Transport of Liposome Encapsulated Drugs in Voxelized Computational Model of Human Brain Tumors

Area of Science:

• Biomedical Engineering
• Pharmacology
• Medical Imaging

Background:

• Drug delivery to tumors faces challenges like irregular uptake, impacting treatment efficacy.
• Liposome-mediated drug delivery offers a promising strategy to target tumors and minimize side effects.

Purpose of the Study:

• To develop and apply a computational fluid dynamics (CFD) model for predicting drug transport in human brain tumors.
• To compare the tumor accumulation and retention of stealth liposomes, conventional liposomes, and free doxorubicin.

Main Methods:

• A CFD model was created using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data of human brain tumors.
• Voxel-wise tumor and normal tissue porosity was determined using the general tracer kinetic model (GTKM) from DCE-MRI images.
• The model simulated the transport and deposition of stealth liposomes, conventional liposomes, and free doxorubicin within the tumor vasculature and interstitial space.

Main Results:

• Stealth liposomes demonstrated significantly higher accumulation and longer retention times within tumors compared to conventional liposomes and free doxorubicin.
• The CFD model provided a quantitative and qualitative analysis of drug transport dynamics.
• Tumor vasculature heterogeneity, derived from DCE-MRI, was incorporated to reflect realistic conditions.

Conclusions:

• Stealth liposomes represent a superior drug delivery system for brain tumors over conventional liposomes and free drugs.
• The developed CFD model is a valuable tool for predicting drug transport and optimizing chemotherapy strategies.
• Accurate modeling of tumor vasculature and interstitial space is crucial for effective drug delivery prediction.