Confocal Raman imaging of skin sections containing hair follicles using classical least squares regression and multivariate curve resolution – alternating least squares. (January 2019)

• Record Type: Journal Article
• Authors: Schleusener, J.; Carrer, V.; Patzelt, A.; Guo, S.; Bocklitz, T.; Coderch, L.; Lademann, J.; Darvin, M.E.
• Is Part Of: Quantum electronics. Volume 49:Number 1(2019)
• Page Start: 6
• Page End: 12
• Publication Date: 2019-01
• Subjects: dermatology -- optical profilometry -- multivariate data analysis -- hyperspectral imaging -- skin imaging -- confocal Raman microscopy; Quantum electronics -- Periodicals; 537.5
• DOI: 10.1070/QEL16901
• Languages: English
• ISSNs: 1063-7818

Abstract

Abstract: Confocal Raman microscopy (CRM) is applied ex vivo for imaging of the spatial distribution of different skin components in skin sections containing hair follicles. For multivariate data analysis, different methods are used in order to spectrally decompose the reference spectra of the skin components (dermis, viable epidermis, stratum corneum and hair). Classical least squares regression (CLS) and multivariate curve resolution–alternating least squares (MCR-ALS) are chosen as suitable methods. In comparison to other optical methods, the advantage of CRM is molecular specificity and dispensability of labelling dyes, which is e.g. necessary in fluorescence microscopy. Therefore, a useful future application of CRM in combination with multivariate data analysis lies in the analysis of penetration routes of topically applied substances, such as cosmetic formulations or drugs into the skin, which is particularly interesting in and around hair follicles.