The magnetic particle imaging method allows for the quantitative determination of spatial distributions of superparamagnetic nanoparticles in vivo. Recently, it was shown that the 1-D magnetic particle imaging process can be formulated as a convolution. Analyzing the width of the convolution kernel allows for predicting the spatial resolution of the method. However, this measure does not take into account the noise of the measured data. Furthermore, it does not consider a reconstruction step, which can increase the resolution beyond the width of the convolution kernel. In this paper, the spatial resolution of magnetic particle imaging is investigated by analyzing the modulation transfer function of the imaging process. An expression for the spatial resolution is derived, which includes the noise level and which is validated in simulations and experiments.

It has been shown that magnetic particle imaging (MPI), an imaging method suggested in 2005, is capable of measuring the spatial distribution of magnetic nanoparticles. Since the particles can be administered as biocompatible suspensions, this method promises to perform well as a tracer-based medical imaging technique. It is capable of generating real-time images, which will be useful in interventional procedures, without utilizing any harmful radiation. To obtain a signal from the administered superparamagnetic iron oxide (SPIO) particles, a sinusoidal changing external homogeneous magnetic field is applied. To achieve spatial encoding, a gradient field is superimposed. Conventional MPI works with a spatial encoding field that features a field free point (FFP). To increase sensitivity, an improved spatial encoding field, featuring a field free line (FFL) can be used. Previous FFL scanners, featuring a 1-D excitation, could demonstrate the feasibility of the FFL-based MPI imaging process. In this work, an FFL-based MPI scanner is presented that features a 2-D excitation field and, for the first time, an electronic rotation of the spatial encoding field. Furthermore, the role of relaxation effects in MPI is starting to move to the center of interest. Nevertheless, no reconstruction schemes presented thus far include a dynamical particle model for image reconstruction. A first application of a model that accounts for relaxation effects in the reconstruction of MPI images is presented here in the form of a simplified, but well performing strategy for signal deconvolution. The results demonstrate the high impact of relaxation deconvolution on the MPI imaging process.

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The magnetic particle imaging method is capable of imaging the distribution of magnetic nanoparticles in vivo. The sensitivity of the method can be significantly improved using a signal encoding scheme, which applies a fieldfree line (FFL) instead of the commonly used field-free point (FFP). Recent efforts have considerably improved the efficiency of the coil topology used to generate the FFL. However, until now it has not been investigated how the reconstruction of the particle distribution can be efficiently carried out when using the FFL encoding scheme. In this work, it is shown that the induced signal is linked to the Radon transform of the particle distribution. Hence, a fast algorithm for the reconstruction of the particle distribution can be derived, which first transforms the induced signal into Radon space and second applies a common reconstruction algorithm to transform the Radon data into image space.

The proposed coil assembly is almost as efficient as an equivalent FFP scanner. Furthermore, the assembly cannot only be used for FFL imaging but for FFP imaging as well. Hence, the findings of this article denote an important step toward the first practical implementation of the FFL coil geometry.