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MRI-based computational model of heterogeneous tracer transport following local infusion into a mouse hind limb tumor
Kulam Najmudeen Magdoom1, Gregory L Pishko1, Lori Rice2
1Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, Florida, United States of America.
Abstract:
Systemic drug delivery to solid tumors involving macromolecular therapeutic agents is challenging for many reasons. Amongst them is their chaotic microvasculature which often leads to inadequate and uneven uptake of the drug. Localized drug delivery can circumvent such obstacles and convection-enhanced delivery (CED)--controlled infusion of the drug directly into the tissue--has emerged as a promising delivery method for distributing macromolecules over larger tissue volumes. In this study, a three-dimensional MR image-based computational porous media transport model accounting for realistic anatomical geometry and tumor leakiness was developed for predicting the interstitial flow field and distribution of albumin tracer following CED into the hind-limb tumor (KHT sarcoma) in a mouse. Sensitivity of the model to changes in infusion flow rate, catheter placement and tissue hydraulic conductivity were investigated. The model predictions suggest that 1) tracer distribution is asymmetric due to heterogeneous porosity; 2) tracer distribution volume varies linearly with infusion volume within the whole leg, and exponentially within the tumor reaching a maximum steady-state value; 3) infusion at the center of the tumor with high flow rates leads to maximum tracer coverage in the tumor with minimal leakage outside; and 4) increasing the tissue hydraulic conductivity lowers the tumor interstitial fluid pressure and decreases the tracer distribution volume within the whole leg and tumor. The model thus predicts that the interstitial fluid flow and drug transport is sensitive to porosity and changes in extracellular space. This image-based model thus serves as a potential tool for exploring the effects of transport heterogeneity in tumors.
Insights
Convection-enhanced delivery (CED) models tumor drug distribution. Optimized infusion parameters maximize macromolecule uptake in tumors, improving localized drug delivery strategies.
Area of Science:
- Biomedical Engineering
- Computational Biology
- Oncology
Background:
- Systemic macromolecule delivery to solid tumors is hindered by chaotic tumor vasculature.
- Localized drug delivery, like convection-enhanced delivery (CED), offers a promising alternative for improved distribution.
Purpose of the Study:
- To develop and validate a 3D computational model for predicting drug distribution via CED in tumors.
- To investigate the impact of infusion parameters and tumor properties on drug transport.
Main Methods:
- A 3D MR image-based computational porous media transport model was created.
- The model incorporated realistic anatomical geometry and tumor leakiness.
- Simulations analyzed tracer distribution under varying infusion flow rates, catheter placements, and hydraulic conductivity.
Main Results:
- Tracer distribution was found to be asymmetric due to heterogeneous tumor porosity.
- Distribution volume showed linear correlation with infusion volume in the leg and exponential in the tumor.
- Optimal infusion (central tumor, high flow) maximized tumor coverage with minimal leakage.
- Increased hydraulic conductivity reduced interstitial fluid pressure and distribution volume.
Conclusions:
- Tumor interstitial fluid flow and drug transport are sensitive to porosity and extracellular space heterogeneity.
- The developed image-based model is a valuable tool for optimizing CED strategies and understanding transport heterogeneity in tumors.

