Abstract

To determine 50:50% perceptibility threshold (PT) and 50:50% acceptability threshold (AT) for computer-simulated samples of human gingiva using CIEDE2000 and CIELAB color difference formulas. Each of the 60 pairs of simulated human gingiva was displayed on a calibrated monitor, together with three pairs of upper central incisors of different lightness. The color of gingiva left and right from the midline was compared. A total of 30 observers (15 dentists, 15 laypersons) participated in the study. CIEDE2000 and CIELAB formulas were used to calculate the thresholds and a Takagi-Sugeno-Kang Fuzzy Approximation model was used as fitting procedure. Paired t-test (α = 0.05) was used in evaluation of statistical significance of differences. The PT and AT for CIEDE2000 and 95% confidence intervals were 1.1 [0.4, 1.7] and 2.8 [1.8, 4.0], respectively. Corresponding CIELAB values were 1.7 [0.2, 2.6] and 3.7 [2.1, 5.7]. Significant differences (P < .01) were recorded between PT and AT, between the corresponding threshold values in CIEDE2000 and CIELAB formulas as well as between dentists and laypersons. The difference between the perceptibility and acceptability threshold for gingiva was statistically significant in both CIEDE2000 and CIELAB. The same was true for differences between the corresponding thresholds using two color difference formulas, and between dentists and laypersons. Visual thresholds of human gingiva were not dependent upon lightness of adjacent teeth. Overall, CIEDE2000 color difference formula provided better fit than CIELAB formula in the evaluation of color difference thresholds of human gingiva. The data on visual thresholds for healthy human gingiva can be used as quality control tool/guide for selection and evaluation of dental materials, interpretation of color-related findings in clinical dentistry and research, and for standardization in dentistry. It is of particular value that this study was designed based on in-vivo color evaluation of healthy keratinized gingiva of subjects of different ethnicities, age groups, and gender.

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