Influence of ambient temperature changes on intraoral scanning accuracy.

STATEMENT OF PROBLEM: Different variables that decrease the accuracy of intraoral scanners (IOSs) have been identified. Ambient temperature changes can occur in the dental environment, but the impact of ambient temperature changes on intraoral scanning accuracy is unknown. PURPOSE: The purpose of this in vitro study was to assess the impact of ambient temperature changes on the accuracy (trueness and precision) of an IOS. MATERIAL AND METHODS: A complete arch maxillary dentate Type IV stone cast was obtained. Four 6-mm-diameter gauge balls were added to the maxillary cast to aid future evaluation measurements. The maxillary cast was digitized by using an industrial scanner (GOM Atos Q 3D 12M). The manufacturer's recommendations were followed in obtaining a reference scan. Then, the maxillary cast was digitized by using an IOS (TRIOS 4) according to the scanning protocol recommended by the manufacturer. Four groups were created depending on the ambient temperature change assessed: 24 °C or room temperature (24-D or control group), 19 °C or a 5-degree temperature drop (19-D group), 15 °C or a 9-degree temperature drop (15-D group), and 29 °C or a 5-degree temperature rise (29-D group). The Shapiro-Wilk and Kolmogorov-Smirnov tests revealed that the data were not normally distributed (P<.05). For trueness, the nonparametric Kruskal-Wallis followed by the Dwass-Steel-Critchlow-Fligner pairwise comparison tests were used. Precision analysis was obtained by using the Levene test based on the comparison of the standard deviations of the 4 groups with 95% Bonferroni confidence intervals for standard deviations (α=.05). RESULTS: The Kruskal-Wallis test revealed significant differences in the trueness values among all 4 groups (P<.001). Furthermore, significant differences between the linear discrepancy medians between the control and 19-D groups (P<.001), control and 15-D groups (P=.002), control and 29-D groups (P<.001), 19-D and 29-D groups (P=.003), and 15-D and 29-D groups (P<.001) were found. The Levene test for the comparison of the variances among the 4 groups did not detect a significant difference (P>.999), indicating that precision wise the 4 groups were not significantly different from each other. CONCLUSIONS: Ambient temperature changes had a detrimental effect on the accuracy (trueness and precision) of the IOS tested. Ambient temperature changes significantly decreased the scanning accuracy of the IOS system tested. Increasing the ambient temperature has a greater influence on the intraoral scanning accuracy of the IOS selected when compared with decreasing the ambient temperature.

Best-Fit Algorithm Influences on Virtual Casts' Alignment Discrepancies.

PURPOSE: To measure the influence of best-fit (BF) algorithms (entire dataset, 3 or 6 points landmark-based, or section-based BF) on virtual casts and their alignment discrepancies. MATERIAL AND METHODS: A mandibular typodont was obtained and digitized by using an industrial scanner (GOM Atos Q 3D 12M). A control mesh was acquired. The typodont was digitized by using an intraoral scanner (TRIOS 4). Based on the alignment procedures, four groups were created: BF of the entire dataset (BF group), landmark-based BF using 3 reference points (LBF-3 group), or 6 reference points (LBF-6 group), and section-based BF (SBF group). The root mean square (RMS) error was calculated. One-way ANOVA and post hoc pairwise multi-comparison Tukey were used to analyze the data (α = 0.05). RESULTS: Significant RMS error mean value differences were found across the groups (p < 0.001). Tukey test revealed significant RMS error mean value differences between the BF and LBF-3 groups (p = 0.022), BF and LBF-6 groups (p < 0.001), LB-3 and LB-6 groups (p < 0.001), LBF-3 and SBF groups (p < 0.001), and LBF-6 and SBF groups (p < 0.001). The LBF-6 group had the lowest trueness, while SBF and BF groups obtained the highest trueness values. Furthermore, significant SD differences were revealed across the groups tested (p < 0.001). Tukey test revealed significant SD differences between the BF and LBF-6 groups (p < 0.001), LBF-3 and LB-6 groups (p < 0.001), LBF-3 and SBF groups (p = 0.004), and LBF-6 and SBF groups (p < 0.001). The BF and SBF groups showed equal and highest precision, while the LBF-6 group had the lowest precision. CONCLUSIONS: The best-fit algorithms tested influenced the virtual casts' alignment discrepancy. Entire dataset or section-based best-fit algorithms obtained the highest virtual casts' alignment trueness and precision compared with the landmark-based method.