Techniques of digital image analysis for histological quantification of melanin

Abstract

Melanin is the main pigment related to skin color, and its quantification in histological sections can contribute to clinical, pathophysiological and therapeutic research on skin pigmentation disorders. 1A histological estimation of melanin is usually made in a qualitative way by an experienced dermatopathologist, based on visual grading of the quartiles (0 to 4+) of each of the affected areas evaluated, which are stained with specific stains, such as FontanaMasson. 2,3 However, morphometric analysis of the pixels that represent the melanin pigment in digital images of histological slides is more sensitive, accura- Evaluation of the percentage of pixels equivalent to melanin in samples of the total epidermis, of its layers, or of the dermis seems to be a suitable variable for comparison between groups, since an estimation of the intensity of the individual colors of pixels do not show to be directly useful to research on pigmentation disorders. In addition, its stoichiometric relationship An Bras Dermatol. 2012;87(4):608-11. Techniques of digital image analysis for histological quantification of melanin 609of two color clusters and calculation of the pixels composing the clusters that represent melanin ( Figure 4). The k-means clustering algorithm considers the Euclidean distance of all pixels in the region of interest projected in an orthogonal space of its RxGxB components. That is, if each pixel is represented by a coordinate point (R, G, B), the virtual linear distance between them can be estimated and groups of pixels of similar color can be formed. The algorithm replaces their original values with their k centroids and forms an image with k colors. This is a quick and efficient method for separating histochemical stains such as Masson's trichrome and Hematoxylin-Eosin, in addition to being little sensitive to variations in color saturation and image brightness. 8,9 with color density has not yet been established. 5,6 Thus, the use of image processing techniques that allow for segmentation of the pixels equivalent to the melanin of other structures in a selected area may result in an appropriate choice for analysis of pigmentation disorders.3 In this study, we discuss three techniques for segmentation of pixels related to epidermal melanin using microscopic digital images of facial skin with melasma and adjacent healthy skin, stained with Fontana-Masson and analyzed by ImageJ v.1.44l software (National Institutes of Health -NIH, Bethesda, Maryland, USA, 2010). 7To demonstrate histological quantification of melanin in histological sections (areas of interfollicular epidermis), two slides were photographed with Nikon Coolscope II (Nikon Instruments Inc., Tokyo, Japan, 2009) at 40x magnification, and the 24bit color images, 1280x960 pixels, were stored in .bmp digital files (Figure 1). The amount of epidermal melanin estimated by each method was corrected for the width of each section selected.After manually determining the area of the epidermis to be evaluated, the first analysis technique to be employe...

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“…The photos represented interfollicular spaces and were captured in triplicate for each slide under 40x magnification. The thicknesses of the stratum corneum, epithelium (measured from the basal layer to the upper granular layer), and granular layer (measured as the density of melanin and collagen in the upper dermis) was measured digitally using Image J software 1.46 [7,[17][18][19].…”

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“… Quantification of the diameter of the hair infundibulum which corresponds, in a histological section, to the length of the opening of the hair infundibulum, through software for image analysis (Imagej ® , National Institutes of Health, Bethesda, MD, USA). Quantification of melanin and fluorescein in the deepest hair follicles (hair follicles without granular layer/sebaceous glands) by Fontana–Masson staining 11 and by fluorescent microscopy respectively. …”