Multi-color magnetic nanoparticle imaging using magnetorelaxometry

Development of doxorubicin-encapsulated magnetic liposome@PEG for treatment of breast cancer in BALB/c mice

The magnetic doxorubicin-encapsulated liposome/PEG/Fe3O4 (called as DOX@m-Lip/PEG) was synthesized and studied as a novel nanocarrier for the treatment of breast cancer in BALB/c mice. Nanocarrier was characterized by FT-IR, zeta-potential sizer, EDX elemental analysis, EDX mapping, TEM, and DLS techniques. The results showed that the size of the nanocarrier was determined around 128 nm by TEM. EDX study confirmed PEG-conjugation in the magnetic liposomes and was homogenously distributed in the nanosize range (100-200 nm) with a negative surface charge (-61.7 mV). The kinetic studies indicated that the release of doxorubicin from DOX@m-Lip/PEG follows the Korsmeyer-Peppas model. The n-value of the model was 0.315, indicating that doxorubicin release from the nanocarrier had a slow releasing rate and followed Fick's law. The DOX release from the nanocarrier lasted a long time (more than 300 h). In in vivo part, a mouse 4T1 breast tumor model was used. The in vivo results indicated that DOX@m-Lip/PEG caused much stronger tumor cell necrosis and less cardiotoxic effects than the other groups. In conclusion, we show that m-Lip/PEG is a promising nanocarrier for low dosage and slow release of doxorubicin in treating breast cancer, and treatment with encapsulated DOX (DOX@m-Lip/PEG) demonstrated higher efficacy with low cardiac toxicity. Besides, the magnetic property of m-Lip@PEG nanocarrier allows it to be a potent mater for hyperthermia and MRI studies.

Temperature dependent magnetorelaxometry of magnetic nanoparticle ensembles

Magnetorelaxometry imaging (MRXI) is a non-invasive, quantitative imaging technique for magnetic nanoparticles (MNPs). The image resolution of this technique significantly depends on the relaxation amplitude (ΔB). For this work, we measured the room temperature (299 K) relaxation signals of eight commercial MNP sample systems with different magnetic properties, in both fluid and immobilized states, in order to select the most suitable sample for a particular MRXI setting. Additionally, the effect of elevated temperatures (up to hyperthermia temperature, 335 K) on the relaxation signals of four different MNP systems (Synomag, Perimag, BNF and Nanomag) in both states were investigated. The ΔBvalues of fluid samples significantly decreased with increasing temperature, and the behaviour for immobilized samples depended on their blocking temperature (TB). For samples withTB< 299 K, ΔBalso decreased with increasing temperature. Whereas for samples withTB> 299 K, the opposite behaviour was observed. These results are beneficial for improving the image resolution in MRXI and show, among the investigated systems, and for our setup, Synomag is the best candidate for futurein vitroandin vivostudies. This is due to its consistently high ΔBbetween 299 and 335 K in both states. Our findings demonstrate the feasibility of temperature imaging by MRXI.

Developing magnetorelaxometry imaging for human applications

Objective. Magnetic nanoparticles (MNPs) are a promising tool in biomedical applications such as cancer therapy and diagnosis, where localization and quantification of MNP distributions are often mandatory. This can be obtained by magnetorelaxometry imaging (MRXI). Approach. In this work, the capability of MRXI for quantitative imaging of MNP inside larger volumes such as a human head is investigated. We developed a human head phantom simulating a glioblastoma multiforme (GBM) tumor containing MNP for magnetic hyperthermia treatment. The sensitivity of our MRXI setup for detection of MNP concentrations in the range of 3–19 mg cm−3 was studied. Main result. The results show the high capability of MRXI to detect MNPs in a human head sized volume. Superficial sources with a concentration larger than 12 mg cm-3 could be reconstructed with a resulotion of about 1 cm-3. Significance. The reconstruction of the MNP distribution, mimicking a GBM tumor of 7 cm3 volume with clinically relevant iron concentration, demonstrates the in vivo feasibility of MRXI in humans.

