Imaging with Optimized Magnetite MPI Tracers

Magnetic particle imaging (MPI) is a tracer-based tomographic imaging technique utilized in applications such as lung perfusion imaging, cancer diagnosis, stem cell tracking, etc. The goal of translating MPI to clinical use has prompted studies on further improving the spatial-temporal resolutions of MPI through various methods, including image reconstruction algorithm, scanning trajectory design, magnetic field profile design, and tracer design. Iron oxide magnetic nanoparticles (MNPs) are favored for MPI and magnetic resonance imaging (MRI) over other materials due to their high biocompatibility, low cost, and ease of preparation and surface modification. For core–shell MNPs, the tracers’ magnetic core size and non-magnetic coating layer characteristics can significantly affect MPI signals through dynamic magnetization relaxations. Most works to date have assumed an ensemble of MNP tracers with identical sizes, ignoring that artificially synthesized MNPs typically follow a log-normal size distribution, which can deviate theoretical results from experimental data. In this work, we first characterize the size distributions of four commercially available iron oxide MNP products and then model the collective magnetic responses of these MNPs for MPI applications. For an ensemble of MNP tracers with size standard deviations of σ, we applied a stochastic Langevin model to study the effect of size distribution on MPI imaging performance. Under an alternating magnetic field (AMF), i.e., the excitation field in MPI, we collected the time domain dynamic magnetizations (M-t curves), magnetization-field hysteresis loops (M-H curves), point-spread functions (PSFs), and higher harmonics from these MNP tracers. The intrinsic MPI spatial resolution, which is related to the full width at half maximum (FWHM) of the PSF profile, along with the higher harmonics, serve as metrics to provide insights into how the size distribution of MNP tracers affects MPI performance.

We studied the magnetic resonance imaging liver contrast agent Resovist by a variety of magnetic measurement techniques, in order to understand the physical mechanism of their high magnetic particle imaging (MPI) performance, with a focus on the size-dependent contributions to the MPI signal. To this end, we used asymmetric flow field-flow fractionation to separate Resovist into a set of fractions with defined hydrodynamic diameters. The individual fractions were magnetically characterized by static magnetization and magnetorelaxometry measurements to obtain the corresponding effective magnetic anisotropy and effective size distribution parameters. In addition, the MPI performance of each fraction was assessed by magnetic particle spectroscopy. We observed an MPI signal gain of about 100% with respect to their iron amount for the best fraction. Relating these finding to the results from magnetic characterization provides more insight into the mechanisms of MPI performance of Resovist. This knowledge may help to improve the design of novel MPI tracers.

Superparamagnetic iron oxides as MPI tracers: A primer and review of early applications.

Recent advancements in medical imaging have brought forth various techniques such as magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), and ultrasound, each contributing to improved diagnostic capabilities. Most recently, magnetic particle imaging (MPI) has become a rapidly advancing imaging modality with profound implications for medical diagnostics and therapeutics. By directly detecting the magnetization response of magnetic tracers, MPI surpasses conventional imaging modalities in sensitivity and quantifiability, particularly in stem cell tracking applications. Herein, this comprehensive review explores the fundamental principles, instrumentation, magnetic nanoparticle tracer design, and applications of MPI, offering insights into recent advancements and future directions. Novel tracer designs, such as zinc-doped iron oxide nanoparticles (Zn-IONPs), exhibit enhanced performance, broadening MPI's utility. Spatial encoding strategies, scanning trajectories, and instrumentation innovations are elucidated, illuminating the technical underpinnings of MPI's evolution. Moreover, integrating machine learning and deep learning methods enhances MPI's image processing capabilities, paving the way for more efficient segmentation, quantification, and reconstruction. The potential of superferromagnetic iron oxide nanoparticle chains (SFMIOs) as new MPI tracers further advanced the imaging quality and expanded clinical applications, underscoring the promising future of this emerging imaging modality.

