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.

Cerebral aneurysms are potentially life threatening and nowadays treated by a catheter-guided coiling or by a neurosurgical clipping intervention. Here, we propose a helically shaped magnetic micro-robot, which can be steered by magnetic fields in an untethered manner and could be applied for a novel coiling procedure. This is shown by navigating the micro-robot through an additively manufactured phantom of a human cerebral aneurysm. The magnetic fields are applied with a magnetic particle imaging (MPI) scanner, which allows for the navigation and tomographic visualization by the same machine. With MPI the actuation process can be visualized with a localization accuracy of 0.68 mm and an angiogram can be acquired both without any radiation exposure. First in-vitro phantom experiments are presented, showing an idea of a robot conducted treatment of cerebral aneurysms.

Magnetic Particle Imaging is a new medical imaging modality, which detects superparamagnetic iron oxide nanoparticles. The particles are excited by magnetic fields. Most scanners have a tube-like measurement field and therefore, both the field of view and the object size are limited. A single-sided scanner has the advantage that the object is not limited in size, only the penetration depth is limited. A single-sided scanner prototype for 1D imaging has been presented in 2009. Simulations have been published for a 2D single-sided scanner and first 1D measurements have been carried out. In this paper, the first 2D single-sided scanner prototype is presented and the first calibration-based reconstruction results of measured 2D phantoms are shown. The field free point is moved on a Lissajous trajectory inside a 30 ×30 mm ² area. Images of phantoms with a maximal distance of 10 mm perpendicular to the scanner surface have been reconstructed. Different cylindrically shaped holes of phantoms have been filled with 6.28 μl undiluted Resovist. After the measurement and image reconstruction of the phantoms, particle volumes could be distinguished with a distance of 2 mm and 6 mm in vertical and horizontal direction, respectively.

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.