2D Quantitative Imaging of Magnetic Nanoparticles by an AC Biosusceptometry Based Scanning Approach and Inverse Problem

The use of magnetic nanoparticles (MNPs) in biomedical applications requires the quantitative knowledge of their quantitative distribution within the body. AC Biosusceptometry (ACB) is a biomagnetic technique recently employed to detect MNPs in vivo by measuring the MNPs response when exposed to an alternate magnetic field. The ACB technique presents some interesting characteristics: non-invasiveness, low operational cost, high portability, and no need for magnetic shielding. ACB conventional methods until now provided only qualitative information about the MNPs’ mapping in small animals. We present a theoretical model and experimentally demonstrate the feasibility of ACB reconstructing 2D quantitative images of MNPs’ distributions. We employed an ACB single-channel scanning approach, measuring at 361 sensor positions, to reconstruct MNPs’ spatial distributions. For this, we established a discrete forward problem and solved the ACB system’s inverse problem. Thus, we were able to determine the positions and quantities of MNPs in a field of view of 5×5×1 cm3 with good precision and accuracy. The results show the ACB system’s capabilities to reconstruct the quantitative spatial distribution of MNPs with a spatial resolution better than 1 cm, and a sensitivity of 1.17 mg of MNPs fixed in gypsum. These results show the system’s potential for biomedical application of MNPs in several studies, for example, electrochemical-functionalized MNPs for cancer cell targeting, quantitative sensing, and possibly in vivo imaging.

Model-based optimized steering and focusing of local magnetic particle concentrations for targeted drug delivery

Magnetic drug targeting (MDT) is an application in the field of targeted drug delivery in which magnetic (nano)particles act as drug carriers. The particles can be steered toward specific regions in the human body by adapting the currents of external (electro)magnets. Accurate models of particle movement and control algorithms for the electromagnet currents are two of the many requirements to ensure effective drug targeting. In this work, a control approach for the currents is presented, based on an underlying physical model that describes the dynamics of particles in a liquid in terms of their concentration in each point in space. Using this model, the control algorithm determines the currents generating the magnetic fields that maximize the particle concentration in spots of interest over a period of time. Such an approach is computationally only feasible thanks to our innovative combination of model order reduction with the method of direct multiple shooting. Simulation results of an in-vitro targeting setup demonstrated that a particle collection can be successfully guided toward the targeted spot with limited dispersion through a surrounding liquid. As now present and future particle behavior can be taken into account, and non-stationary surrounding liquids can be dealt with, a more precise and flexible targeting is achieved compared to existing MDT methods. This proves that the presented methodology can bring MDT closer to its clinical application. Moreover, the developed model is compatible with state-of-the-art imaging methods, paving the way for theranostic platforms that combine both therapy as well as diagnostics.

Magnetic measurement methods to probe nanoparticle–matrix interactions

Magnetic nanoparticles (MNPs) are key elements in several biomedical applications, e.g., in cancer therapy. Here, the MNPs are remotely manipulated by magnetic fields from outside the body to deliver drugs or generate heat in tumor tissue. The efficiency and success of these approaches strongly depend on the spatial distribution and quantity of MNPs inside a body and interactions of the particles with the biological matrix. These include dynamic processes of the MNPs in the organism such as binding kinetics, cellular uptake, passage through cell barriers, heat induction and flow. While magnetic measurement methods have been applied so far to resolve the location and quantity of MNPs for therapy monitoring, these methods can be advanced to additionally access these particle–matrix interactions. By this, the MNPs can further be utilized as probes for the physical properties of their molecular environment. In this review, we first investigate the impact of nanoparticle–matrix interactions on magnetic measurements in selected experiments. With these results, we then advanced the imaging modalities magnetorelaxometry imaging and magnetic microsphere tracking to spatially resolve particle–matrix interactions.

