Evaluation of polymerization-dependent changes in color and translucency of resin composites using two formulae.

The aim of this study was to evaluate polymerization-dependent changes in the color and translucency parameter (TP) of resin composites and to compare results obtained using two color-difference metric formulae, CIELAB and CIEDE 2000. Twenty-eight shades of commercial resin composites were analyzed. Specimens (n = 5) were made as discs, 11 mm in diameter and 2-mm thick, using cylindrical molds. Data were collected before and after composite polymerization, using a spectrophotometer. In regard to in vitro color changes of composites (DeltaE*) a DeltaE76 of 3.7 or greater was considered to be an unacceptable color change. Data were analyzed by analysis of variance, and Fisher's protected least significant difference (PLSD) intervals for comparison of means were calculated at the 0.05 level of significance. Mean polymerization-dependent differences in color were DeltaE00 = 4.48 (2.11) and DeltaE76 = 5.51 (2.68). The DeltaTP00 range was 2.57, while the DeltaTP76 range was 2.89. Mean polymerization-dependent differences in translucency were DeltaTP00 = 0.84 (0.77) and DeltaTP76 = 0.87 (0.76). Analysis of variance showed significant differences among composites, shades, and their interactions (P < 0.0001; power = 1.0). Regression equations and r values for the two color-difference formulae and all evaluated TP values showed very strong correlation. In conclusion, within the limitations of this study, polymerization-dependent changes in color and translucency were highly varied. The majority of shades showed polymerization-dependent differences in color higher than the DeltaE76 = 3.7. The TP generally increased after light polymerization by light activation. The very strong correlation (r > 0.97) between the two color-difference formulae indicates that the limitations of the CIELAB system do not appear to be a problem when evaluating composites; however, recorded differences between DeltaE76 and DeltaE00 values stress the importance of data conversion.