Patryk Szwargulski

Increasing the sensitivity for stem cell monitoring in system-function based magnetic particle imaging

The use of superparamagnetic iron oxide nanoparticles (SPIONs) has provided new possibilities in biophysics and biomedical imaging technologies. The magnetization dynamics of SPIONs, which can be influenced by the environment, are of central interest. In this work, different biological SPION environments are used to investigate three different calibration methods for stem cell monitoring in magnetic particle imaging. It is shown that calibrating using SPIONs immobilized via agarose gel or intracellular uptake results in superior stem cell image quality compared to mobile SPIONs in saline. This superior image quality enables more sensitive localization and identification of a significantly smaller number of magnetically labeled stem cells. The results are important for cell tracking and monitoring of future SPION based therapies such as hyperthermia based cancer therapies, targeted drug delivery, or tissue regeneration approaches where it is crucial to image a sufficiently small number of SPIONs interacting with biological matter.

Towards Picogram Detection of Superparamagnetic Iron-Oxide Particles Using a Gradiometric Receive Coil

Superparamagnetic iron-oxide nanoparticles can be used in medical applications like vascular or targeted imaging. Magnetic particle imaging (MPI) is a promising tomographic imaging technique that allows visualizing the 3D nanoparticle distribution concentration in a non-invasive manner. The two main strengths of MPI are high temporal resolution and high sensitivity. While the first has been proven in the assessment of dynamic processes like cardiac imaging, it is unknown how far the detection limit of MPI can be lowered. Within this work, we will present a highly sensitive gradiometric receive-coil unit combined with a noise-matching network tailored for the imaging of mice. The setup is capable of detecting 5 ng of iron in-vitro with an acquisition time of 2.14 sec. In terms of iron concentration we are able to detect 156 μg/L marking the lowest value that has been reported for an MPI scanner so far. In-vivo MPI mouse images of a 512 ng bolus and a 21.5 ms acquisition time allow for capturing the flow of an intravenously injected tracer through the heart of a mouse. Since it has been rather difficult to compare detection limits across MPI publications we propose guidelines to improve the comparability of future MPI studies.

Using data redundancy gained by patch overlaps to reduce truncation artifacts in magnetic particle imaging.

The imaging technology magnetic particle imaging allows the detection of magnetic material, in particular superparamagnetic nanoparticles, by remagnetization of the material via magnetic fields. The application is aimed at medical imaging where the particles are applied as tracer directly into the blood stream. Medical safety considerations such as peripheral nerve stimulation limit the maximal amplitude of the magnetic fields and in turn the field of view size. To handle this constraint the concept of patches was introduced, which allows a shift of a field of view to different positions in order to enlarge the imaging area. If this is done statically an overlap of patches can be used to reduce truncation artifacts occurring at the adjacent edges. In this contribution, a differentiation of two different kinds of patch overlaps, i.e. a trajectory and a system matrix overlap, is made. Further, different concepts to combine the resulting redundant information are investigated with respect to the reduction of truncation artifacts. The methods are analyzed in detail in a simulation study and validated on experimental data.

Non-Equispaced System Matrix Acquisition for Magnetic Particle Imaging Based on Lissajous Node Points

Magnetic Particle Imaging (MPI) is an emerging technology in the field of (pre)clinical imaging. The acquisition of a particle signal is realized along specific sampling trajectories covering a defined field of view (FOV). In a system matrix (SM) based reconstruction procedure, the commonly used acquisition path in MPI is a Lissajous trajectory. Such a trajectory features an inhomogeneous coverage of the FOV, i.e. the center region is sampled less dense than the regions towards the edges of the FOV. Conventionally, the respective SM acquisition and the subsequent reconstruction do not reflect this inhomogeneous coverage. Instead, they are performed on an equispaced grid. The objective of this work is to introduce a sampling grid that inherently features the aforementioned inhomogeneity by using node points of Lissajous trajectories. Paired with a tailored polynomial interpolation of the reconstructed MPI signal, the entire image can be recovered. It is the first time that such a trajectory related non-equispaced grid is used for image reconstruction on simulated and measured MPI data and it is shown that the number of sampling positions can be reduced, while the spatial resolution remains constant.

Magnetic Particle Imaging for Real-Time Perfusion Imaging in Acute Stroke

The fast and accurate assessment of cerebral perfusion is fundamental for the diagnosis and successful treatment of stroke patients. Magnetic particle imaging (MPI) is a new radiation-free tomographic imaging method with a superior temporal resolution, compared to other conventional imaging methods. In addition, MPI scanners can be built as prehospital mobile devices, which require less complex infrastructure than computed tomography (CT) and magnetic resonance imaging (MRI). With these advantages, MPI could accelerate the stroke diagnosis and treatment, thereby improving outcomes. Our objective was to investigate the capabilities of MPI to detect perfusion deficits in a murine model of ischemic stroke. Cerebral ischemia was induced by inserting of a microfilament in the internal carotid artery in C57BL/6 mice, thereby blocking the blood flow into the medial cerebral artery. After the injection of a contrast agent (superparamagnetic iron oxide nanoparticles) specifically tailored for MPI, cerebral perfusion and vascular anatomy were assessed by the MPI scanner within seconds. To validate and compare our MPI data, we performed perfusion imaging with a small animal MRI scanner. MPI detected the perfusion deficits in the ischemic brain, which were comparable to those with MRI but in real-time. For the first time, we showed that MPI could be used as a diagnostic tool for relevant diseases in vivo, such as an ischemic stroke. Due to its shorter image acquisition times and increased temporal resolution compared to that of MRI or CT, we expect that MPI offers the potential to improve stroke imaging and treatment.