Improvement of multisource localization of magnetic particles in an animal

In this simulation work, the linearized Bregman iterative algorithm was applied to solve the magnetic source distribution problem of a magnetic particle imaging (MPI) system for small animals. MPI system can apply an excitation magnetic field, and the induced magnetic field from the magnetic nanoparticles (MNPs) can be detected by the sensors of MPI system. With a gaussian distribution source at the upper side of the mouse brain, sensors set above the mouse brain and the constant excitation magnetic field, the average deviation of the calculated source distribution from the multiplane scanning along the axis away from the mouse brain and the closest plane scanning are 2.78 × 10^–3 and 2.84 × 10^–3 respectively. The simulated result showed that combination of multiplane scanning hardly improves the accuracy of the source localization. In addition, a gradient scan method was developed that uses gradient magnetic field to scan the mouse brain. The position of the maximum of the lead field matrix will be controlled by the gradient field. With a set up gaussian distribution source at the bottom of the mouse brain, the average deviation of the calculated source distribution from the gradient scan method and the constant field are 4.42 × 10^–2 and 5.05 × 10^–2. The location error from the two method are 2.24 × 10^–1 cm and 3.61 × 10^–1 cm. The simulation showed that this method can improve the accuracy compared to constant field when the source is away from the sensor and having a potential for application.

Advanced analysis of magnetic nanoflower measurements to leverage their use in biomedicine

Magnetic nanoparticles are an important asset in many biomedical applications ranging from the local heating of tumours to targeted drug delivery towards diseased sites. Recently, magnetic nanoflowers showed a remarkable heating performance in hyperthermia experiments thanks to their complex structure leading to a broad range of magnetic dynamics. To grasp their full potential and to better understand the origin of this unexpected heating performance, we propose the use of Kaczmarz' algorithm in interpreting magnetic characterisation measurements. It has the advantage that no a priori assumptions need to be made on the particle size distribution, contrasting current magnetic interpretation methods that often assume a lognormal size distribution. Both approaches are compared on DC magnetometry, magnetorelaxometry and AC susceptibility characterisation measurements of the nanoflowers. We report that the lognormal distribution parameters vary significantly between data sets, whereas Kaczmarz' approach achieves a consistent and accurate characterisation for all measurement sets. Additionally, we introduce a methodology to use Kaczmarz' approach on distinct measurement data sets simultaneously. It has the advantage that the strengths of the individual characterisation techniques are combined and their weaknesses reduced, further improving characterisation accuracy. Our findings are important for biomedical applications as Kaczmarz' algorithm allows to pinpoint multiple, smaller peaks in the nanostructure's size distribution compared to the monomodal lognormal distribution. The smaller peaks permit to fine-tune biomedical applications with respect to these peaks to e.g. boost heating or to reduce blurring effects in images. Furthermore, the Kaczmarz algorithm allows for a standardised data analysis for a broad range of magnetic nanoparticle samples. Thus, our approach can improve the safety and efficiency of biomedical applications of magnetic nanoparticles, paving the way towards their clinical use.

Simultaneous Coercivity and Size Determination of Magnetic Nanoparticles

Magnetic nanoparticles are increasingly employed in biomedical applications such as disease detection and tumor treatment. To ensure a safe and efficient operation of these applications, a noninvasive and accurate characterization of the particles is required. In this work, a magnetic characterization technique is presented in which the particles are excited by specific pulsed time-varying magnetic fields. This way, we can selectively excite nanoparticles of a given size so that the resulting measurement gives direct information on the size distribution without the need for any a priori assumptions or complex postprocessing procedures to decompose the measurement signal. This contrasts state-of-the-art magnetic characterization techniques. The possibility to selectively excite certain particle types opens up perspectives in "multicolor" particle imaging, where different particle types need to be imaged independently within one sample. Moreover, the presented methodology allows one to simultaneously determine the size-dependent coercivity of the particles. This is not only a valuable structure-property relation from a fundamental point of view, it is also practically relevant to optimize applications like magnetic particle hyperthermia. We numerically demonstrate that the novel characterization technique can accurately reconstruct several particle size distributions and is able to retrieve the coercivity-size relation of the particles. The developed technique advances current magnetic nanoparticle characterization possibilities and opens up exciting pathways for biomedical applications and particle imaging procedures.

