Noninvasive assessment of light scattering and hemoglobin in cutaneous two-stage chemical carcinogenesis of mice based on multispectral diffuse reflectance images

Due to the topographical location and extensive size, skin encounters high dose of clastogen those cause cancer which can be cured, if diagnosed at the early stage. While visual inspection, histopathological study, bio-sensing, dermoscopy exhibit some limitations, noninvasive optical methods cater comfortable, early and precise diagnosis. In this research, we investigated a multispectral imaging method based on the diffuse reflectance spectroscopy (DRS) to estimate spatiotemporal changes in the light scattering and hemodynamic parameters in mice during cutaneous two-stage chemical carcinogenesis. In this method, Monte Carlo simulation-based empirical formulas assisted in the extraction of the light scattering power b, total hemoglobin concentration Cth, and tissue oxygen saturation StO2 in the skin. In laboratory environment, we induced mice skin cancer by 7,12-dimethylbenz[a]anthracene (DMBA) and 12-Otetradecanoylphorbol-13-acetate (TPA) and monitored the changes in the cutaneous tissue at a particular interval through capturing multispectral diffuse reflectance images and analyzing over the period of initiation, promotion and progression. The results displayed the decrease in b and increases in both Cth and StO2 in tumor regions. Significantly, we found that the inception of rapid changes in the scattering parameter is about one to two week(s) earlier than the hemoglobin concentration. On the other hand, at the advanced stage, we also found the blackish discoloration of the skin in the tip of the papilloma when it experienced necrosis, which corresponds to the regional decrease in StO2 of some large papilloma.

[1]  S. Nagini,et al.  Of humans and hamsters: the hamster buccal pouch carcinogenesis model as a paradigm for oral oncogenesis and chemoprevention. , 2009, Anti-cancer agents in medicinal chemistry.

[2]  Domenico Alfieri,et al.  Spectral morphological analysis of skin lesions with a polarization multispectral dermoscope. , 2013, Optics express.

[3]  Hongshen Ma,et al.  Morphological Differences between Circulating Tumor Cells from Prostate Cancer Patients and Cultured Prostate Cancer Cells , 2014, PloS one.

[4]  I. Nishidate,et al.  Estimation of melanin and hemoglobin in skin tissue using multiple regression analysis aided by Monte Carlo simulation. , 2004, Journal of biomedical optics.

[5]  Angela A. Eick,et al.  Mechanisms of light scattering from biological cells relevant to noninvasive optical-tissue diagnostics. , 1998, Applied optics.

[6]  R J Ott,et al.  Spectrophotometric assessment of pigmented skin lesions: methods and feature selection for evaluation of diagnostic performance. , 2000, Physics in medicine and biology.

[7]  J. Leonardi-Bee,et al.  A systematic review of worldwide incidence of nonmelanoma skin cancer , 2012, The British journal of dermatology.

[8]  N. Aikawa,et al.  Size-Based Differentiation of Cancer and Normal Cells by a Particle Size Analyzer Assisted by a Cell-Recognition PC Software. , 2018, Biological & pharmaceutical bulletin.

[9]  David A. Boas,et al.  "Handbook of biomedical optics", edited by David A. Boas, Constantinos Pitris, and Nimmi Ramanujam , 2012, BioMedical Engineering OnLine.

[10]  J. Kanitakis,et al.  Anatomy, histology and immunohistochemistry of normal human skin. , 2002, European journal of dermatology : EJD.

[11]  David Abookasis,et al.  Imaging cortical absorption, scattering, and hemodynamic response during ischemic stroke using spatially modulated near-infrared illumination. , 2009, Journal of biomedical optics.

[12]  Zhengbin Xu,et al.  Spatiotemporal assessments of dermal hyperemia enable accurate prediction of experimental cutaneous carcinogenesis as well as chemopreventive activity. , 2013, Cancer research.

[13]  Paul A. J. Kolarsick,et al.  Anatomy and Physiology of the Skin , 2011 .

[14]  W. Stolz,et al.  The ABCD rule of dermatoscopy. High prospective value in the diagnosis of doubtful melanocytic skin lesions. , 1994, Journal of the American Academy of Dermatology.

[15]  Gianluca Petrillo,et al.  Vascular structures in skin tumors: a dermoscopy study. , 2004, Archives of dermatology.

[16]  D. Planchard,et al.  A direct comparison of CellSearch and ISET for circulating tumour-cell detection in patients with metastatic carcinomas , 2011, British Journal of Cancer.

