SPFS: SNR peak-based frequency selection method to alleviate resolution degradation in MPI real-time imaging

OBJECTIVE

The primary objective of this study is to address the reconstruction time challenge in Magnetic Particle Imaging (MPI) by introducing a novel approach named SNR-Peak-Based Frequency Selection (SPFS). The focus is on improving spatial resolution without compromising reconstruction speed, thereby enhancing the clinical potential of MPI for real-time imaging.

APPROACH

To overcome the trade-off between reconstruction time and spatial resolution in MPI, the researchers propose SPFS as an innovative frequency selection method. Unlike conventional SNR-based selection, SPFS prioritizes frequencies with Signal-to-Noise Ratio (SNR) peaks that capture crucial system matrix information. This adaptability to varying quantities of selected frequencies enhances versatility in the reconstruction process. The study compares the spatial resolution of MPI reconstruction using both SNR-based and SPFS frequency selection methods, utilizing simulated and real device data.

MAIN RESULTS

The research findings demonstrate that the SPFS approach substantially improves image resolution in Magnetic Particle Imaging, especially when dealing with a limited number of frequency components. By focusing on SNR peaks associated with critical system matrix information, SPFS mitigates the spatial resolution degradation observed in conventional SNR-based selection methods. The study validates the effectiveness of SPFS through the assessment of MPI reconstruction spatial resolution using both simulated and real device data, highlighting its potential to address a critical limitation in the field.

SIGNIFICANCE

The introduction of SNR-Peak-Based Frequency Selection (SPFS) represents a significant breakthrough in MPI technology. The method not only accelerates reconstruction time but also enhances spatial resolution, thus expanding the clinical potential of MPI for various applications. The improved real-time imaging capabilities of MPI, facilitated by SPFS, hold promise for advancements in drug delivery, plaque assessment, tumor treatment, cerebral perfusion evaluation, immunotherapy guidance, and in vivo cell tracking.

In situ theranostic platform combining highly localized magnetic fluid hyperthermia, magnetic particle imaging, and thermometry in 3D

Theranostic platforms, combining diagnostic and therapeutic approaches within one system, have garnered interest in augmenting invasive surgical, chemical, and ionizing interventions. Magnetic particle imaging (MPI) offers a quite recent alternative to established radiation-based diagnostic modalities with its versatile tracer material (superparamagnetic iron oxide nanoparticles, SPION). It also offers a bimodal theranostic framework that can combine tomographic imaging with therapeutic techniques using the very same SPION. Methods: We show the interleaved combination of MPI-based imaging, therapy (highly localized magnetic fluid hyperthermia (MFH)) and therapy safety control (MPI-based thermometry) within one theranostic platform in all three spatial dimensions using a commercial MPI system and a custom-made heating insert. The heating characteristics as well as theranostic applications of the platform were demonstrated by various phantom experiments using commercial SPION. Results: We have shown the feasibility of an MPI-MFH-based theranostic platform by demonstrating high spatial control of the therapeutic target, adequate MPI-based thermometry, and successful in situ interleaved MPI-MFH application. Conclusions: MPI-MFH-based theranostic platforms serve as valuable tools that enable the synergistic integration of diagnostic and therapeutic approaches. The transition into in vivo studies will be essential to further validate their potential, and it holds promising prospects for future advancements.

Dynamic residual Kaczmarz method for noise reducing reconstruction in magnetic particle imaging

OBJECTIVE

Here, we propose a dynamic residual Kaczmarz (DRK) method as an improved reconstruction method for magnetic particle imaging (MPI) to achieve a better reconstruction quality from high-noise signals.

APPROACH

Based on the Kaczmarz (KZ) method, we introduced a residual vector to select parts of the low-noise equations for reconstruction. In each iteration, a low-noise subset was formulated based on the residual vector. Thus, the reconstruction converged to an accurate result with less noise.

MAIN RESULTS

To evaluate the performance of the proposed method, it was compared with classical Kaczmarz-type methods and state-of-the-art regularization models. The numerical simulation results demonstrate that the DRK method can achieve better reconstruction quality than all other comparison methods at similar noise levels. It can acquire a signal-to-background ratio (SBR) that is five times higher than that of classical Kaczmarz-type methods at a 5 dB noise level. Furthermore, the DRK method can acquire up to 0.7 structural similarity (SSIM) indicators at a 5 dB noise level when combined with the non-negative fused LASSO regularization model. In addition, a real experiment based on the OpenMPI data set validated that the proposed DRK method can be applied to real data and perform well.

SIGNIFICANCE

The experimental results demonstrate that the proposed DRK method can significantly improve the reconstruction quality of MPI when the signals contain high noise. It has the potential to be applied to MPI instruments that contain high signal noise, such as human-sized MPI instruments. It is beneficial for expanding the biomedical applications of MPI technology.

