Computational modeling of superferromagnetism in finite-length chains of superparamagnetic Iron Oxide tracers for use in super-resolution Magnetic Particle Imaging

Abstract

Magnetic Particle Imaging (MPI) is a novel tracer imaging modality that images the spatial distribution of super- paramagnetic iron oxide nanoparticles (SPIOs), allowing for the sensitive and radiation-free imaging of labeled cells and targeted disease. Recent works have shown that at high concentrations, SPIOs display extremely sharp magnetic responses, resulting in 10-fold resolution and signal improvements. Dubbed superferromagnetic iron oxide particles (SFMIOs), these particles appear to interact with neighbours, effectively amplifying applied fields. This work performs a simulation of ensembles of linear chains of interacting SPIOs to elucidate SFMIO behavior and guide practical constraints in SFMIO synthesis. We show that working within certain physical constraints (chain length distributions and SPIO separation) preserves the improvements observed from SFMIOs.