Shedding light on the variability of optical skin properties: finding a path towards more accurate prediction of light propagation in human cutaneous compartments
| Autor: | Natallia E. Uzunbajakava, Desmond J. Tobin, M. Zeitouny, Charles Mignon |
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| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
medicine.diagnostic_test
Computer science business.industry Monte Carlo method Spectral properties Human skin Pattern recognition 01 natural sciences Atomic and Molecular Physics and Optics Light scattering Article 010309 optics 030207 dermatology & venereal diseases 03 medical and health sciences 0302 clinical medicine Light propagation Optical coherence tomography 0103 physical sciences Path (graph theory) medicine Biochemical composition Artificial intelligence business Biotechnology |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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