BackgroundIron oxide nanoparticles (IONs) are a promising nanoplatform for contrast-enhanced MRI. Recently, magnetic particle imaging (MPI) was introduced as a new imaging modality, which is able to directly visualize magnetic particles and could serve as a more sensitive and quantitative alternative to MRI. However, MPI requires magnetic particles with specific magnetic properties for optimal use. Current commercially available iron oxide formulations perform suboptimal in MPI, which is triggering research into optimized synthesis strategies. Most synthesis procedures aim at size control of iron oxide nanoparticles rather than control over the magnetic properties. In this study, we report on the synthesis, characterization and application of a novel ION platform for sensitive MPI and MRI.Methods and ResultsIONs were synthesized using a thermal-decomposition method and subsequently phase-transferred by encapsulation into lipidic micelles (ION-Micelles). Next, the material and magnetic properties of the ION-Micelles were analyzed. Most notably, vibrating sample magnetometry measurements showed that the effective magnetic core size of the IONs is 16 nm. In addition, magnetic particle spectrometry (MPS) measurements were performed. MPS is essentially zero-dimensional MPI and therefore allows to probe the potential of iron oxide formulations for MPI. ION-Micelles induced up to 200 times higher signal in MPS measurements than commercially available iron oxide formulations (Endorem, Resovist and Sinerem) and thus likely allow for significantly more sensitive MPI. In addition, the potential of the ION-Micelle platform for molecular MPI and MRI was showcased by MPS and MRI measurements of fibrin-binding peptide functionalized ION-Micelles (FibPep-ION-Micelles) bound to blood clots.ConclusionsThe presented data underlines the potential of the ION-Micelle nanoplatform for sensitive (molecular) MPI and warrants further investigation of the FibPep-ION-Micelle platform for in vivo, non-invasive imaging of fibrin in preclinical disease models of thrombus-related pathologies and atherosclerosis.

By means of laser light scattering, poly(vinylidene fluoride) (PVDF) chains were found to form complex aggregates of very narrow size distribution even at dilute concentrations of good solvents such as propylene carbonate (PC) and γ-butyrolactone (BL). Almost the same radii of gyration for aggregates in both solvents were obtained as RG ∼ 220 ± 10 nm. Their static sizes appeared to be concentration-independent as well as temperature-independent at a wide temperature range of 25−160 °C in each solvent. As for solvent effects, the static scattering intensities had different scattering patterns especially at high-q regimes and also different hydrodynamic radii were observed as RH = 380 ± 10 nm in propylene carbonate and RH = 320 ± 10 nm in γ-butyrolactone, respectively. By the introduction of both core−shell structure and core size distribution, the intensity patterns of scattered light and large ratios of RH/RG could be explained. The attractive inter-/intramolecular force between four consecutive sequences...

Magnetic Particle Imaging (MPI) is a novel tracer modality that images the spatial distribution of superparamagnetic iron oxide nanoparticles (SPIOs) by exploiting their nonlinear response to magnetic fields. MPI image resolution is primarily influenced by the strength of the MPI gradient field and the physical and magnetic properties of the nanoparticle tracers. Although MPI offers exceptional sensitivity, contrast, and penetration depth, its spatial resolution remains limited, particularly in clinical systems due to safety limits on gradient field strength. Consequently, efforts to improve resolution focus on developing MPI‐tailored tracers with enhanced magnetic resolution. This work explores the effects of strong dipole‐dipole coupling between SPIOs in linear chain‐like structures. This leads to the observation of superferromagnetism, a phenomenon in which assemblies of superparamagnetic nanoparticles exhibit transient magnetic behavior similar to ferromagnetism. This transition is associated with order‐of‐magnitude improvements in resolution and sensitivity. The influlence of these interactions on the magnetization curve is analyzed using a positive feedback model, and experimental observations such as coercivity are successfully predicted. The necessary conditions for the observation of superferromagnetism suggested by the theory are also experimentally validated. The positive feedback model is found to be an indispensable tool for the synthesis of high‐resolution MPI tracers, optimizing core size, oxidation state, and coating.

