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Gastrointestinal (GI) bleeding is a potentially life-threatening condition that is typically diagnosed using radiation-based imaging modalities such as computed tomography (CT) or catheter-based angiography. Magnetic Particle Imaging (MPI) could provide non-invasive, real-time volumetric imaging without ionizing radiation in future human-sized scanners that covers the entire GI tract. We have developed a human-sized (3D printed) phantom that represents both the bowel lumen and the vascular compartment of the bowel wall. One version has a perforation between the two compartments and a control phantom does not. For single contrast MPI, we evaluate the fluid exchange between the two lumen by observing an administered blood pool tracer. For multi-contrast MPI, the intestinal lumen was filled with an intestinal tracer, which represents an orally administered tracer, to allow co-registration of both tracers at the same location. Both single-and multi-contrast MPI are feasible to visualize GI bleeding and MPI may prove to be a useful tool for radiation-free detection of bleeding throughout the GI tract.

The Langevin model of paramagnetism is commonly used as a simplified physical model for magnetic particle imaging. In research with immobilized nanoparticles that are non-oriented, the phenomenon is observed that the measured system function components for Lissajous trajectory-based excitation show a high spatial similarity to those from the Langevin model of paramagnetism. In this work we show that this observation can be explained mathematically, since in equilibrium and for anisotropic uniaxial nanoparticles without orientation the model falls back to the Langevin model of paramagnetism. Since previous studies have also shown that the anisotropic equilibrium model for immobilized particles is approximately equivalent to the Néel rotation Fokker-Planck model, the Langevin model of paramagnetism is sufficient to cover the non-oriented immobilized case.

Magnetic Particle Imaging (MPI) is a tracer-based medical imaging modality with great potential due to its high sensitivity, high spatiotemporal resolution, and ability to quantify the tracer concentration. Image reconstruction in MPI is an ill-posed problem, which can be addressed by the use of regularization methods. Single-and multi-contrast MPI reconstructions produce different kinds of artifacts. In this work, the multi-contrast MPI channel leakage is introduced and an analysis of the multi-contrast MPI system matrix properties is conducted to understand the source of the multi-contrast MPI channel leakage.

Exact knowledge on the magnetic fields used in tomographic imaging systems is important for accurate sequence planning and model-based image reconstruction in existing devices. It is common to measure the magnetic fields on a small subset of points and use spherical harmonics to approximate the fields inside a spherical region. However, most scanner bores could be better filled using a cylindrical or ellipsoidal region. In this work, we present the application of ellipsoidal harmonics for efficient approximation of a typical magnetic field in magnetic particle imaging.

Model-based magnetic particle imaging (MPI) is a challenging task both due to the complicated underlying physical model and the high numerical effort required for the solution of the corresponding equations of motion. A third challenge for practical applications is the identification of model parameters that are consistent with the given experimental setting and produce accurate predictions of the MPI signals. In this work, we show how the parameter identification problem can be addressed using a learned physics simulator based on the Fourier neural operator. As an application, we show how model-based system matrices can be estimated from a small set of calibration measurements, which can also be interpreted as a model-based approach to system matrix recovery. We compared our approach to established compressed sensing and interpolation schemes and found that it outperformed both.

The signal chain of a Magnetic Particle Imaging system can be designed to include a dedicated receive-only coil or to combine transmit and receive coils. More common are circuits with separate transmit and receive chains, using dedicated receive coil(s) that cancel the excitation feedthrough. However, combined transmit-receive systems may prove to have several benefits, such as reducing the system complexity, providing a lower resistive noise contribution due to larger copper cross-section, facilitating a transition from 1D to multidimensional signal generation and acquisition, and implementing an embedded band-stop filter. In this theoretical work, a matching condition that governs inductors for resonant combined transmit-receive systems is investigated. To tap the signal, a compromise between the obtained signal strength and power consumption is considered, caused by the chosen circuit topology, that balances both signal loss and power consumption at a −3 dB benchmark.

