Reflectance and color prediction of dental material monolithic samples with varying thickness

To assess accuracy of reflectance reconstruction and color estimation of different dental materials with varying thicknesses using Principal Component Analysis (PCA).

A1, A2, A3, A3.5, B2, C2 and D2 shades and 5 thicknesses (within 0.5-2.5 mm range) of Vita Suprinity (VS-PC) and Vitapan Dentine (VD), were used. Reflectance measurements were performed over black background using a non-contact spectroradiometer with CIE 45^∘∕0^∘ geometry. A PCA based algorithm was proposed to reconstruct spectral data and color of samples, using both extrapolation and interpolation approaches. Root Mean Square Error (RMSE), Goodness of Fit (GFC), correlation coefficient (R²) as well as ΔE₀₀ with corresponding 50:50% acceptability and perceptibly thresholds (AT and PT) were used as performance assessment.

The interpolation approach provided an average RMSE = 0.01 and GFC > 0.999 when comparing predicted and measured spectral reflectances for both materials, while for the extrapolation approach RMSE = 0.02 and GFC > 0.999. Interpolation approach also resulted in lower overall mean color difference ΔE₀₀ = 0.8 (ΔE₀₀ = 0.9 for VS-PC and ΔE₀₀ = 0.7 for VD), while using extrapolation approach resulted in higher overall mean color difference ΔE₀₀ = 1.6, although below the AT (ΔE₀₀ = 1.8 for VS-PC and ΔE₀₀ = 1.5 for VD). Correlation values between predicted and measured spectral reflectances of R² = 0.987 and R² = 0.993 were globally obtained for VS-PC and VD, respectively.

The proposed PCA-based algorithm is able to efficiently predict reflectance spectrum and color of monolithic samples of different dental materials with varying thickness. It can be used to optimize dental materials manufacturing processes and to improve chromatic accuracy of clinical dental restorations.