OBJECTIVES This in vitro study explored quantitative outcome measures as clinical indicators of simulated occlusal tooth wear progression. METHODS Ten sound, extracted human premolars were selected and submitted to occlusal… Click to show full abstract
OBJECTIVES This in vitro study explored quantitative outcome measures as clinical indicators of simulated occlusal tooth wear progression. METHODS Ten sound, extracted human premolars were selected and submitted to occlusal tooth wear simulation in 0.5-mm steps (0/0.5/1.0/1.5 mm). At each step, enamel thickness on the buccal cusp tips was evaluated using cross-polarization optical coherence tomography (CP-OCT) and micro-computed tomography (μ-CT). The occlusal surface of each premolar was also scanned at each step using a 3D digital intraoral scanner, followed by morphological characterization using standard topography attributes (Slope, Relief, RFI, OPCr). Repeated measures ANOVA assessed differences in simulated wear levels for the µ-CT and CP-OCT data as well as the topography values. Correlations were also calculated between the µ-CT/CP-OCT and topography data RESULTS: : Significant differences were observed for enamel thickness at each simulation wear stage, for both CP-OCT (p < 0.001) and μ-CT (p < 0.001), with good agreement between methods (intraclass correlation: 0.89). For topography analysis, as wear increased, the average Slope, RFI, and Relief values decreased, and average OPCr values increased, with more significant differences shown for Slope. Slope showed significant (p < 0.05) positive correlations with CP-OCT. OPCr showed significant negative correlations with µ-CT, and CP-OCT (p < 0.05). RFI and Relief were not correlated with either µ-CT or CP-OCT (p > 0.05). CONCLUSIONS Our findings suggest the potential of PS-OCT for measuring enamel thickness changes in the cusp tips of the occlusal surface. Similarly, conventional intraoral scanners can serve effectively for monitoring overall tooth wear when combined with dental topographic analyses of resultant point clouds.
               
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