Numerical Study of Transport of Anticancer Drugs in Heterogeneous Vasculature of Human Brain Tumors Using Dynamic Contrast Enhanced-Magnetic Resonance Imaging

Abstract

Systemic administration of drugs in tumors is a challenging task due to unorganized microvasculature and nonuniform extravasation. There is an imperative need to understand the transport behavior of drugs when administered intravenously. In this study, a transport model is developed to understand the therapeutic efficacy of a free drug and liposome-encapsulated drugs (LED), in heterogeneous vasculature of human brain tumors. Dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) data is employed to model the heterogeneity in tumor vasculature that is directly mapped onto the computational fluid dynamics (CFD) model. Results indicate that heterogeneous vasculature leads to preferential accumulation of drugs at the tumor position. Higher drug accumulation was found at location of higher interstitial volume, thereby facilitating more tumor cell killing at those areas. Liposome-released drug (LRD) remains inside the tumor for longer time as compared to free drug, which together with higher concentration enhances therapeutic efficacy. The interstitial as well as intracellular concentration of LRD is found to be 2-20 fold higher as compared to free drug, which are in line with experimental data reported in literature. Close agreement between the predicted and experimental data demonstrates the potential of the developed model in modeling the transport of LED and free drugs in heterogeneous vasculature of human tumors.

Image-based spatio-temporal model of drug delivery in a heterogeneous vasculature of a solid tumor — Computational approach

“…Recent computational fluid dynamics (CFD) methodologies for modeling the drug delivery to solid tumors have generated a novel domain of personalized clinical possibilities by integrating more patient-specificity with the medical imaging data. Some of these previously published investigations used magnetic resonance imaging (MRI) such as the works of Bhandari et al (2018) and Tan et al (2003) for brain tumor or Pishko et al (2011) for mice tumor. No one of the literature studies used the image-based geometry of the capillary networks as their main geometry and instead, only the mathematical modeling has been used to generate a synthetic capillary network.…”

Convection-Enhanced Delivery of Antiangiogenic Drugs and Liposomal Cytotoxic Drugs to Heterogeneous Brain Tumor for Combination Therapy

“…The tumor equivalent radius and volume are measured as 16 and 5461 , respectively. Given this study is focused on the drug transport in the brain tumor rather than the whole brain, a rectangular volume [ 41 , 42 ] of interest with the dimension of is generated to fully enclose the brain tumor.…”

“…The final computational mesh consists of 82,944 uniform structured elements, obtained after the mesh-independence test [ 42 ]. The dimension of each element is Drugs are infused into the brain tumor through the catheter with a dimension of , as shown in Figure 2 c.…”

“…The MR images also consist of voxels present outside the brain, which belong neither to the tumor nor its surrounding tissue, i.e., exterior voxels corresponding to air. The model parameters are set as zero for these voxels [ 42 , 48 ].…”

Simulating drug penetration during hyperthermic intraperitoneal chemotherapy

“…Bhandari et al. ( 2017 , 2018 ) developed a CFD-based drug transport model, incorporating realistic vasculature structures and performed several studies predicting the drug distribution in MR-based human brain tumor models. These predictions showed good agreement with experimental results and this approach provides an opportunity for optimizing treatments in a patient-specific way.…”