Hybrid system calibration for multidimensional magnetic particle imaging

Magnetic particle imaging visualizes the spatial distribution of superparamagnetic nanoparticles. Because of its key features of excellent sensitivity, high temporal and spatial resolution and biocompatibility of the tracer material it can be used in multiple medical imaging applications. The common reconstruction technique for Lissajous-type trajectories uses a system matrix that has to be previously acquired in a time-consuming calibration scan, leading to long downtimes of the scanning device. In this work, the system matrix is determined by a hybrid approach. Using the hybrid system matrix for reconstruction, the calibration downtime of the scanning device can be neglected. Furthermore, the signal to noise ratio of the hybrid system matrix is much higher, since the size of the required nanoparticle sample can be chosen independently of the desired voxel size. As the signal to noise ratio influences the reconstruction process, the resulting images have better resolution and are less affected by artefacts. Additionally, a new approach is introduced to address the background signal in image reconstruction. The common technique of subtraction of the background signal is replaced by extending the system matrix with an entry that represents the background. It is shown that this approach reduces artefacts in the reconstructed images.

Trajectory Analysis Using Static Patches for Magnetic Particle Imaging

Magnetic particle imaging (MPI) is an imaging technique based on the determination of magnetic material by moving a field-free point along specified trajectories, which are used to sample the field of view. Due to technical and safety reasons, the field of view is limited in size. To enlarge the size of the field of view, trajectory patches are used, which are sampled separately and combined consecutively to an entire field of view. The aim of this paper is to analyze the effect of different trajectories combined with the patch approach. In addition, an empiric study is performed to analyze the influence of overlapped patches on each trajectory combined with cutoff as postprocessing method. As a follow-up, a new patch formation of the radial trajectory based on a phase shift between each of the patches is introduced. Finally, it can be shown that the Lissajous trajectory, which is commonly used for MPI, provides appropriate results. However, the results of overlapped patches with a circular trajectory increase spatial resolution.

Fast multiresolution data acquisition for magnetic particle imaging using adaptive feature detection

Purpose: Magnetic particle imaging is a tomographic imaging modality capable of determining the distribution of magnetic nanoparticles with high temporal resolution. The spatial resolution of magnetic particle imaging is influenced by the gradient strength of the selection field used for spatial encoding. By increasing the gradient strength, the spatial resolution is improved, but at the same time the imaging volume decreases. For a high‐resolution image of an extended field‐of‐view, a multipatch approach can be used by shifting the sampling trajectory in space. As the total imaging timescales with the number of patches, the downside of the multipatch method is the degradation of the temporal resolution. Methods: The purpose of this work was to develop a scanning procedure incorporating the advantages of imaging at multiple gradient strengths. A low‐resolution overview scan is performed at the beginning followed by a small number of high‐resolution scans at adaptively detected locations extracted from the low‐resolution scan. Results: By combining all data during image reconstruction, it is possible to obtain a large field‐of‐view image of anisotropic spatial resolution. It is measured in a fraction of time compared to a fully sampled high‐resolution field of view image. Conclusions: Magnetic particle imaging is a flexible imaging method allowing to rapidly scan small volumes. When scaling magnetic particle imaging from small animal to human applications, it will be essential to keep the acquisition time low while still capturing larger volumes at high resolution. With our proposed adaptive multigradient imaging sequence, it is possible to capture a large field of view while keeping both the temporal and the spatial resolution high.

Enlarging the field of view in magnetic particle imaging using a moving table approach

Magnetic Particle Imaging (MPI) is a highly sensitive imaging modality, which allows the visualization of magnetic tracer materials with a temporal resolution of more than 40 volumes per second. In MPI the size of the field of view scales with the strength of the applied magnetic fields. In clinical applications this strength is limited by peripheral nerve stimulation and specific absorption rates. Therefore, the size of the field of view is usually no larger than a few cubic centimeters. To bypass this limitation additional focus fields and/or a external object movements can be applied. In this work we investigate the later approach, where an object is moved through the scanner bore one step at a time, while the MPI scanner continuously acquires data from its static field of view. Using 3D phantom and 3D+t in-vivo data it is shown that the data can be jointly reconstructed after reordering the data with respect to the stepwise object shifts and heart beat phases.

Abstract: Patches in Magnetic Particle Imaging

Magnetic Particle Imaging (MPI) is a tracer-based imaging technology [1] with which superparamagnetic nanoparticles can be detected and located using specific magnetic fields. The selection field, a gradient field in form of a field free point (FFP), restricts the area in which particles can be remagnetized. The drive field, a homogeneous and time-varying magnetic field, remagnetizes the particles and moves the FFP. As a result a time dependent signal can be measured and then reconstructed to the actual spatial distribution of the tracer.