Image reconstruction in Magnetic Particle Imaging (MPI) is an ill-posed linear inverse problem. A standard method for solving such a problem is the regularized least squares approach, which uses, a regularization function to reduce the impact of measurement noise in the reconstructed image by leveraging prior knowledge. Various optimization algorithms, including the Kazcmarz method or the Alternating Direction Method of Multipliers (ADMM), and regularization functions, such as l2 or Fused Lasso priors have been employed. Therefore, the creation and implementation of cutting-edge image reconstruction techniques necessitate a robust and adaptable optimization framework. In this work, we present the open-source Julia package RegularizedLeastSquares.jl, which provides a large selection of common optimization algorithms and allows flexible inclusion of regularization functions. These features enable the package to achieve state-of-the-art image reconstruction in MPI.

Model-based reconstruction is still one of the key challenges in magnetic particle imaging (MPI) when using multidimensional Lissajous-type excitation. Besides an appropriate particle model, the model of the MPI system for signal generation and reception has a major impact on the modeled system matrix. We outline the influence of the MPI scanner parameters on the system matrix pattern and review methods to calibrate each parameter.

The Kaczmarz algorithm is widely used for image reconstruction in magnetic particle imaging (MPI) because it converges rapidly and provides good image quality even after a few iterations. It is often combined with Tikhonov regularization to cope with noisy measurements and the ill-posed nature of the imaging problem. In this abstract, we propose to combine the Kaczmarz method with a plug-and-play (PnP) denoiser for regularization, which can provide more specific prior knowledge than handcrafted priors. Using measurement data of a spiral phantom, we show that Kaczmarz-PnP yields excellent image quality, while speeding up the already fast convergence. Since the PnP denoiser is not coupled to the imaging operator, the Kaczmarz-PnP method is very generic and can be used for image reconstruction independently of the measurement sequence and MPI tracer type.

Magnetic particle imaging (MPI) is an imaging modality that measures the response of magnetic nanoparticle tracers to alternating magnetic fields. There has recently been exploration into multi-contrast MPI, in which the signal from different tracer materials or environments is separately reconstructed, resulting in multi-channel images that enable temperature or viscosity quantification. In this work, we investigate the channel leakage in multi-contrast MPI reconstruction and we introduce a two-step measurement and reconstruction method to quantify and reduce channel leakage between multi-contrast MPI channels.

Magnetic Particle Imaging hardware has reached human scale and thus patient safety questions and clinical application scenarios are in the focus of current research. In this work, we present a safe real-time 3D MPI system for cerebral applications. High voltages are avoided to ensure patient safety by a low voltage-high current transmit coil design. The developed 2D drive-field generator generates a field-free-point trajectory in the sagittal xz-plane that is shifted with low frequency by a dynamic selection-field sequence along the y-axis. The scanner generates 3D images with 4 frames/second and allows for direct visualization of the clinically preferred transversal yz-plane, which is crucial for future brain examinations. Advanced reconstruction techniques reach a system sensitivity of 4 µgFe with respect to the iron mass in a sensitivity study., Deutsche Forschungsgemeinschaft (DFG)

In Magnetic Particle Imaging, the spatial distribution of a tracer is measured and depicted with a concentration dependent signal intensity for any location that contains particles, whereas surrounding tissue does not provide any signal. After tracer injection, the signal over time (positive contrast) can be utilized as a transient response to calculate dynamic diagnostic parameters like perfusion parameter maps. In this work, a bolus of physiological saline solution without any particles (negative contrast) is proposed, where the remaining steady state concentration contributes to the image contrast. This opens up the possibility to stretch the total monitoring time of a patient by utilizing a positive-negative contrast sequence, while keeping the total iron dose constant in the subject. Resulting time responses show that normalized signals from positive and negative boli are concurrent in the phantom experiments, indicating identical diagnostic parameters for in-vivo use.

In recent works, arbitrary waveform or pulsed excitation in Magnetic Particle Imaging (MPI) was proposed to offer better resolution and sensitivity. Generating these excitation fields poses a new challenge in MPI hardware design. This work proposes a method which models the excitation chain as a linear system and predicts the required input voltage for the desired output field. The initial prediction is then iteratively improved to compensate for inaccuracies of the model. The method is demonstrated to achieve accurate field waveforms in both linear and slew rate limited regions of the amplifier.

