International Journal on Magnetic Particle Imaging (IJMPI)
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MPI of SuperSPIO20-labeled ALS patient-derived, genome-edited iPSCs and iPSC-derived motor neurons
No full textGenome-edited induced pluripotent stem cells (iPSCs), iPSC-derived neural precursor cells (NPCs) and iPSC-derived motorneurons (MNs) have shown considerable potential for neurorepair in transgenic amyotrophic lateral sclerosis (ALS) rodent models.When pursuing mutant gene-edited iPSC cell therapy in patients, it is highly desirable to have non-invasive imaging techniquesavailable that can report longitudinally on the fate of transplanted cells. With magnetic particle imaging (MPI), one can visualize andquantify the distribution of superparamagnetic iron oxide (SPIO)-labeled stem cells in the body. Here, we report an optimized magneticlabeling protocol for MPI tracking of gene-edited iPSCs and iPSC-derived MNs. We used SuperSPIO20® and Resovist® for celllabeling and found that the MPI performance of SuperSPIO20® is about 20% higher than that for Resovist® when it comes to imagingof labeled cells. Furthermore, we compared the detection sensitivity of MPI with T2-W MRI and concluded that MPI has at least10-fold higher sensitivity in cell detection
Rapid in situ labelling and tracking of neutrophils and macrophages to inflammation using antibody-functionalized MPI tracers
No full textWhite blood cell (WBC) tracking is an imaging technique for clinical diagnoses of inflammation. WBC tracking utilises In-111 scintigraphy with ex vivo WBC labeling, which is cumbersome (~1 hr prep), requires hot chemistry, and kills most WBCs within 24 hours. Magnetic particle imaging (MPI) is a tracer imaging modality that detects superparamagnetic iron oxide nanoparticles (SPIOs), providing a sensitive (~200 cell), radiation-free alternative. As such, this work shows the first in situ labelling and tracking of WBCs to lipopolysaccharide-induced myositis using antibody-targeted MPI (Ab-MPI). SPIOs functionalized with Anti-Ly6G or Anti-F4/80 antibodies were used to track neutrophils or macrophages respectively, yielding differential dynamics and contrast (CNR = ~8-13) in imaging myositis vs. an untargeted control (ferucarbotran). These results showcase Ab-MPI as a radiation-free imaging platform for in situ targeting of immune cell speicific antigen epitopes
Response characteristics of magnetic particle spectroscopy under different excitation waveforms
No full textMagnetic particle spectroscopy (MPS) is a method to characterize the characteristics of magnetic nanoparticles (MNP), which is of great significance for the research of magnetic particle imaging (MPI) and magnetic hyperthermia. In the MPS system, the waveform characteristics of the excitation magnetic field will directly impact the received particle signal. Aiming at the problem that sinusoidal wave is used by default in most current studies, this study has studied the excitation effect of the trapezoidal wave and triangular wave. The results show that under the excitation frequencies of 10kHz and 15kHz, the excitation effect of the trapezoidal wave is obviously better than the other two waveforms, and the effect of the triangular wave is the worst. The research is enormously significant to the optimization of MPS and even MPI
Algorithmic Channel Decoupling for Misaligned Receive Coils in Magnetic Particle Imaging
No full textMagnetic particle imaging (MPI) uses orthogonal receive coils aligned with the drive-field coil directions for signal detection. In case of misaligned receive coils, the particle magnetization couples differently into the receive coils such that a re-calibration involving the measurement of a new system function would be necessary. In this work, we propose a method for decoupling the channels algorithmically into the drive-field coil directions using an MPI transfer function matrix. In that way, system functions for different receive coil units can be reused
The response of magnetic particles with mixed anisotropy at different frequencies
No full textThe response of magnetic particles at different frequencies is important for different applications ranging from mobility magnetic particle imaging in the lower kHz range up to a few hundred kHz for applications like magnetic fluid hyperthermia. In addition, realistic particles have different magnetic anisotropies contributing to the observed response. In this work, the response of particles with mixed cubic and uniaxial anisotropy in the frequency range from 1 kHz to 1 MHz are simulated by solving the corresponding Langevin equations for the mechanical and magnetic rotation of the particles. It is shown that even small ratios of cubic to uniaxial anisotropy visibly influence the response of the particles
A drive filter design for MPI with harmonic notching and selective damping
