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The role of enamel thickness and refractive index on human tooth colour
Accepted Manuscript Title: The role of enamel thickness and refractive index on human tooth colour Author: Rena Oguro Masatoshi Nakajima Naoko Seki Alireza Sadr Junji Tagami Yasunori Sumi PII: DOI: Reference:
S0300-5712(16)30096-3 http://dx.doi.org/doi:10.1016/j.jdent.2016.05.010 JJOD 2625
To appear in:
Journal of Dentistry
Received date: Revised date: Accepted date:
26-7-2015 9-5-2016 26-5-2016
Please cite this article as: Oguro Rena, Nakajima Masatoshi, Seki Naoko, Sadr Alireza, Tagami Junji, Sumi Yasunori.The role of enamel thickness and refractive index on human tooth colour.Journal of Dentistry http://dx.doi.org/10.1016/j.jdent.2016.05.010 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
The role of enamel thickness and refractive index on human tooth colour
Short title: The role of enamel thickness and refractive index on tooth colour Authors: Rena Oguroa, Masatoshi Nakajimaa, Naoko Sekib, Alireza Sadrc, Junji Tagamia,d, Yasunori Sumie a
Cariology and Operative Dentistry, Oral Restitution Department, Graduate School of
Medical and Dental Sciences, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo, 113-8549, Japan b
Dental Education Development Section, Graduate School of Medical and Dental
Sciences, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo, 113-8549, Japan c
Biomimetics Biomaterials Biophotonics & Technology Laboratory, Department of
Restorative Dentistry, University of Washington School of Dentistry, 1959 NE Pacific St. Box 357456, Seattle, WA, 98195-7456, USA d
Global Center of Excellence (GCOE) Program; International Research Center for
Molecular Science in Tooth and Bone Diseases, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo, 113-8549, Japan
e
National Center for Geriatrics and Gerontology, Department for Advanced Dental
Research, Center of Advanced Medicine for Dental and Oral Diseases, 36-3, Gengo, Morioka, Obu, Aichi 474-8511, Japan
*Corresponding author: Masatoshi Nakajima Cariology and Operative Dentistry, Oral Restitution Department, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo, 113-8549, Japan Tel: +81 3 5803 5483
Fax: +81 3 5803 0195
E-mail: [email protected]
Naoko Seki Dental Education Development Section, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo, 113-8549, Japan Tel: +813 5803 4537 E-mail: [email protected]
Abstract Objectives: To investigate the role of enamel thickness and refractive index (n) on tooth colour. Methods: The colour and enamel thickness of fifteen extracted human central incisors were determined according to CIELab colour scale using spectrophotometer (Crystaleye) and swept-source optical coherence tomography (SS-OCT), respectively. Subsequently, labial enamel was trimmed by approximately 100 µm, and the colour and remaining enamel thickness were investigated again. This cycle was repeated until dentin appeared. Enamel blocks were prepared from the same teeth and their n were obtained using SS-OCT. Multiple regression analysis was performed to reveal any effects of enamel thickness and n on colour difference (ΔE00) and differences in colour parameters with CIELCh and CIELab colour scales. Results: Multiple regression analysis revealed that enamel thickness (p=0.02) and n of enamel (p<0.001) were statistically significant predictors of ΔE00 after complete enamel trimming. The n was also a significant predictor of ΔH’ (p=0.01). Enamel thickness and n were not statistically significant predictors of ΔL’, ΔC’, Δa* and Δb*. Conclusions: Enamel affected tooth colour, in which n was a statistically significant predictor for tooth colour change.
Clinical Significance: Understanding the role of enamel in tooth colour could contribute to development of aesthetic restorative materials that mimic the colour of natural tooth with minimal reduction of the existing enamel. Keywords: Enamel, Tooth colour, Refractive index, Enamel thickness
1. Introduction Aesthetic treatments have become widely requested as the standard of care in restorative dentistry. Among factors necessary for aesthetic restorations, tooth colour evaluation is an important step not only for patients who wish to enhance their smile or appearance, but also for dentists who would like to select appropriate materials with the correct shade and provide the best treatment.1 The perception of tooth colour is a complex phenomenon and can be influenced by a number of factors, including the visual state of the observer, the context in which the tooth is viewed, the type of incident light, and the optical properties and colour in dental tissue.1 Optical properties are intrinsic properties resulting from of a combination of various factors, such as specular and diffuse reflection (light scattering) at the surface, specular transmission of light through the tissue, and absorption and scattering of light within the tissue.2,3 These properties are in turn affected by the composition and histological structure of the tissue.2.3
Coronal dentine is covered by an enamel layer with thicknesses that vary according to the type of the tooth and anatomical location, being approximately 1.0 mm on the average.4 Nevertheless, the colour of a tooth is largely determined by properties of dentine.5 On the other hand, the optical properties of enamel have been widely studied, since enamel has minor, yet noticeable effects on the colour and translucency of natural tooth.5-8 The thickness and translucency property of enamel might control chromatic influence of dentine on natural tooth appearance. Moreover, direct restorations placed over remaining dentin will need to mimic the properties of enamel optically. It is well known that enamel has fluorescence9 and opalescence.10 While fluorescence does not contribute to visually observed colour of the tooth,5,11 enamel affects tooth colour through opalescence, which is defined as scattering of light in the blue wavelength range.5,10 Recently, it was demonstrated that tooth colour parameters (hue, chroma, lightness) were influenced by variability in the mineral composition of enamel, namely the size and degree of the carbonization of the enamel hydroxyapatite (HA) crystals.12 On the other hand, mineral content of enamel was reported to affect its local refractive index (n),13 which is associated with light scattering properties inside the tissue. However, there is no published research on the effects that n of enamel and its thickness may have on tooth colour. It was recently reported that the n of dental hard tissues could be investigated by swept source optical coherence tomography (SS-OCT).14,15 SS-OCT is a rapidly growing
non-invasive interferometric technique, which enables cross-sectional imaging of internal biological structures by differentiating between scattered and transmitted or reflected photons using broad-band, near-infrared (near-IR) light sources on micrometer scale resolution.16,17 SS-OCT has been validated to accurately determine the optical thickness of dental tissue in a nondestructive manner.18 Therefore, the purpose of this study was to investigate the role of enamel thickness and n, using SS-OCT, on human tooth colour. In this study, tooth colour evaluation was performed by measurement of the CIELab L* (lightness), a* (green-red coordinate) and b* (blue-yellow coordinate) value, and by calculation of the CIE2000 ΔL’ (differences in lightness), ΔC’ (differences in chroma), ΔH’ (differences in hue) and ΔE00 (colour difference). The null hypotheses tested were that the enamel thickness and n are not predictors of tooth colour change (ΔE00) after trimming of enamel, and also they are not predictors of ΔL’, ΔC’, ΔH’, Δa* and Δb* after trimming of enamel.