The model-based reconstruction problem is still one of the key challenges in magnetic particle imaging (MPI) when using multi-dimensional Lissajous-type excitations. One aspect, which is often highlighted in the literature, is the magnetization behavior of the magnetic nanoparticles in fluids. Another aspect, which is at least as important as the particle model itself but sometimes treated less prominently, is a very careful calibration of the model input, respectively the scanner parameters such as analog filter and applied magnetic fields. The careful consideration of both aspects is the essential requirement for a proper solution to the model-based problem. In the present work we combine previously calibrated scanner components with mono-and polydisperse particle models for immobilized nanoparticles to derive a model-based system function and an calibration routine exploiting applied magnetic field generalizability. It is experimentally validated on the Bruker preclinical MPI system using 2D Lissajous trajectories., Deutsche Forschungsgemeinschaft (DFG)

Micromagnetic fluids are at the core of magnetic particle imaging as underlying tracer materials. They are formed when magnetic nanoparticles are suspended in a fluid such as blood, cytoplasm or water. One of the fundamental assumptions made in current MPI models is that the micromagnetic response of nanoparticles and the dynamics of the fluid transporting them are decoupled. In this contribution, we use a simplified micromagnetic model that takes this interaction into account to investigate scenarios where this assumption breaks down., Deutsche Forschungsgemeinschaft (DFG)

Time-and memory-consuming calibration measurements are a major drawback in system-matrix-based recon-structions in magnetic particle imaging (MPI). Especially, exchanging the receive coils requires new system matrices and therefore new calibration measurements. To reduce the number of such measurements, the MPI transfer function can be used to transfer the system matrix of one receive coil set to another. The transfer function can be obtained by a direct measurement or by estimation using a measured system matrix of each setup. In this abstract, we extend the latter to incorporate coupling of the receive coils while using only a few voxels of the system matrices. In this way, we can transfer system matrices between two different receive setups, both of which may contain non-orthogonal coils.

Magnetic particle imaging (MPI) is a pre-clinical imaging modality, whose system design is still evolving, in particular towards human studies and clinical use. Therefore, many MPI scanners are custom-made distributed systems, both on the hard-and the software side. In this work we present the open-source Julia framework MPIMeasurements.jl, which implements a composable representation of imaging systems. It also offers flexible data structures that allow the implementation of specific imaging protocols, such as online/offline measurements, repeated measurements and system matrix calibrations. The project is designed to be expanded to new systems through community development and component reuse. To showcase the versatility of the software package, we give an overview of four very different MPI systems, which were realized with MPIMeasurements.jl., Deutsche Forschungsgemeinschaft (DFG), Europäischer Fonds für Regionale Entwicklung (EFRE)

Image reconstruction in magnetic particle imaging is a challenging task because the optimal image quality can only be obtained by tuning the reconstruction parameters for each measurement individually. In particular, it requires a proper selection of the Tikhonov regularization parameter. In this work we propose a deep-learning-based post-processing technique, which removes the need for manual parameter optimization. The proposed neural network takes several images reconstructed with different parameters as input and combines them into a single high-quality image.

The imaging quality of Magnetic Particle Imaging (MPI) is not just limited by the MPI system but also by the quality of available tracers. The tracer quality can be improved by optimizing the shape, core size and shell of the nanoparticles. However, such a defined synthesis is quite challenging. Biogenic magnetic nanoparticles, so-called magnetosomes, synthesized by magnetotoactic bacteria, might provide a promising alternative. In this study, magnetosomes isolated from different Magnetospirillum gryphiswaldense mutant strains biomineralizing particles with varying core diameters were investigated with regard to their usability as tracers for MPI., Deutsche Forschungsgemeinschaft (DFG), European Union, Bundesministerium für Bildung und Forschung (BMBF)

Accurate 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 %., Deutsche Forschungsgemeinschaft (DFG)

Many different concepts for selection-field generators have been introduced for Magnetic Particle Imaging so far. In this work, the field generation characteristics of an optimized iron core selection-field generator consisting of two coil arrays with a total of 18 coils are presented. Due to the high number of degrees of freedom, a wide variety of field configurations are possible. The setup allows the generation of arbitrarily shaped fields, including the standard Magnetic Particle Imaging fields such as field-free points and field-free lines. In this work, measurements of static magnetic fields are presented and the current calculation method for generating a specific field configuration is discussed., Deutsche Forschungsgemeinschaft (DFG)

In iterative system-matrix-based reconstruction in Magnetic Particle Imaging, three major parameters control the amount of regularization. Finding the right choice for these parameters is commonly done by user input and requires time and experience. We propose a method that enables automatic reconstruction and achieves good results on a measured concentration series.

