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Detection of pit and fissure sealant microleakage using autofluorescence
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Abstract
Objectives
The aim of this study was to evaluate the feasibility of detecting the presence and severity of microleakage of pit and fissure sealant using Quantitative Light-induced Fluorescence (QLF) technology.
Methods
The areas of interest (AOI) were a total of 160 pit and fissure sites obtained from the occlusal surfaces of 40 permanent teeth. Fluorescent images were acquired using a QLF device, and the ΔFmax of each AOI was analysed. After staining and cross-sectioning of the teeth, histological dye penetration was scored on a 0–3 scale. The relationship between ΔFmax and microleakage depth was analysed, and the areas under the curve (AUC) were calculated.
Results
ΔFmax showed a significant increase as microleakage depth increased, and a strong correlation with histological scores (r = -0.72, P < 0.001). ΔFmax increased 2.6 times between a sound sealant margin and severe dye penetration. AUC analysis showed a high diagnostic accuracy of microleakage depth (AUC = 0.83–0.91). The AUC that differentiated the outer half microleakage of the sealant (histological score 0 vs 1–3) was the highest at 0.91.
Conclusions
The use of autofluorescence detection based on QLF technology enabled the detection of microleakages in sealants non-destructively and demonstrated excellent diagnostic validity.
Title: Detection of pit and fissure sealant microleakage using autofluorescence
Description:
Abstract
Objectives
The aim of this study was to evaluate the feasibility of detecting the presence and severity of microleakage of pit and fissure sealant using Quantitative Light-induced Fluorescence (QLF) technology.
Methods
The areas of interest (AOI) were a total of 160 pit and fissure sites obtained from the occlusal surfaces of 40 permanent teeth.
Fluorescent images were acquired using a QLF device, and the ΔFmax of each AOI was analysed.
After staining and cross-sectioning of the teeth, histological dye penetration was scored on a 0–3 scale.
The relationship between ΔFmax and microleakage depth was analysed, and the areas under the curve (AUC) were calculated.
Results
ΔFmax showed a significant increase as microleakage depth increased, and a strong correlation with histological scores (r = -0.
72, P < 0.
001).
ΔFmax increased 2.
6 times between a sound sealant margin and severe dye penetration.
AUC analysis showed a high diagnostic accuracy of microleakage depth (AUC = 0.
83–0.
91).
The AUC that differentiated the outer half microleakage of the sealant (histological score 0 vs 1–3) was the highest at 0.
91.
Conclusions
The use of autofluorescence detection based on QLF technology enabled the detection of microleakages in sealants non-destructively and demonstrated excellent diagnostic validity.
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