Mini Review
Austin J Cancer Clin Res 2015;2(7): 1057.
Fractal and Spectral Analyses of Peritumoral Skin Melanoma
Piérard GE1,2*, Piérard-Franchimont C1,3,4, Hermanns-Lê T1,3, Piérard SL5 and Delvenne P³
¹Department of Clinical Sciences, Liège University, Belgium
²University of Franche-Comté, France
³Department of Dermatopathology, Unilab Lg, Liège University Hospital, Belgium
4Department of Dermatology, Regional Hospital of Huy, Belgium
5Telecommunications and Imaging Laboratory INTELSIG, University of Liège, Belgium
*Corresponding author: Gérald E Piérard, Department of Clinical Sciences, Laboratory of Skin Bioengineering and Imaging (LABIC), Liège University, B-4000 Liège, Belgium
Received: July 17, 2015; Accepted: August 10, 2015; Published: August 13, 2015
Abstract
Sporadic cutaneous malignant melanoma (SCMM) represents one of the most dramatic skin cancers, and its incidence is steadily growing in Caucasian populations. A sustained relative epidemiological increase has been disclosed in young women during their childbearing ages. In this group of patients, the peritumoral skin was reported to lack obvious signs of repeated ultraviolet light exposures including boosted mottled subclinical melanoderma. The possible impact of endocrine disruptors was suggested. Angiogenesis and lymphangiogenesis associated with SCMM potentially influence the neoplastic progression of the primary tumor and its metastases. In some instances, both the microvasculature is correlated to the extent of the tumoral growth fraction. In addition, the vascular network corresponds to a migration path for the intravascular and perivascular metastatic spread. Accordingly, the analytical quantification of the microvasculature could help establishing a prognostic aspect of the SCMM progression. Fractals and spectral analyses of immunohistochemical sections help defining the microvasculature distribution. The benefit of using spectral analysis is discussed and the modalities of application of this analytical method are scrutinized.
Keywords: Melanoma; Angiogenesis; Spectral analysis
Introduction
Sporadic cutaneous malignant melanoma (SCMM) is a dramatic cancer at risk for releasing metastases in proportion to the thickness of the primary tumor. Early detection of SCMM appears critical to the survival of the patient because at advanced stages, the SCMM metastases dramatically impede survival. The current procedures for early diagnosis of SCMM include clever clinical examination by an experienced physician including an expert dermatologist in dermoscopy. In addition, non-invasive cyanoacrylate skin surface strippings [1,2], and a tissue biopsy are appropriate when dermoscopy suggests the presence of SCMM. A series of immunohistochemical and molecular clues help identifying distinct types and stages of SCMM [3–5]. In our experiences, about 30-40% of suspected lesions correspond to an early SCMM.
The process of malignant transformation, progression and metastasis of SCMM is only partially understood. Furthermore, tumor staging proves to be particularly complex due to its multifaceted nature [5–7]. SCMM tumors are regarded as heterogeneous populations of neoplastic melanocytes displaying temporary unrestricted growth patterns compared with ordinary cells [5]. The progressive thickening of any primary SCMM is accompanied by an increased expression of various proto-oncogenes contrasting with a decreased expression of putative tumor suppressor genes [8]. Clearly, the peritumoral stroma in SCMM exhibits changes in a series of cell phenotypes [9–11]. In particular, the microvasculature shows frequently prominent changes [12–16]. In addition, there is general agreement to consider that the SCMM progression and dissemination are related to the neoplastic cell proliferation [13,17,18].
Of note, gender disparities were reported in the incidence and outcome of SCMM [19–23]. In recent years, some clinical studies were focused on SCMM developed in women during their childbearing age [19–24]. This neoplasm has shown an increased epidemiologic incidence over the past few decades. The vast majority of these SCMM were of the superficial type without any obvious relationship with a large number of dysplastic melanocytic nevi. Signs of frequent and intense sunlight exposure were not disclosed by the extent in the mottled subclinical melanoderma [20,24]. A series of investigations pointed to a possible relationship linking the development of some of these SCMM and the women hormonal status including the possible influence of hormonal disruptors [20,24]. However, these aspects remain yet unsettled.