Quantitative 2D Magnetorelaxometry Imaging of Magnetic Nanoparticles using Optically Pumped Magnetometers

For biomagnetical applications exploiting physical properties of magnetic nanoparticles (MNP), e.g., magnetic hyperthermia, knowledge about the quantitative spatial MNP distribution is crucial, which can be extracted by magnetorelaxometry (MRX) imaging. In this paper, we present quantification, quantitative 1D reconstruction, and quantitative 2D imaging of MNP by exploiting optically pumped magnetometers for MRX. While highlighting the potential of commercially available optically pumped magnetometers (OPM) for MRXI, we discuss current limitations of the used OPM. We show, that with our OPM setup, MNP can be precisely quantified with iron amounts down to ≈6 μg, which can be improved easily. With a 1D-reconstruction setup, point-like and complex MNP phantoms can be reconstructed quantitatively with high precision and accuracy. We show that with our developed 2D MRX imaging setup, which measures 12 cm by 8 cm, point-like MNP distributions with clinically relevant iron concentrations can be reconstructed precisely and accurately. Our 2D setup has the potential to be easily extended to a tomography styled (and thus slice-selective) 3D scanner, by adding a mechanical axis to the phantom.

Multiplex Detection of Different Magnetic Beads Using Frequency Scanning in Magnetic Frequency Mixing Technique

In modern bioanalytical methods, it is often desired to detect several targets in one sample within one measurement. Immunological methods including those that use superparamagnetic beads are an important group of techniques for these applications. The goal of this work is to investigate the feasibility of simultaneously detecting different superparamagnetic beads acting as markers using the magnetic frequency mixing technique. The frequency of the magnetic excitation field is scanned while the lower driving frequency is kept constant. Due to the particles’ nonlinear magnetization, mixing frequencies are generated. To record their amplitude and phase information, a direct digitization of the pickup-coil’s signal with subsequent Fast Fourier Transformation is performed. By synchronizing both magnetic fields, a stable phase information is gained. In this research, it is shown that the amplitude of the dominant mixing component is proportional to the amount of superparamagnetic beads inside a sample. Additionally, it is shown that the phase does not show this behaviour. Excitation frequency scans of different bead types were performed, showing different phases, without correlation to their diverse amplitudes. Two commercially available beads were selected and a determination of their amount in a mixture is performed as a demonstration for multiplex measurements.

Discriminating nanoparticle core size using multi-contrast MPI

Magnetic particle imaging (MPI) is an imaging modality that detects the response of a distribution of magnetic nanoparticle tracers to alternating magnetic fields. There has recently been exploration into multi-contrast MPI, in which the signal from different tracer materials or environments is separately reconstructed, resulting in multi-channel images that could enable temperature or viscosity quantification. In this work, we apply a multi-contrast reconstruction technique to discriminate between nanoparticle tracers of different core sizes. Three nanoparticle types with core diameters of 21.9 nm, 25.3 nm and 27.7 nm were each imaged at 21 different locations within the scanner field of view. Multi-channel images were reconstructed for each sample and location, with each channel corresponding to one of the three core sizes. For each image, signal weight vectors were calculated, which were then used to classify each image by core size. With a block averaging length of 10 000, the median signal-to-noise ratio was 40 or higher for all three sample types, and a correct prediction rate of 96.7% was achieved, indicating that core size can effectively be predicted using signal weight vector classification with close to 100% accuracy while retaining high MPI image quality. The discrimination of the core size was reliable even when multiple samples of different core sizes were placed in the measuring field.