Prince S, Malarvizhi S. Monte Carlo simulation of NIR diffuse reflectance in the normal and diseased human breast tissues.
Biofactors 2007;
30:255-63. [PMID:
18607075 DOI:
10.1002/biof.5520300407]
[Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The spectral reflectance measurements in tissue reveal physiological meaning. Normally, functional changes like, increase in total hemoglobin concentration, decrease in oxygen saturation, etc., are observed when there is an abnormality creeping in the normal tissue. These functional changes can act together to reveal disease by non-invasive near-infrared (NIR) spectroscopy, as it influence its optical properties. In the present study, a simple two dimensional, four layer model of breast is proposed. The four layers are (i) skin (ii) adipose layer (iii) glandular tissue and (iv) muscle. Each layer is modeled with appropriate biological chromophores like hemoglobin, water, lipid and melanin. From the literature, the concentrations and molar extinction coefficients of the chromophores in various layers of the model are obtained. These values are used to calculate the wavelength dependent absorption characteristics of a particular layer. Monte Carlo simulation of diffuse reflectance (percentage of back reflected photons after multiple scattering with the broad variety of angles) are simulated for the modeled breast tissue with and without diseased condition. Near-infrared wavelengths are chosen, as the depth of penetration in tissue is more compared to UV and visible region. Simulations are carried out on the modeled breast tissue for different races (skin colors) at different NIR wavelengths. Results show significant changes in diffuse reflectance and relative absorbance for normal and diseased breast tissues for differently pigmented model. This model can be used to study the photo dynamical therapy, drug delivery and prognosis of cancer.
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