It is possible to differentiate and clearly quantify the SCMM shape, size, scalloped border, and variegated pigmentation using computerized morphometry as well as fractal and multifractal methods [25–27].
The primary aims of the present study were to revisit some analytical aspects of SCMM-related micro-angiogenesis and peritumoral keratinocyte melanosis using novel developments in fractals and spectral analyses. Particularly, some basic aspects and relationships are reported between SCMM progression and the host vasculature, and possible relationships are highlighted in gender influences between both SCMM amplification and proliferation, and SCMM microvasculature.
Morphometry of subclinical epidermal melanoderma
The ultraviolet light-enhanced visualization (ULEV) method conveniently discloses patterns of epidermal melanoderma induced by chronic ultraviolet light exposures [20,28].
At the site of SCMM, the size of the tumor, its axial symmetry, the border irregularity, the form factor can be assessed. In particular, fractal analysis is well suited for assessing the edge structure [25].
Fractal and multifractal analysis of angiogenesis
The peri-SCMM microvasculature shows large interindividual variations in its pattern of distribution and extent [29]. No gender differences were disclosed in these aspects. A relationship between angiogenesis and SCMM progression appears as clear evidence. The microscopic examination of SCMM with specific endothelial cell immunostaining suggests some differences in the distribution of the vascular staining [30]. In fact, the homogeneity of the tissue vascularization is variable, as well as the orientation of the blood vessels.
The possibility of extracting information was explored about the vessel distribution, performing a textural analysis on the grey level of histological sections by means of fractal characterization by both Fourier spectrum and multifractal analysis [29]. Distinct different patterns of vasculature were identified according to the vessel density and distribution. Irregular profiles of ramified vessels appeared at different ranges of the grey level and seemed randomly distributed on the plane of the sections.
Many biologic processes are known to be heterogeneous, especially in the oncologic field. Repartition of estrogenic receptors, ploidy or cellular proliferation is known to be heterogeneous, and the heterogeneity of these variables has been deduced from multiple measures sampled in different sites of the tumor. Although such evaluation does not represent a quantitative approach, it evokes the heterogeneity of the phenomenon. The same is true for angiogenesis among SCMM.
Spectral analysis
Objective quantification of blood vessels and lymphatics [30] potentially represents an assessment of prognostic value. Numerous studies were conducted, but some results are conflicting leading to complex interpretations. One of the difficulties resides in the choice of the method of quantification of the vessels. Fractal and spectral analyses open new horizons.
Diffuse reflectance spectroscopy is well suited for exploring optical biopsies [31]. Diffuse reflectance provides quantitative measures of the wavelength-dependent reduced scattering and absorption coefficient that relate to the tissue structure and function, respectively [32]. A reduced scattering coefficient corresponds to an inverse power law function of wavelength in the visible range, and depends on the scatter size and density [33]. The absorption coefficient of a tissue is a function of physiological parameters particularly including blood volume fraction, oxygen saturation, blood vessel size, and melanin concentration [34].
Growth of SCMM depends upon appropriate neoagnogenesis. Such a relationship is, however, not similar for all tumors. In other respects, the metastatic dissemination is potentially enhanced by such microvascular network as well as by a boosted lymphangiogenesis; the SCMM is a typical archetype for these cancers.
