We present here a new dynamic fluorescence tomographic model that makes use of spatial-Temporal constraints in order to reconstruction both fluorescent biomarkers and anatomical structure simultaneously within reasonable accuracy. A discrete cosine transformation (DCT) is used to compress images in the spatial and temporal domains. The appropriate set of dominant DCT components is found from analyzing mouse internal structure and measurements of dynamic time traces of fluorescent signals. These sought characteristic functions are used later as spatial-Temporal constraints in the reconstruction, which can aid to bring internal structure of major organs as well as fluorescent biomarkers into the reconstruction image. We use radiative transfer equation (RTE) as a light propagation model that provides more accurate predictions of light distribution in small geometries and high absorbing media. In addition, the reconstructed tomographic images are processed with principal components analysis (PCA) in order to differential between various regions with different functional kinetic behaviors. The performance of this new method is tested using a dynamic data of fluorescent signals resulting from changes in tumor vasculature in response to anti-Angiogenesis, and the preliminary results have been presented to show the potential of the proposed dynamic fluorescence tomographic model.