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Image reconstruction for tomographic mapping of cerebral hemodynamics using time-domain detection: simulation and phantom studies

One of the primary applications of diffuse optical imaging is to localize the changes in the cerebral oxygenation during physical or mental activities. Up to now, data from an optical imager is simply presented as a two-dimensional (2-D) topographic map using the modified Beer-Lambert law that assumes the homogeneous optical properties beneath each optode. Due to the highly heterogeneous nature of the optical properties in the brain, the assumption are evidently invalid, leading to both low spatial resolution and inaccurate quantification in the assessment of hemodynamic changes. To cope with the difficulties, we propose a nonlinear image reconstruction algorithm for a two-layered slab geometry using time-resolved reflected light. The algorithm is based on the previously developed generalized pulse spectrum technique, and implemented within a semi three-dimensional (3-D) framework to conform to the topographic visualization and to reduce computational load. We demonstrate the advantages of the algorithm in quantifying simulated changes in hemoglobin concentrations and investigate its robustness to the uncertainties in the cortical structure and optical properties. The methodology is also validated with experiments on a layered phantom.