Nadine Gdaniec

Joint reconstruction of non-overlapping magnetic particle imaging focus-field data.

The focus field is a key component to enable clinical applications in magnetic particle imaging (MPI). Due to physiological constraints, the method of choice is to place the focus of a small acquisition volume at various static positions in space and acquire the full field-of-view using a multi-station approach. In the first experiments, overlapping drive-field patches were used and boundary artifacts between drive-field patches were reduced using image processing. In this work we show that artifact-free reconstruction of non-overlapping focus-field data is feasible by using a joint reconstruction algorithm. This enables maximum scanning efficiency in multi-station focus-field experiments, which is key for reaching sufficiently short acquisition times to image the human heart.

Krylov-space approach to the equilibrium and nonequilibrium single-particle Green’s function

The zero-temperature single-particle Greens function of correlated fermion models with moderately large Hilbert-space dimensions can be calculated by means of Krylov-space techniques. The conventional Lanczos approach consists of finding the ground state in a first step, followed by an approximation for the resolvent of the Hamiltonian in a second step. We analyze the character of this approximation and discuss a numerically exact variant of the Lanczos method which is formulated in the time domain. This method is extended to obtain the nonequilibrium single-particle Greens function defined on the Keldysh-Matsubara contour in the complex time plane which describes the systems nonperturbative response to a sudden parameter switch in the Hamiltonian. The proposed method will be important as an exact-diagonalization solver in the context of self-consistent or variational cluster-embedding schemes. For the recently developed nonequilibrium cluster-perturbation theory, we discuss its efficient implementation and demonstrate the feasibility of the Krylov-based solver. The dissipation of a strong local magnetic excitation into a non-interacting bath is considered as an example for applications.

Magnetic particle imaging: from proof of principle to preclinical applications

Tomographic imaging has become a mandatory tool for the diagnosis of a majority of diseases in clinical routine. Since each method has its pros and cons, a variety of them is regularly used in clinics to satisfy all application needs. Magnetic particle imaging (MPI) is a relatively new tomographic imaging technique that images magnetic nanoparticles with a high spatiotemporal resolution in a quantitative way, and in turn is highly suited for vascular and targeted imaging. MPI was introduced in 2005 and now enters the preclinical research phase, where medical researchers get access to this new technology and exploit its potential under physiological conditions. Within this paper, we review the development of MPI since its introduction in 2005. Besides an in-depth description of the basic principles, we provide detailed discussions on imaging sequences, reconstruction algorithms, scanner instrumentation and potential medical applications.

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.

First experimental comparison between the Cartesian and the Lissajous trajectory for magnetic particle imaging

Magnetic particle imaging (MPI) is a quantitative imaging modality that allows us to determine the distribution of superparamagnetic nanoparticles. Sampling is achieved by moving a field-free point (FFP) along a specific trajectory through the volume of interest. The magnetic material that lies along the path or in the close vicinity of the FFP changes its magnetization and induces a voltage in the surrounding receiver coils. Various trajectories for the FFP are conceivable, but most experimental MPI scanners either use a Cartesian or a Lissajous sampling trajectory. For the first time, this study compares both sampling methods experimentally using an MPI scanner that allows us to implement both sampling patterns. By default, the scanner is capable of scanning 2D and 3D field of views using a Lissajous trajectory. But since it also has a 1D mode, it is possible to perform Cartesian measurements by shifting the 1D scan line in a perpendicular direction to the FFP movement using the focus field. These line scans are jointly reconstructed to obtain a 2D image. In a further step, the unidirectional Cartesian trajectory is improved by interchanging the excitation and the focus-field direction leading to a bidirectional Cartesian trajectory. Our findings reveal similar results for the bidirectional Cartesian and Lissajous trajectory concerning the overall image quality and sensitivity. In a more detailed view, the bidirectional Cartesian trajectory achieves a slightly higher spatial center resolution, whereas the Lissajous trajectory is more efficient regarding the temporal resolution since less acquisition time is needed to reach an adequate image quality.

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.

Detection and Compensation of Periodic Motion in Magnetic Particle Imaging

The temporal resolution of the tomographic imaging method magnetic particle imaging (MPI) is remarkably high. The spatial resolution is degraded for measured voltage signal with low signal-to-noise ratio, because the regularization in the image reconstruction step needs to be increased for system-matrix approaches and for deconvolution steps in

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

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Magnetic-Particle-Imaging mit mehreren Gradientenstärken

-space approaches. To improve the signal-to-noise ratio, blockwise averaging of the signal over time can be advantageous. However, since block-wise averaging decreases the temporal resolution, it prevents resolving the motion. In this paper, a framework for averaging motion-corrupted MPI raw data is proposed. The motion is considered to be periodic as it is the case for respiration and/or the heartbeat. The same state of motion is thus reached repeatedly in a time series exceeding the repetition time of the motion and can be used for averaging. As the motion process and the acquisition process are, in general, not synchronized, averaging of the captured MPI raw data corresponding to the same state of motion requires to shift the starting point of the individual frames. For high-frequency motion, a higher frame rate is potentially required. To address this issue, a binning method for using only parts of complete frames from a motion cycle is proposed that further reduces the motion artifacts in the final images. The frequency of motion is derived directly from the MPI raw data signal without the need to capture an additional navigator signal. Using a motion phantom, it is shown that the proposed method is capable of averaging experimental data with reduced motion artifacts. The methods are further validated on in-vivo data from mouse experiments to compensate the heartbeat.

Abstract: Erweiterung des Bildgebungsbereiches bei der Magnetpartikelbildgebung durch externe axiale Verschiebungen.

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.