Comparative analysis of optical and numerical models for reflectance and color prediction of monolithic dental resin composites with varying thicknesses
Metadatos
Mostrar el registro completo del ítemAutor
Tejada Casado, María de la Nativida; Duveiller, Vincent; Ghinea, Razvan Ionut; Gautheron, Arthur; Clerc, Raphaël; Salomon, Jean-Pierre; Pérez Gómez, María Del Mar; Hébert, Mathieu; Herrera Maldonado, Luis JavierEditorial
Elsevier
Materia
Reflectance prediction Color prediction Optical models
Fecha
2024-09-13Referencia bibliográfica
Tejada Casado, M. et. al. Dental Materials 40 (2024) 1677–1684. [https://doi.org/10.1016/j.dental.2024.07.013]
Patrocinador
Grant PID2022.142151OB.I00 funded by MICIU/AEI/10.13039/501100011033; Grant PID2021- 128317OB-I00 funded by MCIN/AEI/10.13039/501100011033; ‘‘ERDF A way of making Europe’’; French National Research Agency (ANR) under the ‘‘France 2030’’ investment plan, which has the reference EUR MANUTECH SLEIGHT—ANR-17-EURE-0026; Université de Lyon, France through program LABEX PRIMES under Grant ANR-11-LABX-0063 within the program Investissements d’Avenir under Grant ANR- 11-IDEX-0007, operated by the French National Research Agency; France Life Imaging under Grant ANR-11-INBS-0006 within the program Infrastructures d’Avenir en Biologie Santé, operated by the French National Research AgencyResumen
Objective:
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.
Methods:
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 L*a*b*-based) were implemented to predict spectral reflectance of all samples and then convert them into CIE-L*a*b* color coordinates (D65 illuminant, 2°Observer). The CIEDE2000 total color difference formula (
) between predicted and measured colors, and the corresponding 50:50% acceptability and perceptibility thresholds (
and
) were used for performance assessment.
Results:
The best performing optical model was the four-flux model RTE-4F-RT, with an average
= 0.72 over all samples, 94.87% of the differences below
and 65.38% below
. The best performing numerical model was L*a*b*-PCHIP (interpolation mode), with an average
= 0.48, and 100% and 79.69% of the differences below
and
, respectively.
Significance:
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.