Size-isolation of superparamagnetic iron oxide nanoparticles improves MRI, MPI and hyperthermia performance.

Superparamagnetic iron oxide nanoparticles (SPION) are extensively used for magnetic resonance imaging (MRI) and magnetic particle imaging (MPI), as well as for magnetic fluid hyperthermia (MFH). We here describe a sequential centrifugation protocol to obtain SPION with well-defined sizes from a polydisperse SPION starting formulation, synthesized using the routinely employed co-precipitation technique. Transmission electron microscopy, dynamic light scattering and nanoparticle tracking analyses show that the SPION fractions obtained upon size-isolation are well-defined and almost monodisperse. MRI, MPI and MFH analyses demonstrate improved imaging and hyperthermia performance for size-isolated SPION as compared to the polydisperse starting mixture, as well as to commercial and clinically used iron oxide nanoparticle formulations, such as Resovist® and Sinerem®. The size-isolation protocol presented here may help to identify SPION with optimal properties for diagnostic, therapeutic and theranostic applications.

Flexible and modular MPI simulation framework and its use in modelling a µMPI.

The availability of thorough system simulations for detailed and accurate performance prediction and optimization of existing and future designs for a new modality such as magnetic particle imaging (MPI) are very important. Our framework aims to simulate a complete MPI system by providing a description of all (drive and receive) coils, permanent magnet configurations, magnetic nanoparticle (MNP) distributions, and characteristics of the signal processing chain. The simulation is performed on a user defined spatial and temporal discrete grid. The magnetization of the MNP is modelled by either the Langevin theory or as ideal particles with infinite steepness and ideal saturation. The magnetic fields are approximated in first order by calculating the Biot-Savart integral. Additionally the coupling constants between the excitation coils (e.g. drive field coils) and the receive coils can be determined. All coils can be described by an XML description language based on primitive geometric shapes. First simulations of a modelled µMPI system are shown. In this regard µMPI refers to a small one dimensional system for samples of a size of a few tens of a cubic millimeter and a spatial resolution of about 200 µm.

A FIELD CANCELATION SIGNAL EXTRACTION METHOD FOR MAGNETIC PARTICLE IMAGING.

In nowadays Magnetic Particle Imaging (MPI) signal detection and excitation happens at the same time. This concept, however, leads to strong coupling of the drive (excitation) field (DF) with the receive chain. As the induced DF signal is several orders of magnitude higher, special measures have to be taken to suppress this signal portion within the receive signal to keep the required dynamic range of the subsequent analog to digital conversion in a technically feasible range. For "frequency space MPI" high-order band-stop-filters have been successfully used to remove the DF signals, which unfortunately as well removes the fundamental harmonic components of the signal of the magnetic nanoparticles (MNP). According to the Langevin theory the fundamental harmonic component has a large signal contribution and is important for direct reconstruction of the particle concentration. In order to separate the fundamental harmonic component of the MNP from the induced DF signal, different concepts have been proposed using signal cancelation based on additional DF signals, also in combination with additional filtering. In this paper, we propose a field-cancelation (FC) concept in which a receive coil (RC) consists of a series connection of a primary coil in combination with an additional cancelation coil. The geometry of the primary coil was chosen to be sensitive for the MNP signal while the cancelation coil was chosen to minimize the overall inductive coupling of the FC-RC with the DF. Sensitivity plots and mutual coupling coefficients were calculated using a thin-wire approximation. A prototype FC-RC was manufactured and effectiveness of the reduction of the mutual inductive coupling (d) was tested in an existing mouse MPI scanner. The difference between simulations (ds =70 dB) and the measurements (dms =55 dB) indicated the feasibility as well as the need for further investigations.

Image-derived mean velocity measurement for prediction of coronary flow reserve in a canonical stenosis phantom using magnetic particle imaging.

