Jürgen Weizenecker

Tomographic imaging using the nonlinear response of magnetic particles

The use of contrast agents and tracers in medical imaging has a long history. They provide important information for diagnosis and therapy, but for some desired applications, a higher resolution is required than can be obtained using the currently available medical imaging techniques. Consider, for example, the use of magnetic tracers in magnetic resonance imaging: detection thresholds for in vitro and in vivo imaging are such that the background signal from the host tissue is a crucial limiting factor. A sensitive method for detecting the magnetic particles directly is to measure their magnetic fields using relaxometry; but this approach has the drawback that the inverse problem (associated with transforming the data into a spatial image) is ill posed and therefore yields low spatial resolution. Here we present a method for obtaining a high-resolution image of such tracers that takes advantage of the nonlinear magnetization curve of small magnetic particles. Initial ‘phantom’ experiments are reported that demonstrate the feasibility of the imaging method. The resolution that we achieve is already well below 1 mm. We evaluate the prospects for further improvement, and show that the method has the potential to be developed into an imaging method characterized by both high spatial resolution as well as high sensitivity.

Three-dimensional real-time in vivo magnetic particle imaging

Magnetic particle imaging (MPI) is a new tomographic imaging method potentially capable of rapid 3D dynamic imaging of magnetic tracer materials. Until now, only dynamic 2D phantom experiments with high tracer concentrations have been demonstrated. In this letter, first in vivo 3D real-time MPI scans are presented revealing details of a beating mouse heart using a clinically approved concentration of a commercially available MRI contrast agent. A temporal resolution of 21.5 ms is achieved at a 3D field of view of 20.4 x 12 x 16.8 mm(3) with a spatial resolution sufficient to resolve all heart chambers. With these abilities, MPI has taken a huge step toward medical application.

Magnetization response spectroscopy of superparamagnetic nanoparticles for magnetic particle imaging

Magnetic particle imaging (MPI) is a tomographic imaging modality sensitive to the spatial distribution of magnetic particles. The spectrometer, described in this paper, is capable of measuring the remagnetization spectrum of superparamagnetic nanoparticles. With this spectrometer the suitability of particles, for MPI, can be characterized. Furthermore, the spectrometer can be used to estimate the particle size distribution, which allows for more accurate simulations in MPI.

Experimental results on fast 2D-encoded magnetic particle imaging

This paper presents the first experimental results on magnetic particle imaging with full 2D encoding. The encoding speed achieved was 3.88 ms for a field of view of 1x1 cm2. Small phantoms composed of several dots each filled with 200 nl undiluted Resovist (500 mmol(Fe) l(-1)) were scanned. A resolution of better than 1 mm was achieved for a frame rate of 25 frames s(-1).

Trajectory analysis for magnetic particle imaging

Recently a new imaging technique called magnetic particle imaging was proposed. The method uses the nonlinear response of magnetic nanoparticles when a time varying magnetic field is applied. Spatial encoding is achieved by moving a field-free point through an object of interest while the field strength in the vicinity of the point is high. A resolution in the submillimeter range is provided even for fast data acquisition sequences. In this paper, a simulation study is performed on different trajectories moving the field-free point through the field of view. The purpose is to provide mandatory information for the design of a magnetic particle imaging scanner. Trajectories are compared with respect to density, speed and image quality when applied in data acquisition. Since simulation of the involved physics is a time demanding task, moreover, an efficient implementation is presented utilizing caching techniques.

Model-Based Reconstruction for Magnetic Particle Imaging

Magnetic particle imaging (MPI) is a new imaging modality capable of imaging distributions of superparamagnetic nanoparticles with high sensitivity, high spatial resolution and, in particular, high imaging speed. The image reconstruction process requires a system function, describing the mapping between particle distribution and acquired signal. To date, the system function is acquired in a tedious calibration procedure by sequentially measuring the signal of a delta sample at the positions of a grid that covers the field of view. In this work, for the first time, the system function is calculated using a model of the signal chain. The modeled system function allows for reconstruction of the particle distribution in a 1-D MPI experiment. The approach thus enables fast generation of system functions on arbitrarily dense grids. Furthermore, reduction in memory requirements may be feasible by generating parts of the system function on the fly during reconstruction instead of keeping the complete matrix in memory.