2. Materials and Methods 2.1. Measurement of colour of the teeth Fifteen extracted human central incisors, without endodontic treatment or restorations and stored at 4 oC water were used in this study, according to a protocol approved by the Human Research Ethics Committee, Tokyo Medical and Dental University, Japan (No.725). The teeth
were placed in a jaw model; in order to enable repositioning in the same location, molds were fabricated from silicon putty (EXAFINE PUTTY TYPE, GC, Tokyo, Japan). The jaw model was placed in a black box (inspection kit, OLYMPUS, Tokyo, Japan) which was shielded from external light. The colour of all these intact teeth were then measured using a dental spectrophotometer (Crystaleye, OLYMPUS, Tokyo, Japan) with capture time of 0.2 s, in which 7 light emitting diodes (LEDs) are used as an illumination source corresponding to the standard illuminant D65 with 45°/0° geometry. Prior to data acquisition, the spectrophotometer was calibrated using a calibration plate (OLYMPUS, Tokyo, Japan) and positioned at a consistent distance of 16 mm from the specimen surface using the special contact cap for object measurement. All measurements were performed by the same researcher who was extensively trained. The spectral data was acquired from the captured image of the tooth.19 The reflectance values for each pixel in the range of 400 to 700 nm with 1 nm intervals were transferred from the spectrometer to a personal computer with a Crystaleye software (Crystaleye Application version 1.4, Olympus, Tokyo, Japan).19 In this study, evaluation area (1.0 mm×1.0 mm) was identified on the captured image of the tooth (Fig.1a), in which the colour was analysed using Commission Internationale de lÉclairage colour coordinates L* (lightness), a* (green-red coordinate) and b* (blue-yellow coordinate), known as CIELAB colour coordinates.20 The Crystaleye software also provided tooth colour shade in minimum area of 0.5 mm×0.5 mm by
comparing the database of VITA Classical (VITA, Bad Säckingen, Germany) with the data acquired from the digital image of the teeth. 2.2. Optical enamel thickness measurement using SS-OCT The optical enamel thickness of the teeth were investigated using SS-OCT (OCT-2000, Santec Co., Komaki, Japan).18 The system incorporates a high-speed frequency swept tuneable external cavity laser with wavelength range of 1260 to 1360 nm (centred at 1310 nm) at a 20-kHz sweep rate. The laser beam is projected over the object, and the backscattered light is coupled back to the SS-OCT system, in which the interference signal is digitized in time scale, and then analysed in the Fourier domain to reveal the depth information of the object. The axial and lateral resolutions of the system in air were 11 and 17 µm, respectively. The system acquired the image data (B-scan) in 0.3 s, including the processing time. The imaging window range in this study was 5 mm (width) by 6.6 mm (height) forming a 2000 × 1019 pixel image. The sensitivity of this system and the shot-noise limited sensitivity were 106 and 119 dB, respectively.21 Enamel thickness measurement location was a fixed window of interest (1.0 mm×1.0 mm) on labial mid-coronal surface (Fig.1a). Image analysis software (ImageJ 1.42q; National Institutes of Health, Bethesda, MD, USA) was used to perform SS-OCT image analysis. 2.3. Evaluation of colour and remaining enamel thickness after trimming
Labial enamel of the teeth were trimmed to remove approximately 100 µm thickness using 600-grit and 1000-grit silicon carbide (SiC) papers (Sankyo, Saitama, Japan) under running water. The surface was polished using 1500-grit SiC papers under running water and the optical thickness of remaining labial enamel at the window was investigated on SS-OCT images. Digital colour images of the teeth were also obtained by Crystaleye after their repositioning on the jaw model using the silicon putty mold. Enamel trimming, and optical thickness measurement and spectrophotometer colour determination cycles were repeated until enamel was completely removed and dentine appeared. Each tooth was kept moist at all times in order to avoid its dehydration. In order to evaluate the colour change with enamel trimming, CIEDE2000 color difference (ΔE00) between before and after enamel trimming at each trimming step were calculated via Microsoft Excel spreadsheet at Sharma’s website.22 The CIEDE2000 color-difference formula is based on the CIELAB color space.23 Given a pair of color values in CIELAB space L*1 ,a*1 ,b*1 and L*2 ,a*2 ,b*2, we denote the CIEDE2000 color difference between them.23 The CIEDE2000 color difference formula is given as follows:23 ‘
‘
‘
‘
‘
ΔL’, ΔC’, and ΔH’ between before and after enamel trimming at each trimming step are the differences in lightness, chroma, and hue between before and after enamel trimming and RT is a function (the so-called rotation function) that accounts for the interaction between chroma and
hue differences in the blue region. SL, SC, and SH are the weighing functions for the lightness, chroma, and hue components, respectively. KL, KC, and KH are the parametric factors to be adjusted according to different viewing parameters. ΔL’, ΔC’, and ΔH’ were calculated in the following equations as two step:23 1. Calculate
,
: C ∗,
∗
1, 2
C∗ , 2 ̅∗
0.5 1
̅∗ ∗
1
0 ∗ ∗ tan ,
25
∗
C ∗,
̅∗
G
∗
1, 2
0
1, 2
1, 2
2. Calculate ΔL’, ΔC’, ΔH’: ΔL
L∗
L∗
ΔC
C
C
0 Δ
0
0; | 0; 0;
360 360 Δ
2
sin
Δ 2
|
180° 180° 180°
Additionally, Δa* and Δb* values were calculated as colour coordinate changes at each trimming step, where Δa* was the difference in a* and Δb* was the difference in b* between before and after enamel trimming, using following formula. Δa∗
a∗
a∗
Δb∗
b∗
b∗
2.4. Measurement of refractive index (n) of enamel Following trimming and colour and optical thickness measurement, a 0.5 mm thick enamel block (1.0 mm × 4.0 mm) was prepared from the incisal labial enamel of each tooth (Fig. 1b), using a low-speed diamond saw (Isomet, Buehler, Lake Bluff, IL, USA) under water-cooling. The n values were obtained following the optical path length (OPL) matching method previously described;13,14 briefly, a B-scan along the direction marked with a line was taken to obtain the OCT image (Fig. 2). The lines which represented the reflected light from the upper surface of the sample and the metal plate without the sample, were Z0, and Z1 respectively, and finally Z2 represented the position of the reflector (metal plate) imaged through the tissue. The actual thickness (t) of the sample could be determined by subtraction of the vertical position of the reflector (metal plate) outside the tissue (Z1) from the vertical position of the sample surface (Z0) in the OCT image, and the additional OPL delay can be measured by subtraction of the
vertical position of the reflector imaged through the tissue (Z2) from the vertical position of the sample surface (Z0). Assuming the OPL in the sample is Z2－Z0 and the actual thickness (t) of the sample is Z1－Z0, we can obtain n of the enamel blocks using Eq. (1) as
Eq. (1) was used to calculate the n at each location on average signal intensity profiles as shown in Fig. 2. Each value was calculated using an average profile obtained on an area (10 pixels or 25 mm in width) on the sample.14 Five areas were randomly selected on the region to be evaluated on each slice using the software, from which average n of the region on that enamel block was calculated.14 2.5. Calculation of actual remaining enamel thickness of the teeth The actual remaining enamel thickness of the evaluation area in each tooth was obtained by dividing the optical thickness of enamel on SS-OCT image measured in 2.2 by the n value of the enamel block calculated in 2.4 using Eq. (1). 2.6. Statistical analysis A multiple linear regression analysis was used to reveal any effects of enamel thickness of intact teeth and n of enamel on ΔE00 after complete enamel trimming. Additionally, their effects on ΔL’, ΔC’ and ΔH’ after complete enamel trimming and ΔL*, Δa* and Δb* after complete enamel trimming were analysed. Model fit was assessed using the coefficient of
determination (R squared). The significance level used was alpha=0.05. All statistical procedures were done with the Statistical Package for the Social Science (SPSS Advanced Statistics 23).
3. Results The shades of intact teeth used in this study were A2 (2 teeth), A3 (2 teeth), A3.5 (3 teeth), A4 (2 teeth), B3 (2 teeth), B4 (1 tooth), C1(1 tooth), C2 (1 tooth) and C3(1 tooth). The colour difference (ΔE00) between before and after enamel trimming at each enamel thickness are plotted in Fig. 3. ΔE00 of each tooth steadily increased with decrease of the remaining enamel thickness, and the range of ΔE00 values after complete enamel trimming was from 1.05 to 10.46. In terms of ΔL’, ΔC’ and ΔH’, the colour differences between before and after enamel trimming at each enamel thickness are plotted in Fig. 4. ΔL’ values changed differently among different teeth, ranged from -4.39 to 11.28 after complete enamel trimming (Fig. 4a), and ΔC’ values were highly variable, ranging from -6.40 to 8.87 after complete enamel trimming (Fig. 4b). ΔH’ of each tooth ranged from -0.37 to 5.92 after complete enamel trimming (Fig. 4c). In terms of Δa* and Δb*, Δa* of each tooth hardly showed changes on the plot, ranging from -4.27 to 0.46 after complete enamel trimming (Fig. 4d), while Δb* values were highly variable, ranging from -6.6 to 9.15 after complete enamel trimming (Fig. 4e).
