Background: The difference in autofluorescence between enamel and dentine layer has prompted recommendations to use the quantitative light-induced fluorescence (QLF) method for quantifying tooth wear (TW). This study investigated the potential of QLF for distinguishing the severity of occlusal TW based on differences in the autofluorescence intensity. Methods: In total, 106 extracted permanent molars and premolars having suspected wear without pulp exposure were used. The severity of wear was determined by visually examining all teeth using the tooth wear index (TWI) of Smith and Knight. QLF images were captured and converted into 8-bit grayscale images. The difference in the fluorescence intensity (ΔG) was calculated by comparing mean grayscale levels between sound and worn areas. Finally, histological examination was conducted by stereomicroscope to confirm the presence of dentine exposure. Results: 100 teeth were included in the final analysis without six teeth having enamel cracks around worn area. The ΔG values increased with the severity of TW as quantified using conventional TWI codes, and differed significantly between the sound and enamel- and dentine-wear teeth (P < 0.001). The histology indicated that enamel remained on 57 teeth, while 43 teeth had dentine-exposed wear and showed significant differences in ΔG compared with enamel-remained teeth. Conclusions: The fluorescence intensity differed significantly depending on the presence of dentine exposure. ΔG could be used to distinguish between sound and enamel- and dentine-wear teeth with a significant correlation. These findings indicate that QLF could be useful for determining the severity of TW of occlusal surfaces noninvasively.
Bibliographical noteFunding Information:
This study was supported by a grant from the Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry and Fisheries (IPET) through High Value-added Food Technology Development Program, funded by Ministry of Agriculture, Food and Rural Affairs (MAFRA) ( 31607103HD020 ).
© 2019 Elsevier B.V.
All Science Journal Classification (ASJC) codes
- Pharmacology (medical)