Quantitative Analysis of Skin Erythema Due to Laser Hair Removal: A Diffusion Optical Spectroscopy Analysis
Journal of Lasers in Medical Sciences,
Vol. 10 No. 2 (2019),
25 February 2019
,
Page 97-103
Abstract
Introduction: Laser hair removal needs an accurate understanding of tissue structure and chromophores content in order to optimize the selection of laser irradiation parameters. None of the optimized laser therapy might lead to side effects in skin tissue such as severe erythema, burn, scar etc. Therefore, guidance by a noninvasive real-time diagnostic method like optical spectroscopy technique is beneficial. The purpose of this survey is to analysis the skin hemoglobin spectrum quantitatively before and after hair removal laser irradiation to minimize the side effects of the procedure.
Methods: To carry out a spectroscopy study, a halogen-tungsten light source was used in the wavelength region of 400-700 nm on an ocean optic device. The measurements were made on the facial area under identical conditions. Total 19 volunteers for laser hair removal by gentle laser Candela, ranging 14- 49 years old, were included in the study. A total of 18 spectra were taken from each person, 9 spectra before hair removal as a reference and 9 subsequent spectra. Colorimetry was done for all acquired before and after spectrums using Origin software (version 8.6). Then, the erythema index derived for each spectrum. Statistical analysis of correlation and normalization in colorimetry data were done using data analysis by SPSS (version 16).
Results: Spectra analysis, before and after optical reflectance spectrums in laser hair removal procedure, revealed the subpeak derivation, and concentration on special visible wavelength 510-610 nm. We studied the changes of skin chromophores absorption. The derived erythema index [E] and colorimetry parameters a*, b*, l* were compared and correlated statistically. There was a statistically considerable direct linear correlation between a* and E while inverse linear correlation was observed for l* and E and no correlation for b* and E.
Conclusion: Diffuse reflectance spectroscopy showed its potency as an accurate, noninvasive real-time as complementary method for laser treatment to detect erythema as a complication of the method, in order to optimize the parameters based on the tissue characteristics in various candidates.
- Laser hair removal
- Erythema
- Diffuse reflectance
- Spectrum analysis
- Colorimetry.
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References
Boer M, Duchnik E, Maleszka R, Marchlewicz M. Structural and biophysical characteristics of human skin in maintaining proper epidermal barrier function. Postepy Dermatol Alergol. 2016;33(1):1-5. doi:10.5114/ pdia.2015.48037
Hammes S, Karsai S, Metelmann HR, et al. Treatment errors resulting from use of lasers and IPL by medical laypersons: results of a nationwide survey. J Dtsch Dermatol Ges. 2013;11(2):149-156. doi:10.1111/j.1610-0387.2012.08042.x
Sahu RK, Mordechai S. Spectroscopic techniques in medicine: The future of diagnostics. Appl Spectrosc Rev. 2016;51(6):484-499. doi:10.1080/05704928.2016.1157809
LaRosa C, Chiaravalloti A, Jinna S, Berger W, Finch J. Laser treatment of medical skin disease in women. Int J Womens Dermatol. 2017;3(3):131-139. doi:10.1016/j. ijwd.2017.05.002
Bolognia JL, Jorizzo JL, Schaffer JV. Bolognia: Dermatology. 3rd ed. St. Louis, MO: Elsevier Saunders; 2012.
Argenbright LW, Forbes PD. Erythema and skin blood content. Br J Dermatol. 1982;106(5):569-574.
Wanner M. Laser hair removal. Dermatol Ther. 2005;18(3):209-216. doi:10.1111/j.1529-8019.2005.05020.x
Krishnaswamy A, Baranoski GVG. A biophysically‐based spectral model of light interaction with human skin. Comput Graph Forum. 2004;23(3):331-340. doi:10.1111/ j.1467-8659.2004.00764.x
Tuchin VV. Light scattering study of tissues. Physics-Uspekhi. 1997;40(5):495-515. doi:10.1070/ PU1997v040n05ABEH000236
Nishidate I, Wiswadarma A, Hase Y, et al. Noninvasive spectral imaging of skin chromophores based on multiple regression analysis aided by Monte Carlo simulation. Opt Lett. 2011;36(16):3239-3241. doi:10.1364/ol.36.003239
Jaya Chandra Lekha TR, Saravana Kumar C. NIR spectroscopic algorithm development for glucose detection. International Conference on Innovations in Information,Embedded and Communication Systems (ICIIECS); 2015. doi:10.1109/ICIIECS.2015.7192936
Kussw SB. Spectral imaging and analysis of human skin [thesis]. Finland: University of Eastern Finland; 2010.
Stamatas GN, Zmudzka BZ, Kollias N, Beer JZ. Non-invasive measurements of skin pigmentation in situ. Pigment Cell Res. 2004;17(6):618-626. doi:10.1111/j.1600- 0749.2004.00204.x
Sujatha N, Anand BSS, Nivetha KB, Narayanamurthy VB, Seshadri V, Poddar R. Assessment of microcirculatory hemoglobin levels in normal and diabetic subjects using diffuse reflectance spectroscopy in the visible region—a pilot study. J Appl Spectrosc. 2015;82(3):432-437. doi:10.1007/s10812-015-0125-9
Nakhaeva IA, Mohammed MR, Zyuryukina OA, Sinichkin YP. The effect of an external mechanical compression on in vivo optical properties of human skin. Opt Spectrosc. 2014;117(3):506-512. doi:10.1134/s0030400x14090173
Koukouvinos G, Petrou P, Goustouridis D, Misiakos K, Kakabakos S, Raptis I. Development and Bioanalytical Applications of a White Light Reflectance Spectroscopy Label-Free Sensing Platform. Biosensors (Basel). 2017;7(4). doi:10.3390/bios7040046
Anand S, Sujatha N. Quantification of tissue oxygenation levels using diffuse reflectance spectroscopy. Tenth International Conference on Fiber Optics and Photonics; 2011. doi:10.1117/12.897811
Gienger J, Gross H, Neukammer J, Bar M. Determining the refractive index of human hemoglobin solutions by Kramers-Kronig relations with an improved absorption model. Appl Opt. 2016;55(31):8951-8961. doi:10.1364/ ao.55.008951
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