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RESEARCH REPORT |
Clinic of Fixed and Removable Prosthodontics and Dental Material Sciences, Center for Dental and Oral Medicine, University of Zürich, Plattenstrasse 11, 8028 Zurich, Switzerland;
* corresponding author, spaul{at}zzmk.unizh.ch
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS & METHODSRESULTSDISCUSSIONREFERENCES |
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E values of visually assessed tooth shades were higher than spectrophotometrically assessed E values (p < 0.0001). The results suggest that spectrophotometric shade analysis is more accurate and more reproducible compared with human shade assessment.
KEY WORDS: shade analysis • spectrophotometric • visual human
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS & METHODSRESULTSDISCUSSIONREFERENCES |
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Determination of tooth color by visual means is considered highly subjective. General variables such as external light conditions, experience, age, and fatigue of the human eye and physiological variables such as color blindness lead to inconsistencies (Wyszecki and Stiles, 1982; Hunter and Harold, 1987; Berns, 2000). In addition, standardized verbal means for the communication of visually assessed color characteristics are limited (Seghi et al., 1989). Despite these limitations, the human eye is very efficient in detecting even small differences in the color between two objects.
Based on CIE-Lab (1971) parameters (Commission Internationale de l’Eclairage, L = lightness, a = chroma along red-green axis, b = chroma along yellow-blue axis), data obtained from computerized colorimetry or spectrophotometry allow for a mathematical comparison (Seghi et al., 1989). However, even computerized data collection is still subject to errors (Seghi, 1990).
For reflectance spectrophotometry, two basic geometries are used (i.e., diffuse illumination and observation at 0° or illumination at 45° and observation at 0°; Judd and Wyszecki, 1975). Since access to the oral cavity is limited, only the 45°/0° geometry is a suitable method for clinical use. The accuracy and reliability of such devices have been demonstrated (Johnston and Kao, 1989; Seghi et al., 1989).
Finally, the color "standard" (i.e., commercially available shade guides) varies greatly. Due to difficult-to-control parameters during fabrication (layering), none of the commercially available dental shade guides is identical. In addition, no commercially available dental shade guides are made of commercially available dental ceramics and as such have different light absorption and reflective properties. Despite this lack in standardization today, such shade guides still are the only "standard" upon which determination of color is based in dentistry.
The aim of the present clinical study was to assess the match of visually vs. spectrophotometrically performed selection of body tooth shade, testing the null hypothesis that there is no match.
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MATERIALS & METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS & METHODSRESULTSDISCUSSIONREFERENCES |
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= 400 – 720 nm) by means of a grating. This light was split so that teeth could be illuminated simultaneously from two sides at a 45° angle with the use of an intra-oral camera. The reflected light was directed at 0° on both the system’s detector areas (both 18 x 13 mm2). One detector area was a color CCD chip responsible for the generation of the colored video image. A black and white CCD detector area recorded the spectrophotometric data. During a measuring process, light originating from the monochromator of the device was emitted in 20-nm intervals on a tooth so that 17 photometric spectra of each object were recorded. To finalize a measuring process, we brought the monochromator into a position where no light was emitted. A reflexion spectrum was recorded which was due only to surrounding ambient light. This ambient spectrum was then subtracted from an object’s total spectrum to obtain the object’s spectrum that originated only from reflexion of the standard illumination. Polarization filters were used to eliminate surface gloss. Resulting images consisted of 300,000 pixels. CIE-Lab parameters for each object were then calculated from the 17 spectra of each object according to Equations (1) and (2)
. Prior to every measuring cycle, the spectrophotometer was calibrated to a white ceramic tile supplied by the manufacturer.
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is wavelength of the measured spectrum (from 400 to 720 nm), M is the total of measuring values from the object, D is measuring values from the object due to ambient light (dark value), W is the total of measuring values from a reference object (white ceramic tile), Dw is measuring values from reference due to ambient light, and Rw is reflexion from reference object (given by manufacturer).
 | (2) |
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) is the spectral value of the light source (D65). [Authors’ note: "CIE 1931 standard colorimetric observer" is a fixed standard that is always referenced. However, CIE itself re-published it in 1971, as listed in our reference list.] Each sample of that Vita shade guide later used for the clinical visual assessment was exposed to a spectrophotometric measurement by means of a positioning guide. Samples were placed into a black box with adjacent teeth and pink scallop-shaped silicon (Shofu GUMY medium, Nr. S07040, Swissdent, Thun, Switzerland) to imitate the gingiva. From the spectrophotometric readings, CIE-Lab color parameters were determined, and a color library was generated. Tooth color could then be expressed according to either the Vita Classic Shade guide (e.g., A1, B2, etc.) or in CIE-Lab color parameters.
