RESUMEN
PURPOSE: Assessment of the predictability of tooth color coordinates according to the CIELab system to estimate the color of the maxillary central incisor based on patient age and gender. MATERIAL AND METHODS: The tooth color of one of the maxillary central incisors of 1361 Caucasian Spanish individuals aged 16 to 89 years, male and female, was measured using the Easyshade compact spectrophotometer. Color coordinates L*, C*, h*, a*, and b* were recorded according to age and gender. RESULTS: The results obtained show that differences in age account for 45% of the total variation of the L (lightness) coordinate; 21% of the variation in coordinate a*, and 17% of the variation in coordinate b* is due to the same reason. At a confidence level of 95% it may be proposed that the mean estimated color difference (ΔEab *) between real natural color and that predicted by the linear regression model is between 6.4 and 6.9 units. CONCLUSIONS: In this sample of Caucasians from Spain, teeth became darker yellow and more reddish with increasing age. The L* coordinate is most strongly related to tooth color in aging.
Asunto(s)
Color , Incisivo/anatomía & histología , Adolescente , Adulto , Factores de Edad , Anciano , Anciano de 80 o más Años , Femenino , Humanos , Masculino , Maxilar , Persona de Mediana Edad , Factores Sexuales , España , EspectrofotometríaRESUMEN
OBJECTIVES: To measure the impact of the superimposition methods on accuracy analyses in digital implant research using an ISO-recommended 3-dimensional (3D) metrology-grade inspection software. MATERIALS AND METHODS: A six-implant edentulous maxillary model was scanned using a desktop scanner (7Series; DentalWings; Montreal, Canada) and an intraoral scanner (TRIOS 4; 3Shape; Copenhagen, Denmark) to generate a reference and an experimental mesh, respectively. Thirty experimental standard tesselletion language (STL) files were superimposed onto the reference model's STL using the core features of six superimposition methods, creating the following groups: initial automated pre-alignment (GI), landmark-based alignment (G1), partial area-based alignment (G2), entire area-based alignment (G3), and double alignment combining landmark-based alignment with entire model area-based alignment (G4 ) or the scan bodies' surface (G5). The groups underwent various alignment variations, resulting in sixteen subgroups (n = 30). The alignment accuracy between experimental and reference meshes was quantified by using the root mean square (RMS) error as trueness and its fluctuation as precision. The Kruskal-Wallis test with a subsequent adjusted post-hoc Dunn's pairwise comparison test was used to analyze the data (α = 0.05). The reliability of the measurements was assessed using the intraclass correlation coefficient (ICC). RESULTS: A total of 480 superimpositions were performed. No significant differences were found in trueness and precision among the groups (p > 0.05), except for partial area-based alignment (p < 0.001). Subgroup analysis showed significant differences for partial area-based alignment considering only one scan body (p < 0.001). Initial automated alignment was as accurate as landmark-based, partial, or entire area-based alignments (p > 0.05). Double alignments did not improve alignment accuracy (p > 0.05). The entire area-based alignment of the scan bodies' surface had the least effect on accuracy analyses. CONCLUSIONS: Digital oral implant investigation remains unaffected by the superimposition method when ISO-recommended 3D metrology-grade inspection software is used. At least two scan bodies are needed when considering partial area-based alignments. CLINICAL SIGNIFICANCE: The superimposition method choice within the tested ISO-recommended 3D inspection software did not impact accuracy analyses in digital implant investigation.