plaque covered and non-covered tooth surfaces.

The quantification of dental plaque using an image analysis system: reliability and validation

Established clinical indices used to measure dental plaque have limitations. The aim of this study was to develop and evaluate a new method of quantitative plaque measurement, with increased sensitivity and reproducibility, using a purpose designed image analysis system. After plaque disclosure, the patient was positioned in a cephalometric head holder mounted in a custom-built frame with standard lighting and camera position. A 32-bit Digital Camera grabbed the image of the patient's teeth, which was analysed using Adobe Photoshop (V5.02, Adobe Systems Ltd, Europe) and Image Pro Plus software (V4.0, Media Cybernetics, USA). Measurements were made on 120 incisors in 15 patients and reproducibility was assessed using Fliess' Coefficient of Reliability. Sensitivity was assessed by comparison of results of treatment effects from a clinical trial involving 30 patients. Analysis of covariance was used to compare the image analysis system with the Turesky modification of the Quigley and Hein plaque index and the Addy plaque area index. The results were within the 'Excellent Reliability' category, for inter-operator reproducibility and intra-operator repeatability. This new system provided accurate quantitative measurements of dental plaque and labial tooth surfaces and was shown to have increased sensitivity when compared with the Turesky modification of the Quigley and Hein plaque index and the Addy plaque area index. The stored images can be re-measured for reliability and comparability between studies.

The quantification of dental plaque using an image analysis system: reliability and validation

AbstractAim: Established clinical indices used to measure dental plaque have limitations. The aim of this study was to develop and evaluate a new method of quantitative plaque measurement, with increased sensitivity and reproducibility, using a purpose designed image analysis system.Method: After plaque disclosure, the patient was positioned in a cephalometric head holder mounted in a custom‐built frame with standard lighting and camera position. A 32‐bit Digital Camera grabbed the image of the patient’s teeth, which was analysed using Adobe Photoshop (V5.02, Adobe Systems Ltd, Europe) and Image Pro Plus software (V4.0, Media Cybernetics, USA). Measurements were made on 120 incisors in 15 patients and reproducibility was assessed using Fliess’ Coefficient of Reliability. Sensitivity was assessed by comparison of results of treatment effects from a clinical trial involving 30 patients. Analysis of covariance was used to compare the image analysis system with the Turesky modification of the Quigley and Hein plaque index and the Addy plaque area index.Results: The results were within the ‘Excellent Reliability’ category, for inter‐operator reproducibility and intra‐operator repeatability.Conclusions: This new system provided accurate quantitative measurements of dental plaque and labial tooth surfaces and was shown to have increased sensitivity when compared with the Turesky modification of the Quigley and Hein plaque index and the Addy plaque area index. The stored images can be re‐measured for reliability and comparability between studies.