A review of reported tissue optical properties summarizes the wavelength-dependent behavior of scattering and absorption. Formulae are presented for generating the optical properties of a generic tissue with variable amounts of absorbing chromophores (blood, water, melanin, fat, yellow pigments) and a variable balance between small-scale scatterers and large-scale scatterers in the ultrastructures of cells and tissues.

Linearly polarized light that illuminates skin is backscattered by superficial layers and rapidly depolarized by birefringent collagen fibers. It is possible to distinguish such superficially backscattered light from the total diffusely reflected light that is dominated by light penetrating deeply into the dermis. The method involves acquisition of two images through an analyzing linear polarizer in front of the camera, one image $(Ipar)$ acquired with the analyzer oriented parallel to the polarization of illumination and one image $(Iper)$ acquired with the analyzer oriented perpendicular to the illumination. An image based on the polarization ratio, $Pol=(Ipar−Iper)/(Ipar+Iper),$ is created. This paper compares normal light images, represented by $Iper,$ and Pol images of various skin pathologies in a pilot clinical study using incoherent visible-spectrum light. Images include pigmented skin sites (freckle, tattoo, pigmented nevi) and unpigmented skin sites [nonpigmented intradermal nevus, neurofibroma, actinic keratosis, malignant basal cell carcinoma, squamous cell carcinoma, vascular abnormality (venous lake), burn scar]. Images of a shadow cast from a razor blade onto a forearm skin site illustrate the behavior of Pol values near the shadow edge. Near the shadow edge, Pol approximately doubles in value because no $Iper$ photons are superficially scattered into the shadow-edge pixels by the shadow region while $Ipar$ photons are directly backscattered from the superficial layer of these pixels. This result suggests that the point spread function in skin for cross-talk between Pol pixels has a half-width-half-max of about 390 μm. © 2002 Society of Photo-Optical Instrumentation Engineers.

A tutorial introduction to diffuse light transport is presented. The basic analytic equations of time-resolved, steady-state and modulated light transport are introduced. The perturbation method for handling slight heterogeneities in optical properties is outlined. The treatment of boundary conditions such as an air/tissue surface is described. Finite mesh-based numerical methods are introduced to calculate the diffuse light field in complex tissues with arbitrary boundaries. Applications in tissue spectroscopy and imaging illustrate these theoretical and computational tools.

Determination of tissue optical properties is fundamental for application of light in either therapeutical or diagnostics procedures. In the present work we implemented a spatially resolved steady-state diffuse reflectance method where only two fibers (one source and one detector) spaced 2.5 mm apart are used for the determination of the optical properties. The method relies on the spectral characteristics of the tissue chromophores (water, dry tissue, and blood) and the assumption of a simple wavelength dependent expression for the determination of the reduced scattering coefficient. Because of the probe dimensions the method is suited for endoscopic measurements. The method was validated against more traditional models, such as the diffusion theory combined with adding doubling for in vitro measurements of bovine muscle. Mean and standard deviation of the absorption coefficient and the reduced scattering coefficient at 630 nm for normal mucosa were 0.87±0.22 cm⁻¹ and 7.8±2.3 cm⁻¹, respectively. Cancerous mucosa had values 1.87±1.10 cm⁻¹ and 8.4±2.3 cm⁻¹, respectively. These values are similar to data presented by other authors. Blood perfusion was the main variable accounting for differences in the absorption coefficient between the studied tissues. © 2005 Society of Photo-Optical Instrumentation Engineers.

The generation of photoacoustic signals for imaging objects embedded within tissues is dependent on how well light can penetrate to and deposit energy within an optically absorbing object, such as a blood vessel. This report couples a 3D Monte Carlo simulation of light transport to stress wave generation to predict the acoustic signals received by a detector at the tissue surface. The Monte Carlo simulation allows modeling of optically heterogeneous tissues, and a simple MATLAB™ acoustic algorithm predicts signals reaching a surface detector. An example simulation considers a skin with a pigmented epidermis, a dermis with a background blood perfusion, and a 500-μm-dia. blood vessel centered at a 1-mm depth in the skin. The simulation yields acoustic signals received by a surface detector, which are generated by a pulsed 532-nm laser exposure before and after inserting the blood vessel. A MATLAB™ version of the acoustic algorithm and a link to the 3D Monte Carlo website are provided.