Deborah Kreher1, Kyung-Jin Park1, Gerhard Schmalz1, Ellen Schulz-Kornas1, Rainer Haak1, Dirk Ziebolz2. 1. Department of Cariology, Endodontology and Periodontology, University of Leipzig, Liebigstr. 12, Leipzig 04103, Germany. 2. Department of Cariology, Endodontology and Periodontology, University of Leipzig, Liebigstr. 12, Leipzig 04103, Germany. Electronic address: dirk.ziebolz@medizin.uni-leipzig.de.
Abstract
BACKGROUND: This in vitro study aimed to assess carious lesions on root surfaces using quantitative light-induced fluorescence (QLF) and to compare the readings with axial lesion depth on µCT. METHODS: The root surfaces of 107 extracted human teeth were included after visual-tactile inspection. For further analysis, the following parameters were assessed: clinical findings (non-cavitated: leathery or hard, cavitated), QLF- (QLF-D Biluminator 2+), and µCT-images (Bruker Skyscan 1172). The shape of the undamaged tooth surface of the cavitated lesions was virtually re-constructed during µCT analysis. Clinical surface texture,% fluorescence loss, and lesion depth (µCT) were determined. STATISTICAL ANALYSIS: chi²-test, Spearman-Rho test, regression analysis. RESULTS: ∆F was significantly lower in non-cavitated leathery (-50.37 ± 15.10) and cavitated (-61.23 ± 9.92) compared to non-cavitated surfaces with a hard texture (-17.04 ± 16.10, p < 0.01). For non-cavitated surfaces, a negative correlation was observed between ∆F and lesion depth in µCT images regardless of texture (-0.748, p < 0.01). Regression analysis revealed that ∆F predicted lesion depth in µCT for non-cavitated surfaces (β: 0.703, CI95: 0.67--0.43, p < 0.01). CONCLUSION: The percentage of fluorescence loss (∆F) in QLF predicted lesion depth of non-cavitated demineralized root surfaces. Therefore, QLF can be recommended for estimating the lesion depth of carious root lesions and seems to expand the possibilities of follow-up and lesion monitoring, especially for non-cavitated surfaces.
BACKGROUND: This in vitro study aimed to assess carious lesions on root surfaces using quantitative light-induced fluorescence (QLF) and to compare the readings with axial lesion depth on µCT. METHODS: The root surfaces of 107 extracted human teeth were included after visual-tactile inspection. For further analysis, the following parameters were assessed: clinical findings (non-cavitated: leathery or hard, cavitated), QLF- (QLF-D Biluminator 2+), and µCT-images (Bruker Skyscan 1172). The shape of the undamaged tooth surface of the cavitated lesions was virtually re-constructed during µCT analysis. Clinical surface texture,% fluorescence loss, and lesion depth (µCT) were determined. STATISTICAL ANALYSIS: chi²-test, Spearman-Rho test, regression analysis. RESULTS: ∆F was significantly lower in non-cavitated leathery (-50.37 ± 15.10) and cavitated (-61.23 ± 9.92) compared to non-cavitated surfaces with a hard texture (-17.04 ± 16.10, p < 0.01). For non-cavitated surfaces, a negative correlation was observed between ∆F and lesion depth in µCT images regardless of texture (-0.748, p < 0.01). Regression analysis revealed that ∆F predicted lesion depth in µCT for non-cavitated surfaces (β: 0.703, CI95: 0.67--0.43, p < 0.01). CONCLUSION: The percentage of fluorescence loss (∆F) in QLF predicted lesion depth of non-cavitated demineralized root surfaces. Therefore, QLF can be recommended for estimating the lesion depth of carious root lesions and seems to expand the possibilities of follow-up and lesion monitoring, especially for non-cavitated surfaces.