Patients
Thirty patients were recruited at the Clinic of Fixed and Removable Prosthodontics. There were 14 male and 16 female patients, with an age range from 17 to 44 yrs (mean, 28.63 yrs). For a genuine measurement, all patients were required to present with at least one maxillary central incisor that was free of any restoration. The president of the Ethics Committee of the University of Zürich Center for Dental and Oral Medicine confirmed that the protocol conformed to the guidelines of good clinical practice. Written informed consent was obtained from every patient after a full explanation of the experiment.
Visual Assessment of Tooth Shades
Three dentists (H1, H2, H3) with a negative history of visual color deficiency (Pseudo-Isochromatic Plates, Good-Lite, Streamwood, IL, USA) independently selected the best match to the middle third of one of the patient’s upper central incisors, using the same Vita shade guide that had been used for generating the spectrophotometer’s color library. Each patient was standing against a white wall with ceiling lighting of 5000 K, and away from all windows. A conventional picture (Minolta 500Si, Macro Lens AF 100 mm, Flash 1200 AF, F 22, Lightness +0.5) was taken, with uniform flash, of each patient’s incisor with the selections of the best matching shade samples of all three dentists (Kodak Ektachrome EPP 100 Plus).
Spectrophotometric Assessment of Tooth Shades
The sterilizable adapter of the spectrophotometer’s intra-oral camera was positioned on the alveolar process over the respective tooth. Once the resulting video image of the tooth was centered in an orthoradial way in the measuring square depicted on the computer screen, the spectrophotometric data were recorded three consecutive times for each of the 30 teeth. Shade determination was finally executed by the positioning of a standardized circular measuring area of 3 mm in diameter over the same middle third of the tooth surface that had been used for the visual assessment. Computer software was used to compare these reflectance spectra with the spectra from the color library, for selection of a shade with a minimal E, according to the equation 
Comparison of Visual and Spectrophotometric Data
For the visual shade assessment, a final shade was determined following the principle of majority. If all three evaluators chose the same shade (H1 = H2 = H3), the respective shade was the final shade (øH) for that tooth. If one evaluator chose a different shade (H1) and two evaluators matched (H2 = H3), the latter shade was the final shade. If all three evaluators differed (H1 
H2 H3), the shade chosen by the spectrophotometer was used as the final shade. Usually this shade coincided with that selected by one of the three differing human evaluators.
The spectrophotometric data (SP1, SP2, SP3, and ESP1, ESP2, ESP3) were expected to result in the same shade selection in all three readings; otherwise the principle of majority was to be used as described for the visual assessment.
Finally, the color difference E = øEH - øESP was calculated between E values of the visual average shade (øEH) and the shade selected by the spectrophotometer (øESP). Since the human evaluators could not directly express E values for the shades they chose (H1, H2, H3), the software of the spectrophotometer was used to obtain these values.
Assessment of Error and Statistical Analysis
The measuring error of the spectrophotometric set-up was evaluated by means of the same positioning guide that was used for measurement of the reference color library. Error measurements included electrically induced "noise" over time (10 consecutive measurements over a period of 8 days), horizontal and vertical "mal-"positioning, horizontal and vertical "mal-"inclination, and potential errors in distance to the object (n = 10 for all groups). Means and respective standard deviations for CIE-Lab values in every group were calculated as shown for noise in Table 1. Individual errors were calculated according to the formula
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) was determined according to the equation |
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS & METHODSRESULTSDISCUSSIONREFERENCES |
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documents the spectrophotometer’s error if all measuring parameters remained unchanged. Table 2 displays errors for "mal-"positioning. The resulting overall error was E = 0.48.
Clinical values are displayed in Table 3. In eight out of 30 patients (26.6%), all three visual shade selections matched (H1 = H2 = H3). In 14 patients (46.6%), two visual shade selections were identical, and in the remaining eight cases (26.6%), all three visual selections differed (H1 H2 H3). In contrast, in 25 out of 30 readings (83.3%), all three spectrophotometric shade selections matched (SP1 = SP2 = SP3). In the remaining five cases (16.6%), only one out of three shade selections differed.
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E values of visually assessed shades were higher than spectrophotometric values. Therefore, the mean E of 3.15 ± 1.08 for the visual shade selection and the mean E of 2.099 ± 0.94 for the spectrophotometric shade determination documented an increase of accuracy for the spectrophotometric shade selection of 33%.
