Optical tomographic mapping of cerebral haemodynamics by means of time-domain detection: methodology and phantom validation.

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