Comparison of red autofluorescing plaque and disclosed plaque-a cross-sectional study

A scoping review of new technologies for dental plaque quantitation: Benefits and limitations

OBJECTIVES

To determine the validity and reliability of novel digitalized tools for dental plaque detection and explore the benefits and limitations connected to their use.

DATA

Reporting followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Extension for Scoping Reviews. All human clinical studies comparing dental plaque detection using digitalized systems against a standard reference were included.

SOURCES

PubMed and Scopus were screened from 01 January 2013 to 28 September 2023. Bibliographies of primary studies and principal peer-reviewed scientific journals were manually searched.

STUDY SELECTION

The initial search identified 576 articles, with a total of 13 included in the review, published between 2015 and 2023. Most of the studies included (77 %) were cross-sectional with three being prospective. Digital devices captured 2D and 3D images via cameras and intra-oral scanners, respectively. The Turesky's modified plaque index was the most frequent clinical index. Correlation with clinical examination was moderate to strong, with good to excellent intra- and inter-system agreement.

CONCLUSIONS

Within the limitations of this scoping review, image analysis-based plaque detection systems demonstrated good correlations with clinical plaque indices, using both 2D and 3D imaging systems. Whilst digital plaque detection devices offer advantages in terms of procedural standardization and reproducibility, they also have limitations, therefore currently, their application should be underpinned by a comprehensive clinical examination.

CLINICAL SIGNIFICANCE

Digital plaque detection tools, that provide standardized measurements and store acquired images, facilitate more informed feedback to patients. This objective analysis may enhance clinician confidence in their utility for clinical trials and other applications.

Methods for Evaluating the Effectiveness of Home Oral Hygiene Measures-A Narrative Review of Dental Biofilm Indices

Dental plaque is a biofilm structured in an extracellular matrix of polymers of host and microbial origin; the microorganisms can coexist in harmony with the host, thus guarantying oral health. Environmental modifications can lead to dysbiosis and onset of oral diseases; in fact, plaque is the etiological agent both of periodontal disease and dental decay. The use of an effective oral hygiene index should be considered as a relevant goal for the clinicians and the researchers, and consequently, numerous plaque indices have been proposed during the years. The present literature review aims primarily to obtain a complete summary of these scores to assess plaque deposits. It is useful because the clinician/researcher will select the right scoring method for the specific situation only if he knows the available options and if he is aware of both their strengths and weaknesses. This review applies a basic classification of plaque indices that distinguishes the ones that use non-quantitative methods from the ones that use quantitative methods. Non-quantitative methods are more subjective because they are based on the ability of the clinician to point out the presence or the entity of deposits, while quantitative methods introduce objectifiable means to measure plaque deposits.

Artificial Intelligence Its Uses and Application in Pediatric Dentistry: A Review

In the global epidemic era, oral problems significantly impact a major population of children. The key to a child’s optimal health is early diagnosis, prevention, and treatment of these disorders. In recent years, the field of artificial intelligence (AI) has seen tremendous pace and progress. As a result, AI’s infiltration is witnessed even in those areas that were traditionally thought to be best left to human specialists. The ultimate ability to improve patient care and make precise diagnoses of illnesses has revolutionized the world of healthcare. In the field of dentistry, the competence to execute treatment measures while still providing appropriate patient behavior counseling is in high demand, particularly in the field of pediatric dental care. As a result, we decided to conduct this review specifically to examine the applications of AI models in pediatric dentistry. A comprehensive search of the subjects was done using a wide range of databases to look for studies that have been published in peer-reviewed journals from its inception until 31 December 2022. After the application of the criteria, only 25 of the 351 articles were taken into consideration for this review. According to the literature, AI is frequently used in pediatric dentistry for the purpose of making an accurate diagnosis and assisting clinicians, dentists, and pediatric dentists in clinical decision making, developing preventive strategies, and establishing an appropriate treatment plan.