Weighted iterative reconstruction for magnetic particle imaging

Magnetic particle imaging (MPI) is a new imaging technique capable of imaging the distribution of superparamagnetic particles at high spatial and temporal resolution. For the reconstruction of the particle distribution, a system of linear equations has to be solved. The mathematical solution to this linear system can be obtained using a least-squares approach. In this paper, it is shown that the quality of the least-squares solution can be improved by incorporating a weighting matrix using the reciprocal of the matrix-row energy as weights. A further benefit of this weighting is that iterative algorithms, such as the conjugate gradient method, converge rapidly yielding the same image quality as obtained by singular value decomposition in only a few iterations. Thus, the weighting strategy in combination with the conjugate gradient method improves the image quality and substantially shortens the reconstruction time. The performance of weighting strategy and reconstruction algorithms is assessed with experimental data of a 2D MPI scanner.

Analysis of a 3-D System Function Measured for Magnetic Particle Imaging

Magnetic particle imaging (MPI) is a new tomographic imaging approach that can quantitatively map magnetic nanoparticle distributions in vivo. It is capable of volumetric real-time imaging at particle concentrations low enough to enable clinical applications. For image reconstruction in 3-D MPI, a system function (SF) is used, which describes the relation between the acquired MPI signal and the spatial origin of the signal. The SF depends on the instrumental configuration, the applied field sequence, and the magnetic particle characteristics. Its properties reflect the quality of the spatial encoding process. This work presents a detailed analysis of a measured SF to give experimental evidence that 3-D MPI encodes information using a set of 3-D spatial patterns or basis functions that is stored in the SF. This resembles filling 3-D k-space in magnetic resonance imaging, but is faster since all information is gathered simultaneously over a broad acquisition bandwidth. A frequency domain analysis shows that the finest structures that can be encoded with the presented SF are as small as 0.6 mm. SF simulations are performed to demonstrate that larger particle cores extend the set of basis functions towards higher resolution and that the experimentally observed spatial patterns require the existence of particles with core sizes of about 30 nm in the calibration sample. A simple formula is presented that qualitatively describes the basis functions to be expected at a certain frequency.

2D model‐based reconstruction for magnetic particle imaging

PURPOSE Magnetic particle imaging (MPI) is a new quantitative imaging technique capable of determining the spatial distribution of superparamagnetic nanoparticles at high temporal and spatial resolution. For reconstructing this spatial distribution, the particle dynamics and the scanner properties have to be known. To date, they are obtained in a tedious calibration procedure by measuring the magnetization response of a small delta sample shifted through the measuring field. Recently, first reconstruction results using a 1D model-based system function were published, showing comparable image quality as obtained with a measured system function. In this work, first 2D model-based reconstruction results of measured MPI data are presented. METHODS To simulate the system function, various parameters have to be modeled, namely, the magnetic field, the particle magnetization, the voltage induced in the receive coils, and the transfer function of the receive chain. To study the accuracy of the model-based approach, 2D MPI data are measured and reconstructed with modeled and measured system functions. RESULTS It is found that the model-based system function is sufficiently accurate to allow for reconstructing experimental data. The resulting image quality is close to that obtained with a measurement-based reconstruction. CONCLUSIONS The model-based system function approach addresses a major drawback of the measurement-based procedure, namely, the long acquisition time. In this work, the acquisition of the measurement-based system function took 45 min, while the model-based system function was obtained in only 15 s. For 3D data, where the acquisition of the measurement-based system function takes more than 6 h, the need for an efficient system function generation is even more obvious.

Fundamentals and applications of magnetic particle imaging

Magnetic particle imaging (MPI) is a new medical imaging technique which performs a direct measurement of magnetic nanoparticles, also known as superparamagnetic iron oxide. MPI can acquire quantitative images of the local distribution of the magnetic material with high spatial and temporal resolution. Its sensitivity is well above that of other methods used for the detection and quantification of magnetic materials, for example, magnetic resonance imaging. On the basis of an intravenous injection of magnetic particles, MPI has the potential to play an important role in medical application areas such as cardiovascular, oncology, and also in exploratory fields such as cell labeling and tracking. Here, we present an introduction to the basic function principle of MPI, together with an estimation of the spatial resolution and the detection limit. Furthermore, the above-mentioned medical applications are discussed with respect to an applicability of MPI.