Department of Optics, Faculty of Science, University of Granada, Campus de Fuentenueva, s/n 18071 Granada, Spain.
Université Jean Monnet Saint-Etienne, CNRS, Institut d Optique Graduate School, Laboratoire Hubert Curien UMR 5516, Saint-Étienne, France.
Dent Mater. 2024 Oct;40(10):1677-1684. doi: 10.1016/j.dental.2024.07.013. Epub 2024 Aug 3.
To assess the prediction accuracy of recent optical and numerical models for the spectral reflectance and color of monolithic samples of dental materials with different thicknesses.
Samples of dental resin composites of Aura Easy Flow (Ae1, Ae3 and Ae4 shades) and Estelite Universal Flow Super Low (A1, A2, A3, A3.5, A4 and A5 shades) with thicknesses between 0.3 and 1.8 mm, as well as Estelite Universal Flow Medium (A2, A3, OA2 and OA3 shades) with thicknesses between 0.4 and 2.0 mm, were used. Spectral reflectance and transmittance factors of all samples were measured using a X-Rite Color i7 spectrophotometer. Four analytical optical models (2 two-flux models and 2 four-flux models) and two numerical models (PCA-based and Lab*-based) were implemented to predict spectral reflectance of all samples and then convert them into CIE-Lab* color coordinates (D65 illuminant, 2°Observer). The CIEDE2000 total color difference formula (ΔE) between predicted and measured colors, and the corresponding 50:50% acceptability and perceptibility thresholds (AT and PT) were used for performance assessment.
The best performing optical model was the four-flux model RTE-4F-RT, with an average ΔE = 0.72 over all samples, 94.87% of the differences below AT and 65.38% below PT. The best performing numerical model was Lab*-PCHIP (interpolation mode), with an average ΔE = 0.48, and 100% and 79.69% of the differences below AT and PT, respectively.
Both optical and numerical models offer comparable color prediction accuracy, offering flexibility in model choice. These results help guide decision-making on prediction methods by clarifying their strengths and limitations.
评估最近的光学和数值模型对不同厚度的牙科材料整体样本光谱反射率和颜色的预测精度。
使用厚度在 0.3 至 1.8 毫米之间的 Aura Easy Flow(Ae1、Ae3 和 Ae4 色调)和 Estelite Universal Flow Super Low(A1、A2、A3、A3.5、A4 和 A5 色调)的牙科树脂复合材料样本,以及厚度在 0.4 至 2.0 毫米之间的 Estelite Universal Flow Medium(A2、A3、OA2 和 OA3 色调)的样本。使用 X-Rite Color i7 分光光度计测量所有样本的光谱反射率和透射率因子。实施了四个分析光学模型(两个两流模型和两个四流模型)和两个数值模型(基于 PCA 和基于 Lab*-的模型),以预测所有样本的光谱反射率,然后将其转换为 CIE-Lab*颜色坐标(D65 照明,2°观测者)。使用 CIEDE2000 总色差公式(ΔE)来评估预测和测量颜色之间的差异,以及相应的 50:50%可接受性和可感知性阈值(AT 和 PT)。
表现最好的光学模型是四流模型 RTE-4F-RT,所有样本的平均 ΔE=0.72,94.87%的差异低于 AT,65.38%低于 PT。表现最好的数值模型是 Lab*-PCHIP(插值模式),平均 ΔE=0.48,100%和 79.69%的差异低于 AT 和 PT。
光学和数值模型都提供了相当的颜色预测精度,在模型选择上具有灵活性。这些结果有助于通过阐明它们的优势和局限性来指导预测方法的决策。