Precision periodontal care: from omics discoveries to chairside diagnostics

The interface of molecular science and technology is guiding the transformation of personalized to precision healthcare. The application of proteomics, genomics, transcriptomics, and metabolomics is shaping the suitability of biomarkers for disease. Prior validation of such biomarkers in large and diverse patient cohorts helps verify their clinical usability. Incorporation of molecular discoveries into routine clinical practice relies on the development of customized assays and devices that enable the rapid delivery of analytical data to the clinician, while the patient is still in session. The present perspective review addresses this topic under the prism of precision periodontal care. Selected promising research attempts to innovate technological platforms for oral diagnostics are brought forward. Focus is placed on (a) the suitability of saliva as a conveniently sampled biological specimen for assessing periodontal health, (b) proteomics as a high-throughput approach for periodontal disease biomarker identification, and (c) chairside molecular diagnostic assays as a technological funnel for transitioning from the laboratory benchtop to the clinical point-of-care.

Detecting and monitoring dental plaque levels with digital 2D and 3D imaging techniques

Detecting and monitoring dental plaque is an important issue in research and clinical practice. In this context, new digital imaging methods that permit permanent documentation of the clinical findings could be promising tools. The aim of the study was therefore to investigate whether disclosed plaque can be reliably visualised on 2D and 3D images captured with digital intraoral imaging devices. Clinical examination was the reference method. Twenty subjects (27.5±1.2 years) were included and plaque was measured at three different stages: habitual plaque (T1), after 72 h without oral hygiene (T2) and after a subsequent habitual brushing exercise (T3). At each time point, plaque was disclosed followed by the clinical examination and capturing the 2D and 3D images (intraoral-camera CS 1500 and intraoral-scanner CS 3600; Carestream Dental, Germany). Plaque amounts were recorded on oral and vestibular surfaces of the Ramfjord-teeth (16, 21, 24, 36, 41, 44) using the Rustogi-modified-Navy-Plaque-Index (RMNPI) and expressed as percentage of plaque-containing RMNPI areas of all RMNPI areas. At T1, percentages (mean±SD) obtained from the clinical examination, 2D and 3D images were 62.2±10.6, 65.1±10.0 and 64.4±10.6 resp. increasing to 76.9±8.0, 77.9±8.6 and 77.5±9.4 resp. at T2. After toothbrushing (T3), values decreased to 56.3±11.1, 58.2±12.1 and 61.2±10.8 resp. All methods were able to show statistically significant changes in plaque amounts at the different time points with in part statistically significant but minor differences between them. The Bland-Altmann analysis revealed a good agreement between values from both 2D and 3D images with the clinical examination. The agreement of the scores obtained with the both image-based methods for the single RMNPI areas with the clinical examination was mainly classified as substantial to almost perfect. Amounts of plaque can be reliably detected and monitored on 2D images from an intraoral camera and on 3D images from an intraoral scanner.

Are oral hygiene instructions with aid of plaque-disclosing methods effective in improving self-performed dental plaque control? A systematic review of randomized controlled trials

OBJECTIVES

To systematically evaluate the literature on whether plaque-disclosing (PD) methods, applied by dental professionals (FQ1) or at-home (FQ2), combined with verbal oral hygiene instructions and brushing demonstration (standard OHI) lead to improvements in self-performed dental plaque control in comparison to standard OHI alone.

MATERIALS AND METHODS

Seven databases were searched by two independent reviewers according to pre-specified eligibility criteria up to September 2020. No restrictions regarding language, date and type of report were imposed. The Cochrane Collaboration's Risk of Bias tool (RoB 2.0) was used for quality appraisal. Multiple comparisons referring to a single study were included if the articles evaluated different PD agents. Narrative synthesis using evidence tables were performed.

