International Journal on Magnetic Particle Imaging (IJMPI)
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Fast detection of Sars-CoV2 Antibodies by the use of critical off-set magnetic particle spectroscopy (COMPASS)
No full textCurrent bioassays for detection of antibodies or antigens such as ELISA (Enzyme-linked Immunosorbent Assay) are relatively inflexible, expensive and time-consuming. Upcoming methods, such as ACS (AC susceptometry) or MPS (Magnetic Particle Spectroscopy), exploit the magnetization response of functionalized MNP ensembles to assess specific information about the MNP mobility as well as conjugations of chemical or biological compounds on their surface. Both methods have shown promising results in the past but cannot reach the sensitivity of above-mentioned techniques. We used a novel method based on a modified MPS being sensitive to minimal changes in mobility of MNP ensembles. This facilitates robust and easy-to-handle measurements of minimal changes in the diameter of MNPs. As an example, we detected SARS-CoV-2 antibodies binding to the S1 antigen on the surface of functionalized MNPs. Without any purification or incubation, we could show a sensitivity of less than 50 ng/mL of SARS-CoV-2 antibodies in human blood
A Modular Magnetic Particle Imaging Simulation system for fast reconstruction
No full textHow to developa modular simulation system forfast reconstruction of different dimensional MPI images is significant fordesign of MPI system. In this study, we propose a modular and open-source MPI simulation system, which consists of the virtual phantom module, MPI scanner module, particle magnetization module, reconstruction module, and quantitative evaluation module. Combining the MPI scanner module and the particle magnetization module can produce the simulated voltage signal of the superparamagnetic iron oxide (SPIO) magnetization. The system enables the integration of the different MPI reconstruction methods to reconstruct an image from the simulated voltage signal of the SPIO magnetization. The quantitative evaluation module can analyze the MPI system performance by comparing the differences between the simulation reconstruction image and the virtual phantom image. Each module can be easily extended. Now, our simulation system is implemented using Python 3.8 with the open scientific computing libraries Numpy and Scipy and supports the simulation of 1-D, 2-D and 3-D MPI systems and batch simulation tasks. We have shown in this work the early stages of the development of our MPI simulation system which is designed to provide an optimal design solution is selected for the new MPI system. In future, we will improve the system with a focus on adding more features, such as field-free line simulation, non-Langevin particle magnetization and other relaxation modeling, etc. The source code of the simulation system is available on http://mpilab.net/en/simulation/
MPI Reconstruction Based on System Matrix using a Field Free Line
No full textMagnetic particle imaging (MPI) is a new imaging modality which draws much attention due to its high sensitivity and spatial resolution. The spatial information encoded using a field free line (FFL) exhibit better sensitivity and signal-to-noise ratio compared to field free point (FFP) scanning. In this study, we investigate different reconstruction methods for MPI image based on system matrix and FFL scanning using simulation data. Our results show that existing reconstructed methods are influenced by particle size, noise, iteration coefficient, and trajectory density. We evaluate the weighting iterative method and the results are shown with a phantom. This work bridges the gap between simulation and measurement experimental work by demonstrating the feasibility of reconstructing 2D images using a simulated MPI system matrix and FFL
MPI Signal Performance of Resotran
No full textAn important ingredient for clinical translation of Magnetic Particle Imaging (MPI) is the availability of superparamagnetic iron-oxid nanoparticles (SPIOs) with given medical approval for human interventions. Many SPIOs used as tracer-material in magnetic resonance imaging (MRI), do not have the magnetic properties needed for a potent signal generation in MPI. In particular they are often too small and thus the thermal energy dominates the magnetic energy leading to a linear magnetization behavior, which is not suitable for signal generation and spatial encoding in MPI. Some particle types are too large and block the Neél relaxation process due to strong magnetic anisotropies, reducing their ability to follow the field at excitation frequencies between 10 kHz to 150 kHz. At the same time, the medical approval of dedicated MPI tracers with optimal signal performance is very costly and tedious and will only turn profitable for companies with a clear clinical business case. Fortunately, there are some tracers that are suitable for both MRI and MPI and thus evaluating newly introduced MRI tracers is essential for potential human MPI studies. We show that the new MRI contrast agent Resotran (b.e.imaging GmbH, Baden-Baden, Germany, medically approved in 10/2022 under reg. no. 7002837.00.00 in Germany) is suitable for MPI. Initial Magnetic Particle Spectroscopy measurements indicate that Resotran shows a similar performance as the formerly approved tracer Resovist (Bayer Schering Pharma, Berlin, Germany) and the pre-clinical MPI tracer perimag (micromod Partikeltechnologie, Rostock, Germany). In combination with human-sized MPI systems, this paves the way towards first human MPI experiments
Extending a commercial preclinical MPI scanner into an MPI-MFH platform using a hyperthermia insert
