Special Section on Vibrational Spectroscopy and Imaging

Raman spectroscopy: in vivo quick response code of skin physiological status

[+] Author Affiliations
Raoul Vyumvuhore

Université Paris-Sud, Faculty of Pharmacy, Group of Analytical Chemistry of Paris-Sud (GCAPS), 51100 Chatenay-Malabry, France

Ali Tfayli

Université Paris-Sud, Faculty of Pharmacy, Group of Analytical Chemistry of Paris-Sud (GCAPS), 51100 Chatenay-Malabry, France

Olivier Piot

Université Reims Champagne Ardennes, CNRS FRE3481 MEDyC, Faculty of Pharmacy, MéDIAN-”Biophotonics and Technologies for Health”, 51100 Reims, France

Maud Le Guillou

SILAB, Department of Research and Development, 19100 BP 213, Brive Cedex, France

Nathalie Guichard

SILAB, Department of Research and Development, 19100 BP 213, Brive Cedex, France

Michel Manfait

Université Reims Champagne Ardennes, CNRS FRE3481 MEDyC, Faculty of Pharmacy, MéDIAN-”Biophotonics and Technologies for Health”, 51100 Reims, France

Arlette Baillet-Guffroy

Université Paris-Sud, Faculty of Pharmacy, Group of Analytical Chemistry of Paris-Sud (GCAPS), 51100 Chatenay-Malabry, France

J. Biomed. Opt. 19(11), 111603 (May 19, 2014). doi:10.1117/1.JBO.19.11.111603
History: Received September 23, 2013; Revised February 1, 2014; Accepted February 5, 2014
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Abstract.  Dermatologists need to combine different clinically relevant characteristics for a better understanding of skin health. These characteristics are usually measured by different techniques, and some of them are highly time consuming. Therefore, a predicting model based on Raman spectroscopy and partial least square (PLS) regression was developed as a rapid multiparametric method. The Raman spectra collected from the five uppermost micrometers of 11 healthy volunteers were fitted to different skin characteristics measured by independent appropriate methods (transepidermal water loss, hydration, pH, relative amount of ceramides, fatty acids, and cholesterol). For each parameter, the obtained PLS model presented correlation coefficients higher than R2=0.9. This model enables us to obtain all the aforementioned parameters directly from the unique Raman signature. In addition to that, in-depth Raman analyses down to 20 μm showed different balances between partially bound water and unbound water with depth. In parallel, the increase of depth was followed by an unfolding process of the proteins. The combinations of all these information led to a multiparametric investigation, which better characterizes the skin status. Raman signal can thus be used as a quick response code (QR code). This could help dermatologic diagnosis of physiological variations and presents a possible extension to pathological characterization.

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© 2014 Society of Photo-Optical Instrumentation Engineers

Topics

Skin

Citation

Raoul Vyumvuhore ; Ali Tfayli ; Olivier Piot ; Maud Le Guillou ; Nathalie Guichard, et al.
"Raman spectroscopy: in vivo quick response code of skin physiological status", J. Biomed. Opt. 19(11), 111603 (May 19, 2014). ; http://dx.doi.org/10.1117/1.JBO.19.11.111603


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