International Journal on Magnetic Particle Imaging (IJMPI)
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Image Time-Series Stability for MPI-Based Functional Neuroimaging
No full textThe temporal stability of an image time-series becomes a critical performance metric when MPI is used as a functional neuroimaging modality. We apply an existing framework for assessing time-series variance from the functional MRI (fMRI) literature to phantom MPI time-series images. In this framework, sources of time-series variance are divided into those arising from thermal noise sources (which do not scale with the signal level) and intensity variations that scale with the signal level. The latter are often thought of as “physiological noise” if they arise from physiological processes or as instrumental “nuisance fluctuations” when arising from instrumental instabilities, such as system gain fluctuations. We analyze the phantom imaging time-series stability of a rodent-sized field-free line (FFL) MPI scanner and assess the relative contributions of these two variance sources to the time-series by varying the super-paramagnetic iron-oxide nanoparticle (SPION) concentration. These measurements permit characterization of our system’s time-series noise, identify future areas of improvement, and suggest the signal levels at which the time-series will be dominated by instrumental instabilities rather than thermal noise or physiological modulations
Drive and receive coil design for a human-scale MPI system
No full textScaling MPI imaging hardware to image a human head presents challenges for the primary drive and receive coils. The larger imaging volume necessitates increased inductance, power delivery, and large physical sizes. Here, we present human-head scale drive and receive solenoid coils in a split gradiometer configuration designed for a mechanically-rotating field-free line MPI system. The design efficiency allows for 8mT drive fields (at ?26 kHz) from the water-cooled drive coil using an amplifier providing 21 A RMS and ?120 V RMS into the drive filter. The geometric decoupling between the drive and Rx coil of the gradiometer pair is -52 dB
Side Lobe Informed Center Extraction (SLICE): a projection-space forward model reconstruction for a 2D imaging system
No full textA two-dimensional MPI acquisition allows signal from SPIONs outside the intended 2D imaging plane to interfere destructively with that from SPIONs in the desired slice, creating unwanted artifacts in the reconstructed image. We address this "side-lobe" signal interference with a Side Lobe Informed Center Extraction (SLICE) reconstruction, which utilizes a projection-space 3D forward model of the detected harmonics. The developed method reduces the out-of-plane interference artifacts in the 2D image reconstruction without the need to change the simplified acquisition schemes or hardware of the gradiometer detection based FFL system, for example by adding true 3D encoding which would interfere with the goal of fast <5 sec temporal resolution needed for functional brain imaging
System matrix compression using Chebyshev polynomials of first and second kind
No full textA common procedure for the reconstruction in Lissajous-type magnetic particle imaging is solving a linear system of equations which is based on the measurement of the so-called system matrix and the induced voltage signal of the unknown magnetic particle distribution. To speed up the reconstruction process and to reduce memory consumption, different compression techniques for the system matrix have been investigated. In this work, we propose a system matrix compression using the tensor product of Chebyshev polynomials of first and second kind. This method is motivated by recently published theoretical findings on the system function. For evaluation, simulated and real-world system matrices have been compressed with the proposed method and other state-of-the-art techniques. When using only one compression coefficient per row, the proposed compression outperforms the compared methods for all tested system matrices in terms of the normalized error metric and better reconstruction results.
Int. J. Mag. Part. Imag. 8(2), 2022, Article ID: 2212003, DOI: 10.18416/IJMPI.2022.221200
Synomag®: The new high-performance tracer for magnetic particle imaging
No full textThe success of tracer-based tomographic methods, such as Magnetic Particle Imaging (MPI), depends on two factors primarily: scanner hardware and tracer performance. Within the last years, several hardware improvements have been presented improving temporal and spatial resolution of MPI systems. However, there was still a lack of efficient commercially available tracers for MPI. Here we report on synomag® particles as a new tracer tailored for MPI, which shows almost four-times higher signal in a Traveling Wave MPI scanner than the established tracer Resovist®.
Int. J. Mag. Part. Imag. 7(1), 2021, Article ID: 2103003, DOI: 10.18416/IJMPI.2021.210300
Optimized sampling patterns for the sparse recovery of system matrices in Magnetic Particle Imaging
No full textIn Magnetic Particle Imaging (MPI), the system matrix plays an important role, as it encodes the relationship between particle concentration and the measured signal. Its acquisition requires a time-consuming calibration scan, which can be a limiting factor in practical applications. Calibration time can be reduced using compressed sensing, which exploits the knowledge that the MPI system matrix has a sparse representation in a suitably chosen domain. This work seeks to further enhance sparse system matrix recovery by optimizing the sampling points to the signal class at hand. For this purpose we introduce an experiment design method based on the Bayesian Fisher information matrix. Our technique uses a previously measured system matrix to tailor the sampling pattern to the signal class at hand. Our tests show that the optimized sampling patterns lead to a more accurate system matrix recovery than popular random sampling approaches. Moreover, our tests demonstrate that the optimized sampling patterns are sufficiently robust to enhance the recovery of system matrices for other types of particles or other experimental conditions.