Mixed Metal Metal-Organic Frameworks Derived Carbon Supporting ZnFe2O4/C for High-Performance Magnetic Particle Imaging

Recently, magnetic particle imaging (MPI) has shown diverse biomedical applications such as cell tracking, lung perfusion, image-guided hyperthermia, and so forth. However, the currently reported MPI agents cannot achieve the possible theoretical detection limit of MPI (20 nM). A previous theoretical study has shown that the MPI performance of superparamagnetic iron oxide nanoparticles (SPIONs) can be enhanced by carbon supporting and metal doping. In the current study, a series of mixed metal metal-organic framework-derived carbon supporting SPIONs were synthesized by pyrolysis. Among the synthesized SPIONs, the MPI signal intensity of ZnFe₂O₄/C@PDA was found to be 4.7 times higher than the commercial MPI contrast (Vivotrax) having the same Fe concentration. ZnFe₂O₄/C@PDA also showed the highest MPI intensity in tumor-bearing-mice among all tested samples. Furthermore, they were found highly biocompatible and showed linear cell quantification. This work can open new avenues for the design and development of novel and high-performance MPI agents.

Characterization of noise and background signals in a magnetic particle imaging system

Magnetic Particle Imaging (MPI) is a novel technology, which opens new possibilities for promising biomedical applications. MPI uses magnetic fields to generate a specific response from magnetic nanoparticles (MNPs), to determine their spatial location non-invasively and without using ionizing radiation. One open challenge of MPI is to achieve further improvements in terms of sensitivity to translate the currently preclinical performed research into clinical applications. In this work, we study the noise and background signals of our preclinical MPI system, to identify and characterize disturbing signal contributions. The current limit of detection achieved with our device was determined previously to be 20 ng of iron. Based on the results presented in this work, we describe possible hardware and software improvements and estimate that the limit of detection could be lowered to about 200-400 pg. Additionally, a long-term analysis of the scanner performance over the last three years is presented, which proved to be an easy and effective way to monitor possible changes or damage of hardware components. All the presented results were obtained by analysing empty scanner measurements and the presented methodology can easily be adapted for different scanner types, to compare their performances.

Complex Relationship Between Iron Oxide Nanoparticle Degradation and Signal Intensity in Magnetic Particle Imaging

Magnetic particle imaging (MPI), using superparamagnetic nanoparticles as an imaging tracer, is touted as a quantitative biomedical imaging technology, but MPI signal properties have never been characterized for magnetic nanoparticles undergoing biodegradation. We show that MPI signal properties can increase or decrease as iron oxide nanoparticles degrade, depending on the nanoparticle formulation and nanocrystal size, and degradation rate and mechanism. Further, we show that long-term in vitro MPI experiments only roughly approximate long-term in vivo MPI signal properties. Further, we demonstrate for the first time, an environmentally sensitive MPI contrast mechanism opening the door to smart contrast paradigms in MPI.

Using magnetic particle imaging systems to localize and guide magnetic hyperthermia treatment: tracers, hardware, and future medical applications

Magnetic fluid hyperthermia (MFH) treatment makes use of a suspension of superparamagnetic iron oxide nanoparticles, administered systemically or locally, in combination with an externally applied alternating magnetic field, to ablate target tissue by generating heat through a process called induction. The heat generated above the mammalian euthermic temperature of 37°C induces apoptotic cell death and/or enhances the susceptibility of the target tissue to other therapies such as radiation and chemotherapy. While most hyperthermia techniques currently in development are targeted towards cancer treatment, hyperthermia is also used to treat restenosis, to remove plaques, to ablate nerves and to alleviate pain by increasing regional blood flow. While RF hyperthermia can be directed invasively towards the site of treatment, non-invasive localization of heat through induction is challenging. In this review, we discuss recent progress in the field of RF magnetic fluid hyperthermia and introduce a new diagnostic imaging modality called magnetic particle imaging that allows for a focused theranostic approach encompassing treatment planning, treatment monitoring and spatially localized inductive heating.

Take a Deep Breath - Monitoring of Inhaled Nanoparticles with Magnetic Particle Imaging

Magnetic Particle Imaging (MPI) is a new imaging modality based on the visualization of Superparamagnetic Iron Oxide Nanoparticles (SPIONs) using magnetic fields. The potential of MPI was recently evaluated in numerous ex vivo and in vivo studies and the technique can now be considered as an established preclinical imaging modality with a promising perspective of clinical applications.