RESULTS

Seven eligible studies were retrieved, including data of 430 individuals (159 wearers of orthodontic appliances). The studies exhibited considerable heterogeneity regarding outcome assessments and follow-up. Eleven (eight corresponding to FQ1 and three to FQ2) out of 13 relevant comparisons found no significant difference between techniques for dental plaque outcomes and three (two corresponding to FQ1 and one to FQ2) out of five comparisons indicated a positive effect of standard OHI with aid of PD methods on gingival inflammation scores. With respect specifically to orthodontic patients, three out of four comparisons indicated significant improvements on gingival inflammation scores for individuals instructed with PD methods.

CONCLUSION

Clinicians should consider PD agents as adjunct to standard OHI in orthodontic patients. For those without appliances, PD methods can be used as an alternative.

Arrest of root caries with an adjuvant chlorhexidine-fluoride varnish over a 12-months observation period: a QLF-analyzed, placebo-controlled, randomized, clinical trial (RCT)

This study aimed at evaluating the effectiveness of an adjuvant chlorhexidine–fluoride varnish (Cervitec F) for prevention and arrest of root caries on elderly participants using quantitative light-induced fluorescence (QLF). 23 participants with two or three non-cavitated root carious lesions were included and assigned to three groups of different varnishes (CF: Cervitec F, P: placebo, DP: Duraphate). Agents were applied once to root surface at baseline and in follow-up after 3, 6 and 9 months. The lesions were assessed clinically and with QLF. QLF-images were analyzed regarding fluorescence loss (ΔF), lesion volume (ΔQ) and bacterial activity (ΔR) before (t₀), after 14 days (t₁), 6- (t₂) and 12-months (t₃). CF showed a significant difference between t₀ and t₃: ∆F (− 12.51 [15.41] vs. − 7.80 [16.72], p = 0.012), ∆Q (− 2339.97 (20,898.30) vs. − 751.82 (5725.35), p < 0.001), ∆R (23.80 [41.70] vs. 7.07 [37.50], p = 0.006). Independently of the varnish application, preventive care seems positively influence the root caries progress. Although within CF group the strongest effect was observed, no superiority of a specific varnish application was confirmed over a 12-months QLF observation period. Extra topical fluoride can help remineralise dentin lesions and QLF can be used as a measurement method to determine changes in the dentin lesions.

Use of wide-field optical fluorescence for visualization of oral biofilm in a patient with peri-implant mucositis: a new approach

Peri-implant diseases, caused by bacteria from biofilm related to dental implants, are one of the main causes of late loss of implants. In this sense, peri-implant diseases are divided into peri-implant mucositis, when it affects only the soft tissues, and peri-implantitis, when there is a bone involvement, which can lead to the failure of dental implant therapy. Thus, biofilm removal is essential for peri-implant health, allowing long-term success in implant therapy. To improve the visualization of oral biofilm, which is usually transparent or colorless, disclosing agents have been routinely used. However, disclosing agents have allergenic potential and can cause staining extrinsically in restorative and prosthetic materials, leading to aesthetic impairment. Thus, the use of fluorescence has been studied as an alternative for visualization of oral biofilm. Therefore, this report describes the use of wide-field optical fluorescence for visualization of oral biofilm associated with implants and teeth, in a routine appointment and follow-up of a partially edentulous patient with peri-implant mucositis. In addition, this report showed wide-field optical fluorescence can be used in a clinical routine of care of patients with dental implants. In this sense, wide-field optical fluorescence allowed easy and immediate visualization of the mature oral biofilm for its adequate removal, evaluation of the quality of restoration to sealing of screw access-hole of implant and identification of cariogenic lesions, without risk of allergic reactions or staining of prostheses and restorations.

Light-Induced Fluorescence-Based Device and Hybrid Mobile App for Oral Hygiene Management at Home: Development and Usability Study

Background

Dental diseases can be prevented through the management of dental plaques. Dental plaque can be identified using the light-induced fluorescence (LIF) technique that emits light at 405 nm. The LIF technique is more convenient than the commercial technique using a disclosing agent, but the result may vary for each individual as it still requires visual identification.

