Such a model could potentially help assess the efficacy of CED in tumors and provide better understanding of the biophysical IFP and interstitial fluid velocity changes due to CED, which are otherwise difficult to measure experimentally. Also DCE-MRI is likely to improve drug efflux estimates of current software models, our model being the first one to use DCE-MRI derived parameters to predict CED distributions. Simulations were carried out based on a voxelized modeling approach developed by our group. In this approach, heterogeneous tissue properties and anatomical boundaries are assigned from MRI data. These properties are then incorporated into a porous media transport model to predict CED of tracers. This RWJ 64809 methodology has been previously used by our group to model CED in spinal cord and brain tissues and systemic delivery in tumors. It should however be noted that the physics, governing equations and resulting physiological flows of the current problem are different. For example, the tumor microenvironment differs significantly from that of the brain due to its aforementioned chaotic vasculature and high IFP. Also porosity dependent formulations for hydraulic conductivity and tracer diffusivity were incorporated in this model, which were not present in our previous studies. Parameter analysis was performed to study the effects of infusion flow rate, catheter placement and spatially-varying tissue hydraulic conductivity on interstitial fluid flow and albumin tracer transport. This was done to understand the sensitivity of CED distribution to these variables. The flow rate was varied since the capillary fluid exchange is pressure dependent. Catheter placement is also known to be important in CED ; studies involving infusions at different locations in the brain have revealed the presence of a optimal site for achieving maximum distribution volumes within a targeted region. The tissue hydraulic conductivity, a measure of fluid conductance through the tissue, was also varied because of its direct influence on tumor IFP and convective flow fields in intratumoral infusions. Higher values of hydraulic conductivity are thought to reduce tumor IFP thereby increasing the filtration of fluids and extravasation of macromolecules. A MR image-based computational model for predicting distribution of a macro-molecular protein tracer following CED in a mouse tumor was developed. The key advancement and contribution is that our model incorporates vasculature as a realistic and heterogeneous entity, which is novel to CED models. By non-invasively probing the vasculature of the tumor and surrounding area, and incorporating heterogeneous transport into our model we have made some interesting discoveries. 1) Penetration of tracer/drug into surrounding tissue was found to be highly dependent on flow rate.