Three-dimensional frequency-domain optical anisotropy imaging of biological tissues with near-infrared light

Near-infrared optical imaging aims to reconstruct the absorption $$ and scattering $$ coefficients in order to detect tumors at early stage. However, the reconstructions have only been limited to $$ and $$ due to theoretical and computational limitations. The authors propose an efficient method of the reconstruction, in three-dimensional geometries, of the anisotropy factor g of the Henyey-Greenstein phase function as a new optical imaging biomarker.

The light propagation in biological tissues is accurately modeled by the radiative transfer equation (RTE) in the frequency-domain. The reconstruction algorithm is based on a gradient-based updating scheme. The adjoint method is used to efficiently compute the gradient of the objective function which represents the discrepancy between simulated and measured boundary data. A parallel implementation is carried out to reduce the computational time.

We show that by illuminating only one surface of a tissue-like phantom, the algorithm is able to accurately reconstruct optical values and different shapes (spherical and cylindrical) that characterize small tumor-like inclusions. Numerical simulations show the robustness of the algorithm to reconstruct the anisotropy factor with different contrast levels, inclusion depths, initial guesses, heterogeneous background, noise levels, and two-layered medium. The crosstalk problem when reconstructing simultaneously $$ and g has been reported and achieved with a reasonable quality.

The proposed RTE-based reconstruction algorithm is robust to spatially retrieve and localize small tumoral inclusions. Heterogeneities in g-factor have been accurately reconstructed which makes the new algorithm a candidate of choice to image this factor as new intrinsic contrast biomarker for optical imaging.