Topographic characterization of canine teeth using atomic force microscopy images in nano-scale
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The purpose of the present study was to investigate a new method to evaluate micro topography and micro morphology of hard tissue of canine teeth using an atomic force microscope (AFM). For this aim, three extracted human canine teeth were applied. The unpolished surfaces were analyzed with AFM images with 15 µm × 5 µm area and their information obtained by power spectral density (PSD) method and fast Fourier transform algorithm. It was observed that PSD analyses extract suitable information about surface morphological variations so that by moving from enamel to cementum, the fractal dimension and surface complexity were increased.
KeywordsCanine tooth Surface morphology Power spectral density
Surface morphology at nanoscale is a key factor in technological applications as well as fundamental science [1, 2, 3]. In the past decade, atomic force microscope (AFM) images were considered as the best source of information about surface topography obtained through a very small probe which forms the profile of the surface morphology quantitatively . There exist various types of methods which give information about surface texture, i.e. surface regulations including skewness, power spectral density (PSD), autocorrelation function, RMS roughness, and fractal dimension (Df) . Statistical descriptions of RMS roughness represent the average square of the difference between the heights of peaks and valleys and they do not describe lateral distribution. One of the significant differences between investigating surface topography by RMS roughness and PSD methods is that the first method does not describe surfaces with complex morphology and behavior in the appropriate way since it may show the same value of RMS roughness. In addition, the first method depends just on the length scale. Thus, PSD is a more accurate method due to its ability in performing fast Fourier transform (FFT) of the squared height profile versus wavelength. PSD method helps to compare roughness in different spatial frequency regions [6, 7].
Among various types of surfaces whose morphology can be estimated, human tooth attracts a lot of attention nowadays . Enamel, dentin, and cementum are three hard tissues which form human tooth. Amongst, enamel which covers the crown is the most rigid and mineralized tissue whose main content is 96 wt% inorganic materials mainly composed of hydroxyapatite (HAP) crystals  composed of phosphorous and calcium. Formation of enamel, called amelogenesis, occurs by cytodifferentiation, matrix secretion, and maturation process . Dentin is the second tissue which contains dental pulps and it is composed of mineral components and complex protein . Dentin is formed by odontoblasts where 30% and 50% of its compositions are collagen and HAP minerals . Finally, Cementum, whose composition is similar to bone, is mainly composed of HAP (65 wt%), along with organic matrix including collagen and noncollagenous proteins and also water . These tissues with their complex structure are highly organized. In order to investigate surface morphology of enamel, dentin, and cementum, atomic force microscopy (AFM) was applied as the best technique to specify surface morphology along x, y, and z axes. The aim of the present work was to analyze AFM images of hard tissue of canine teeth by PSD plots which provide information about height distribution. Afterward, fractal geometry was extracted through FFT algorithm as a tool which can describe dental complex nature. The calculated parameters can affect physical properties of each tissue as the hallmark of fractals.
In a dental clinic, three extracted human canine teeth were placed in saline and transferred to the laboratory. After when they reached the laboratory, they were all cleaned ultrasonically and finally air-dried. Each tooth was sectioned with diamond discs (Discoflex, KG Sorensen, Brazil) to access inter enamel. Enamel, inter enamel, dentin, and cementum tissue of each tooth were imaged with an AFM (Veeco, Santa Barbara, CA, USA) in non-contact mode at room temperature with scan rates of 10–20 μm/s over square areas of 1 μm × 1 μm. Quantitative information including PSD and fractal dimension was obtained from the AFM images.
Results and discussion
As mentioned before, Rrms evaluation does not give essential information about height scale and makes scientists replace it with another statistical parameter called PSD which describes roughness changes with length scale.
PSD is defined as the square of surface roughness amplitude versus wavelength which is applied to compare surface quality quantitatively . AFM images are for PSD analysis as presented in Fig. 2 for all tissue. Figure 3 represents the PSD plots of dental hard tissue, i.e. enamel out, inter enamel, dentin, and cementum calculated through FFT algorithm. Moreover, frequency distribution versus frequency are calculated by FFT and finally PSD functions as |F(x, y)|2 in which F(x, y) are FFT coefficients. On the other hand, normalizing PSD reaches units of (length)4 .
Here, “A” is the magnitude of low spatial frequency, “B” is the ‘knee,’ i.e. the slope of connective line between two points of the surface of enamel, dentin, and camentum, and “C” with its constant value refers to the nature of roughness.
The values of Df for each tissue extracted from Eq. (6)
Fractal dimension (D)
The values of Df and slopes in specified frequency region of enamel
The values of Df and slopes in specified frequency region of dentin
The values of Df and slopes in specified frequency region of cementum
Moreover, Table 3 shows that by decreasing slope from low to mid frequency region in dentin, fractal dimension was increased while by moving to high-frequency region, increasing slope reduces the fractal dimension. In Table 4, as can be seen for cementum, increasing frequency from low to mid decreases fractal dimension while moving from mid to high-frequency region decreases the slope which finally ends in increase of fractal dimension.
The present work focused on the surface morphology of hard tissue of canine tooth including enamel, dentin, and cementum. The obtained results confirm that PSD method and fractal dimension are the best candidates for measuring surface morphology and performing functional characteristics of surface. According to the statistical parameters obtained from 3D AFM images, surface roughness parameters were measured precisely so that surface characterization was strongly affected by external factors. In addition, the dependency of surface roughness on the slope of log PSD–log K diagram along with fractal dimensions was investigated for different dental tissue. As can be seen, increasing slope ends in increase of fractal dimension and surface complexity. Moreover, by moving from enamel to cementum, fractal dimension has been increased. Finally, fine but complex structure of dental tissues was observed through Raman spectra in which functional groups of HAP were clear.
Compliance with ethical standards
Conflict of interest
The authors report no conflict of interests. The authors alone are responsible for the content and writing of the paper.
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