Discussion
The worldwide increase in epidemiological incidence of SCMM in Caucasians over the past decades is possibly genuine and/or related to multiple close screenings in individuals with light complexion. Obviously, the risk markedly varies according to the combination of both the ethnic skin pigmentation and individual behavior regarding ultraviolet light (UVL) exposure [35,36]. SCMM commonly occurs in young adults [36,37]. SCMM is generally more common in women than in men (sex ratio 2:1), but carries a better prognosis for affected women. In some Caucasian populations of Western Europe, the rising incidence of SCMM over the past decades has particularly affected young women [20,38–40]. The cause for such sex- and age-related SCMM risk remains presently unsettled. Environmental factors, including UVL exposure from the sun and tanning sun beds [40] could be suspected, but the role of some chemical xenobiotics, particularly hormonal disruptors, is not ruled out [41–44]. Tackling the causative origin of SCMM appears to be provided by fractal analysis of ULEV pictures of the peritumoral skin. Chronic exposure of the epidermis to UVL induces an increased production of melanin by melanocytes and its transfer to neighbour keratinocytes in each epidermal melanin unit. Such activation is responsible for the presentation of fain mosaic melanoderma (FMM), particularly evident in Caucasian skin.
The acquired discrete uneven skin pigmentation forming the FMM pattern is a hallmark of photoaging [30,45]. Once delivered by melanocytes to keratinocytes, melanin acts, in part, as a UVL filter. However, according to individual parameters, including the phototype, age, and previous cumulative UVL exposures, skin presents distinct FMM appearances [45]. The diverse patterns of age-related FMM is conveniently disclosed and magnified using computerized ULEV [45], a charge-coupled device (CCD) camera equipped with an internal UVL-emitting unit is suitable for precise quantification of the epidermal melanin content [1]. The increased contrast between the FMM and the rest of the skin is the combined result of (a) the greater reflection of UVL wavelengths than visible light by dermal fibers, and (b) the greater UVL absorption by epidermal melanin [22]. Any other UVL-absorbing or –reflecting structure interposed above the dermal fibrous networks likely will alter the ULEV reading. In previous observations, some individuals exhibit rare and discrete foci of nearly total depigmentation [19]; the focal amelanotic skin appears as white iridescent skin ivory spots.
Beyond regular morphologic parameters including tumor thickness and the proliferative rate, other prognostic markers might add important information improving prognosis, treatment and survival. Immunohistochemical markers, gene expression arrays, genomic hybridization and mutational profiling are possible. These methods require specially equipped laboratories. Fractal and spectral analyses can be added to the list helping improving SCMM classifications. Computerized analysis of SCMM achieves high sensitivity and specificity in diagnosis in the interpretations of pictorial data according subjectivity.
Acknowledgement
The authors appreciate the excellent secretarial assistance of Mrs. Marie Pugliese and Ida Leclercq.
References
- Piérard-Franchimont C, Piérard GE. [The value of morphometry and of surface biopsy in the detection of malignant melanoma]. Rev Med Liege. 1989; 44: 610-614.
- Piérard GE, Piérard-Franchimont C, Paquet P, Hermanns-Lê T, Radermacher J, Delvenne P. Cyanoacrylate skin surface stripping and the 3S-Biokit advent in tropical dermatology: a look from Liège. ScientificWorldJournal. 2014; 2014: 462634.
- Ohsie SJ, Sarantopoulos GP, Cochran AJ, Binder SW. Immunohistochemical characteristics of melanoma. J Cutan Pathol. 2008; 35: 433-444.
- Elder DE. Pathological staging of melanoma. Methods Mol Biol. 2014; 1102: 325-351.
- Piérard-Franchimont C, Hermanns-Lê T, Delvenne P, Piérard GE. Dormancy of growth-stunted malignant melanoma: sustainable and smoldering patterns. Oncol Rev. 2014; 8: 252.
- Marcoval J, Moreno A, Graells J, Vidal A, Escribà JM, Garcia-Ramírez M, et al. Angiogenesis and malignant melanoma. Angiogenesis is related to the development of vertical (tumorigenic) growth phase. J Cutan Pathol. 1997; 24: 212–218.
- Chu VH, Tetzlaff MT, Torres-Cabala CA, Prieto VG, Bassett R Jr, Gershenwald JE, et al. Impact of the 2009 (7th edition) AJCC melanoma staging system in the classification of thin cutaneous melanomas. Biomed Res Int. 2013; 2013: 898719.
- Piérard GE, Piérard-Franchimont C. HOX Gene Aberrant Expression in Skin Melanoma: A Review. J Skin Cancer. 2012; 2012: 707260.