For ΔE00 after complete enamel trimming vs. enamel thickness of intact teeth and n of enamel, multiple linear regression analysis revealed that enamel thickness of intact teeth (p=0.02) and n of enamel (p<0.001) were statistically significant predictors of ΔE00. The overall model (ΔE00
= 138.204 × n + 0.007 × enamel thickness (µm) – 224.435) was statistically significant (p<0.001) with a coefficient of determination of 76% (Table 1).
For ΔH’ after complete enamel trimming vs. enamel thickness of intact teeth and n of enamel, multiple linear regression analysis revealed that n of enamel was a statistically significant predictor of ΔH’ (p=0.01). The overall model was statistically significant (p=0.01) with a coefficient of determination of 42%. Enamel thickness of intact teeth was not a statistically significant predictor of ΔH’ (p=0.30) (Table 2c). On the other hand, for ΔL’and ΔC’ after complete enamel trimming vs. enamel thickness of intact teeth and n of enamel, it was demonstrated that enamel thickness of intact teeth and n of enamel were not statistically significant predictors of ΔL’ (Table 2a), ΔC’ (Table 2b). For Δa* and Δb* after complete enamel trimming vs. enamel thickness of intact teeth and n of enamel, it was demonstrated that enamel thickness of intact teeth and n of enamel were not statistically significant predictors of Δa* (Table 3a) and Δb* (Table 3b).
4. Discussion
In this study, a multiple linear regression analysis demonstrated that enamel thickness of intact teeth (p=0.02) and n of enamel (p<0.001) were statistically significant predictors of ΔE00 after complete enamel trimming (Table 1). In the investigation of each colour parameter, It was revealed that n of enamel was a statistically significant predictor of ΔH’ after complete enamel trimming (p=0.01), but enamel thickness of intact teeth was not a statistically significant predictor of ΔH’ (p=0.30) (Table 2c). On the other hand, enamel thickness of intact teeth and n of enamel were not statistically significant predictors of ΔL’ (Table 2a), ΔC’ (Table 2b), Δa* (Table 3a) and Δb* (Table 3b) after complete enamel trimming. Thus the null hypotheses are partially rejected. ΔE00 increased steadily in different teeth with decrease of the remaining enamel thickness (Fig. 3), and the ΔE00 of 10 specimen out of 15 (66.7%) showed a variation more than 2.23 units, which is considered as the average colour difference acceptability threshold.24 Furthermore, enamel thickness of intact teeth and n of enamel were statistically significant predictors of ΔE00 after complete enamel trimming (ΔE00 = 138.204 × n + 0.007 × enamel thickness (µm) – 224.435) (Table 1). These results indicate that enamel does play a role in determining tooth colour. Furthermore, it was demonstrated that n of enamel was the major predictor of ΔE00 after complete enamel trimming (Table 1). The n is an important parameter of light propagation in biological tissue, including teeth.16 The n of tissue can serve as an indicator
of its scattering properties within the tissue, as scattering itself is the end result of local n variation.16 The values of n in this study were similar to those reported previously.13,14 It was reported that the prism orientations in enamel did not significantly affect n values under SS-OCT.14 SS-OCT is based on low-coherence interferometry and thus at near-infrared wavelength, where enamel is almost completely transparent with the smallest attenuation coefficients,14 it can be used to measure the OPL of this tissue effectively.21 The n of tissue is calculated by ratio of the OPL to the actual thickness.14 Therefore, using n value of enamel block from incisal site of each tooth, actual enamel thickness could be accurately calculated from OPL measured at the evaluation window.14,25 In the investigation of each colour parameter alteration, ΔL’ changed differently among different teeth with decrease of the remaining enamel thickness; the values were mainly in the range of -1.89 to 3.6 (excluding 3 specimens) (Fig. 4a) and the ΔC’ changes were widely distributed in range from -6.40 to 8.87 with removal of the enamel (Fig. 4b). These results would be concerned with translucency and opalescence properties of enamel. The translucency effect is influenced by thickness of material and its translucency property, which would determine the influence of background colour on the colour appearance. If among optical properties of enamel, translucency played a major role in influence on tooth colour, the enamel thickness also would significantly affect it. However, the results of this study demonstrated that
enamel thickness of intact teeth was not statistically significant predictors of ΔL’ (Table 2a), ΔC’ (Table 2b) after complete enamel trimming. Therefore, translucency of enamel would be a minor factor in influencing tooth colour. On the other hand, the ΔH’ change with decrease of enamel thickness was limited, but slightly increased (Fig. 4c). This result would indicate that the hue of an intact tooth comes mainly from dentine and enamel could slightly provide a bluish appearance on frontal view of intact tooth due to the opalescence although it is intrinsically colourless. Opalescence occurs where there is light scattering of the shorter wavelengths of the visible spectrum, giving a bluish appearance to an object under reflected light and an orange/brown appearance under transmitted light.10 The scattering coefficient of enamel increases with decreasing wavelength;6 therefore, the shorter wavelengths (e.g. blue light) are strongly scattered at enamel and are reflected as bluish-white,10 while the longer wavelengths (e.g. orange light) could transmit to dentine through enamel. In this study, Δb* (blue-yellow) changes were widely distributed in range from -6.6 to 9.15 with decrease of the remaining enamel thickness (Fig. 4e) although Δa* (green-red) hardly showed any changes as the remaining enamel got thinner (Fig. 4d). These results indicate that tooth colour change with decrease of enamel thickness was most greatly relying on changes in b* values; this finding is in agreement with a previous study,5 and is thought to be due to the opalescence of enamel. The opalescence might be a major factor to determine colour appearance
of natural tooth as in the optical properties of enamel. However, the results of this study demonstrated that enamel thickness of intact teeth was not statistically significant predictors of ΔH’ (Table 2c) and Δb* (Table 3b) after complete enamel trimming. The opalescence phenomenon in enamel might not be influenced by enamel thickness. Presumably, light scattering of shorter wavelengths might take place at the exposed enamel subsurface, not within the enamel body. Additionally, n of enamel was a statistically significant predictor of ΔH’ after complete enamel trimming (Table 2c). Presumably, n of enamel would be concerned with opalescence of enamel and/or transilluminating behavior of the reflecting colour from underlying dentine within enamel body, resulting in the change in the hue of tooth. On the other hand, the results of this study revealed that n of enamel was not statistically significant predictors of ΔL’ (Table 2a) and ΔC’ (Table 2b); a previous study demonstrated that scattering coefficient of enamel was significantly correlated with tooth lightness (r=0.60).5 Therefore, light scattering at enamel surface would affect tooth lightness. However, the previous study also indicated that since the regression was not very steep, light scattering within enamel body does not contribute much to lightness.5 Tooth colour is different among various types of teeth, locations and ages. Generally, teeth in older people appear darker and yellower, as its enamel HA crystals become larger.26 It
was demonstrated that teeth composed of large enamel HA crystals appeared to be darker than teeth composed of smaller enamel HA crystals.12 Therefore, the age regulated increase in the mean size of enamel HA crystals might be one of the reasons behind tooth shade darkening in elder individuals.12 The age-dependent changes might affect its optical properties, and might play a role in determining tooth colour. Unfortunately, the age of extracted human teeth used in this study were not registered, therefore relationship between n and age of tooth is unclear. Nonetheless, the correlation between n values and ΔE00 is interesting; on one hand it was demonstrated that n of enamel depended on compositional factors, mainly mineral content.13 In this regard, enamel with a larger volume of crystals will have a higher n.13 Moreover, carbonated apatite which is the dominant crystal in human enamel has a lower n than pure HA, while fluoridated apatite has a higher n.13 On the other hand, it was demonstrated that both the carbonate content and size of enamel apatite crystals played role in tooth colour appearance.12 The n appears to be a relevant and important variable while considering the effects of enamel crystalline composition on tooth colour. These findings could provide better understanding of enamel optical properties and aesthetics, and further development of aesthetic restorative materials. Therefore, further research about the role of enamel with age on tooth colour is required in order to successfully mimic the colour and translucency of natural tooth. In the multiple regression analyses of this study, the six regression models (ΔE00, ΔL’,
ΔC’, ΔH’, Δa* and Δb*) have been fitted to the data using the same two predictor variables (enamel thickness and n). A minimum of four hypothesis tests have been carried out for each model (overall model, constant, enamel thickness and n). Using Bonferroni adjustment in model fitting, which is a conservative method for adjusting significance levels to account for multiple testing, would give an alpha of 0.05/24 = 0.002 for all tests in the analyses, assuming no iterations. However, n of enamel would remain a statistically significant predictor of ΔE00 even after adjustment for multiple models fitted (p<0.001). Additionally, the small sample size may have impacted on finding statistically significant results.