No full textA harmonically pure and stable drive field is an essential component of any MPI system. Here, we present a filter topology and design methodology tailored for FFL MPI driven at a single frequency. It is a balanced and differential design that minimizes Ohmic losses by transforming the load impedance to a high value for the filtering stages and then back down with a transformer to present an input impedance of ~6 Ohms to the drive amplifier. We implement resistors in tuned elements of the drive filter to damp the high-amplitude side resonances these coupled,tuned elements would otherwise generate in the filter design. This helps damp the undesired resonances to avoid noise in the received signal. In addition to the pass-band at the drive frequency, we place notches at the 2nd and 3rd harmonics (total 100dB and 140dB attenuation, respectively) to specifically target these important harmonics. Finally, the circuit elements are picked to maximize stability of the drive current to temperature-induced tuning shifts. The design software (written in Julia), which calculates component values given load parameters and notch locations, has been made available at OS-MPI.github.io
A Deblurring Model for X-space MPI Based on Coded Calibration Scenes
No full textX-space reconstructions suffer from blurring caused by the point spread function (PSF) of the Magnetic Particle Imaging (MPI) system. Here, we propose a deep learning method for deblurring x-space reconstructed images. Our proposed method learns an end-to-end mapping between the gridding-reconstructed collinear images from two partitions of a Lissajous trajectory and the underlying magnetic nanoparticle (MNP) distribution. This nonlinear mapping is learned using measurements from a coded calibration scene (CCS) to speed up the training process. Numerical experiments show that our learning-based method can successfully deblur x-space reconstructed images across a broad range of measurement signal-to-noise ratios (SNR) following training at a moderate SNR
Joint multi-patch reconstruction: fast and improved results by stochastic optimization
No full textIn order to measure larger volumes in magnetic particle imaging, it is necessary to divide the region of interest into several patches and measure those patches individually due to a limited size of the field of view. This procedure yields truncation artifacts at the patches boundaries during reconstruction. Applying a regularization which takes into account neighbourhood structures not only on one patch but across all patches can significantly reduce those artifacts. However, the current state-of-the-art reconstruction method using the Kaczmarz algorithm is limited to Tikhonov regularization. We thus propose to use the stochastic primal-dual hybrid gradient method to solve the multi-patch reconstruction task. Our experiments show that the quality of our reconstructions is significantly higher than those obtained by Tikhonov regularization and Kaczmarz method. Moreover, using our proposed method, a joint reconstruction considerably reduces the computational costs compared to multiple single-patch reconstructions. The algorithm proposed is thus competitive to the current state-of-the-art method not only regarding reconstruction quality but also concerning the computational effort.
Int. J. Mag. Part. Imag. 8(2), 2022, Article ID: 2212002, DOI: 10.18416/IJMPI.2022.221200
Characterization of the Synomag®-D-PEG-OMe nanoparticles for the encapsulation in human and murine red blood cells
No full textIt was shown that the encapsulation of SPIO-based contrast agents in the red blood cells (RBCs) increases the circulation time in blood of these nanomaterials. Not all iron oxide particles are eligible for the entrapment into RBCs, depending on several factors and synthesis protocol. We have recently identified some type of nanoparticles that can be loaded with our method into RBCs to produce biocompatible SPIO-RBCs carriers that could be used as new intravascular tracers for biomedical applications, such as Magnetic Particle Imaging (MPI). Here, we report the first in vitro results obtained by using the Synomag®-D-PEG-OMe nanoparticles with both human and murine RBCs. MPS analysis showed that human Synomag®-D-PEG-OMe-loaded RBCs produced a signal that is weaker respect to the remarkable signal obtained with ferucarbotran loaded-RBCs prepared at the same condition, but it is to be noted that the encapsulation efficiency of Synomag®-D-PEG-OMe into cells is lower compared to ferucarbotran nanoparticles
Improving Model-Based MPI Image Reconstructions: Baseline Recovery, Receive Coil Sensitivity, Relaxation and Uncertainty Estimation
No full textImage reconstruction is an integral part of Magnetic Particle Imaging (MPI). Over the last years, several methods have been proposed for reconstructing MPI images more efficiently and accurately. One major challenge for model-based MPI image reconstruction methods is the realistic modeling of the measurement system; effects like non-linear gradient fields, non-uniform drive fields, space-dependent coil sensitivities, drive frequency filtering and particle relaxation, if not properly accounted for in the model, may yield inaccurate reconstructions. This work addresses these issues by means of an image reconstruction method that accounts for the coil sensitivity, baseline recovery and particle relaxation. We investigate the proposed approach for a 1D MPI setup, and provide an approach for the calculation of the uncertainties of the reconstructed images.
Int. J. Mag. Part. Imag. 8(1), 2022, Article ID: 2208001, DOI: 10.18416/IJMPI.2022.220800