Reflectance-type image reconstruction algorithm for time-resolved optical tomography of cerebral hemodynamics

Optical imaging can be used for localizing the oxygenation changes in the cortex in response to physical or mental tasks, with the advantages of flexibility and low cost. Up to now, data from optical imager is simply presented as a two-dimensional (2-D) topographic map rather than being tomographically reconstructed onto the cerebral cortex, based on the assumptions that the optical properties beneath each optode pair are homogeneous and the modified Beer-Lambert law can be used. Due to the high heterogeneity of optical properties in the brain, the assumptions are evidently invalid, leading to both low spatial resolution and quantitative inaccuracy in the assessment of hemodynamic changes. To solve the problem, we propose a nonlinear image reconstruction algorithm for a two-layered slab geometry using time-resolved reflected light and demonstrate its advantages in quantifying simulated changes in hemoglobin concentrations. The algorithm is based on the previously developed generalized pulse spectrum technique, and implemented within a semi three-diensional (3-D) framework, where the changes of optical properties assumed invariable in depth, to conform to the topographic visualization and to reduce computational load. We also investigate the robustness of the algorithm to the uncertainties in the cortical structure and optical properties.