5. Conclusion Within the limitations of this study with a small sample size and multiple models fitted to the same data, it was concluded that refractive index (n) of enamel was a statistically significant predictor of tooth colour change (ΔE00) after complete enamel trimming.
Acknowledgement This work was supported by the Global Center of Excellence (GCOE) Program; International Research Center for Molecular Science in Tooth and Bone Diseases at
Tokyo Medical and Dental University, and a Grant-in Aid from the Japan Society for the Promotion of Science (JSPS No. 50272604).
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Figure legends Fig. 1 – (a) The evaluation area (1.0 mm × 1.0 mm) for measuring tooth colour and optical enamel thickness on labial mid-coronal surface.
(b) Enamel blocks (1.0 mm × 4.0 mm, 0.5 mm thick) made from the remaining enamel at incisal site of the prepared teeth.
Fig. 2 –OCT image (a) and corresponding signal intensity profile (b) obtained from the locations marked by arrows. Z0 and Z2 represent top and bottom of enamel specimen, respectively, from which the OPL was calculated. Z1 shows the location of metal stage over which the enamel was placed. The n was calculated by diving the OPL over the actual thickness or (Z2－Z0)/(Z1－Z0). The values of Z0, Z1 and Z2 were found according to the axial locations of peaks in the corresponding signal intensity profiles (b).
Fig. 3 – The colour differences (ΔE00) between before and after enamel trimming at each enamel thickness. The shade of intact teeth are shown in the right legend column.
Fig. 4 - The colour differences between before and after enamel trimming, in terms of colour coordinate changes [(a) ΔL’, (b) ΔC’, (c) ΔH’, (d) Δa* and (e) Δb*] at each enamel thickness. The shade of intact teeth are shown in the right legend column.
Table Table 1; Summary of the multiple linear regression analysis for colour difference (ΔE00) after complete enamel trimming vs. enamel thickness of intact teeth and refractive index (n) of enamel. ANOVA Model
Sum
of
Squares
df
Mean Square
F
Sig.
22.554
<0.001
Regression
79.278
2
39.639
Residual
21.09
12
1.758
Total
100.368
14
Model
Unstandardized
Standardized
Coefficients
Coefficients
Collinearity Sig.
B
Std. Error
(Constant)
-224.435
42.753
Thickness (m)
0.007
0.003
0.364
0.022
1.088
n
138.204
26.721
0.714
<0.001
1.088
R2=0.755
Beta
Statistics VIF
<0.001
Table 2; Summaries of the multiple linear regression analyses for colour coordinate changes in colour parameters of CIELCh after complete enamel trimming vs. enamel thickness of intact teeth and refractive index (n) of enamel. (a) ΔL’ after complete enamel trimming vs. enamel thickness of intact teeth and n of enamel ANOVA Model
Sum
of
Squares
df
Mean Square
F
Sig.
2.455
0.128
Regression
69.837
2
34.918
Residual
170.663
12
14.222
Total
240.499
14
Model
Unstandardized
Standardized
Coefficients
Coefficients
Collinearity Sig.
Beta
Statistics
B
Std. Error
VIF
(Constant)
-120.478
121.617
thickness (m)
0.012
0.007
0.423
0.121
1.088
n
70.291
76.012
0.235
0.373
1.088
0.341
2
R =0.172 (b) ΔC’ after complete enamel trimming vs. enamel thickness of intact teeth and n of enamel ANOVA Model
Sum
of
Squares
df
Mean Square
F
Sig.
1.672
0.229
Regression
60.894
2
30.447
Residual
218.540
12
18.212
Total
279.434
14
Model
Unstandardized
Standardized
Coefficients
Coefficients
Collinearity Sig.
B
Std. Error
(Constant)
-113.283
137.623
thickness (m)
-0.015
0.008
-0.475
0.100
1.088
n
76.763
86.015
0.238
0.390
1.088
2
R =0.088
Beta
Statistics VIF
0.426
(c) ΔH’ after complete enamel trimming vs. enamel thickness of intact teeth and n of enamel ANOVA Model
Sum
of
Squares
df
Mean Square
F
Sig.
6.159
0.014
Regression
20.184
2
10.092
Residual
19.661
12
1.638
Total
39.845
14
Model
Unstandardized
Standardized
Coefficients
Coefficients
Collinearity Sig.
B
Std. Error
(Constant)
-120.721
41.279
thickness (m)
0.003
0.002
0.228
0.302
1.088
n
74.75
25.8
0.613
0.013
1.088
2
R =0.424
Beta
Statistics VIF
0.013
Table 3; Summaries of the multiple linear regression analyses for colour coordinate changes in colour parameters of CIELab after complete enamel trimming vs. enamel thickness of intact teeth and refractive index (n) of enamel. The result of ΔL* in CIELab colour scale is same as that of ΔL’ in CIELCh colour scale (see Table 2a). (a) Δa* after complete enamel trimming vs. enamel thickness of intact teeth and n of enamel ANOVA Model
Sum
of
Squares
df
Mean Square
F
Sig.
3.674
0.057
Regression
7.806
2
3.903
Residual
12.748
12
1.062
Total
20.553
14
Model
Unstandardized
Standardized
Coefficients
Coefficients
Collinearity Sig.
Beta
Statistics
B
Std. Error
VIF
(Constant)
58.925
33.238
thickness (m)
-0.003
0.002
-0.358
0.157
1.088
n
-35.927
20.774
-0.410
0.109
1.088
0.102
R2=0.276 (b) Δb* after complete enamel trimming vs. enamel thickness of intact teeth and n of enamel ANOVA Model
Sum
of
Squares
df
Mean Square
F
Sig.
1.823
0.204
Regression
70.892
2
35.446
Residual
233.317
12
19.443
Total
304.209
14
Model
Unstandardized
Standardized
Coefficients
Coefficients
Collinearity Sig.
