Po‐Poster ‐ 33: A finite element model for bioluminescence imaging in small animals

Abstract

Bioluminescence imaging is a powerful technique for visualizing gene expression in small animals but it suffers a serious limitation: the absorption and scattering of light in tissue. Several factors influence the image: source strength and depth, effective numerical aperture of the imaging optics, and attenuation by the tissue between the source and the camera. Our overall goal is to account for these effects and to recover the actual strength and spatial location of the bioluminescence sources in vivo. An essential first step in this research is to develop a physical model that accurately predicts the light reaching the surface of the animal for an arbitrary distribution of sources and optical absorption and scattering coefficients. The calculations must be fast, so that the model can be used eventually in an iterative algorithm to solve the inverse problem. We use the diffusion approximation, valid when scattering dominates absorption and when it is not necessary to calculate the light field close to sources. The diffusion equation expresses the light fluence rate as a function of position and the spatially dependent absorption coefficient, scattering coefficient, and source function. A finite element code called NIRFAST has been developed to generate numerical solutions. NIRFAST has been implemented in MATLAB and uses a 2 or 3 dimensional model to represent the object. The absorption and scattering coefficients are specified at each node of the mesh. We have assigned “reasonable” values of the absorption and scattering coefficients to each node based on tissue identification by x‐ray CT.