Modified Jiles–Atherton Model for Dynamic Magnetization in X-Space Magnetic Particle Imaging

Objective:
Magnetic particle imaging (MPI) is a promising medical modality that can image superparamagnetic iron-oxide nanoparticle (SPIO) concentration distributions safely and with high sensitivity. In the x-space reconstruction algorithm, the Langevin function is inaccurate in modeling the dynamic magnetization of SPIOs. This problem prevents the x-space algorithm from achieving a high spatial resolution reconstruction.
Methods:
We propose a more accurate model to describe the dynamic magnetization of SPIOs, named the modified Jiles–Atherton (MJA) model, and apply it to the x-space algorithm to improve the image resolution. Considering the relaxation effect of SPIOs, the MJA model generates the magnetization curve via an ordinary differential equation. Three modifications are also introduced to further improve its accuracy and robustness.
Results:
In magnetic particle spectrometry experiments, the MJA model shows higher accuracy than the Langevin and Debye models under various test conditions. The average root-mean-square error is 0.055, 83% and 58% lower than the Langevin and Debye models, respectively. In MPI reconstruction experiments, the MJA x-space improves the spatial resolution by 64% and 48% compared to the x-space and Debye x-space methods, respectively.
Conclusion:
The MJA model shows high accuracy and robustness in modeling the dynamic magnetization behavior of SPIOs. By integrating the MJA model into the x-space algorithm, the spatial resolution of MPI technology was improved.
Significance:
Improving the spatial resolution by using the MJA model helps MPI have a better performance in medical fields, including cardiovascular imaging.