A Computational Modeling Approach For Magnetic Resonance Navigation In Targeted Embolization: Impact of Aggregate Shape and Hemodynamics Forces

Magnetic resonance navigation (MRN) is gaining popularity in the treatment of liver cancer. The method involves magnetic particles that form aggregates in response to the MRI magnetic field. These aggregates are injected into the bloodstream, where they are directed towards the targeted branch by the combination of the magnetic gradient force and gravity. However, this procedure's success depends highly on the aggregate shape. Prior studies have been limited to a few forces investigation, drag approximation or bead-chain models of aggregates unsuitable for MRN. In addition, the wall effect on aggregates is not well known. To resolve it, we devise a computational model: particle trajectories are simulated with the point-particle approach, solving the modified Maxey-Riley equation. Additionally, we employ the immersed boundary method (IBM) to construct an effective drag library, enabling accurate modeling of hemodynamic forces acting on the aggregates based on their specific sizes and shapes. Preliminary findings exhibit promising outcomes for various aggregate sizes, validating IBM's effectiveness in determining drag coefficients. The results align well with both the bead drag model and experimental data. However, it is essential to conduct further research to generalize the impact of hemodynamic forces on aggregates with diverse shapes.