The magnetic response of magnetic particle imaging (MPI) tracers varies with the slew rate of the applied magnetic field, as well as with the tracer's average magnetic core size. Currently, 25 kHz and 20 mT/μ0 drive fields are common in MPI, but lower field amplitudes may be necessary for patient safety in future designs. We studied how several different sizes of monodisperse MPI tracers behaved under different drive field amplitude and frequency, using magnetic particle spectrometry and ac hysteresis for drive field conditions at 16, 26, and 40 kHz, with field amplitudes from 5 to 40 mT/μ0. We observed that both field amplitude and frequency can influence the tracer behavior, but that the magnetic behavior is consistent when the slew rate (the product of field amplitude and frequency) is consistent. However, smaller amplitudes provide a correspondingly smaller field of view, sometimes resulting in excitation of a minor hysteresis loop.

Signal stability is crucial for an accurate diagnosis via magnetic particle imaging (MPI). However, MPI-tracer nanoparticles frequently agglomerate during their in vivo applications leading to particle interactions altering the signal. Here, we investigate the influence of such magnetic coupling phenomena on the MPI signal. We prepared Zn0.4Fe2.6O4 nanoparticles by flame spray synthesis and controlled their inter-particle distance by varying SiO2 coating thickness. The silica shell affected the magnetic properties indicating stronger particle interactions for a smaller inter-particle distance. The SiO2-coated Zn0.4Fe2.6O4 outperformed the bare sample in magnetic particle spectroscopy (MPS) in terms of signal/noise, however, the shell thickness itself only weakly influenced the MPS signal. To investigate the importance of magnetic coupling effects in more detail, we benchmarked the MPS signal of the bare and SiO2-coated Zn-ferrites against commercially available PVP-coated Fe3O4 nanoparticles in water and PBS. PBS is known to destabilize nanoparticle colloids mimicking in vivo-like agglomeration. The bare and coated Zn-ferrites showed excellent signal stability, despite their agglomeration in PBS. We attribute this to their process-intrinsic aggregated morphology formed during their flame-synthesis, which generates an MPS signal only little affected by PBS. On the other hand, the MPS signal of commercial PVP-coated Fe3O4 strongly decreased in PBS compared to water, indicating strongly changed particle interactions. The relevance of this effect was further investigated in a human cell model. For PVP-coated Fe3O4, we detected a strong discrepancy between the particle concentration obtained from the MPS signal and the actual concentration determined via ICP-MS. The same trend was observed during their MPI analysis; while SiO2-coated Zn-ferrites could be precisely located in water and PBS, PVP-coated Fe3O4 could not be detected in PBS at all. This drastically limits the sensitivity and also general applicability of these commercial tracers for MPI and illustrates the advantages of our flame-made Zn-ferrites concerning signal stability and ultimately diagnostic accuracy.

On the effect of reference and sample volume on magnetic particle imaging quantification.

Magnetic Particle Imaging (MPI) is an emerging tomographic modality that allows for precise three-dimensional (3D) mapping of magnetic nanoparticles (MNPs) concentration and distribution. Although significant progress has been made towards improving MPI since its introduction, scaling it up for human applications has proven challenging. High-quality images have been obtained in animal-scale MPI scanners with gradients up to 7 T/m/ , however, for MPI systems with bore diameters around 200 mm the gradients generated by electromagnets drop significantly to below 0.5 T/m/ . Given the current technological limitations in image reconstruction and the properties of available MNPs, these low gradients inherently impose limitations on improving MPI resolution for higher precision medical imaging. Utilizing superconductors stands out as a promising approach for developing a human-scale MPI system. In this study, we introduce, for the first time, a human-scale amplitude modulation (AM) MPI system with superconductor-based selection coils. The system achieves an unprecedented magnetic field gradient of up to 2.5 T/m/ within a 200 mm bore diameter, enabling large fields of view of mm3 at 2.5 T/m/ for 3D imaging. While obtained spatial resolution is in the order of previous animal-scale AM MPIs, incorporating superconductors for achieving such high gradients in a 200 mm bore diameter marks a major step toward clinical MPI.

