Volume 58, Issue 6 - Special Issue: Magnetic Particle Imaging / Guest Editor: Thorsten M. Buzug

Magnetic particle imaging (MPI) is an attractive new modality for imaging distributions of iron oxide nanoparticle tracers in vivo . With exceptional contrast, high sensitivity, and good spatial resolution, MPI shows promise for clinical imaging in angiography and oncology. Critically, MPI requires high-quality iron oxide nanoparticle tracers with tailored magnetic and surface properties to achieve its full potential. In this review, we discuss optimizing iron oxide nanoparticles’ physical, magnetic, and pharmacokinetic properties for MPI, highlighting results from our recent work in which we demonstrated tailored, biocompatible iron oxide nanoparticle tracers that provided two times better linear spatial resolution and five times better signal-to-noise ratio than Resovist.

Magnetic particle imaging (MPI) is a new imaging technique for visualizing the three-dimensional distribution of superparamagnetic iron oxide nanoparticles with specific properties (MPI tracers). Initial results obtained with MPI using superparamagnetic iron oxide as blood pool markers suggest that the method has great potential for cardiovascular imaging. Conversely, no clinically approved MPI tracers currently exist that could be used to exploit this potential of MPI. This article describes thermal decomposition and coprecipitation, two relevant methods for synthesizing and optimizing superparamagnetic iron oxide nanoparticles for MPI. Furthermore it summarizes the recent literature on MPI tracers and explores what can be learned from structural studies with Resovist ® for novel synthesis approaches.

Red blood cells (RBCs) represent intravascular carriers for drugs, biologics, and other therapeutic agents, characterized by their unique longevity in the bloodstream, availability, considerable surface and volume, high biocompatibility, and natural mechanisms for safe elimination. Recently, the potential of RBCs loaded with superparamagnetic iron oxide (SPIO) nanoparticles as a tracer material for magnetic particle imaging (MPI) to realize a blood-pool tracer agent with longer blood retention time for imaging of the circulatory system, has been investigated. MPI is a new tomographic imaging approach that can quantitatively map magnetic nanoparticle distributions in vivo . However, SPIO contrast agents, such as Resovist, have a short blood half-life due to rapid uptake by the reticuloendothelial system, which limits the applicability of such compounds for certain applications such as long-term monitoring. Here, we report the in vitro magnetic characterization study of human SPIO-loaded RBCs and the first MPI results obtained after intravenous injection of murine SPIO-loaded RBCs in an in vivo MPI experiment.

Magnetic particle imaging (MPI) recently emerged as a new tomographic imaging method directly visualizing the amount and location of superparamagnetic iron oxide particles (SPIOs) with high spatial resolution. To fully exploit the imaging performance of MPI, specific requirements are demanded on the SPIOs. Most important, a sufficiently high number of detectable harmonics of the receive signal spectrum is required. In this study, an assessment of commercial iron oxide-based MRI contrast agents is carried out, and the result is compared with that of a new self-synthesized high-performance MPI tracer. The decay of the harmonics is measured with a magnetic particle spectrometer (MPS). For the self-synthesized carboxymethyldextran-coated SPIO, it can be demonstrated that despite a small iron core diameter, the particle performance is as good as in Resovist, the best-performing commercial SPIO today. However, the self-synthesized particles show the lowest iron concentration compared with Resovist, Sinerem, and Endorem. As the iron dose will be an important issue in human MPI, the synthesis technique and the separation chain for self-synthesis will be pursued for further improvements. In evaluations carried out with MPS, it can be shown in this work that the quality of the self-synthesized nanoparticles outperforms the three commercial tracer materials when the decay of harmonics is normalized by the iron concentration. The results of this work emphasize the importance of producing highly uniform and monodisperse superparamagnetic particles contributing to lower application of tracer concentration, better sensitivity, or a higher spatial resolution.

The optimization of magnetic nanoparticles (MNPs) as markers for magnetic particle imaging (MPI) requires an understanding of the relationship between the harmonics spectrum and the structural and magnetic properties of the MNPs. Although magnetic particle spectroscopy (MPS) – carried out at the same excitation frequency as the given MPI system – represents a straightforward technique to study MNPs for their suitability for MPI, a complete understanding of the mechanisms and differences between different tracer materials requires additional measurements of the static and dynamic magnetic behavior covering additional field and time ranges. Furthermore, theoretical models are needed, which correctly account for the static and dynamic magnetic properties of the markers. In this paper, we give an overview of currently used theoretical models for the explanation of amplitude and phase of the harmonics spectra as well as of the various static and dynamic magnetic techniques, which are applied for the comprehensive characterization of MNPs for MPI. We demonstrate on two multicore MNP model systems, Resovist ® and FeraSpin™ Series, how a detailed picture of the MPI performance can be obtained by combining various static and dynamic magnetic measurements.

The rigidity of the extracellular matrix and of the integrin links to the cytoskeleton regulates signaling cascades, controlling critical aspects of cancer progression including metastasis and angiogenesis. We demonstrate that the matrix stiffness can be monitored using magnetic spectroscopy of nanoparticle Brownian motion (MSB). We measured the MSB signal from nanoparticles bound to large dextran polymers. The number of glutaraldehyde induced cross-links was used as a surrogate for material stiffness. There was a highly statistically significant change in the MSB signal with the number of cross-links especially prominent at higher frequencies. The p-values were all highly significant. We conclude that the MSB signal can be used to identify and monitor changes in the stiffness of the local matrix to which the nanoparticles are bound.

