Abstract
Diffusion approximation (DA) of the radiative transport equation allows derivation of enclosed solutions for diffuse reflectance from multi-layer scattering structures, such as human skin. Although the DA is known to be inadequate near tissue boundaries and light sources, analytical tractability makes such solutions very attractive for use in noninvasive characterization of biological organs based on measured diffuse reflectance spectra (DRS). For the presented three-layer model of human skin, which enables a good match with DRS in visible spectral range measured with an integrating sphere, the DA solutions systematically overshoot numerically simulated DRS (using Monte Carlo approach) by 1–2 percentage points. However, using the former in inverse analysis of the latter can result in much larger artifacts, most notably overestimations of the melanin and blood contents by up to 15%, which must be considered when analyzing experimental DRS. Despite such systematic errors, the described approach allows simple and robust monitoring of physiological changes in human skin, as demonstrated in tests involving temporary obstruction of blood circulation and seasonal variations due to extensive sun exposure.
Highlights
Diffuse reflectance spectroscopy is a practical and affordable technique for noninvasive characterization of biological organs in vivo
The Diffusion approximation (DA) is known to be inadequate near tissue boundaries and light sources, analytical tractability makes such solutions very attractive for use in noninvasive characterization of biological organs based on measured diffuse reflectance spectra (DRS)
We find that the DA solutions overshoot numerically simulated DRS in visible spectral range by 1–2 percentage points, in good agreement with similar previous reports
Summary
Diffuse reflectance spectroscopy is a practical and affordable technique for noninvasive characterization of biological organs in vivo. Applying this approach to extraction of tissue properties from experimental DRS by means of iterative optimization (a.k.a. inverse MC) remains challenging and time consuming, especially when involving simultaneous assessment of multiple parameters. To overcome this limitation, some researchers employed so-called look-up tables (LUT), which include pre-calculated reflectance values for a large number of tissue property combinations [20,21]. As we demonstrate further on (to the best of our knowledge for the first time), much larger systematic errors can occur in the inverse analysis, i.e., assessment of skin properties by fitting the DA solutions to simulated DRS Such artifacts most likely occur in analyses of experimental DRS using the same approach, which should be considered in interpretation of the assessed values. The same approach allows simple and robust monitoring of physiological changes in human skin in vivo when assessment of accurate absolute values is unnecessary, as demonstrated in our tests involving temporary obstruction of blood circulation using a blood-pressure cuff and seasonal variations due to extended sun exposure
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