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• W2787183830 endingPage "852" @default.
• W2787183830 startingPage "852" @default.
• W2787183830 abstract "Finding a path towards a more accurate prediction of light propagation in human skin remains an aspiration of biomedical scientists working on cutaneous applications both for diagnostic and therapeutic reasons. The objective of this study was to investigate variability of the optical properties of human skin compartments reported in literature, to explore the underlying rational of this variability and to propose a dataset of values, to better represent an in vivo case and recommend a solution towards a more accurate prediction of light propagation through cutaneous compartments. To achieve this, we undertook a novel, logical yet simple approach. We first reviewed scientific articles published between 1981 and 2013 that reported on skin optical properties, to reveal the spread in the reported quantitative values. We found variations of up to 100-fold. Then we extracted the most trust-worthy datasets guided by a rule that the spectral properties should reflect the specific biochemical composition of each of the skin layers. This resulted in the narrowing of the spread in the calculated photon densities to 6-fold. We conclude with a recommendation to use the identified most robust datasets when estimating light propagation in human skin using Monte Carlo simulations. Alternatively, otherwise follow our proposed strategy to screen any new datasets to determine their biological relevance." @default.
• W2787183830 created "2018-02-23" @default.
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• W2787183830 date "2018-01-29" @default.
• W2787183830 modified "2023-10-14" @default.
• W2787183830 title "Shedding light on the variability of optical skin properties: finding a path towards more accurate prediction of light propagation in human cutaneous compartments" @default.
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• W2787183830 doi "https://doi.org/10.1364/boe.9.000852" @default.
• W2787183830 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/5854084" @default.
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• W2787183830 hasPublicationYear "2018" @default.
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