Recently, the potential of red blood cells (RBCs) loaded with superparamagnetic iron oxide (SPIO)-based nanoparti-cles as new blood-pool tracer material for the Magnetic Particle Imaging (MPI) has been investigated. It was shown that the encapsulation of SPIO-based contrast agents in the RBCs increase the circulation time in blood of these nanomaterials. However, not all iron oxide nanoparticles are eligible to the encapsulation into RBCs, depending on several factors such as dispersant agent nature, nanoparticle size and synthesis protocol. Therefore, we have recently started a program to identify those nanoparticles that can be potentially loaded with our method into RBCs. The goal is to produce biocompatible SPIO-RBCs carriers that can be used as new intravascular magnetic susceptible agents in biomedical applications, such as MRI and MPI. Here, we report the in vitro results obtained by using the Synomag®-D-PEG-OMe nanoparticle suspension (micromod Partikeltechnologie GmbH) with both human and murine red blood cells. MPS analysis showed that human Synomag®-D-PEG-OMe-loaded RBCs produced a signal that is weaker respect to the remarkable signal of 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.

Modern imaging modalities, such as magnetic particle imaging (MPI), are based on complex sequences which require synchronous multi-channel signal generation and reception. The component of anMPI scanner responsible for this functionality is the data acquisition (DAQ) system. Different scanner topologies and the nature of (digital) signal processing impose varying requirements on such a system. In this work, we introduce the RedPitayaDAQServer project, which implements a flexible and scalable DAQ system. It is based on the low-cost hardware RedPitaya STEMlab 125-14 and is able to meet the requirements of most MPI scanner concepts that have been proposed to date.

A major issue for human-sizedMagnetic Particle Imaging scanners is the generation of sufficiently large magnetic gradient fields. By taking advantage of the field amplification properties of soft-iron, a considerable amount of power can be saved. In this work, an optimized selection and focus field generator is presented, that can generate flexible and high gradient fields at comparatively lowpower consumption. Coil spacing and possible field-free-point positions are similar to conventional MPI scanners designed with air coils, but with significantly less demands on infrastructure and cooling design. The optimization process is discussed and first field measurements are presented.

The achievable sensitivity inMagnetic Particle Imaging is not only limited by noise, but also depends on the stability of the system. Thermal dependencies of the current carrying components lead to drive-field distortions in amplitude and phase, causing drifting background signals. In this work, an active capacitor heating system is developed that allows for thermal stabilization and trimming a resonance circuit to the desired frequency.

For imaging and magnetic manipulation experiments in Magnetic Particle Imaging several field generating coils are required to produce sufficiently high and flexible magnetic fields. To minimize the power consumption, coils with iron cores are the best choice for low and medium frequency ranges. Such coils have comparatively high reactance and are often inductively coupled. The trivial approach to ensure target currents is to provide each coil with a current controlled source resulting in high system complexity and high costs. This paper presents a circuit design to distribute bipolar target currents from a single unipolar source with high accuracy, reducing unwanted coil coupling by a feedback controller. Thus, the number of current sources can be significantly reduced. With a regenerative concept, reactive power is stored and can be reused, allowing efficient and fast current switching., Bundesministerium für Bildung und Forschung (BMBF)

It 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., Bundesministerium für Bildung und Forschung (BMBF)

Non-sinusoidal excitation waveforms have the ability to improve the signal-to-noise ratio and image resolution under certain conditions. Yet, the ability to use phase information for spatial encoding is expected to diminish as sharp pulses lead to concurrent signal response due to steep slopes and therefore less phase information. This motivates investigations into alternate sampling approaches that mitigate a loss in spatial encoding. However, measurements and image reconstruction results indicate that 10 times faster slew rates compared to sine excitation lead to enough phase information to resolve basic features using system matrix reconstruction.

Magnetic Particle Imaging (MPI) is a tracer based medical imaging modality with great potential due to its high sensi-tivity, 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.

In 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.

Magnetic particle imaging is capable of determining very small concentrations of particles if only a single concentra-tion is present in the field-of-view. Meanwhile the determination of particles with widely differing concentrations is still challenging. In a recent work, we introduced a two-step reconstruction method that tackles this problem by isolating the signal of the lower concentrated tracer for a separate reconstruction. In this work, we adapt the two-step reconstruction method in order to apply a joint reconstruction to the entire signal of all particle concentrations. This is achieved by spatially adaptive Tikhonov regularization.