B
Std. Error
(Constant)
-124.341
140.200
thickness (m)
-0.016
0.008
-0.490
0.088
1.088
n
84.170
88.876
0.250
0.362
1.088
R2=0.105
Beta
Statistics VIF
0.399
S0300-5712(16)30096-3 http://dx.doi.org/doi:10.1016/j.jdent.2016.05.010 JJOD 2625
To appear in:
Journal of Dentistry
Received date: Revised date: Accepted date:
26-7-2015 9-5-2016 26-5-2016
Please cite this article as: Oguro Rena, Nakajima Masatoshi, Seki Naoko, Sadr Alireza, Tagami Junji, Sumi Yasunori.The role of enamel thickness and refractive index on human tooth colour.Journal of Dentistry http://dx.doi.org/10.1016/j.jdent.2016.05.010 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
The role of enamel thickness and refractive index on human tooth colour
Short title: The role of enamel thickness and refractive index on tooth colour Authors: Rena Oguroa, Masatoshi Nakajimaa, Naoko Sekib, Alireza Sadrc, Junji Tagamia,d, Yasunori Sumie a
Cariology and Operative Dentistry, Oral Restitution Department, Graduate School of
Medical and Dental Sciences, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo, 113-8549, Japan b
Dental Education Development Section, Graduate School of Medical and Dental
Sciences, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo, 113-8549, Japan c
Biomimetics Biomaterials Biophotonics & Technology Laboratory, Department of
Restorative Dentistry, University of Washington School of Dentistry, 1959 NE Pacific St. Box 357456, Seattle, WA, 98195-7456, USA d
Global Center of Excellence (GCOE) Program; International Research Center for
Molecular Science in Tooth and Bone Diseases, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo, 113-8549, Japan
e
National Center for Geriatrics and Gerontology, Department for Advanced Dental
Research, Center of Advanced Medicine for Dental and Oral Diseases, 36-3, Gengo, Morioka, Obu, Aichi 474-8511, Japan
*Corresponding author: Masatoshi Nakajima Cariology and Operative Dentistry, Oral Restitution Department, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo, 113-8549, Japan Tel: +81 3 5803 5483
Fax: +81 3 5803 0195
E-mail: [email protected]
Naoko Seki Dental Education Development Section, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo, 113-8549, Japan Tel: +813 5803 4537 E-mail: [email protected]
Abstract Objectives: To investigate the role of enamel thickness and refractive index (n) on tooth colour. Methods: The colour and enamel thickness of fifteen extracted human central incisors were determined according to CIELab colour scale using spectrophotometer (Crystaleye) and swept-source optical coherence tomography (SS-OCT), respectively. Subsequently, labial enamel was trimmed by approximately 100 µm, and the colour and remaining enamel thickness were investigated again. This cycle was repeated until dentin appeared. Enamel blocks were prepared from the same teeth and their n were obtained using SS-OCT. Multiple regression analysis was performed to reveal any effects of enamel thickness and n on colour difference (ΔE00) and differences in colour parameters with CIELCh and CIELab colour scales. Results: Multiple regression analysis revealed that enamel thickness (p=0.02) and n of enamel (p<0.001) were statistically significant predictors of ΔE00 after complete enamel trimming. The n was also a significant predictor of ΔH’ (p=0.01). Enamel thickness and n were not statistically significant predictors of ΔL’, ΔC’, Δa* and Δb*. Conclusions: Enamel affected tooth colour, in which n was a statistically significant predictor for tooth colour change.
Clinical Significance: Understanding the role of enamel in tooth colour could contribute to development of aesthetic restorative materials that mimic the colour of natural tooth with minimal reduction of the existing enamel. Keywords: Enamel, Tooth colour, Refractive index, Enamel thickness
1. Introduction Aesthetic treatments have become widely requested as the standard of care in restorative dentistry. Among factors necessary for aesthetic restorations, tooth colour evaluation is an important step not only for patients who wish to enhance their smile or appearance, but also for dentists who would like to select appropriate materials with the correct shade and provide the best treatment.1 The perception of tooth colour is a complex phenomenon and can be influenced by a number of factors, including the visual state of the observer, the context in which the tooth is viewed, the type of incident light, and the optical properties and colour in dental tissue.1 Optical properties are intrinsic properties resulting from of a combination of various factors, such as specular and diffuse reflection (light scattering) at the surface, specular transmission of light through the tissue, and absorption and scattering of light within the tissue.2,3 These properties are in turn affected by the composition and histological structure of the tissue.2.3
Coronal dentine is covered by an enamel layer with thicknesses that vary according to the type of the tooth and anatomical location, being approximately 1.0 mm on the average.4 Nevertheless, the colour of a tooth is largely determined by properties of dentine.5 On the other hand, the optical properties of enamel have been widely studied, since enamel has minor, yet noticeable effects on the colour and translucency of natural tooth.5-8 The thickness and translucency property of enamel might control chromatic influence of dentine on natural tooth appearance. Moreover, direct restorations placed over remaining dentin will need to mimic the properties of enamel optically. It is well known that enamel has fluorescence9 and opalescence.10 While fluorescence does not contribute to visually observed colour of the tooth,5,11 enamel affects tooth colour through opalescence, which is defined as scattering of light in the blue wavelength range.5,10 Recently, it was demonstrated that tooth colour parameters (hue, chroma, lightness) were influenced by variability in the mineral composition of enamel, namely the size and degree of the carbonization of the enamel hydroxyapatite (HA) crystals.12 On the other hand, mineral content of enamel was reported to affect its local refractive index (n),13 which is associated with light scattering properties inside the tissue. However, there is no published research on the effects that n of enamel and its thickness may have on tooth colour. It was recently reported that the n of dental hard tissues could be investigated by swept source optical coherence tomography (SS-OCT).14,15 SS-OCT is a rapidly growing
non-invasive interferometric technique, which enables cross-sectional imaging of internal biological structures by differentiating between scattered and transmitted or reflected photons using broad-band, near-infrared (near-IR) light sources on micrometer scale resolution.16,17 SS-OCT has been validated to accurately determine the optical thickness of dental tissue in a nondestructive manner.18 Therefore, the purpose of this study was to investigate the role of enamel thickness and n, using SS-OCT, on human tooth colour. In this study, tooth colour evaluation was performed by measurement of the CIELab L* (lightness), a* (green-red coordinate) and b* (blue-yellow coordinate) value, and by calculation of the CIE2000 ΔL’ (differences in lightness), ΔC’ (differences in chroma), ΔH’ (differences in hue) and ΔE00 (colour difference). The null hypotheses tested were that the enamel thickness and n are not predictors of tooth colour change (ΔE00) after trimming of enamel, and also they are not predictors of ΔL’, ΔC’, ΔH’, Δa* and Δb* after trimming of enamel.
