The purpose of this work is to develop, calibrate, and validate a spatiotemporal model of convection enhanced rhenium-186 ( 186Re) liposome delivery for pre-surgical estimation of dosimetry in treatment of recurrent glioblastoma multiforme (GBM). Diffusion MRI data informs liposome diffusivity and permeability, while the post-contrast T1 data informs perfusion. An advection diffusion model of post-delivery liposome transport is developed. The model is calibrated to match SPECT images through 120 hours post-infusion, and predicts the distribution of liposomes at 196 hours. The performance of a simplified model based on a small molecule agent, and constant material properties from literature, is used as a reference for model comparison. Qualitatively, the reference model over-estimates the delivery volume of liposomes to the target region. Utilizing a diffusion imaging-informed diffusivity model, calibrated to patient data reduced the error by 14%. Further addition of a T1-informed clearance term to the diffusion-informed model reduced error by 26%. To conclude, models of convection enhanced liposome delivery, which assume a small molecular agent, are less accurate at predicting liposome distribution than patient-calibrated models making no assumptions of liposome size. The addition of imaging data further increased the accuracy of the model. These preliminary results indicate the potential of a patient-specific modeling tool for pre-surgical dosimetry, similar to those used for planning external beam therapy.