Int. J. Mag. Part. Imag. 7(2), 2021, Article ID: 2112001, DOI: 10.18416/IJMPI.2021.211200
2D projection image reconstruction for field free line single-sided magnetic particle imaging scanner: simulation studies
No full textMagnetic Particle Imaging is an imaging modality that exploits the nonlinear response of superparamagnetic iron oxide nanoparticles to a time-varying magnetic field. In the past years, various scanner topologies have been proposed, which includes a single-sided scanner. Such a scanner features all its hardware located on one side, offering accessibility without limitations due to the size of the object of interest. In this paper, we present a proof of concept image reconstruction simulation studies for a single-sided field-free line scanner utilizing non-uniform magnetic fields. Specifically, we implemented a filtered backprojection algorithm allowing a 2D image reconstruction over a field of view of 4 x 4 cm2 with a spatial resolution of up to 2 mm for noiseless case.
Int. J. Mag. Part. Imag. 7(1), 2021, Article ID: 2104001, DOI: 10.18416/IJMPI.2021.210400
Spatial selectivity enhancement in magnetic fluid hyperthermia by magnetic flux confinement
No full textAiming to increase spatial selectivity to enhance the precision in Magnetic Fluid Hyperthermia (MFH) therapy and the spatial resolution in imaging, we propose a strategy to increase the selection field gradient in Magnetic Particle Imaging (MPI). In this study, a solution for an existing MPI system topology was simulated, using an additional soft magnetic material as iron core retrofit at the center of the selection field coil. Due to the core\u27s high magnetic permeability relative to air, the magnetic flux is confined, increasing the selection field gradient. Within this simulation study, the optimal core position is evaluated, whilst its effects on the magnet system are validated. According to our results, this strategy can achieve a 27 % reduction in theranostic field of therapy. We found that this technique increases the magnetic field gradient up to a factor of 1.4 (from 2.5 to 3.4 T/m) in z-direction, without significant loading of the drive field resonance circuit caused by eddy currents in the MPI compatible iron core shielding.
Int. J. Mag. Part. Imag. 7(1), 2021, Article ID: 2103002, DOI: 10.18416/IJMPI.2021.210300
Reduction of bias for sparsity promoting regularization in MPI
No full textMagnetic Particle Imaging (MPI) is a tracer based medical imaging modality with great potential due to its high sensitivity, high spatial and temporal resolution, and its ability to quantify the tracer concentration. Image reconstruction in MPI is an ill-posed problem, which can be addressed by regularization methods that lead to a reconstruction bias, which is apparent in a systematic mismatch between true and reconstructed tracer distribution. This is expressed in a background signal, a mismatch of the spatial support of the tracer distribution and a mismatch of its values. In this work, MPI reconstruction bias and its impact are investigated and a recently proposed debiasing method with significant bias reduction capabilities is adopted.
Int. J. Mag. Part. Imag. 7(2), 2021, Article ID: 2112002, DOI: 10.18416/IJMPI.2021.211200
Enhancing spatial resolution in magnetic particle imaging using eigen-reconstructions: opportunities and limitations
No full textEnhancements in spatial resolution can open new avenues for novel applications, but acquiring data at higher resolutions generally comes with penalties in measurement times, signal-to-noise ratios and safety concerns. Therefore, maximizing the spatial resolution of the available data during image reconstruction is paramount. Magnetic Particle Imaging (MPI) has already reached sub-millimeter spatial resolutions. With standard tracers, this has been achieved using a reconstruction method that compensates for the point spread function of the system and the superparamagnetic iron oxide particles (SPIOs). This method is known as the system matrix approach and uses a calibration measurement, relating the concentration of SPIOs and the true particle response to the measured signal. Using a calibration measurement for reconstruction requires a comprehensive assessment of the quality of the system matrix in addition to the measured image data. Analyzing the system matrix by reconstructing selected measurements contained in itself and visualizing them in image space (henceforward called eigen-reconstructions) can provide clear information regarding image quality and artifacts. This is equivalent to using ideal measurement data. Thus, it is possible to identify sources of image artifacts arising solely from the reconstruction, which can be then compensated. In a preliminary report, we presented the principle of eigen-reconstructions to identify and reduce reconstruction-induced artifacts. In this work, we focus on the application of the method to enhance spatial resolution in MPI reconstructions. The principles of an iterative algorithm based on eigen-reconstructions are also further detailed. It is shown that the algorithm compensates the blur arising during image reconstruction effectively. For validation, we present tests of our method using 2D and 3D datasets including an homogeneous and a resolution phantom to demonstrate potential opportunities and limitations.
Int. J. Mag. Part. Imag. 7(2), 2021, Article ID: 2112003, DOI: 10.18416/IJMPI.2021.211200