INTRODUCTION: Aim of this study is to evaluate whether magnetic particle imaging (MPI) is capable of measuring velocities occurring in the coronary arteries and to compute coronary flow reserve (CFR) in a canonical phantom as a preliminary study. METHODS: For basic velocity measurements, a circulation phantom was designed containing replaceable glass tubes with three varying inner diameters, matching coronary-vessel diameters. Standardised boluses of superparamagnetic-iron-oxide-nanoparticles were injected and visualised by MPI. Two image-based techniques were competitively applied to calibrate the respective glass tube and to compute the mean velocity: full-duration-at-half-maximum (FDHM) and tracer dilution (TD) method. For CFR-calculation, four necessary settings of the circulation model of a virtual vessel with an inner diameter of 4 mm were generated using differently sized glass tubes and a stenosis model. The respective velocities in stenotic glass tubes were computed without recalibration. RESULTS: On velocity level, comparison showed a good agreement (rFDHM = 0.869, rTD = 0.796) between techniques, preferably better for 4 mm and 6 mm inner diameter glass tubes. On CFR level MPI-derived CFR-prediction performed considerably inferior with a relative error of 20-44%. CONCLUSIONS: MPI has the ability to reliably measure coronary blood velocities at rest as well as under hyperaemia and therefore may be suitable for CFR calculation. Calibration-associated accuracy of CFR-measurements has to be improved substantially in further studies.

Multifrequency magnetic particle imaging enabled by a combined passive and active drive field feed-through compensation approach.

PURPOSE: Magnetic particle imaging (MPI) allows fast imaging of the spatial distribution of superparamagnetic iron-oxide based nanoparticles (SPIONs). Recent research suggests that MPI furthermore promises in-vivo access to environmental parameters of SPIONs as temperature or viscosity. Various medical applications as nanomedicine, stem cell-based therapies or magnetic hyperthermia could benefit from in-vivo multiparameter estimation by MPI. One possible approach to get access to functional parameters is particle excitation at multiple frequencies. To enable the investigation of the mentioned approach, a novel MPI device capable of multifrequency excitation is needed. METHODS: MPI usually employs analog band-stop filters to cancel the drive field feed-through, which is magnitudes higher than the particle signal. To enable drive field frequency flexibility over a wide bandwidth, we propose a combined passive and active drive field feed-through compensation approach. This cancellation technique further allows the direct detection of the SPIONs' signal at the fundamental excitation frequency. RESULTS: A combined feed-through suppression of up to -125 dB is reported, which allows to adjust the drive field frequency from 500 Hz to 20 kHz. Initial spectroscopic measurements and images are shown that demonstrate the concept of multifrequency excitation and prove the imaging capability of the presented scanner. A mean signal-to-noise ratio (SNR) enhancement by the factor of 1.7 was shown when the first harmonic is used for measurement-based image reconstruction compared to when it is omitted. CONCLUSIONS: In this paper, the first one-dimensional multifrequency magnetic particle imaging (mf-MPI) that features adjustable excitation frequencies from 500 Hz to 20 kHz is presented. The device will be used to study the principle of multiparameter estimation by employing multifrequency excitation.

Joint Reconstruction of Tracer Distribution and Background in Magnetic Particle Imaging.

Magnetic particle imaging (MPI) is a novel tomographic imaging technique, which visualizes the distribution of a magnetic nanoparticle-based tracer material. However, reconstructed MPI images often suffer from an insufficiently compensated image background caused by rapid non-deterministic changes in the background signal of the imaging device. In particular, the signal-to-background ratio (SBR) of the images is reduced for lower tracer concentrations or longer acquisitions. The state-of-the-art procedure in MPI is to frequently measure the background signal during the sample measurement. Unfortunately, this requires a removal of the entire object from the scanner's field of view (FOV), which introduces dead time and repositioning artifacts. To overcome these considerable restrictions, we propose a novel method that uses two consecutive image acquisitions as input parameters for a simultaneous reconstruction of the tracer distribution, as well as the background signal. The two acquisitions differ by just a small spatial shift, while keeping the object always within the focus of a slightly reduced FOV. A linearly interpolated background between the initial and final background measurement is used to seed the iterative reconstruction. The method has been tested with simulations and phantom measurements. Overall, a substantial reduction of the image background was observed, and the image SBR is increased by a factor of 2(7) for the measurement (simulation) data.