Objective

The objective of this study is to introduce and validate a deep learning–based oral hygiene monitoring system that makes it easy to identify dental plaques at home.

Methods

We developed a LIF-based system consisting of a device that can visually identify dental plaques and a mobile app that displays the location and area of dental plaques on oral images. The mobile app is programmed to automatically determine the location and distribution of dental plaques using a deep learning–based algorithm and present the results to the user as time series data. The mobile app is also built with convergence of naive and web applications so that the algorithm is executed on a cloud server to efficiently distribute computing resources.

Results

The location and distribution of users’ dental plaques could be identified via the hand-held LIF device or mobile app. The color correction filter in the device was developed using a color mixing technique. The mobile app was built as a hybrid app combining the functionalities of a native application and a web application. Through the scrollable WebView on the mobile app, changes in the time series of dental plaque could be confirmed. The algorithm for dental plaque detection was implemented to run on Amazon Web Services for object detection by single shot multibox detector and instance segmentation by Mask region-based convolutional neural network.

Conclusions

This paper shows that the system can be used as a home oral care product for timely identification and management of dental plaques. In the future, it is expected that these products will significantly reduce the social costs associated with dental diseases.

Clinical assessment of an automated fluorescent plaque index scoring with quantitative light-induced fluorescence

OBJECTIVE

The aims of this study were to evaluate the clinical applicability of a new fluorescent plaque index scoring (FPI) with the Turesky modified Quigley-Hein plaque index (mQH) and to evaluate its relationship with plaque maturity.

METHODS

In total 69 subjects participated in this study. White-light and fluorescent images of anterior teeth were acquired using a Qraycam (AIOBIO, Seoul, Korea). FPI was obtained from fluorescent images using the proprietary software (Q-Ray v.1.39, Inspektor Research System BV, Amsterdam, The Netherlands). Teeth were stained with a two-tone disclosing agent. mQH was used to manually score the combined red and blue disclosed plaque (Combi-mQH) and blue disclosed plaque (Blue-mQH) with the white-light images. Linear relationships between FPI and Combi-mQH (or Blue-mQH) were evaluated by using simple linear regression analysis. Differences of Combi-mQH (or Blue-mQH) with respect to FPI scores were statistically evaluated by using ANOVA with Duncan post hoc correction.

RESULTS

FPI showed a moderate positive correlation with Combi-mQH (r = 0.66, P < 0.001) and a high positive correlation with Blue-mQH (r = 0.78, P < 0.001). The model explanatory power (R²) between FPI and Blue-mQH was 60.8 %, which is 16.8 % higher than the explanatory power observed with Combi-mQH (44.0 %). Both Combi-mQH and Blue-mQH increased significantly with increasing FPI score (P < 0.001).

CONCLUSION

In this study we found that the FPI scoring system can be used to detect plaque and quantitatively distinguish plaque levels. In addition, FPI was determined to be useful in clinic because of its ability to detect and distinguish old and mature plaque.

Deep learning-based dental plaque detection on primary teeth: a comparison with clinical assessments

BACKGROUND

Dental plaque causes many common oral diseases (e.g., caries, gingivitis, and periodontitis). Therefore, plaque detection and control are extremely important for children's oral health. The objectives of this study were to design a deep learning-based artificial intelligence (AI) model to detect plaque on primary teeth and to evaluate the diagnostic accuracy of the model.

METHODS

A conventional neural network (CNN) framework was adopted, and 886 intraoral photos of primary teeth were used for training. To validate clinical feasibility, 98 intraoral photos of primary teeth were assessed by the AI model. Additionally, tooth photos were acquired using a digital camera. One experienced pediatric dentist examined the photos and marked the regions containing plaque. Then, a plaque-disclosing agent was applied, and the areas with plaque were identified. After 1 week, the dentist drew the plaque area on the 98 photos taken by the digital camera again to evaluate the consistency of manual diagnosis. Additionally, 102 intraoral photos of primary teeth were marked to denote the plaque areas obtained by the AI model and the dentist to evaluate the diagnostic capacity of each approach based on lower-resolution photos. The mean intersection-over-union (MIoU) metric was employed to indicate detection accuracy.

