Theoretical and computational fluid mechanics modeling for transport in dense tumors

Solid tumors, such as pancreatic tumors, have dense structures, leading to high resistance to diffusive transport, while limited blood and lymphatic flows impede convection. Accurate quantification of the particulate distribution in the blood and tumor regions is crucial for cancer diagnosis. Tumor growth and drug delivery depend on complex flow-structure interactions at multiple scales. Additionally, aberrations and permeability in the tumor vasculature elevate interstitial pressure in the tumor microenvironment. To address inadequate tumor perfusion, this study proposes a novel theoretical model called the diffusion-reverse advective (DRA) model, informed by CFD insights. This model uses convection-diffusion equations and boundary conditions from numerical simulations to estimate local concentrations at the tumor inlet and near the necrotic core. This model predicts perfusion trends across various tumor features and will be refined through comparison with benchmark 3D microfluidic and cell culture experiments to study nanoparticle penetration into tumors. Integrating experimental data could provide valuable insights into tumor uptake and enhance our understanding of tumor behavior and drug delivery in cancer research.