- Mikesh LM, Kumar M, Erdag G, Hogan KT, Molhoek KR, Mayo MW, et al. Evaluation of molecular markers of mesenchymal phenotype in melanoma. Melanoma Res. 2010; 20: 485-495.
- Piérard GE, Piérard-Franchimont C, Delvenne P. Malignant melanoma and its stromal nonimmune microecosystem. J Oncol. 2012; 2012: 584219.
- McCarthy N. Tumour microenvironment: more than just a mutagen. Nat Rev Cancer. 2014; 14: 213.
- Piérard GE, Piérard-Franchimont C. Stochastic relationship between the growth fraction and vascularity of thin malignant melanomas. Eur J Cancer. 1997; 33: 1888-1892.
- Piérard-Franchimont C, Henry F, Heymans O, Piérard GE. Vascular retardation in dormant growth-stunted malignant melanomas. Int J Mol Med. 1999; 4: 403-406.
- Mandriota SJ, Jussila L, Jeltsch M, Compagni A, Baetens D, Prevo R, et al. Vascular endothelial growth factor-C-mediated lymphangiogenesis promotes tumour metastasis. EMBO J. 2001; 20: 672-682.
- Dadras SS, Paul T, Bertoncini J, Brown LF, Muzikansky A, Jackson DG, et al. Tumor lymphangiogenesis: a novel prognostic indicator for cutaneous melanoma metastasis and survival. Am J Pathol. 2003; 162: 1951-1960.
- Nagaoka T, Nakamura A, Okutani H, Kiyohara Y, Sota T. A possible melanoma discrimination index based on hyperspectral data: a pilot study. Skin Res Technol. 2012; 18: 301-310.
- Frahm SO, Schubert C, Parwaresch R, Rudolph P. High proliferative activity may predict early metastasis of thin melanomas. Hum Pathol. 2001; 32: 1376-1381.
- Piérard GE. Cell proliferation in cutaneous malignant melanoma: relationship with neoplastic progression. ISRN Dermatol. 2012; 2012: 828146.
- Piérard-Franchimont C, Uhoda I, Piérard GE. Cutaneous cancers in the Mosan region and Ardennes of Belgium. Dermatology. 1999; 198: 187-191.
- Hermanns-Lê T, Piérard-Franchimont C, Piérard GE. Scrutinizing skinfield melanin patterns in young Caucasian women. Expert Opin Med Diagn. 2013; 7: 455-462.
- Burton AL, Egger ME, Quillo AR, Stromberg AJ, Hagendoorn L, Scoggins CR, et al. Prognostic factors in young women with cutaneous melanoma. Am J Surg. 2014; 207: 102-108.
- Hermanns-Lê T, Piérard S. Streamlining cutaneous melanomas in young women of the Belgian Mosan region. Biomed Res Int. 2014; 2014: 320767.
- Nosrati A, Wei ML. Sex disparities in melanoma outcomes: the role of biology. Arch Biochem Biophys. 2014; 563: 42-50.
- Piérard GE, Hermanns-Lê T, Piérard SL, Dewalque L, Charlier C, Piérard-Franchimont C, et al. In vivo skin fluorescence imaging in young Caucasian adults with early malignant melanomas. Clin Cosmet Investig Dermatol. 2014; 7: 225-230.
- Heymans O, Blacher S, Brouers F, Piérard GE. Fractal quantification of the microvasculature heterogeneity in cutaneous melanoma. Dermatology. 1999; 198: 212-217.
- Quatresooz P, Piérard GE, Piérard-Franchimont C, Humbert P, Piérard S. [Spectral analysis of the microvasculature of primary cutaneous melanoma]. Pathol Biol (Paris). 2012; 60: 149-153.
- Cross SS, McDonagh AJ, Stephenson TJ, Cotton DW, Underwood JC. Fractal and integer-dimensional geometric analysis of pigmented skin lesions. Am J Dermatopathol. 1995; 17: 374-378.