RESULTS

The MIoU for detecting plaque on the tested tooth photos was 0.726 ± 0.165. The dentist's MIoU was 0.695 ± 0.269 when first diagnosing the 98 photos taken by the digital camera and 0.689 ± 0.253 after 1 week. Compared to the dentist, the AI model demonstrated a higher MIoU (0.736 ± 0.174), and the results did not change after 1 week. When the dentist and the AI model assessed the 102 intraoral photos, the MIoU was 0.652 ± 0.195 for the dentist and 0.724 ± 0.159 for the model. The results of a paired t-test found no significant difference between the AI model and human specialist (P > .05) in diagnosing dental plaque on primary teeth.

CONCLUSIONS

The AI model showed clinically acceptable performance in detecting dental plaque on primary teeth compared with an experienced pediatric dentist. This finding illustrates the potential of such AI technology to help improve pediatric oral health.

Discoloration of surface sealants by plaque disclosing solution

Purpose

Surface sealants are widely used as a prevention strategy and are indicated for young patients with insufficient oral hygiene who also need plaque removal by professional tooth cleaning. The aim of this study was to evaluate discoloration of surface sealants by plaque disclosing solutions and to test to what extent this discoloration can be reduced again by professional tooth cleaning.

Methods

In all, 96 extracted lesion-free human teeth were randomly assigned to treatment with either Pro Seal® (PS; Opal Orthodontics, South Jordan, UT, USA) or Opal®Seal™ (OS; Reliance Orthodontic Products, Itasca, IL, USA). Color evaluations after application of the plaque disclosing solution Mira-2-Ton® (Hager & Werken, Duisburg, Germany) were performed using a clinical spectrophotometer. Staining and polishing were repeated once. Color differences (∆E) above 3.77 were regarded as clinically relevant.

Results

All sealants showed high, clinically relevant ∆E values after the first staining. Polishing led to significantly decreased ∆E values on PS-treated teeth; however, the median ∆E value remained above the clinically relevant threshold. Polishing on OS-treated teeth only slightly reduced ∆E values. After professional tooth cleaning both PS and OS showed clinically relevant ∆E values.

Conclusion

Surface sealants show clinically relevant discoloration after exposure to plaque disclosing solution under in vitro conditions. Such discolorations could not be removed by professional tooth cleaning. Thus, in clinical practice, plaque disclosing solutions might cause esthetic deficits in surface sealant-treated teeth. The impact of plaque disclosing solutions under clinical conditions (e.g., in the presence of saliva and by various aspects of a person’s nutrition) should be investigated in clinical 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.

Comparison of dental plaque reduction after use of electric toothbrushes with and without QLF-D-applied plaque visualization: a 1-week randomized controlled trial

Background

To evaluate the efficacy of a newly developed electric toothbrush in reducing dental plaque via a quantitative light-induced fluorescence-digital (QLF-D)-applied visualisation system in the brush head.

Methods

Participants included 20 adults aged 19 to 28 years. Participants were randomly assigned either (i) an electric toothbrush with a monitor to visualise red-fluorescent dental plaque via a camera built into the brush head (monitor usage group, n = 10) or (ii) an electric toothbrush without a monitor (monitor-non-use group, n = 10). The amount of dental plaque was assessed by personal hygiene performance (PHP) at baseline and 1 week later.

Results

In the monitor-usage group, PHP score was significantly lower at the 1-week follow-up than at baseline (6 vs 16; range, 0–12 vs 13–21; P = 0.029). This change was not observed in the monitor-non-use group (14 vs 13; range, 6–21 vs 2–26; P = 0.778). After 1 week, the change in PHP scores in the monitor usage group was significantly greater than that in the monitor non-use group (− 10 vs 0; range, − 21 to 9 vs − 8 to 16; P = 0.021).