The second issue of the sixth volume of the International Journal on Magnetic Particle Imaging presents three original research papers spanning theoretical and experimental studies designed to improve various aspects of existing MPI technology. The papers present methods for improving image reconstruction processes during magnetic particle imaging by the adoption of new statistical methods, for reducing artifacts in reconstructed images arising from non-ideal selection-field gradients, and a theoretical study modelling how the magnetic particle imaging signal is influenced by parameters of the nanoparticle tracer including the magnetic anisotropy and core radius. The papers provide a snap-shot of current advances in the engineering of magnetic particle imaging systems, and provide insight into how the development and uptake of the technology can be accelerated. Int. J. Mag. Part. Imag. 6(2), 2021, Article ID: 2106001, DOI: 10.18416/IJMPI.2021.2106001

Simple SummaryMagnetic Particle Imaging (MPI) is an emerging imaging technique that provides quantitative direct imaging of superparamagnetic iron oxide nanoparticles. In the last decade, MPI has shown great prospects as one of the magnetic methods other than Magnetic Resonance Imaging with applications covering cancer diagnosis, targeting enhancement, actuating cancer therapy, and post-therapy monitoring. Working on different physical principles from Magnetic Resonance Imaging, MPI benefits from ideal image contrast with zero background tissue signal, enabling hotspot-type images similar to Nuclear Medicine scans but using magnetic agents rather than radiotracers. In this review, we discussed the relevance of MPI to cancer diagnostics and image-guided therapy as well as recent progress to clinical translation.Background: Magnetic Particle Imaging (MPI) is an emerging imaging modality for quantitative direct imaging of superparamagnetic iron oxide nanoparticles (SPION or SPIO). With different physics from MRI, MPI benefits from ideal image contrast with zero background tissue signal. This enables clear visualization of cancer with image characteristics similar to PET or SPECT, but using radiation-free magnetic nanoparticles instead, with infinite-duration reporter persistence in vivo. MPI for cancer imaging: demonstrated months of quantitative imaging of the cancer-related immune response with in situ SPION-labelling of immune cells (e.g., neutrophils, CAR T-cells). Because MPI suffers absolutely no susceptibility artifacts in the lung, immuno-MPI could soon provide completely noninvasive early-stage diagnosis and treatment monitoring of lung cancers. MPI for magnetic steering: MPI gradients are ~150 × stronger than MRI, enabling remote magnetic steering of magneto-aerosol, nanoparticles, and catheter tips, enhancing therapeutic delivery by magnetic means. MPI for precision therapy: gradients enable focusing of magnetic hyperthermia and magnetic-actuated drug release with up to 2 mm precision. The extent of drug release from the magnetic nanocarrier can be quantitatively monitored by MPI of SPION’s MPS spectral changes within the nanocarrier. Conclusion: MPI is a promising new magnetic modality spanning cancer imaging to guided-therapy.

Magnetic particle imaging (MPI) scanners cannot only be used to image the distribution of magnetic nanoparticles, but the magnetic fields also facilitate to actuate magnetic devices. This enables the dual use of MPI scanners for simultaneous actuation and visualization of magnetic objects. It is of great interest for a variety of medical applications to magnetically steer devices, such as catheters or capsule endoscopes. Endoscopic capsules, which are driven by the natural peristaltic movements, are already in clinical routine. However, they cannot be used for the investigation of the stomach, since the capsules cannot be steered. Hence, steerable magnetic capsules can be used to endoscopically investigate the whole gastrointestinal tract, to take a biopsy or to deliver drugs locally. The 3D tomographic localization of such steerable capsules is an open task, but it is essential to localize detected abnormalities for subsequent treatments. Since MPI provides tomographic real-time images of magnetic material, it seems to be beneficial to visualize the actuation process with MPI. In this work, a material for additive manufacturing is investigated, which consists of polylactide with incorporated iron powder of µm-sized particles. The material is analyzed by light microscopy, vibrating sample magnetometry and magnetic particle spectrometry. Then the feasibility to actuate and visualize macroscopic devices made of this material inside an MPI scanner is shown. The fabricated object has a length of about 2 cm and can be rotated when applying sinusoidal currents to the focus field coils of an MPI scanner. In addition, the objects' shape led to a forward velocity in water. The suitability of the 3D-printing material for MPI is shown and static 3D images are presented. Int. J. Mag. Part. Imag. 6(1), 2020, Article ID: 2003001, DOI: 10.18416/IJMPI.2020.2003001

Finding the magnetic size distribution of magnetic nanoparticles from magnetization measurements via the iterative Kaczmarz algorithm