The role of cerebral spinal fluid in light propagation through the mouse head: improving fluorescence tomography with Monte Carlo modeling

Optical Neuroimaging is a highly dynamical field of research owing to the combination of many advanced imaging techniques and computational tools that uncovered unexplored paths through the functioning of the brain. Light propagation modelling through such complicated structures has always played a crucial role as the basis for a high resolution and quantitative imaging where even the slightest improvement could lead to significant results. Fluorescence Diffuse Optical Tomography (fDOT), a widely used technique for three dimensional imaging of small animals and tissues, has been proved to be inaccurate for neuroimaging the mouse head without the knowledge of a-priori anatomical information of the subject. Commonly a normalized Born approximation model is used in fDOT reconstruction based on forward photon propagation using Diffusive Equation (DE) which has strong limitations in the optically clear regime. The presence of the Cerebral Spinal Fluid (CSF) instead, a thin optically clear layer surrounding the brain, can be more accurately taken into account using Monte Carlo approaches which nowadays is becoming more usable thanks to parallelized GPU algorithms. In this work we discuss the results of a synthetic experimental comparison, resulting to the increase of the accuracy for the Born approximation by introducing the CSF layer in a realistic mouse head structure with respect to the current model. We point out the importance of such clear layer for complex geometrical models, while for simple slab phantoms neglecting it does not introduce a significant error.