Matthias Graeser

Magnetic particle imaging: current developments and future directions

Magnetic particle imaging (MPI) is a novel imaging method that was first proposed by Gleich and Weizenecker in 2005. Applying static and dynamic magnetic fields, MPI exploits the unique characteristics of superparamagnetic iron oxide nanoparticles (SPIONs). The SPIONs’ response allows a three-dimensional visualization of their distribution in space with a superb contrast, a very high temporal and good spatial resolution. Essentially, it is the SPIONs’ superparamagnetic characteristics, the fact that they are magnetically saturable, and the harmonic composition of the SPIONs’ response that make MPI possible at all. As SPIONs are the essential element of MPI, the development of customized nanoparticles is pursued with the greatest effort by many groups. Their objective is the creation of a SPION or a conglomerate of particles that will feature a much higher MPI performance than nanoparticles currently available commercially. A particle’s MPI performance and suitability is characterized by parameters such as the strength of its MPI signal, its biocompatibility, or its pharmacokinetics. Some of the most important adjuster bolts to tune them are the particles’ iron core and hydrodynamic diameter, their anisotropy, the composition of the particles’ suspension, and their coating. As a three-dimensional, real-time imaging modality that is free of ionizing radiation, MPI appears ideally suited for applications such as vascular imaging and interventions as well as cellular and targeted imaging. A number of different theories and technical approaches on the way to the actual implementation of the basic concept of MPI have been seen in the last few years. Research groups around the world are working on different scanner geometries, from closed bore systems to single-sided scanners, and use reconstruction methods that are either based on actual calibration measurements or on theoretical models. This review aims at giving an overview of current developments and future directions in MPI about a decade after its first appearance.

Magnetic particle imaging: Introduction to imaging and hardware realization

Magnetic Particle Imaging (MPI) is a recently invented tomographic imaging method that quantitatively measures the spatial distribution of a tracer based on magnetic nanoparticles. The new modality promises a high sensitivity and high spatial as well as temporal resolution. There is a high potential of MPI to improve interventional and image-guided surgical procedures because, today, established medical imaging modalities typically excel in only one or two of these important imaging properties. MPI makes use of the non-linear magnetization characteristics of the magnetic nanoparticles. For this purpose, two magnetic fields are created and superimposed, a static selection field and an oscillatory drive field. If superparamagnetic iron-oxide nanoparticles (SPIOs) are subjected to the oscillatory magnetic field, the particles will react with a non-linear magnetization response, which can be measured with an appropriate pick-up coil arrangement. Due to the non-linearity of the particle magnetization, the received signal consists of the fundamental excitation frequency as well as of harmonics. After separation of the fundamental signal, the nanoparticle concentration can be reconstructed quantitatively based on the harmonics. The spatial coding is realized with the static selection field that produces a field-free point, which is moved through the field of view by the drive fields. This article focuses on the frequency-based image reconstruction approach and the corresponding imaging devices while alternative concepts like x-space MPI and field-free line imaging are described as well. The status quo in hardware realization is summarized in an overview of MPI scanners.

Electronic Field Free Line Rotation and Relaxation Deconvolution in Magnetic Particle Imaging

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.

Analog receive signal processing for magnetic particle imaging

PURPOSE Magnetic particle imaging (MPI) applies oscillating magnetic fields to determine the distribution of magnetic nanoparticles in vivo. Using a receive coil, the change of the particle magnetization can be detected. However, the signal induced by the nanoparticles is superimposed by the direct feedthrough interference of the sinusoidal excitation field, which couples into the receive coils. As the latter is several magnitudes higher, the extraction of the particle signal from the excitation signal is a challenging task. METHODS One way to remove the interfering signal is to suppress the excitation signal by means of a band-stop filter. However, this technique removes parts of the desired particle signal, which are essential for direct reconstruction of the particle concentration. A way to recover the entire particle signal is to cancel out the excitation signal by coupling a matching cancellation signal into the receive chain. However, the suppression rates that can be achieved by signal cancellation are not as high as with the filtering method, which limits the sensitivity of this method. In order to unite the advantages of both methods, in this work the authors propose to combine the filtering and the cancellation technique. All methods were compared by measuring 10 μl Resovist, in the same field generator only switching the signal processing parts. RESULTS The reconstructed time signals of the three methods, show the advantage of the proposed combination of filtering and cancellation. The method preserves the fundamental frequency and is able to detect the tracer signal at its full bandwidth even for low concentrations. CONCLUSIONS By recovering the full particle signal the SNR can be improved and errors in the x-space reconstruction are prevented. The authors show that the combined method provides this full particle signal and makes it possible to improve image quality.

Magnetic particle imaging: kinetics of the intravascular signal in vivo.

The highest spectral MPI signal was measured directly after Resovist^® administration (3,21*10^-9 Am2Hz^-1). After application of Resovist^® the signal decreased to 39.7 % within 5 minutes and to 20.5 % and 12.1 % within 10 and 15 minutes, respectively (see Fig. 1). Within 30 minutes, the measured signal was below the background noise level.

Dynamic single-domain particle model for magnetite particles with combined crystalline and shape anisotropy

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.

Towards Picogram Detection of Superparamagnetic Iron-Oxide Particles Using a Gradiometric Receive Coil

Superparamagnetic iron-oxide nanoparticles can be used in medical applications like vascular or targeted imaging. Magnetic particle imaging (MPI) is a promising tomographic imaging technique that allows visualizing the 3D nanoparticle distribution concentration in a non-invasive manner. The two main strengths of MPI are high temporal resolution and high sensitivity. While the first has been proven in the assessment of dynamic processes like cardiac imaging, it is unknown how far the detection limit of MPI can be lowered. Within this work, we will present a highly sensitive gradiometric receive-coil unit combined with a noise-matching network tailored for the imaging of mice. The setup is capable of detecting 5 ng of iron in-vitro with an acquisition time of 2.14 sec. In terms of iron concentration we are able to detect 156 μg/L marking the lowest value that has been reported for an MPI scanner so far. In-vivo MPI mouse images of a 512 ng bolus and a 21.5 ms acquisition time allow for capturing the flow of an intravenously injected tracer through the heart of a mouse. Since it has been rather difficult to compare detection limits across MPI publications we propose guidelines to improve the comparability of future MPI studies.

Trajectory dependent particle response for anisotropic mono domain particles in magnetic particle imaging

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.

System Matrix Recording and Phantom Measurements with a Single-Sided Magnetic Particle Imaging Device

Magnetic particle imaging (MPI) is a new imaging method, which uses superparamagnetic iron oxide nanoparticles as tracer material. Due to their tube-like design, most MPI devices have limited patient access. In this paper, an improved oil-cooled single-sided MPI device is presented that has the advantage that all coils, which are generating the magnetic fields or receiving the particle signal, are coplanar and on one side of the patient only. In consequence, the object, which will be scanned, is not limited in size. In this paper, a first 1-D image recorded with the new device is presented.

Truncation artifacts in Magnetic Particle Imaging

Figure 1 clearly shows the effect of truncation artifacts when particles are not covered by the trajectory. With the removal of edge pixels these artifacts disappear. However, some information of the image is lost depending on the size of the necessary cut-off. With the multi-resolution approach the full information is used. Instead of removing pixels they are combined to large pixels. This method results in a better quality with small cut-offs compared to the non-compensated images.