2. Materials and Methods 2.1. Measurement of colour of the teeth Fifteen extracted human central incisors, without endodontic treatment or restorations and stored at 4 oC water were used in this study, according to a protocol approved by the Human Research Ethics Committee, Tokyo Medical and Dental University, Japan (No.725). The teeth
were placed in a jaw model; in order to enable repositioning in the same location, molds were fabricated from silicon putty (EXAFINE PUTTY TYPE, GC, Tokyo, Japan). The jaw model was placed in a black box (inspection kit, OLYMPUS, Tokyo, Japan) which was shielded from external light. The colour of all these intact teeth were then measured using a dental spectrophotometer (Crystaleye, OLYMPUS, Tokyo, Japan) with capture time of 0.2 s, in which 7 light emitting diodes (LEDs) are used as an illumination source corresponding to the standard illuminant D65 with 45°/0° geometry. Prior to data acquisition, the spectrophotometer was calibrated using a calibration plate (OLYMPUS, Tokyo, Japan) and positioned at a consistent distance of 16 mm from the specimen surface using the special contact cap for object measurement. All measurements were performed by the same researcher who was extensively trained. The spectral data was acquired from the captured image of the tooth.19 The reflectance values for each pixel in the range of 400 to 700 nm with 1 nm intervals were transferred from the spectrometer to a personal computer with a Crystaleye software (Crystaleye Application version 1.4, Olympus, Tokyo, Japan).19 In this study, evaluation area (1.0 mm×1.0 mm) was identified on the captured image of the tooth (Fig.1a), in which the colour was analysed using Commission Internationale de lÉclairage colour coordinates L* (lightness), a* (green-red coordinate) and b* (blue-yellow coordinate), known as CIELAB colour coordinates.20 The Crystaleye software also provided tooth colour shade in minimum area of 0.5 mm×0.5 mm by
comparing the database of VITA Classical (VITA, Bad Säckingen, Germany) with the data acquired from the digital image of the teeth. 2.2. Optical enamel thickness measurement using SS-OCT The optical enamel thickness of the teeth were investigated using SS-OCT (OCT-2000, Santec Co., Komaki, Japan).18 The system incorporates a high-speed frequency swept tuneable external cavity laser with wavelength range of 1260 to 1360 nm (centred at 1310 nm) at a 20-kHz sweep rate. The laser beam is projected over the object, and the backscattered light is coupled back to the SS-OCT system, in which the interference signal is digitized in time scale, and then analysed in the Fourier domain to reveal the depth information of the object. The axial and lateral resolutions of the system in air were 11 and 17 µm, respectively. The system acquired the image data (B-scan) in 0.3 s, including the processing time. The imaging window range in this study was 5 mm (width) by 6.6 mm (height) forming a 2000 × 1019 pixel image. The sensitivity of this system and the shot-noise limited sensitivity were 106 and 119 dB, respectively.21 Enamel thickness measurement location was a fixed window of interest (1.0 mm×1.0 mm) on labial mid-coronal surface (Fig.1a). Image analysis software (ImageJ 1.42q; National Institutes of Health, Bethesda, MD, USA) was used to perform SS-OCT image analysis. 2.3. Evaluation of colour and remaining enamel thickness after trimming
Labial enamel of the teeth were trimmed to remove approximately 100 µm thickness using 600-grit and 1000-grit silicon carbide (SiC) papers (Sankyo, Saitama, Japan) under running water. The surface was polished using 1500-grit SiC papers under running water and the optical thickness of remaining labial enamel at the window was investigated on SS-OCT images. Digital colour images of the teeth were also obtained by Crystaleye after their repositioning on the jaw model using the silicon putty mold. Enamel trimming, and optical thickness measurement and spectrophotometer colour determination cycles were repeated until enamel was completely removed and dentine appeared. Each tooth was kept moist at all times in order to avoid its dehydration. In order to evaluate the colour change with enamel trimming, CIEDE2000 color difference (ΔE00) between before and after enamel trimming at each trimming step were calculated via Microsoft Excel spreadsheet at Sharma’s website.22 The CIEDE2000 color-difference formula is based on the CIELAB color space.23 Given a pair of color values in CIELAB space L*1 ,a*1 ,b*1 and L*2 ,a*2 ,b*2, we denote the CIEDE2000 color difference between them.23 The CIEDE2000 color difference formula is given as follows:23 ‘
‘
‘
‘
‘
ΔL’, ΔC’, and ΔH’ between before and after enamel trimming at each trimming step are the differences in lightness, chroma, and hue between before and after enamel trimming and RT is a function (the so-called rotation function) that accounts for the interaction between chroma and
hue differences in the blue region. SL, SC, and SH are the weighing functions for the lightness, chroma, and hue components, respectively. KL, KC, and KH are the parametric factors to be adjusted according to different viewing parameters. ΔL’, ΔC’, and ΔH’ were calculated in the following equations as two step:23 1. Calculate
,
: C ∗,
∗
1, 2
C∗ , 2 ̅∗
0.5 1
̅∗ ∗
1
0 ∗ ∗ tan ,
25
∗
C ∗,
̅∗
G
∗
1, 2
0
1, 2
1, 2
2. Calculate ΔL’, ΔC’, ΔH’: ΔL
L∗
L∗
ΔC
C
C
0 Δ
0
0; | 0; 0;
360 360 Δ
2
sin
Δ 2
|
180° 180° 180°
Additionally, Δa* and Δb* values were calculated as colour coordinate changes at each trimming step, where Δa* was the difference in a* and Δb* was the difference in b* between before and after enamel trimming, using following formula. Δa∗
a∗
a∗
Δb∗
b∗
b∗
2.4. Measurement of refractive index (n) of enamel Following trimming and colour and optical thickness measurement, a 0.5 mm thick enamel block (1.0 mm × 4.0 mm) was prepared from the incisal labial enamel of each tooth (Fig. 1b), using a low-speed diamond saw (Isomet, Buehler, Lake Bluff, IL, USA) under water-cooling. The n values were obtained following the optical path length (OPL) matching method previously described;13,14 briefly, a B-scan along the direction marked with a line was taken to obtain the OCT image (Fig. 2). The lines which represented the reflected light from the upper surface of the sample and the metal plate without the sample, were Z0, and Z1 respectively, and finally Z2 represented the position of the reflector (metal plate) imaged through the tissue. The actual thickness (t) of the sample could be determined by subtraction of the vertical position of the reflector (metal plate) outside the tissue (Z1) from the vertical position of the sample surface (Z0) in the OCT image, and the additional OPL delay can be measured by subtraction of the
vertical position of the reflector imaged through the tissue (Z2) from the vertical position of the sample surface (Z0). Assuming the OPL in the sample is Z2－Z0 and the actual thickness (t) of the sample is Z1－Z0, we can obtain n of the enamel blocks using Eq. (1) as
Eq. (1) was used to calculate the n at each location on average signal intensity profiles as shown in Fig. 2. Each value was calculated using an average profile obtained on an area (10 pixels or 25 mm in width) on the sample.14 Five areas were randomly selected on the region to be evaluated on each slice using the software, from which average n of the region on that enamel block was calculated.14 2.5. Calculation of actual remaining enamel thickness of the teeth The actual remaining enamel thickness of the evaluation area in each tooth was obtained by dividing the optical thickness of enamel on SS-OCT image measured in 2.2 by the n value of the enamel block calculated in 2.4 using Eq. (1). 2.6. Statistical analysis A multiple linear regression analysis was used to reveal any effects of enamel thickness of intact teeth and n of enamel on ΔE00 after complete enamel trimming. Additionally, their effects on ΔL’, ΔC’ and ΔH’ after complete enamel trimming and ΔL*, Δa* and Δb* after complete enamel trimming were analysed. Model fit was assessed using the coefficient of
determination (R squared). The significance level used was alpha=0.05. All statistical procedures were done with the Statistical Package for the Social Science (SPSS Advanced Statistics 23).
3. Results The shades of intact teeth used in this study were A2 (2 teeth), A3 (2 teeth), A3.5 (3 teeth), A4 (2 teeth), B3 (2 teeth), B4 (1 tooth), C1(1 tooth), C2 (1 tooth) and C3(1 tooth). The colour difference (ΔE00) between before and after enamel trimming at each enamel thickness are plotted in Fig. 3. ΔE00 of each tooth steadily increased with decrease of the remaining enamel thickness, and the range of ΔE00 values after complete enamel trimming was from 1.05 to 10.46. In terms of ΔL’, ΔC’ and ΔH’, the colour differences between before and after enamel trimming at each enamel thickness are plotted in Fig. 4. ΔL’ values changed differently among different teeth, ranged from -4.39 to 11.28 after complete enamel trimming (Fig. 4a), and ΔC’ values were highly variable, ranging from -6.40 to 8.87 after complete enamel trimming (Fig. 4b). ΔH’ of each tooth ranged from -0.37 to 5.92 after complete enamel trimming (Fig. 4c). In terms of Δa* and Δb*, Δa* of each tooth hardly showed changes on the plot, ranging from -4.27 to 0.46 after complete enamel trimming (Fig. 4d), while Δb* values were highly variable, ranging from -6.6 to 9.15 after complete enamel trimming (Fig. 4e).
For ΔE00 after complete enamel trimming vs. enamel thickness of intact teeth and n of enamel, multiple linear regression analysis revealed that enamel thickness of intact teeth (p=0.02) and n of enamel (p<0.001) were statistically significant predictors of ΔE00. The overall model (ΔE00
= 138.204 × n + 0.007 × enamel thickness (µm) – 224.435) was statistically significant (p<0.001) with a coefficient of determination of 76% (Table 1).
For ΔH’ after complete enamel trimming vs. enamel thickness of intact teeth and n of enamel, multiple linear regression analysis revealed that n of enamel was a statistically significant predictor of ΔH’ (p=0.01). The overall model was statistically significant (p=0.01) with a coefficient of determination of 42%. Enamel thickness of intact teeth was not a statistically significant predictor of ΔH’ (p=0.30) (Table 2c). On the other hand, for ΔL’and ΔC’ after complete enamel trimming vs. enamel thickness of intact teeth and n of enamel, it was demonstrated that enamel thickness of intact teeth and n of enamel were not statistically significant predictors of ΔL’ (Table 2a), ΔC’ (Table 2b). For Δa* and Δb* after complete enamel trimming vs. enamel thickness of intact teeth and n of enamel, it was demonstrated that enamel thickness of intact teeth and n of enamel were not statistically significant predictors of Δa* (Table 3a) and Δb* (Table 3b).
