"The Standard Procedure" for Investigation of Oral Neutrophils in Oral Diseases.

Aim: There is need of an objective "standard procedure" that is reliable and clinically applicable for estimating oral neutrophil content in relation to oral diseases. Methods: Forty-one patients with suspected oral candidosis (OC) and nine healthy controls with no oral mucosal disease were flushing with 10 ml mouth rinse (MR) (sterile phosphate-buffered saline) for 1 min. Aliquots were stored on different conditions to explore stability, storage, and fixation conditions for analysis by flow cytometry. Results: The optimal storage and fixation condition for MR was by fixation 1 : 1 in 10% formalin and stored at 5°C. This procedure yielded stable results up to 7 days after collection. The ability of the optimized method to relate oral neutrophils to inflammation was demonstrated by the significantly higher number of neutrophils in patients with primary OC (p = 0.0334) compared to healthy controls. Conclusion: This method is rapid, reliable, and clinically applicable for establishing the content of oral neutrophils. We demonstrate increased density of oral neutrophils in the MR of patients with OC. The potential of the method is to be "the standard procedure" for investigation of the oral inflammation in patients with oral diseases as it is noninvasive and provides high stability, clinical relevance, and minimal handling.

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.

AIM: To develop a simple and reproducible method for semi-automated planimetric quantification of dental plaque. MATERIALS AND METHODS: 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. RESULTS: 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). CONCLUSIONS: 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.