Optical methods such as reflectance and fluorescence spectroscopy are being investigated for their potential to aid cancer detection in a quantitative, minimally invasive manner. Mathe­matical models of reflectance and fluorescence provide an important link between measured optical data and biomedically-relevant tissue parameters that can be extracted from these data to characterize the presence or absence of disease. The most commonly-used mathematical models in biomedical optics are the diffusion approximation (DA) to the radiative transfer equation, Monte Carlo (MC) computational models of light transport, and semi-empirical models. This paper presents a review of the applications of these models to reflectance and endogenous fluorescence sensing for cancer diagnostics in human tissues. Specific examples are given for cervical, breast, and pancreatic tissues. A comparison of the DA and MC methods in two biologically-relevant regimes of optical parameter space will also be discussed.

Key words: Tissue spectroscopy; Cancer; Reflectance; Fluorescence; Monte Carlo; Diffusion; Breast; Cervix; Pancreas.

This article can be cited as:
Wilson, R.H., Mycek, M-A. Models of Light Propagation in Human Tissue Applied to Cancer Diagnostics Technol Cancer Res Treat. 10, 121-134 (2011).