Sinusoidal patterns of spatially modulated near-infrared ͑650 nm͒ structured light are used to interrogate multilayer phantoms and tissue. Diffuse reflectance is imaged at multiple spatial frequencies from 0 -0.3 mm −1 . ac and dc components of the image are fit to a two layer model formulated from the diffusion approximation to the Boltzman transport equation. The two-layer model depends on optical properties ͑absorption, a , and reduced scattering, s Ј͒ in each layer and on top layer thickness ͑d͒. Layered tissue phantoms with variable optical properties in each layer ͑ a = 0.006-0.034 mm −1 and s Ј= 0.89-1.45 mm −1 ͒ were constructed to test the accuracy of the model. Constraining top layer thickness to within 25% of the correct value in a four-parameter fit results in recovery of upper layer optical properties with average accuracies of Ϯ2% for top layer s Ј and Ϯ17% for top layer a . Bottom layer a can then be recovered to an average accuracy of Ϯ25% with two parameter fits. Average accuracies of top and bottom layer absorption can further be improved to 12% and 18%, respectively, by fitting for each alone. Bottom layer scattering and top layer thickness do not vary significantly from initial guesses because of poor sensitivity to these parameters in frequency dependent reflectance data. Measurements of in vivo volar forearm optical properties at 650 nm produced spatially varying skin ͑d =2 mm͒ optical property maps that range from 0.025-0.045 and 1.7-2 mm −1 for upper layer a and s Ј and 0.005-0.015 and 0.5-3 mm −1 for lower layer a and s Ј, respectively. These preliminary results suggest that spatial modulation of the source provides sufficient depth sensitivity to allow noncontact mapping and quantification of layered tissue optical properties using a wide-field, noncontact approach.

Abstract. We present an approach for rapidly and quantitatively mapping tissue absorption and scattering spectra in a wide-field, noncontact imaging geometry by combining multifrequency spatial frequency domain imaging (SFDI) with a computed-tomography imaging spectrometer (CTIS). SFDI overcomes the need to spatially scan a source, and is based on the projection and analysis of periodic structured illumination patterns. CTIS provides a throughput advantage by simultaneously diffracting multiple spectral images onto a single CCD chip to gather spectra at every pixel of the image, thus providing spatial and spectral information in a single snapshot. The spatial-spectral data set was acquired 30 times faster than with our wavelength-scanning liquid crystal tunable filter camera, even though it is not yet optimized for speed. Here we demonstrate that the combined SFDI-CTIS is capable of rapid, multispectral imaging of tissue absorption and scattering in a noncontact, nonscanning platform. The combined system was validated for 36 wavelengths between 650-1000 nm in tissue simulating phantoms over a range of tissue-like absorption and scattering properties. The average percent error for the range of absorption coefficients (μ a ) was less than 10% from 650-800 nm, and less than 20% from 800-1000 nm. The average percent error in reduced scattering coefficients (μ s ) was less than 5% from 650-700 nm and less than 3% from 700-1000 nm. The SFDI-CTIS platform was applied to a mouse model of brain injury in order to demonstrate the utility of this approach in characterizing spatially and spectrally varying tissue optical properties. C 2011 Society of Photo-Optical Instrumentation Engineers (SPIE).

We present forward modeling and measurement of spatially modulated illumination in layered turbid tissue systems. This technique is used to provide quantitative, depth-resolved functional physiologic information with applications in layered tissues including cortex, retina and skin.

. Significance: Raman spectroscopy (RS) applied to surgical guidance is attracting attention among scientists in biomedical optics. Offering a computational platform for studying depth-resolved RS and probing molecular specificity of different tissue layers is of crucial importance to increase the precision of these techniques and facilitate their clinical adoption. Aim: The aim of this work was to present a rigorous analysis of inelastic scattering depth sampling and elucidate the relationship between sensing depth of the Raman effect and optical properties of the tissue under interrogation. Approach: A new Monte Carlo (MC) package was developed to simulate absorption, fluorescence, elastic, and inelastic scattering of light in tissue. The validity of the MC algorithm was demonstrated by comparison with experimental Raman spectra in phantoms of known optical properties using nylon and polydimethylsiloxane as Raman-active compounds. A series of MC simulations were performed to study the effects of optical properties on Raman sensing depth for an imaging geometry consistent with single-point detection using a handheld fiber optics probe system. Results: The MC code was used to estimate the Raman sensing depth of a handheld fiber optics system. For absorption and reduced scattering coefficients of 0.001 and , the sensing depth varied from 105 to for a range of Raman probabilities from to . Further, for a realistic Raman probability of , the sensing depth ranged between 10 and for the range of absorption coefficients 0.001 to and reduced scattering coefficients of 0.5 to . Conclusions: A spectroscopic MC light transport simulation platform was developed and validated against experimental measurements in tissue phantoms and used to predict depth sensing in tissue. It is hoped that the current package and reported results provide the research community with an effective simulating tool to improve the development of clinical applications of RS.