- Handels H, Ross T, Kreusch J, Wolff HH, Pöppl SJ. Image analysis and pattern recognition for computer supported skin tumor diagnosis. Stud Health Technol Inform. 1998; 52 Pt 2: 1056-1062.
- Messadi M, Bessaid A, Taleb-Ahmed A. Extraction of specific parameters for skin tumour classification. J Med Eng Technol. 2009; 33: 288-295.
- Petit L, Fogouang L, Uhoda I, Smitz S, Piérard-Franchimont C, Piérard GE. Regional variability in mottled subclinical melanoderma in the elderly. Exp Gerontol. 2003; 38: 327-331.
- Piérard-Franchimont C, Loussouarn G, Panhard S, Saint Léger D, Mellul M, Piérard GE. Immunohistochemical patterns in the interfollicular Caucasian scalps: influences of age, gender, and alopecia. Biomed Res Int. 2013; 2013: 769489.
- Swanson DL, Laman SD, Biryulina M, Nielsen KP, Ryzhikov G, Stamnes JJ, et al. Optical transfer diagnosis of pigmented lesions: a pilot study. Skin Res Technol. 2009; 15: 330-337.
- Marchesini R, Cascinelli N, Brambilla M, Clemente C, Mascheroni L, Pignoli E, et al. In vivo spectrophotometric evaluation of neoplastic and non-neoplastic skin pigmented lesions. II: Discriminant analysis between nevus and melanoma. Photochem Photobiol. 1992; 55: 515–522.
- Rajaram N, Aramil TJ, Lee K, Reichenberg JS, Nguyen TH, Tunnell JW, et al. Design and validation of a clinical instrument for spectral diagnosis of cutaneous malignancy. Appl Opt. 2010; 49: 142-152.
- Gaudi S, Meyer R, Ranka J, Granahan JC, Israel SA, Yachik TR, et al. Hyperspectral imaging of melanocytic lesions. Am J Dermatopathol. 2014; 36: 131-136.
- Stamatas GN, Zmudzka BZ, Kollias N, Beer JZ. Non-invasive measurements of skin pigmentation in situ. Pigment Cell Res. 2004; 17: 618-626.
- Vo-Dinh T, Stokes DL, Wabuyele MB, Martin ME, Song JM, Jagannathan R, et al. A hyperspectral imaging system for in vivo optical diagnostics. Hyperspectral imaging basic principles, instrumental systems, and applications of biomedical interest. IEEE Eng Med Biol Mag. 2015; 23: 40–49.
- Nielsen KP, Lu Z, Juzenas P, Stamnes JJ, Stamnes K, Moan J. Reflectance spectra of pigmented and nonpigmented skin in the UV spectral region. Photochem Photobiol. 2004; 80: 450-455.
- Leiter U, Garbe C. Epidemiology of melanoma and nonmelanoma skin cancer--the role of sunlight. Adv Exp Med Biol. 2008; 624: 89-103.
- Boniol M, Autier P, Boyle P, Gandini S. Cutaneous melanoma attributable to sunbed use: systematic review and meta-analysis. BMJ. 2012; 345: e4757.
- Little EG, Eide MJ. Update on the current state of melanoma incidence. Dermatol Clin. 2012; 30: 355-361.
- Reed KB, Brewer JD, Lohse CM, Bringe KE, Pruitt CN, Gibson LE. Increasing incidence of melanoma among young adults: an epidemiological study in Olmsted County, Minnesota. Mayo Clin Proc. 2012; 87: 328-334.
- Chen ST, Geller AC, Tsao H. Update on the Epidemiology of Melanoma. Curr Dermatol Rep. 2013; 2: 24-34.
- Piérard SL, Piérard GE, Hermanns-Lê T, Hermanns JF, Piérard-Franchimont C. Greenhouse gas-related climate changes and some expected skin alterations. Austin J Dermatol. 2014; 1: 3.
- Siegel R, Naishadham D, Jemal A. Cancer statistics, 2012. CA Cancer J Clin. 2012; 62: 10–29.