Statistical analysis revealed a highly significant difference between the two groups of observation (human (øEH) vs. spectrophotometric (øESP) assessment of shade) with p < 0.0001.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS & METHODSRESULTSDISCUSSIONREFERENCES |
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Colorimeters, spectrophotometers, and even color video cameras may be used for photo-optical assessment of color. However, delivery of information is required to be similar or identical to the human eye for the sake of comparability. For color video cameras, this is not the case. Figs. 1 and 2 show the difference in color sensitivity for a color video camera compared with the human eye. Identification of unknown colors will therefore lead to erratic results when metameric pairs of color are determined.
It has been reported that human observers can be expected to detect color differences of 1 E unit under standardized laboratory conditions (Kuehni and Marcus, 1979). In the oral cavity, however, a match for compared teeth was reported, with an average of 3.7 E units (Johnston and Kao, 1989). Therefore, the spectrophotometer used in the present study allowed a very high degree of standardization to be established for the measuring process, with a total error of 0.48 E units. This might account for the fact that, in 83.3% of the cases, all three spectrophotometric measurements led to the same shade selection. The three human evaluators chose the same shade in only 46.6% of all cases, making the computerized assessment much more reproducible for selection.
Light emitted from the intra-oral camera is either reflected directly on the convex surface of a tooth or it is reflected from deeper layers after complex transformations (scattering, absorption). The final input on the spectrophotometer’s optical sensor is a composite of light from a convex object with depth-dependent translucency. In summary, the three-dimensional information is translated into a two-dimensional map of light intensities. The closest match of the readings from a tooth with the data of the color library results in the shade chosen by the spectrophotometer. The mathematical background of this operation and the improved standardization of the measuring procedure compared with the observation by the human eye may explain why the spectrophotometer offered a 33% increase in accuracy and a closer match in 93.3% of the cases. At p < 0.0001, the level of significance for the statistical difference between the two groups of observation (human vs. spectrophotometric assessment of shade) seems to underline this finding.
If translucency effects—as found in the incisal third of human teeth—are of importance, two-dimensional information might not be accurate enough for the fabrication of a final restoration. However, in a rejection of the null hypothesis, the spectrophotometer used in the present study revealed a very good match with visual shade determination of the body color of natural teeth. Further clinical testing must be done to reveal if spectrophotometers can be used as color determination tools with the potential to support or perhaps replace the human eye during the fabrication of indirect restorations.
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ACKNOWLEDGMENTS |
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Received November 28, 2001; Last revision April 9, 2002; Accepted May 28, 2002
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REFERENCES |
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TOPABSTRACTINTRODUCTIONMATERIALS & METHODSRESULTSDISCUSSIONREFERENCES |
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CIE (Commission Internationale de l’Eclairage) (1971). Colorimetry, official recommendations of the International Commission on Illumination. Publication CIE No. 15 (E-1.3.1). Paris, France: Bureau Central de la CIE, 4 Av. du Recteur Poincaré, 75782 Paris Cedex 16.
Hunter RS, Harold RW (1987). The measurement of appearance. New York: Wiley, pp. 3-68.
Johnston WM, Kao EC (1989). Assessment of appearance match by visual observation and clinical colorimetry. J Dent Res 68:819–822.
Judd DB, Wyszecki G (1975). Color in business, science and industry. 3rd ed. New York: Wiley.
Kuehni RG, Marcus RT (1979). An experiment in visual scaling of small color differences. Color Res Appl 4:83–91.
Miller L (1987). Organizing color in dentistry. J Am Dent Assoc (Spec Iss):26E–40E.
Seghi RR (1990). Effects of instrument-measuring geometry on colorimetric assessments of dental porcelains. J Dent Res 69:1180–1183.
Seghi RR, Johnston WM, O’Brien WJ (1989). Performance assessment of colorimetric devices on dental porcelains. J Dent Res 68:1755–1759.
Sony (2001). www.sel.sony.com/semi/PDF, Data Sheet ICX205AK, p. 8.
Van der Burgt TP, ten Bosch JJ, Borsboom PC, Kortsmit WJ (1990). A comparison of new and conventional methods for quantification of tooth color. J Prosthet Dent 63:155–162.[Medline]
Wyszecki G, Stiles WS (1982). Color science concepts and methods, quantitative data and formulae. 2nd ed. New York: Wiley, pp. 83-116.
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