ИСТИНА

Diffuse reflectance spectroscopy (DRS) is one of the methods for quantifying the content of molecular components in the skin and other biological tissues. This diagnostic method is attractive both in comparison with other medical diagnostic methods due to its non-invasiveness and acquisition speed, and in comparison with other biomedical optical methods due to the relative ease of implementation. Using DRS one may asses the content of hemoglobin in oxygenated and deoxygenated forms, melanin [1], moiety of the stratum corneum [2], sebum content [3], carotenoids [3] and other skin chromophores. However, since the diffuse reflection spectrum is formed not only due chromophores absorption, but also due to scattering, the problem of determining the concentration of the components contained in the skin does not have a ready-made simple solution. In this regard, the authors of works often use different algorithms for (semi-) quantitative estimation of the concentration of various chromophores from the diffuse reflection spectroscopy data of the visible and near-IR ranges. In these algorithms, a specific set of wavelengths are used and a number of additional assumptions are often made to take into account scattering, cross-correlation between the determined chromophores, etc. However, the accuracy of the predictions of the used DRS data analysis algorithms is not validated on the standard set of spectra, and no comparisons are made with other quantitative methods DRS methods. For the practical application of the algorithms, it is necessary to compare them on the same data sets with clearly selected quality metrics. In order to identify optimal methods for the quantitative analysis of DRS data, in this work, we compared the accuracy of predictions, cross-correlation, and robustness of several algorithms that quantify the concentrations of chromophores (oxygenated and deoxygenated hemoglobin, melanin, water) skin using diffuse reflectance spectroscopy data. The analysis was carried out using the open-accessed Reference Data Set of Human Skin Reflectance (provided by NIST: National Institute of Standards and Technology) [5], as well as on the data of diffuse reflectance spectra of the visible and near infrared ranges simulated using the Monte Carlo method. [1] Dolotov, L. E., et al. "Design and evaluation of a novel portable erythema‐melanin‐meter." Lasers in Surgery and Medicine 34.2 (2004): 127-135. [2] Egawa, Mariko, et al. "Visualization of water distribution in the facial epidermal layers of skin using high-sensitivity near-infrared (nir) imaging." Applied spectroscopy 69.4 (2015): 481-487. [3] Ezerskaia, Anna, et al. "Quantitative and simultaneous non-invasive measurement of skin hydration and sebum levels." Biomedical optics express 7.6 (2016): 2311-2320. [4] Darvin, Maxim E., et al. "Comparison of two methods for noninvasive determination of carotenoids in human and animal skin: Raman spectroscopy versus reflection spectroscopy." Journal of biophotonics 5.7 (2012): 550-558. [5] Cooksey, C., David W. Allen, and Benjamin K. Tsai. "Reference Data Set of Human Skin Reflectance." NIST J. Res. 122 (2017).