After realizing the worlds’ first preclinical magnetic particle imaging (MPI) demonstrator, Philips is now realizing the worlds’ first whole-body clinical prototype to prove the feasibility of MPI for clinical imaging. After a brief introduction of the basic MPI imaging process, this contribution presents an overview on the determining factors for key properties, i.e., spatial resolution, acquisition speed, sensitivity, and quantitativeness, and how these properties are influenced by scaling up from preclinical to clinical instrumentation. Furthermore, it is discussed how this scale up affects the physiological compatibility of the method as well as hardware parameters such as power requirements for drive field generation, selection and focus field generation, and the design of the receive chain of the MPI device.

Magnetic particle imaging (MPI) can be used as a fast diagnostic method for obtaining three-dimensional images from inside the body of small animals by the use of functionalized magnetic nanoparticles as tracer. Here, we present our scanner setup working at 10-kHz drive-field frequency to sample a field of view of 22×22×15 mm 3 with up to 32 volume images per second. A resolution of about 1×2×1 mm 3 is achieved with iron oxide nanoparticles (Resovist). We discuss the properties of the complete system for application in imaging small animals such as mice.

We experimentally demonstrate a 20-fold improvement in acquisition time in projection reconstruction (PR) magnetic particle imaging (MPI) relative to the state-of-the-art PR MPI imaging results. We achieve this acceleration in our imaging system by introducing an additional Helmholtz electromagnet pair, which creates a slow shift (focus) field. Because of magnetostimulation limits in humans, we show that scan time with three-dimensional (3D) PR MPI is theoretically within the same order of magnitude as 3D MPI with a field free point; however, PR MPI has an order of magnitude signal-to-noise ratio gain.

Magnetic particle imaging (MPI) is a novel tracer-based imaging method detecting the distribution of superparamagnetic iron oxide (SPIO) nanoparticles in vivo in three dimensions and in real time. Conventionally, MPI uses the signal emitted by SPIO tracer material located at a field free point (FFP). To increase the sensitivity of MPI, however, an alternative encoding scheme collecting the particle signal along a field free line (FFL) was proposed. To provide the magnetic fields needed for line imaging in MPI, a very efficient scanner setup regarding electrical power consumption is needed. At the same time, the scanner needs to provide a high magnetic field homogeneity along the FFL as well as parallel to its alignment to prevent the appearance of artifacts, using efficient radon-based reconstruction methods arising for a line encoding scheme. This work presents a dynamic FFL scanner setup for MPI that outperforms all previously presented setups in electrical power consumption as well as magnetic field quality.

In magnetic particle imaging (MPI), the spatial distribution of magnetic nanoparticles is determined by applying various static and dynamic magnetic fields. Due to the complex physical behavior of the nanoparticles, it is challenging to determine the MPI system matrix in practice. Since the first publication on MPI in 2005, different methods that rely on measurements or simulations for the determination of the MPI system matrix have been proposed. Some methods restrict the simulation to an idealized model to speed up data reconstruction by exploiting the structure of an idealized MPI system matrix. Recently, a method that processes the measurement data in x -space rather than frequency space has been proposed. In this work, we compare the different approaches for image reconstruction in MPI and show that the x -space and the frequency space reconstruction techniques are equivalent.

Current simulations of the signal in magnetic particle imaging (MPI) are either based on the Langevin function or on directly measuring the system function. The former completely ignores the influence of finite relaxation times of magnetic particles, and the latter requires time-consuming reference scans with an existing MPI scanner. Therefore, the resulting system function only applies for a given tracer type and the properties of the applied scanning trajectory. It requires separate reference scans for different trajectories and does not allow simulating theoretical magnetic particle suspensions. The most accessible and accurate way for including relaxation effects in the signal simulation would be using the Langevin equation. However, this is a very time-consuming approach because it calculates the stochastic dynamics of the individual particles and averages over large particle ensembles. In the current article, a numerically efficient way for approximating the averaged Langevin equation is proposed, which is much faster than the approach based on the Langevin equation because it is directly calculating the averaged time evolution of the magnetization. The proposed simulation yields promising results. Except for the case of small orthogonal offset fields, a high agreement with the full but significantly slower simulation could be shown.

Ferrofluids, which are stable, colloidal suspensions of single-domain magnetic nanoparticles, have a large impact on medical technologies like magnetic particle imaging (MPI), magnetic resonance imaging (MRI) and hyperthermia. Here, computer simulations promise to improve our understanding of the versatile magnetization dynamics of diluted ferrofluids. A detailed algorithmic introduction into the simulation of diluted ferrofluids will be presented. The algorithm is based on Langevin equations and resolves the internal and the external rotation of the magnetic moment of the nanoparticles, i.e., the Néel and Brown diffusion. The derived set of stochastic differential equations are solved by a combination of an Euler and a Heun integrator and tested with respect to Boltzmann statistics.

Magnetic particle imaging (MPI) is a new imaging modality using oscillating magnetic fields in the frequency range of 10 kHz to 100 kHz. The duration of data acquisition becomes smaller, and signal-to-noise ratio improves if the amplitude of these fields is increased – technically amplitudes of up to 100 mT might be feasible for human-sized systems. On the other hand, with increasing field strength, adverse health effects must be expected: oscillating magnetic fields can stimulate nerves and muscle and heat up tissue. Thresholds for stimulation with magnetic fields in this frequency range are not precisely known, neither is the local temperature rise following exposure. The ICNIRP guidelines define reference levels for magnetic field exposure for the general public that contain large safety factors – for medical diagnostics, they might be exceeded for a short time. In this article, research and guidelines in this field are briefly reviewed, and new results are presented in order to contribute to a future definition of safety limits for oscillating magnetic fields in MPI.