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Computational Multiphase Characterization of Perfusion Trends Inside Biomimetic Reduced-Order Dense Tumors

crossref(2022)

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摘要
AbstractDense fibrous extracellular constitution of solid tumors exerts high resistance to diffusive transport into it; additionally, the scarcity of blood and lymphatic flows hinders convection. The complexity of fluidic transport mechanisms in such tumor environments still presents open questions with translational end goals. For example, clinical diagnosis and targeted drug delivery platforms for such dense tumors can ideally benefit from a quantitative framework on plasma uptake into the tumor. In this study, we present a computational model for physical parameters that may influence blood percolation and penetration into a simple biomimetic solid tumor geometry. The model implements 3-phase viscous laminar transient simulation to mimic the transport physics inside a tumor-adhering blood vessel and measures the constituent volume fractions of the three considered phases, viz. plasma, RBCs (Red Blood Cells, also known as “erythrocytes”), and WBCs (White Blood Cells, also known as “leukocytes”) at three different flow times, while simultaneously recording the plasma pressure and velocity at the entry point to the tumor’s extracellular space. Subsequently, to quantify plasma perfusion within the tumor zone, we have proposed a reduced-order 2D transport model for the tumor entry zone and its extracellular space for three different fenestra diameters: 0.1, 0.3, and 0.5 μm; the simulations were 2-phase viscous laminar transient. The findings support the hypothesis that plasma percolation into the tumor is proportional to the leakiness modulated by the fenestra openings, quantifiable through the opening sizes.
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