4. Discussion
In this study, a multiple linear regression analysis demonstrated that enamel thickness of intact teeth (p=0.02) and n of enamel (p<0.001) were statistically significant predictors of ΔE00 after complete enamel trimming (Table 1). In the investigation of each colour parameter, It was revealed that n of enamel was a statistically significant predictor of ΔH’ after complete enamel trimming (p=0.01), but enamel thickness of intact teeth was not a statistically significant predictor of ΔH’ (p=0.30) (Table 2c). On the other hand, enamel thickness of intact teeth and n of enamel were not statistically significant predictors of ΔL’ (Table 2a), ΔC’ (Table 2b), Δa* (Table 3a) and Δb* (Table 3b) after complete enamel trimming. Thus the null hypotheses are partially rejected. ΔE00 increased steadily in different teeth with decrease of the remaining enamel thickness (Fig. 3), and the ΔE00 of 10 specimen out of 15 (66.7%) showed a variation more than 2.23 units, which is considered as the average colour difference acceptability threshold.24 Furthermore, enamel thickness of intact teeth and n of enamel were statistically significant predictors of ΔE00 after complete enamel trimming (ΔE00 = 138.204 × n + 0.007 × enamel thickness (µm) – 224.435) (Table 1). These results indicate that enamel does play a role in determining tooth colour. Furthermore, it was demonstrated that n of enamel was the major predictor of ΔE00 after complete enamel trimming (Table 1). The n is an important parameter of light propagation in biological tissue, including teeth.16 The n of tissue can serve as an indicator
of its scattering properties within the tissue, as scattering itself is the end result of local n variation.16 The values of n in this study were similar to those reported previously.13,14 It was reported that the prism orientations in enamel did not significantly affect n values under SS-OCT.14 SS-OCT is based on low-coherence interferometry and thus at near-infrared wavelength, where enamel is almost completely transparent with the smallest attenuation coefficients,14 it can be used to measure the OPL of this tissue effectively.21 The n of tissue is calculated by ratio of the OPL to the actual thickness.14 Therefore, using n value of enamel block from incisal site of each tooth, actual enamel thickness could be accurately calculated from OPL measured at the evaluation window.14,25 In the investigation of each colour parameter alteration, ΔL’ changed differently among different teeth with decrease of the remaining enamel thickness; the values were mainly in the range of -1.89 to 3.6 (excluding 3 specimens) (Fig. 4a) and the ΔC’ changes were widely distributed in range from -6.40 to 8.87 with removal of the enamel (Fig. 4b). These results would be concerned with translucency and opalescence properties of enamel. The translucency effect is influenced by thickness of material and its translucency property, which would determine the influence of background colour on the colour appearance. If among optical properties of enamel, translucency played a major role in influence on tooth colour, the enamel thickness also would significantly affect it. However, the results of this study demonstrated that
enamel thickness of intact teeth was not statistically significant predictors of ΔL’ (Table 2a), ΔC’ (Table 2b) after complete enamel trimming. Therefore, translucency of enamel would be a minor factor in influencing tooth colour. On the other hand, the ΔH’ change with decrease of enamel thickness was limited, but slightly increased (Fig. 4c). This result would indicate that the hue of an intact tooth comes mainly from dentine and enamel could slightly provide a bluish appearance on frontal view of intact tooth due to the opalescence although it is intrinsically colourless. Opalescence occurs where there is light scattering of the shorter wavelengths of the visible spectrum, giving a bluish appearance to an object under reflected light and an orange/brown appearance under transmitted light.10 The scattering coefficient of enamel increases with decreasing wavelength;6 therefore, the shorter wavelengths (e.g. blue light) are strongly scattered at enamel and are reflected as bluish-white,10 while the longer wavelengths (e.g. orange light) could transmit to dentine through enamel. In this study, Δb* (blue-yellow) changes were widely distributed in range from -6.6 to 9.15 with decrease of the remaining enamel thickness (Fig. 4e) although Δa* (green-red) hardly showed any changes as the remaining enamel got thinner (Fig. 4d). These results indicate that tooth colour change with decrease of enamel thickness was most greatly relying on changes in b* values; this finding is in agreement with a previous study,5 and is thought to be due to the opalescence of enamel. The opalescence might be a major factor to determine colour appearance
of natural tooth as in the optical properties of enamel. However, the results of this study demonstrated that enamel thickness of intact teeth was not statistically significant predictors of ΔH’ (Table 2c) and Δb* (Table 3b) after complete enamel trimming. The opalescence phenomenon in enamel might not be influenced by enamel thickness. Presumably, light scattering of shorter wavelengths might take place at the exposed enamel subsurface, not within the enamel body. Additionally, n of enamel was a statistically significant predictor of ΔH’ after complete enamel trimming (Table 2c). Presumably, n of enamel would be concerned with opalescence of enamel and/or transilluminating behavior of the reflecting colour from underlying dentine within enamel body, resulting in the change in the hue of tooth. On the other hand, the results of this study revealed that n of enamel was not statistically significant predictors of ΔL’ (Table 2a) and ΔC’ (Table 2b); a previous study demonstrated that scattering coefficient of enamel was significantly correlated with tooth lightness (r=0.60).5 Therefore, light scattering at enamel surface would affect tooth lightness. However, the previous study also indicated that since the regression was not very steep, light scattering within enamel body does not contribute much to lightness.5 Tooth colour is different among various types of teeth, locations and ages. Generally, teeth in older people appear darker and yellower, as its enamel HA crystals become larger.26 It
was demonstrated that teeth composed of large enamel HA crystals appeared to be darker than teeth composed of smaller enamel HA crystals.12 Therefore, the age regulated increase in the mean size of enamel HA crystals might be one of the reasons behind tooth shade darkening in elder individuals.12 The age-dependent changes might affect its optical properties, and might play a role in determining tooth colour. Unfortunately, the age of extracted human teeth used in this study were not registered, therefore relationship between n and age of tooth is unclear. Nonetheless, the correlation between n values and ΔE00 is interesting; on one hand it was demonstrated that n of enamel depended on compositional factors, mainly mineral content.13 In this regard, enamel with a larger volume of crystals will have a higher n.13 Moreover, carbonated apatite which is the dominant crystal in human enamel has a lower n than pure HA, while fluoridated apatite has a higher n.13 On the other hand, it was demonstrated that both the carbonate content and size of enamel apatite crystals played role in tooth colour appearance.12 The n appears to be a relevant and important variable while considering the effects of enamel crystalline composition on tooth colour. These findings could provide better understanding of enamel optical properties and aesthetics, and further development of aesthetic restorative materials. Therefore, further research about the role of enamel with age on tooth colour is required in order to successfully mimic the colour and translucency of natural tooth. In the multiple regression analyses of this study, the six regression models (ΔE00, ΔL’,
ΔC’, ΔH’, Δa* and Δb*) have been fitted to the data using the same two predictor variables (enamel thickness and n). A minimum of four hypothesis tests have been carried out for each model (overall model, constant, enamel thickness and n). Using Bonferroni adjustment in model fitting, which is a conservative method for adjusting significance levels to account for multiple testing, would give an alpha of 0.05/24 = 0.002 for all tests in the analyses, assuming no iterations. However, n of enamel would remain a statistically significant predictor of ΔE00 even after adjustment for multiple models fitted (p<0.001). Additionally, the small sample size may have impacted on finding statistically significant results.
5. Conclusion Within the limitations of this study with a small sample size and multiple models fitted to the same data, it was concluded that refractive index (n) of enamel was a statistically significant predictor of tooth colour change (ΔE00) after complete enamel trimming.