No full textMagnetic particle imaging (MPI) and magnetic fluid hyperthermia (MFH) have the potential of being integrated in a single device to allow for seamless switching between imaging and therapeutic modes. In an MPI-MFH platform, the field free region of an MPI scanner can serve not only for imaging diagnostics but, by adding a radio-frequency magnetic field, also for therapeutic use of the magnetic particles by heating. It enables precisely localized heating to a specific target temperature deep in the tissue via MFH. In addition, MPI provides targeted visualization and temperature information of systemically injected magnetic nanoparticles providing direct feedback. In this work, the integration process of a hyperthermia insert which is capable of extending a commercial magnetic particle imaging scanner with the functionality of magnetic fluid hyperthermia is presented. Furthermore, the thermal resolution of the MPI-MFH platformis measured
Exploiting the Fourier Neural Operator for faster magnetization model evaluations based on the Fokker-Planck equation
No full textAccurate modeling of the mean magnetic moment of an ensemble of magnetic particles in dynamic magnetic fields is a challenging task that requires sophisticated differential equation solvers. However, these methods are computationally costly and therefore not practical for long excitation sequences such as those of the Lissajous type. In this paper we propose to accelerate simulations by using a neural network mapping from the input parameter functions that are applied to the original particle simulator directly to the mean magnetic moment output function. The architecture of the neural network is based on the Fourier neural operator, which allows to train mappings between function spaces. Our results show that the particle simulation can be accelerated by a factor of about 200 while the relative error of the neural network simulator remains below 1.5%
A Denoiser Scaling Technique for Plug-and-Play MPI Reconstruction
No full textImage reconstruction based on the system matrix in magnetic particle imaging (MPI) involves an ill-posed inverse problem, which is often solved using iterative optimization procedures that use regularization. Reconstruction performance is highly dependent on the quality of information captured by the regularization prior. Learning-based methods have been recently introduced that significantly improve prior information in MPI reconstruction. Yet, these methods can perform suboptimally under drifts in the image scale between the training and test sets. In this study, we assess the influence of scale drifts on the performance a recent plug-ang-play method (PP-MPI) that uses a pre-trained denoiser. We introduce a new denoiser scaling technique that improves reliability of PP-MPI against deviations in image scale. The proposed technique enables high quality reconstructions that are robust against scale drifts between training and testing sets
Investigating the Harmonic Dependence of MPI Resolution
No full textIn this work we investigate how the MPI resolution changes as a function of signal harmonics. Based on a simulation study that models a lock-in measurement of the point spread function we apply our findings to actual measurement data obtained from NIST\u27s MPI instrument. In both cases we show that the image resolution improves by a factor of more than two between the 3rd and 7th harmonic
Improving heating performance in Iron-based nanoparticles by tuning saturation magnetization
No full textNanoparticles (NPs) with higher magnetization compared to the conventionally used iron oxides have potential in magnetic fluid hyperthermia [1] and possibly beyond. In this study, the saturation magnetization was tuned by changing the ratio of surfactant ligands during the thermal decomposition process of Iron pentacarbonyl Fe(CO)5. Firstly, only one type of surfactant ligand has been added separately to prepare Iron-NPs @oleic acid and Iron-NPs @ oleylamine. Additionally, a third nanosystem has been prepared by a mixture of ratios between oleic acid/oleylamine (1/1) (Iron-NPs @oleic acid/oleylamine). Monodispersed core-shell nanoparticles with narrow size distribution were obtained after carefully controlled synthesis. The presence of a core-shell structure has been confirmed by high-resolution transmission electron microscopy (HRTEM). The mean size of the nanoparticles is 13.45nm, 14.55nm, and 15.75nm for Iron-NPs @oleic acid, Iron-NPs @ oleylamine, and Iron-NPs @oleic acid/oleylamine, respectively. The shape was mainly spherical for nanoparticles synthesized with oleic acid. However, the shape is changed after adding the oleylamine. The interaction between both surfactants has contributed to an increase in the saturation magnetization Msat at room temperature from 80 Am2/kg for Iron-NPs @oleic acid to 140 Am2/kg under an applied magnetic field ?0H=2T for Iron-NPs@oleic acid/oleylamine. Furthermore, to test these nanoparticles for magnetic hyperthermia application, their magnetic heating properties have been measured with an AC magnetic field applicator under an AC magnetic field 30mT, with different frequencies (98 kHz, 200 kHz, and 400 kHz). The intrinsic loss power (ILP) values are determined as a normalization of specific absorption rate (SAR) values measured at different magnetic field amplitudes/frequencies [2]. The ILP values are 2, 0.48, and 1.14 nH.m2/kg for Iron-NPs @oleic acid/oleylamine, Iron-NPs @oleic acid, and Iron-NPs @ oleylamine, respectively. In conclusion, the surface modification of the core-shell nanoparticles using a mixture of surfactants has significantly improved the magnetic fluid hyperthermia heating rate.
Multi sequence hardware design for rotational drift spectroscopy
No full textRotational Drift Spectroscopy (RDS) is a novel spectroscopic method for magnetic nanoparticles. It is based on measuring the rotational drift of magnetic nanoparticle ensembles in liquid suspension in a rotating magnetic field, that is below the magnetic field strength necessary for rotating the magnetic nanoparticles synchronously. The resulting asynchronous rotational drift strongly depends on the properties of the magnetic nanoparticles and their environment. This allows for, e.g., detecting specific molecules via functionalized magnetic nanoparticles. The following work presents a compact rotational drift spectroscopy hardware design, which is controllable with python scripts and is especially designed for accommodating various kinds of RDS measurement sequences with differing hardware requirements