Objectives: To determine whether quantitative light-induced fluorescence (QLF) technology can be used to classify the colour of teeth specimens before and after resin infiltration (RI) treatment, and calculate the correlation between the δF value and colour difference (δE) in fluorescence images of the specimens obtained using a QLF-digital (QLF-D) device. Methods: Sixty sound bovine permanent teeth specimens were immersed in demineralized solution. Two exposed windows were formed in each specimen, and RI treatment was applied to one of them. The δE values were obtained for the differences between a sound tooth surface (SS), an early dental caries surface (ECS) and an ECS treated with RI (RS) in white-light and fluorescence images obtained using QLF-D, respectively. The δF value was obtained from fluorescence images using dedicated software for QLF-D. The mean differences between the δE values obtained from the white-light and fluorescence images were analyzed by paired t-test. Pearson correlation analysis and Bland-Altman plots were applied to the differences between the δF value for ECS (δFSS-ECS) and the δE value between SS and ECS (δESS-ECS), and between the δF value for RS (δFSS-RS) and the δE value between SS and RS (δESS-RS) in fluorescence images. Results: The δE values obtained from fluorescence images were three times higher than the δE values obtained from white-light images (p < 0.001). Significant correlations were confirmed between δESS-ECS and δFSS-ECS (r = -0.492, p < 0.001) and between δESS-RS and δFSS-RS (r = -0.661, p < 0.001). Conclusion: QLF technology can be used to confirm the presence of RI in teeth.
|Number of pages||5|
|Journal||Photodiagnosis and Photodynamic Therapy|
|Publication status||Published - 2016 Sept 1|
Bibliographical noteFunding Information:
This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI) , funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI15C0889 )
© 2016 Elsevier B.V.
All Science Journal Classification (ASJC) codes
- Pharmacology (medical)