IADR Abstract Archives
Autofluorescent properties of bovine teeth during demineralisation – A Pilot Study
Objectives:
The aim of this study was to explore the relationship between the mineral and organic components of mineralised tissue and their role in autofluorescence.
Methods:
Twelve specimens were prepared from bovine teeth and immersed in 10% nitric acid for a total of eight 1hour cycles. Data was acquired at baseline and every hour until demineralisation was complete. Each sample was illuminated with a 405nm exciting light. Fluorescent images were captured using a QLF-D BiluminatorTM (Inspektor, Amsterdam, Netherlands). Also, the spectra of the fluorescence was acquired with the NuanceTM Multispectral Imaging System, (CRi, Woburn, USA), between 420 - 720 nm. The percentage of fluorescence loss (ΔF) was calculated using QA2 image analysis software (Inspektor, Amsterdam, Netherlands), and statistically tested for correlation with the NuanceTM data using the Pearson correlation coefficient (r). The means of both methods of fluorescence detection were calculated at each cycle. Complete demineralisation was assessed by radiography. Then the specimens were analysed using Raman spectrometry.
Results:
Both methods detected and quantified loss of fluorescence. The Pearson coefficients (r) QLF-D/ NuanceTM was 0.902 (95%CI 0.851 to 0.936). The NuanceTM detected higher and more specific ΔF values than QLF-D. At the last demineralisation cycle, NuanceTM mean value was -80.89 (± 9.45), QLF-D mean -65.65, (± 18.04). At the complete demineralisation stage the remaining fluorescence is related to the presence of collagen as shown by Raman spectrometry.
Conclusions:
Both methods show a high correlation between the fluorescence intensity and the presence of mineralised tissue. NuanceTM can also detect the autofluorescent properties of collagen. The autofluorescence of mineralised tissues is directly related to the presence of collagen and the intensity of the autofluorescence is linked to the degree of mineralisation. However, further work is required to fully understand the exact origin and its properties.
The aim of this study was to explore the relationship between the mineral and organic components of mineralised tissue and their role in autofluorescence.
Methods:
Twelve specimens were prepared from bovine teeth and immersed in 10% nitric acid for a total of eight 1hour cycles. Data was acquired at baseline and every hour until demineralisation was complete. Each sample was illuminated with a 405nm exciting light. Fluorescent images were captured using a QLF-D BiluminatorTM (Inspektor, Amsterdam, Netherlands). Also, the spectra of the fluorescence was acquired with the NuanceTM Multispectral Imaging System, (CRi, Woburn, USA), between 420 - 720 nm. The percentage of fluorescence loss (ΔF) was calculated using QA2 image analysis software (Inspektor, Amsterdam, Netherlands), and statistically tested for correlation with the NuanceTM data using the Pearson correlation coefficient (r). The means of both methods of fluorescence detection were calculated at each cycle. Complete demineralisation was assessed by radiography. Then the specimens were analysed using Raman spectrometry.
Results:
Both methods detected and quantified loss of fluorescence. The Pearson coefficients (r) QLF-D/ NuanceTM was 0.902 (95%CI 0.851 to 0.936). The NuanceTM detected higher and more specific ΔF values than QLF-D. At the last demineralisation cycle, NuanceTM mean value was -80.89 (± 9.45), QLF-D mean -65.65, (± 18.04). At the complete demineralisation stage the remaining fluorescence is related to the presence of collagen as shown by Raman spectrometry.
Conclusions:
Both methods show a high correlation between the fluorescence intensity and the presence of mineralised tissue. NuanceTM can also detect the autofluorescent properties of collagen. The autofluorescence of mineralised tissues is directly related to the presence of collagen and the intensity of the autofluorescence is linked to the degree of mineralisation. However, further work is required to fully understand the exact origin and its properties.