Reduced-order modeling of solute transport within physiologically realistic solid tumor microenvironment

Solid tumors are characterized by densely packed extracellular matrices and limited vascularization, creating significant resistance to both diffusive and convective transport. Tumor growth depends on complex flow-structure interactions across multiple scales, while vascular abnormalities and enhanced permeability elevate interstitial pressure in the tumor microenvironment.

In this study, we developed an integrated computational framework with a theoretical modeling framework that couples three phase, viscous-laminar, transient simulations of glycocalyx-patched tumor vessel-resolving plasma, red blood cells (RBCs), and white blood cells (WBCs) and tracking their volume fractions with a calibrated reverse advection-diffusion (RAD) model for intratumoral plasma transport. The reduced-order tumor microenvironment model incorporates electrohydrodynamic (EHD) force at the tumor vessel wall via glycocalyx patches on the luminal surface.

At the fenestra, EHD increases inlet plasma intensity relative to a non-EHD framework across all 15 numerical models (means: 0.576 non-EHD vs. 0.722 EHD; gain $25.34\%$ ). Numerical simulations of plasma perfusion in both the tumor ECM domain and a microfluidic benchmark exhibit two-stage kinetics, with an initial advection-dominated regime. The RAD model reproduces this behavior and, after temporal calibration, matches the observed propagation.

By using fully resolved, EHD-inclusive multiphase CFD simulations to calibrate a reduced-order RAD model parameterized by measurable geometric features, we bridge the gap between classical Darcy-Starling perfusion models and fully resolved CFD. The resulting framework provides a tractable mechanism-grounded tool for quantifying plasma progression in dense solid tumors and for establishing the baseline transport capacity of the tumor extracellular matrix, independent of solute-specific biochemical properties.