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Predictive algorithms for determination of reflectance data from quantity of pigments within experimental dental resin composites.

Ghinea R, Pecho O, Herrera LJ, Ionescu AM, Cardona Jde L, Sanchez MP, Paravina RD, Perez Mdel M - Biomed Eng Online (2015)

Bottom Line: The average value of the prediction error of the model was 3.46% (SD: 1.82) across all wavelengths for samples before aging and 3.54% (SD: 1.17) for samples after aging.The differences found between the predicted and measured values of the chromatic coordinates are smaller than the acceptability threshold and, in some cases, are even below the perceptibility threshold.Within the framework of this pilot study, the nonlinear predictive models developed allow the prediction, with a high degree of accuracy, of the reflectance spectrum of the experimental dental resin composites.

View Article: PubMed Central - HTML - PubMed

ABSTRACT

Background: Being able to estimate (predict) the final spectrum of reflectance of a biomaterial, especially when the final color and appearance are fundamental for their clinical success (as is the case of dental resin composites), could be a very useful tool for the industrial development of these type of materials. The main objective of this study was the development of predictive models which enable the determination of the reflectance spectrum of experimental dental resin composites based on type and quantity of pigments used in their chemical formulation.

Methods: 49 types of experimental dental resin composites were formulated as a mixture of organic matrix, inorganic filler, photo activator and other components in minor quantities (accelerator, inhibitor, fluorescent agent and 4 types of pigments). Spectral reflectance of all samples were measured, before and after artificial chromatic aging, using a spectroradiometer. A Multiple Nonlinear Regression Model (MNLR) was used to predict the values of the Reflectance Factors values in the visible range (380 nm-780 nm), before and after aging, from % Pigment (%P1, %P2, %P3 and %P4) within the formulation.

Results: The average value of the prediction error of the model was 3.46% (SD: 1.82) across all wavelengths for samples before aging and 3.54% (SD: 1.17) for samples after aging. The differences found between the predicted and measured values of the chromatic coordinates are smaller than the acceptability threshold and, in some cases, are even below the perceptibility threshold.

Conclusions: Within the framework of this pilot study, the nonlinear predictive models developed allow the prediction, with a high degree of accuracy, of the reflectance spectrum of the experimental dental resin composites.

No MeSH data available.


Related in: MedlinePlus

Total color differences in terms of ΔE00 (left) and  (right) between the predicted and measured values for samples in the Validation Group before aging.
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Figure 10: Total color differences in terms of ΔE00 (left) and (right) between the predicted and measured values for samples in the Validation Group before aging.

Mentions: The study on the accuracy of the MNLR predictive models can be extended with the calculation of the total color differences (in terms of ΔE00 and total color differences), between the predicted and measured values of the chromatic coordinates, and consequently evaluate them through comparisons with the available perceptibility and acceptability thresholds for dentistry[19]. The total color differences in terms of ΔE00 and between the predicted and measured values for the samples included in the Validation Group before aging are presented in Figure 10 while the values obtained for samples after aging are presented in Figure 11. In the case of Sample 47, the differences found were higher than both thresholds, probably due to the high discrepancies between the predicted and measured value of lightness (L*). After the artificial aging procedure was applied, if the differences between the predicted and measured values are computed with the newest ΔE00 formula, all values fall within the acceptability threshold, and in 75% of the studied cases, the differences are even smaller than the perceptibility threshold. If, instead, the CIE1976 total color difference formula is used (), for Sample 47, similar to what happens before aging, the value of the difference is higher than both thresholds, while for the other 4 samples included in the Validation Group, the calculated total color differences are smaller than both perceptibility and acceptability thresholds.


Predictive algorithms for determination of reflectance data from quantity of pigments within experimental dental resin composites.

Ghinea R, Pecho O, Herrera LJ, Ionescu AM, Cardona Jde L, Sanchez MP, Paravina RD, Perez Mdel M - Biomed Eng Online (2015)

Total color differences in terms of ΔE00 (left) and  (right) between the predicted and measured values for samples in the Validation Group before aging.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4547340&req=5

Figure 10: Total color differences in terms of ΔE00 (left) and (right) between the predicted and measured values for samples in the Validation Group before aging.
Mentions: The study on the accuracy of the MNLR predictive models can be extended with the calculation of the total color differences (in terms of ΔE00 and total color differences), between the predicted and measured values of the chromatic coordinates, and consequently evaluate them through comparisons with the available perceptibility and acceptability thresholds for dentistry[19]. The total color differences in terms of ΔE00 and between the predicted and measured values for the samples included in the Validation Group before aging are presented in Figure 10 while the values obtained for samples after aging are presented in Figure 11. In the case of Sample 47, the differences found were higher than both thresholds, probably due to the high discrepancies between the predicted and measured value of lightness (L*). After the artificial aging procedure was applied, if the differences between the predicted and measured values are computed with the newest ΔE00 formula, all values fall within the acceptability threshold, and in 75% of the studied cases, the differences are even smaller than the perceptibility threshold. If, instead, the CIE1976 total color difference formula is used (), for Sample 47, similar to what happens before aging, the value of the difference is higher than both thresholds, while for the other 4 samples included in the Validation Group, the calculated total color differences are smaller than both perceptibility and acceptability thresholds.

Bottom Line: The average value of the prediction error of the model was 3.46% (SD: 1.82) across all wavelengths for samples before aging and 3.54% (SD: 1.17) for samples after aging.The differences found between the predicted and measured values of the chromatic coordinates are smaller than the acceptability threshold and, in some cases, are even below the perceptibility threshold.Within the framework of this pilot study, the nonlinear predictive models developed allow the prediction, with a high degree of accuracy, of the reflectance spectrum of the experimental dental resin composites.

View Article: PubMed Central - HTML - PubMed

ABSTRACT

Background: Being able to estimate (predict) the final spectrum of reflectance of a biomaterial, especially when the final color and appearance are fundamental for their clinical success (as is the case of dental resin composites), could be a very useful tool for the industrial development of these type of materials. The main objective of this study was the development of predictive models which enable the determination of the reflectance spectrum of experimental dental resin composites based on type and quantity of pigments used in their chemical formulation.

Methods: 49 types of experimental dental resin composites were formulated as a mixture of organic matrix, inorganic filler, photo activator and other components in minor quantities (accelerator, inhibitor, fluorescent agent and 4 types of pigments). Spectral reflectance of all samples were measured, before and after artificial chromatic aging, using a spectroradiometer. A Multiple Nonlinear Regression Model (MNLR) was used to predict the values of the Reflectance Factors values in the visible range (380 nm-780 nm), before and after aging, from % Pigment (%P1, %P2, %P3 and %P4) within the formulation.

Results: The average value of the prediction error of the model was 3.46% (SD: 1.82) across all wavelengths for samples before aging and 3.54% (SD: 1.17) for samples after aging. The differences found between the predicted and measured values of the chromatic coordinates are smaller than the acceptability threshold and, in some cases, are even below the perceptibility threshold.

Conclusions: Within the framework of this pilot study, the nonlinear predictive models developed allow the prediction, with a high degree of accuracy, of the reflectance spectrum of the experimental dental resin composites.

No MeSH data available.


Related in: MedlinePlus