Multi-Color Magnetic Particle Imaging Based on Superparamagnetic and Superferromagnetic Nanoparticles.

Abstract

Objective: Magnetic Particle Imaging (MPI) is a tracer based biomedical imaging modality that enables quantitative visualization of magnetic nanoparticles (MNPs). Current MPI technology mainly focuses on single-channel imaging. In recent years, the multi-color MPI has emerged, allowing for the simultaneous imaging of multiple distinct tracers, significantly broadening MPI's application spectrum. For instance, multi-color MPI can concurrently visualize distinct cell types or molecular markers, facilitating the investigation of spatio-temporal interactions between cells or biomolecules. However, existing multi-color MPI techniques use different superparamagnetic MNPs for imaging. Their similar magnetization responses limit the imaging effect when there is a large particle signal difference.

Methods: In this study, we propose a semi-periodic x-space method to use superparamagnetic and superferromagnetic particles for multi-color MPI. The method takes advantage of their distinct coercivity characteristics, allowing for robust multi-color imaging without requiring iterative solving or any additional prior information beyond coercivity.

Results: We validate the feasibility and robustness of the proposed multi-color method under conditions of low signal-to-noise ratio (5 dB) and high signal intensity ratios (16:1) through simulation and in vitro experiments. Furthermore, we showcase the in vivo imaging capability using a mouse tumor model to simultaneously visualize superparamagnetic and superferromagnetic MNPs within the tumor.

Conclusion: We propose a method that can effectively and robustly reconstruct superparamagnetic and superferromagnetic MNPs simultaneously in MPI. Its performance has been rigorously validated through comprehensive simulations and experiments.

Significance: The proposed method successfully leverages the coercivity characteristics of superparamagnetic and superferromagnetic MNPs, improving the performance of multi-color MPI.