Conclusions

Our results clearly demonstrate that brushing teeth while looking at a monitor that depicts red-autofluorescent dental plaque via application of QLF-D improved the efficacy of dental-plaque removal relative to brushing teeth without a monitor.

Trial registration

Trial registration number: UMIN000033699.

Name of registry: Study on effect of new devise for oral care on dental plaque clearance.

Date of registration: 8th September 2018.

Status of registration: Completed.

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

Background

Significant numbers of adults and children have untreated plaque due to poor oral hygiene and consequently suffer from associate dental and systemic diseases.

Methods

A 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.

Results

The 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.

Conclusions

The 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 registration

ClinicalTrials.gov NCT03379337, December 19 2017. Retrospectively registered.

Electronic supplementary material

The online version of this article (doi: 10.1186/s12903-017-0472-4) contains supplementary material, which is available to authorized users.

Tissue characterization with depth-resolved attenuation coefficient and backscatter term in intravascular optical coherence tomography images

An important application of intravascular optical coherence tomography (IVOCT) for atherosclerotic tissue analysis is using it to estimate attenuation and backscatter coefficients. This work aims at exploring the potential of the attenuation coefficient, a proposed backscatter term, and image intensities in distinguishing different atherosclerotic tissue types with a robust implementation of depth-resolved (DR) approach. Therefore, the DR model is introduced to estimate the attenuation coefficient and further extended to estimate the backscatter-related term in IVOCT images, such that values can be estimated per pixel without predefining any delineation for the estimation. In order to exclude noisy regions with a weak signal, an automated algorithm is implemented to determine the cut-off border in IVOCT images. The attenuation coefficient, backscatter term, and the image intensity are further analyzed in regions of interest, which have been delineated referring to their pathology counterparts. Local statistical values were reported and their distributions were further compared with a two-sample t-test to evaluate the potential for distinguishing six types of tissues. Results show that the IVOCT intensity, DR attenuation coefficient, and backscatter term extracted with the reported implementation are complementary to each other on characterizing six tissue types: mixed, calcification, fibrous, lipid-rich, macrophages, and necrotic core.

Red and Green Fluorescence from Oral Biofilms

Red and green autofluorescence have been observed from dental plaque after excitation by blue light. It has been suggested that this red fluorescence is related to caries and the cariogenic potential of dental plaque. Recently, it was suggested that red fluorescence may be related to gingivitis. Little is known about green fluorescence from biofilms. Therefore, we assessed the dynamics of red and green fluorescence in real-time during biofilm formation. In addition, the fluorescence patterns of biofilm formed from saliva of eight different donors are described under simulated gingivitis and caries conditions. Biofilm formation was analysed for 12 hours under flow conditions in a microfluidic BioFlux flow system with high performance microscopy using a camera to allow live cell imaging. For fluorescence images dedicated excitation and emission filters were used. Both green and red fluorescence were linearly related with the total biomass of the biofilms. All biofilms displayed to some extent green and red fluorescence, with higher red and green fluorescence intensities from biofilms grown in the presence of serum (gingivitis simulation) as compared to the sucrose grown biofilms (cariogenic simulation). Remarkably, cocci with long chain lengths, presumably streptococci, were observed in the biofilms. Green and red fluorescence were not found homogeneously distributed within the biofilms: highly fluorescent spots (both green and red) were visible throughout the biomass. An increase in red fluorescence from the in vitro biofilms appeared to be related to the clinical inflammatory response of the respective saliva donors, which was previously assessed during an in vivo period of performing no-oral hygiene. The BioFlux model proved to be a reliable model to assess biofilm fluorescence. With this model, a prediction can be made whether a patient will be prone to the development of gingivitis or caries.