[17]  Brian W Pogue,et al.  Approximation of Mie scattering parameters in near-infrared tomography of normal breast tissue in vivo. , 2005, Journal of biomedical optics.

[18]  G. Cooper.  The Cell: A Molecular Approach , 1996 .

[19]  G. Escobedo,et al.  In vivo assessment of liver fibrosis using diffuse reflectance and fluorescence spectroscopy: a proof of concept. , 2012, Photodiagnosis and photodynamic therapy.

[20]  Jason S Reichenberg,et al.  Handheld Diffuse Reflectance Spectral Imaging (DRSi) for in-vivo characterization of skin. , 2014, Biomedical optics express.

[21]  Sheng-Hao Tseng,et al.  Noninvasive evaluation of collagen and hemoglobin contents and scattering property of in vivo keloid scars and normal skin using diffuse reflectance spectroscopy: pilot study. , 2012, Journal of biomedical optics.

[22]  R Marchesini,et al.  In vivo SPECTROPHOTOMETRIC EVALUATION OF NEOPLASTIC AND NON‐NEOPLASTIC SKIN PIGMENTED LESIONS–I. REFLECTANCE MEASUREMENTS , 1991, Photochemistry and photobiology.

[23]  D. Brash,et al.  Sunlight and the onset of skin cancer. , 1997, Trends in genetics : TIG.

[24]  P. Séroul,et al.  SpectraCam®: A new polarized hyperspectral imaging system for repeatable and reproducible in vivo skin quantification of melanin, total hemoglobin, and oxygen saturation , 2018, Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging.

[25]  Tibor Pasinszki,et al.  Carbon Nanomaterial Based Biosensors for Non-Invasive Detection of Cancer and Disease Biomarkers for Clinical Diagnosis , 2017, Sensors.

[26]  Meenakshi Singh,et al.  Rat Models of Premalignant Breast Disease , 2000, Journal of Mammary Gland Biology and Neoplasia.

[27]  Izumi Nishidate,et al.  Noninvasive estimation of light scattering and hemoglobin concentration in mice cutaneous carcinogenesis through multispectral imaging , 2018, Other Conferences.

[28]  L Wang,et al.  MCML--Monte Carlo modeling of light transport in multi-layered tissues. , 1995, Computer methods and programs in biomedicine.

[29]  David D Sampson,et al.  Toward the discrimination of early melanoma from common and dysplastic nevus using fiber optic diffuse reflectance spectroscopy. , 2005, Journal of biomedical optics.

[30]  Hans C Gerritsen,et al.  Studying skin tumourigenesis and progression in immunocompetent hairless SKH1-hr mice using chronic 7,12-dimethylbenz(a)anthracene topical applications to develop a useful experimental skin cancer model , 2017, Laboratory animals.

[31]  Lihong V. Wang,et al.  Biomedical Optics: Principles and Imaging , 2007 .

[32]  J. Mourant,et al.  Predictions and measurements of scattering and absorption over broad wavelength ranges in tissue phantoms. , 1997, Applied optics.

[33]  R. Garg,et al.  Curcumin decreases 12-O-tetradecanoylphorbol-13-acetate-induced protein kinase C translocation to modulate downstream targets in mouse skin. , 2008, Carcinogenesis.

[34]  P. Friedl,et al.  Tumour-cell invasion and migration: diversity and escape mechanisms , 2003, Nature Reviews Cancer.

[35]  Izumi Nishidate,et al.  Evaluation of light scattering properties and chromophore concentrations in skin tissue based on diffuse reflectance signals at isosbestic wavelengths of hemoglobin , 2016 .

[36]  Josep Malvehy,et al.  Atlas of Dermoscopy , 2004 .

[37]  Izumi Nishidate,et al.  Noninvasive spectral imaging of skin chromophores based on multiple regression analysis aided by Monte Carlo simulation. , 2011, Optics letters.

[38]  G. Argenziano,et al.  Epiluminescence microscopy for the diagnosis of doubtful melanocytic skin lesions. Comparison of the ABCD rule of dermatoscopy and a new 7-point checklist based on pattern analysis. , 1998, Archives of dermatology.

[39]  J. Bromberg,et al.  Stat3 is required for the development of skin cancer. , 2004, The Journal of clinical investigation.

[40]  Sujatha Narayanan Unni,et al.  Model-based quantitative optical biopsy in multilayer in vitro soft tissue models for whole field assessment of nonmelanoma skin cancer , 2018, Journal of medical imaging.

[41]  Josep Malvehy,et al.  Handbook of Dermoscopy , 2006 .