For the utilization of the magnetic field of rotating Halbach cylinders in MPI scanners, a rotation unit is required which houses the used permanent magnets and allows their rotation. The setup proposed here allows the concentric arrangement and individual rotation of four Halbach cylinders, whose purely mechanic agitation allows the movement of the field-free region through the field of view. Based on the requirements for such a rotation system, basic design approaches are presented and compared. Initial strength calculations and further simulations were performed on the resulting constructive concept, which, upon implementation, forms the basis for almost purely mechanical MPI scanners.

A recent work introduced a balloon catheter from a polymer mixed with magnetic nanoparticles that was visible in magnetic particle imaging (MPI) in initial trials. In this work, dynamic multi-patch and multi-contrast experiments were performed to validate the applicability of the balloon catheter for complex application scenarios in MPI. In both cases, the balloon was successfully imaged, although there are limitations in resolution and dynamic imaging range.

Magnetic Particle Imaging (MPI) achieves a high temporal resolution, which opens up a wide range of real-time medical applications such as device tracking and navigation. These applications usually rely on automated techniques for finding and localizing devices and fiducial markers in medical images. In this work, we show that submillimeter-accurate automatic marker localization from low gradient MPI tomograms with a spatial resolution of several millimeters is possible. Markers are initially identified within the tomograms by a thresholding-based segmentation algorithm. Subsequently, their positions are accurately determined by calculating the center of mass of the gray values inside the pre-segmented regions. A series of phantom measurements taken at full temporal resolution (46 Hz) is used to analyze statistical and systematical errors and to discuss the performance and stability of the automatic submillimeter-accurate marker localization algorithm.

Magnetic particle imaging is a very useful tool in the detection of stroke. To study the ability of stroke in a mouse model the data acquisition is challenging as a mouse brain contains only a very small ratio of blood compared to large animals or humans. The effective concentration within the whole organ is therefore very small, especially compared to the heart or the liver. Typical MPI receiver coils however cover a sensitive region of around 30 mm to 50 mm and have a bore size of above 40 mm. This leads on the one hand to non-optimal signal coupling due to the distance to the particles and on the other hand strong signals from the heart can cause artifacts in the low signal regions. In this work we present a coil optimized for mouse brain imaging, which due to its small size, also dampens signal from regions outside of the coil.

Although Magnetic Particle Imaging (MPI) is not yet in clinical use, it is highly promising for several medical ap-plications, and especially for applications in diagnostic vascular in vivo imaging and imaging-guided vascular interventions. Furthermore, in the last years, different superparamagnetic iron oxide (SPIO) based contrast agents have been developed and approved for niche clinical applications in Magnetic Resonance Imaging (MRI) as alterna-tive to Gadolinium-based contrast agents (GBCAs) due to the risk for patients suffering from kidney dysfunction or nephrogenic systemic fibrosis (NSF). Recently, the potential of RBCs loaded with different SPIO nanoparticles as blood-pool tracer agents with longer blood retention time for MRI and MPI has been investigated. Here, we report the first in vitro results with the highly efficient dextran-based MPI tracer particles perimag® and synomag®-D to study their eligibility to be encapsulated into human RBCs and the potential of these new SPIO-RBC constructs as tracer material for MPI.

Magnetic Particle Imaging (MPI) is used to visualize the distribution of superparamagnetic nanoparticles within 3D volumes with high sensitivity in real time. Recently, MPI is utilized to navigate micron-sized particles and micron-sized swimmers, since the magnetic field topology of the MPI scanner is well suited to apply magnetic forces. In this work, we analyze the magnetic mobility and imaging performance of nanomag/synomag-D for Magnetic Particle Imaging/Navigation (MPIN). With MPIN the focus fields are constantly switching between imaging and magnetic force mode, thus enabling quasi-simultaneous navigation and imaging of particles. In flow bifurcation experiment with a 100 % stenosis on one branch, we determine the limiting flow velocity of 1.36 mL/s, which allows all particles to flow only through one branch towards the stenosis. During this experiment, we image the accumulation of the particles within the stenosis. In combination with therapeutic substances, this approach has high potential for targeted drug delivery., Deutsche Forschungsgemeinschaft (DFG), Bundesministerium für Bildung und Forschung (BMBF)