Search

In magnetic particle imaging, scanners use different spatial sampling techniques to cover the field of view (FOV). As spatial encoding is realized by a selective low field region (a field-free-point, or field-free-line), this region has to be moved through the FOV on specific sampling trajectories. To achieve these trajectories complex time dependent magnetic fields are necessary. Due to the superposition of the selection field and the homogeneous time dependent fields, particles at different spatial positions experience different field sequences. As a result, the dynamic behaviour of those particles can be strongly spatially dependent. So far, simulation studies that determined the trajectory quality have used the Langevin function to model the particle response. This however, neglects the dynamic relaxation of the particles, which is highly affected by magnetic anisotropy. More sophisticated models based on stochastic differential equations that include these effects were only used for one dimensional excitation. In this work, a model based on stochastic differential equations is applied to two-dimensional trajectory field sequences, and the effects of these field sequences on the particle response are investigated. The results show that the signal of anisotropic particles is not based on particle parameters such as size and shape alone, but is also determined by the field sequence that a particle ensemble experiences at its spatial position. It is concluded, that the particle parameters can be optimized in terms of the used trajectory. [ABSTRACT FROM AUTHOR]

The dynamical behaviour of superparamagnetic iron oxide nanoparticles (SPIONs) is not yet fully understood. In magnetic particle imaging (MPI) SPIONs are used to determine quantitative real-time medical images of a tracer material distribution. For reaching spatial resolution in the sub-millimetre range, MPI requires a well engineered instrumentation providing a magnetic field gradient exceeding 2 T m. However, as the particle performance strongly affects the sensitivity of the imaging process, optimization of the particle parameters is a crucial factor, which is not easy to address. Today most simulations of MPI use the Langevin model to describe the particle behaviour. In equilibrium, the model matches the measured data. If alternating fields in the mid kHz frequency range are applied, the dynamic behaviour of the particles differs from the Langevin theory due to anisotropy effects, particle–particle-interactions and/or exchange interaction in case of multi-core particles. In this paper a model based on previous work is introduced, which was adopted to include crystal and shape anisotropy of immobilised mono-domain single-core particles. The model is applied to typical MPI frequencies and field strengths with different possible superposition of the anisotropy effects, leading to differences in the particle response. It is shown that, despite comparatively high anisotropy constants, the magnetocrystalline anisotropy energy does not quench the signal response for MPI. The constructive superposition of shape and crystal anisotropy leads to the best performance in terms of sensitivity and resolution of the associated imaging modality and slightly reduces the energy barriers compared to a sole-shape anisotropy. [ABSTRACT FROM AUTHOR]

Magnetic particle imaging (MPI) is a tomographic imaging modality sensitive to the spatial distribution of magnetic particles. The spectrometer, described in this paper, is capable of measuring the remagnetization spectrum of superparamagnetic nanoparticles. With this spectrometer the suitability of particles, for MPI, can be characterized. Furthermore, the spectrometer can be used to estimate the particle size distribution, which allows for more accurate simulations in MPI. [ABSTRACT FROM AUTHOR]