Drug distribution in tumors is strongly dependent on tumor biological properties such as tumor volume, vasculature, and porosity. An understanding of the drug distribution pattern in tumors can help in enhancing the effectiveness of anticancer treatment. A numerical model is employed to study the distribution of contrast agent in the heterogeneous vasculature of human brain tumors of different volumes. Dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) has been done for a number of patients with different tumor volumes. Leaky tracer kinetic model (LTKM) is employed to obtain perfusion parameters from the DCE-MRI data. These parameters are used as input in the computational fluid dynamics (CFD) model to predict interstitial fluid pressure (IFP), interstitial fluid velocity (IFV), and distribution of the contrast agent in different tumors. Numerical results demonstrate that the IFP is independent of tumor volume. On the other hand, the IFV increases as the tumor volume increases. Further, the concentration of contrast agent also increases with the tumor volume. The results obtained in this work are in line with the experimental DCE-MRI data. It is observed that large volume tumors tend to retain a higher concentration of contrast agent for a longer duration of time because of large extravasation flux and slow washout as compared to smaller tumors. These results may be qualitatively extrapolated to chemotherapeutic drug delivery, implying faster healing in large volume tumors. This study helps in understanding the effect of tumor volume on the treatment outcome for a wide range of human tumors.

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