Detection and Compensation of Periodic Motion in Magnetic Particle Imaging

Weighted sum of harmonic signals for direct imaging in magnetic particle imaging

Objective.Magnetic particle imaging (MPI) is a novel radiation-free medical imaging modality that can directly image superparamagnetic iron oxide tracers (SPIOs) with high sensitivity, temporal resolution, and good spatial resolution. The MPI reconstruction task can be formulated mathematically as a Fredholm integral problem, but the concrete inversion is not easily possible because of the particle dynamics or scanner issues. Measurement based system matrix inversion takes these factors into account, but prior measurement and calibration are time consuming.Approach.We proposed a direct imaging method based on the weighted sum of harmonic signals. The harmonic signals with spatial information are obtained by the short-time Fourier transform, and odd harmonic components are selected for recombination and then mapped to the sampling trajectory to image the concentration distribution of SPIOs. In addition, we adopt a normalized-weighted sum of harmonics to improve the resolution of the native image.Main results.The effectiveness of the proposed method is verified by simulation imaging experiments and our in-house scanner-based experiments. Quantitative evaluation results show that compared with traditional methods, the structural similarity improved by 48%, mean square error decreased by 88%, and signal-to-artifact ratio increased by 2.5 times.Significance.The proposed method can rapidly image the concentration distribution of nanoparticles without any prior calibration measurements and reduce the blur of MPI images without deconvolution, which has the potential to be implemented as a multi-patch imaging method in MPI.

Motion compensation for non-periodic dynamic tracer distributions in multi-patch magnetic particle imaging

Objective. While the spatial and temporal resolution of magnetic particle imaging is very high, the size of the field of view is limited due to physiological constraints. Multi-patch scans allow for covering larger areas by sequentially scanning smaller subvolumes, so-called patches. The visualization of tracer dynamics with a high temporal resolution are of particular interest in many applications, e.g. cardiovascular interventions or blood flow measurements. The reconstruction of non-periodic dynamic tracer distributions is currently realized by the reconstruction of a time-series of frames under the assumption of nearly static behavior during the scan of each frame. While this approach is feasible for limited velocities, it results in data gaps in multi-patch scans leading thus to artifacts for strong dynamics. In this article, we are aiming for the reconstruction of dynamic tracer concentrations with high velocities and the compensation of motion and multi-patch artifacts. Approach. We present a reconstruction method for dynamic tracer distributions using a dynamic forward model and representing the concentration within each voxel by a spline curve. The method is evaluated with simulated single- and multi-patch data. Main results. The dynamic model enables for the reconstruction of fast tracer dynamics from few frames and the spline approach approximates the missing data which reduces multi-patch artifacts. Significance. The presented method allows to compensate motion and multi-patch artifacts and to reconstruct fast dynamic tracer distributions with arbitrary motion patterns.

Suppression of Motion Artifacts Caused by Temporally Recurring Tracer Distributions in Multi-Patch Magnetic Particle Imaging

Magnetic particle imaging is a tracer based imaging technique to determine the spatial distribution of superparamagnetic iron oxide nanoparticles with a high spatial and temporal resolution. Due to physiological constraints, the imaging volume is restricted in size and larger volumes are covered by shifting object and imaging volume relative to each other. This results in reduced temporal resolution, which can lead to motion artifacts when imaging dynamic tracer distributions. A common source of such dynamic distributions are cardiac and respiratory motion in in-vivo experiments, which are in good approximation periodic. We present a raw data processing technique that combines data snippets into virtual frames corresponding to a specific state of the dynamic motion. The technique is evaluated on the basis of measurement data obtained from a rotational phantom at two different rotational frequencies. These frequencies are determined from the raw data without reconstruction and without an additional navigator signal. The reconstructed images give reasonable representations of the rotational phantom frozen in several different states of motion while motion artifacts are suppressed.

Moving table magnetic particle imaging: a stepwise approach preserving high spatio-temporal resolution

Magnetic particle imaging (MPI) is a highly sensitive imaging method that enables the visualization of magnetic tracer materials with a temporal resolution of more than 46 volumes per second. In MPI, the size of the field of view (FoV) scales with the strengths of the applied magnetic fields. In clinical applications, those strengths are limited by peripheral nerve stimulation, specific absorption rates, and the requirement to acquire images of high spatial resolution. Therefore, the size of the FoV is usually a few cubic centimeters. To bypass this limitation, additional focus fields and/or external object movements can be applied. The latter approach is investigated. An object is moved through the scanner bore one step at a time, whereas the MPI scanner continuously acquires data from its static FoV. Using a 3-D phantom and dynamic 3-D in vivo data, it is shown that the data from such a moving table experiment can be jointly reconstructed after reordering the data with respect to the stepwise object shifts and heart beat phases.

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.