Acknowledgement This work was supported by the Global Center of Excellence (GCOE) Program; International Research Center for Molecular Science in Tooth and Bone Diseases at
Tokyo Medical and Dental University, and a Grant-in Aid from the Japan Society for the Promotion of Science (JSPS No. 50272604).
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2007;35:690-694. 11. Johnson WM, Kao EC. Assessment of appearance match by visual observation and clinical colorimetry. Journal of Dental Research 1989;68:819-822. 12. Eimar H, Marelli B, Nazhat SN, Abi Nader S, Amin WM, Torres J, et al. The role of enamel crystallography on tooth shade. Journal of Dentistry 2011;39:3-10. 13. Hariri I, Sadr A, Nakashima S, Shimada Y, Tagami J, Sumi Y. Estimation of the Enamel and Dentin Mineral Content from the Refractive Index. Caries Research 2013;47:18-26. 14. Hariri I, Sadr A, Nakashima S, Shimada Y, Tagami J, Sumi Y. Effects of structural orientation of enamel and dentine on light attenuation and local refractive index: An optical coherence tomography study. Journal of Dentistry 2012;40:387-396 15. Meng Z, Yao XS, Yao H, Liang Y, Liu T, Li Y, et al. Measurement of the refractive index of human teeth by optical coherence tomography. Journal of Biomedical Optics 2009;14: 034010. 16. Knuttel A, Bonev S, Knaak W. New method for evaluation of in vivo scattering and refractive index properties obtaind with optical coherence tomography. Journal of Biomedical Optics 2014;9:265-273. 17. Tearney GJ, Brezinski ME, Southern JF, Bouma BE, Hee MR, Fujimoto JG. Determination of the refractive-index of highly scattering human tissue by optical coherence tomography. Optics Letters 1995;20:2258–60. 18. Majkut P, Sadr A, Shimada Y, Sumi Y, Tagami J. Validation of Optical Coherence Tomography against Micro-computed Tomography for Evaluation of Remaining Coronal Dentin Thickness. Journal of Endodontics (in press) doi: 10.1016/j.joen.2015.03.016. 19. Ishikawa-Nagai S, Yoshida A, Sakai M, Kristiansen J, DaSilva JD. Clinical evaluation of perceptibility of color differences between natural teeth and all-ceremic crowns. Journal of Dentistry 2009;37:57–63. 20. CIE Publication No. 15: Colorimetry Technical Report. 3rd ed. Vienna, Austria:
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Figure legends Fig. 1 – (a) The evaluation area (1.0 mm × 1.0 mm) for measuring tooth colour and optical enamel thickness on labial mid-coronal surface.
(b) Enamel blocks (1.0 mm × 4.0 mm, 0.5 mm thick) made from the remaining enamel at incisal site of the prepared teeth.
Fig. 2 –OCT image (a) and corresponding signal intensity profile (b) obtained from the locations marked by arrows. Z0 and Z2 represent top and bottom of enamel specimen, respectively, from which the OPL was calculated. Z1 shows the location of metal stage over which the enamel was placed. The n was calculated by diving the OPL over the actual thickness or (Z2－Z0)/(Z1－Z0). The values of Z0, Z1 and Z2 were found according to the axial locations of peaks in the corresponding signal intensity profiles (b).
Fig. 3 – The colour differences (ΔE00) between before and after enamel trimming at each enamel thickness. The shade of intact teeth are shown in the right legend column.
Fig. 4 - The colour differences between before and after enamel trimming, in terms of colour coordinate changes [(a) ΔL’, (b) ΔC’, (c) ΔH’, (d) Δa* and (e) Δb*] at each enamel thickness. The shade of intact teeth are shown in the right legend column.
Table Table 1; Summary of the multiple linear regression analysis for colour difference (ΔE00) after complete enamel trimming vs. enamel thickness of intact teeth and refractive index (n) of enamel. ANOVA Model
Sum
of
Squares
df
Mean Square
F
Sig.
22.554
<0.001
Regression
79.278
2
39.639
Residual
21.09
12
1.758
Total
100.368
14
Model
Unstandardized
Standardized
Coefficients
Coefficients
Collinearity Sig.
B
Std. Error
(Constant)
-224.435
42.753
Thickness (m)
0.007
0.003
0.364
0.022
1.088
n
138.204
26.721
0.714
<0.001
1.088
R2=0.755
Beta
Statistics VIF
<0.001
Table 2; Summaries of the multiple linear regression analyses for colour coordinate changes in colour parameters of CIELCh after complete enamel trimming vs. enamel thickness of intact teeth and refractive index (n) of enamel. (a) ΔL’ after complete enamel trimming vs. enamel thickness of intact teeth and n of enamel ANOVA Model
Sum
of
Squares
df
Mean Square
F
Sig.
2.455
0.128
Regression
69.837
2
34.918
Residual
170.663
12
14.222
Total
240.499
14
Model
Unstandardized
Standardized
Coefficients
Coefficients
Collinearity Sig.
Beta
Statistics
B
Std. Error
VIF
(Constant)
-120.478
121.617
thickness (m)
0.012
0.007
0.423
0.121
1.088
n
70.291
76.012
0.235
0.373
1.088
0.341
2
R =0.172 (b) ΔC’ after complete enamel trimming vs. enamel thickness of intact teeth and n of enamel ANOVA Model
Sum
of
Squares
df
Mean Square
F
Sig.
1.672
0.229
Regression
60.894
2
30.447
Residual
218.540
12
18.212
Total
279.434
14
Model
Unstandardized
Standardized
Coefficients
Coefficients
Collinearity Sig.
B
Std. Error
(Constant)
-113.283
137.623
thickness (m)
-0.015
0.008
-0.475
0.100
1.088
n
76.763
86.015
0.238
0.390
1.088
2
R =0.088
Beta
Statistics VIF
0.426
(c) ΔH’ after complete enamel trimming vs. enamel thickness of intact teeth and n of enamel ANOVA Model
Sum
of
Squares
df
Mean Square
F
Sig.
6.159
0.014
Regression
20.184
2
10.092
Residual
19.661
12
1.638
Total
39.845
14
Model
Unstandardized
Standardized
Coefficients
Coefficients
Collinearity Sig.
B
Std. Error
(Constant)
-120.721
41.279
thickness (m)
0.003
0.002
0.228
0.302
1.088
n
74.75
25.8
0.613
0.013
1.088
2
R =0.424
Beta
Statistics VIF
0.013
Table 3; Summaries of the multiple linear regression analyses for colour coordinate changes in colour parameters of CIELab after complete enamel trimming vs. enamel thickness of intact teeth and refractive index (n) of enamel. The result of ΔL* in CIELab colour scale is same as that of ΔL’ in CIELCh colour scale (see Table 2a). (a) Δa* after complete enamel trimming vs. enamel thickness of intact teeth and n of enamel ANOVA Model
Sum
of
Squares
df
Mean Square
F
Sig.
3.674
0.057
Regression
7.806
2
3.903
Residual
12.748
12
1.062
Total
20.553
14
Model
Unstandardized
Standardized
Coefficients
Coefficients
Collinearity Sig.
Beta
Statistics
B
Std. Error
VIF
(Constant)
58.925
33.238
thickness (m)
-0.003
0.002
-0.358
0.157
1.088
n
-35.927
20.774
-0.410
0.109
1.088
0.102
R2=0.276 (b) Δb* after complete enamel trimming vs. enamel thickness of intact teeth and n of enamel ANOVA Model
Sum
of
Squares
df
Mean Square
F
Sig.
1.823
0.204
Regression
70.892
2
35.446
Residual
233.317
12
19.443
Total
304.209
14
Model
Unstandardized
Standardized
Coefficients
Coefficients
Collinearity Sig.
B
Std. Error
(Constant)
-124.341
140.200
thickness (m)
-0.016
0.008
-0.490
0.088
1.088
n
84.170
88.876
0.250
0.362
1.088
R2=0.105
Beta
Statistics VIF
0.399