Rodent Cerebral Blood Volume (CBV) changes during hypercapnia observed using Magnetic Particle Imaging (MPI) detection

Magnetic Particle Imaging (MPI) is a rapidly developing imaging modality that directly measures and maps the concentration of injected superparamagnetic iron oxide nanoparticles (SPIOs). Since the agent does not cross the blood-brain barrier, cerebral SPIO concentration provides a direct probe of Cerebral Blood Volume (CBV). Here we provide an initial demonstration of the ability of MPI to detect functional CBV changes (fCBV) by monitoring SPIO concentration during hypercapnic manipulation in a rat model. As a tracer detection method, MPI offers a more direct probe of agent concentration and therefore fCBV than MRI measurements in which the agent is indirectly detected through perturbation of water relaxation time constants such as T₂^∗. We found that MPI detection could measure CBV changes during hypercapnia with high CNR (CNR = 50) and potentially with high temporal resolution. Although the detection process more closely resembles a tracer method, we also identify evidence of physiological noise in the MPI time-series, with higher time-series variance at higher concentration levels. Our findings suggest that CBV-based MPI can provide a detection modality for hemodynamic changes. Further investigation with tomographic imaging is needed to assess tomographic ability of the method and further study the presence of time-series fluctuations which scale with signal level similar to physiological noise in resting fMRI time-courses.

A FIELD CANCELATION SIGNAL EXTRACTION METHOD FOR MAGNETIC PARTICLE IMAGING

In nowadays Magnetic Particle Imaging (MPI) signal detection and excitation happens at the same time. This concept, however, leads to strong coupling of the drive (excitation) field (DF) with the receive chain. As the induced DF signal is several orders of magnitude higher, special measures have to be taken to suppress this signal portion within the receive signal to keep the required dynamic range of the subsequent analog to digital conversion in a technically feasible range. For "frequency space MPI" high-order band-stop-filters have been successfully used to remove the DF signals, which unfortunately as well removes the fundamental harmonic components of the signal of the magnetic nanoparticles (MNP). According to the Langevin theory the fundamental harmonic component has a large signal contribution and is important for direct reconstruction of the particle concentration. In order to separate the fundamental harmonic component of the MNP from the induced DF signal, different concepts have been proposed using signal cancelation based on additional DF signals, also in combination with additional filtering. In this paper, we propose a field-cancelation (FC) concept in which a receive coil (RC) consists of a series connection of a primary coil in combination with an additional cancelation coil. The geometry of the primary coil was chosen to be sensitive for the MNP signal while the cancelation coil was chosen to minimize the overall inductive coupling of the FC-RC with the DF. Sensitivity plots and mutual coupling coefficients were calculated using a thin-wire approximation. A prototype FC-RC was manufactured and effectiveness of the reduction of the mutual inductive coupling (d) was tested in an existing mouse MPI scanner. The difference between simulations (d_s =70 dB) and the measurements (d_ms =55 dB) indicated the feasibility as well as the need for further investigations.

Tuning surface coatings of optimized magnetite nanoparticle tracers for in vivo Magnetic Particle Imaging

Surface coatings are important components of Magnetic Particle Imaging (MPI) tracers - they preserve their key properties responsible for optimum tracer performance in physiological environments. In vivo, surface coatings form a physical barrier between the hydrophobic SPION cores and the physiological environment, and their design dictates the blood half-life and biodistribution of MPI tracers. Here we show the effect of tuning poly(ethylene glycol) (PEG)-based surface coatings on both in vitro and in vivo (mouse model) MPI performance of SPIONs. Our results showed that varying PEG molecular weight had a profound impact on colloidal stability, characterized using Dynamic Light Scattering (DLS), and the m'(H) response of SPIONs, measured in a 25 kHz/20 mTμ₀^-1_max Magnetic Particle Spectrometer (MPS). Increasing PEG molecular weight from 5 kDa to 20 kDa preserved colloidal stability and m'(H) response of ~25 nm SPIONs - the optimum core diameter for MPI - in serum-rich cell culture medium for up to 24 hours. Furthermore, we compared the in vivo circulation time of SPIONs as a function of hydrodynamic diameter and showed that clustered SPIONs can adversely affect blood half-life; critically, SPIONs with clusters had 5 times shorter blood half-life than individually coated SPIONs. We anticipate that the development of MPI SPION tracers with long blood half-lives have potential not only in vascular imaging applications, but also enable opportunities in molecular targeting and imaging - a critical step towards early cancer detection using the new MPI modality.

Flexible and modular MPI simulation framework and its use in modelling a μMPI

The availability of thorough system simulations for detailed and accurate performance prediction and optimization of existing and future designs for a new modality such as magnetic particle imaging (MPI) are very important. Our framework aims to simulate a complete MPI system by providing a description of all (drive and receive) coils, permanent magnet configurations, magnetic nanoparticle (MNP) distributions, and characteristics of the signal processing chain. The simulation is performed on a user defined spatial and temporal discrete grid. The magnetization of the MNP is modelled by either the Langevin theory or as ideal particles with infinite steepness and ideal saturation. The magnetic fields are approximated in first order by calculating the Biot-Savart integral. Additionally the coupling constants between the excitation coils (e.g. drive field coils) and the receive coils can be determined. All coils can be described by an XML description language based on primitive geometric shapes. First simulations of a modelled μMPI system are shown. In this regard μMPI refers to a small one dimensional system for samples of a size of a few tens of a cubic millimeter and a spatial resolution of about 200 μm.