Time-resolved optical fluorescence spectroscopy of heterogeneous turbid media with special emphasis on brain tissue structures including diseased regions: A sensitivity analysis

Fluorescence-enhanced optical imaging based on near-infrared light provides a promising tool to differentiate diseased lesions from normal tissue. However, the measurement sensitivity of the fluorescence signals acquired at the output surface of the tissue is greatly influenced by the tissue structure, the optical properties, the location and the size of the target. In this paper, we present a numerical model based on the Monte Carlo method that allows to simulate time-resolved reflectance signals acquired on the surface of the scalp of a human head model bearing a fluorescent diseased region (tumor, glioma). The influence of tumor depth, tumor size and tumor shape evolution on the computed signals are analyzed by taking into account the multi-layered tissue structure. The simulations show that the mean-time-of-flight and the difference between two mean-times acquired at two source–detector distances are both relevant to this problem type. Furthermore, the simulations suggest that the use of the difference between mean-flight-times may be interesting to probe scattering changes that occur in the cerebrospinal fluid (CSF).