Spectroscopic AC Susceptibility Imaging (sASI) of Magnetic Nanoparticles

Adaptive Model for Magnetic Particle Mapping Using Magnetoelectric Sensors

Imaging of magnetic nanoparticles (MNPs) is of great interest in the medical sciences. By using resonant magnetoelectric sensors, higher harmonic excitations of MNPs can be measured and mapped in space. The proper reconstruction of particle distribution via solving the inverse problem is paramount for any imaging technique. For this, the forward model needs to be modeled accurately. However, depending on the state of the magnetoelectric sensors, the projection axis for the magnetic field may vary and may not be known accurately beforehand. As a result, the projection axis used in the model may be inaccurate, which can result in inaccurate reconstructions and artifact formation. Here, we show an approach for mapping MNPs that includes sources of uncertainty to both select the correct particle distribution and the correct model simultaneously.

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.

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.

Multi-color magnetic nanoparticle imaging using magnetorelaxometry

Magnetorelaxometry (MRX) is a well-known measurement technique which allows the retrieval of magnetic nanoparticle (MNP) characteristics such as size distribution and clustering behavior. This technique also enables the non-invasive reconstruction of the spatial MNP distribution by solving an inverse problem, referred to as MRX imaging. Although MRX allows the imaging of a broad range of MNP types, little research has been done on imaging different MNP types simultaneously. Biomedical applications can benefit significantly from a measurement technique that allows the separation of the resulting measurement signal into its components originating from different MNP types. In this paper, we present a theoretical procedure and experimental validation to show the feasibility of MRX imaging in reconstructing multiple MNP types simultaneously. Because each particle type has its own characteristic MRX signal, it is possible to take this a priori information into account while solving the inverse problem. This way each particle type's signal can be separated and its spatial distribution reconstructed. By assigning a unique color code and intensity to each particle type's signal, an image can be obtained in which each spatial distribution is depicted in the resulting color and with the intensity measuring the amount of particles of that type, hence the name multi-color MNP imaging. The theoretical procedure is validated by reconstructing six phantoms, with different spatial arrangements of multiple MNP types, using MRX imaging. It is observed that MRX imaging easily allows up to four particle types to be separated simultaneously, meaning their quantitative spatial distributions can be obtained.

A Feasibility Study of Nonlinear Spectroscopic Measurement of Magnetic Nanoparticles Targeted to Cancer Cells

OBJECTIVE

Magnetic nanoparticles (MNPs) are an emerging platform for targeted diagnostics in cancer. An important component needed for translation of MNPs is the detection and quantification of targeted MNPs bound to tumor cells.

METHOD

This study explores the feasibility of a multifrequency nonlinear magnetic spectroscopic method that uses excitation and pickup coils and is capable of discriminating between quantities of bound and unbound MNPs in 0.5 ml samples of KB and Igrov human cancer cell lines. The method is tested over a range of five concentrations of MNPs from 0 to 80 μg/ml and five concentrations of cells from 50 to 400 000 count per ml.

RESULTS

A linear model applied to the magnetic spectroscopy data was able to simultaneously measure bound and unbound MNPs with agreement between the model-fit and lab assay measurements (p < 0.001). The detectable iron of the presented method to bound and unbound MNPs was < 2 μg in a 0.5 ml sample. The linear model parameters used to determine the quantities of bound and unbound nanoparticles in KB cells were also used to measure the bound and unbound MNP in the Igrov cell line and vice versa.

CONCLUSION

Nonlinear spectroscopic measurement of MNPs may be a useful method for studying targeted MNPs in oncology.

SIGNIFICANCE

Determining the quantity of bound and unbound MNP in an unknown sample using a linear model represents an exciting opportunity to translate multifrequency nonlinear spectroscopy methods to in vivo applications where MNPs could be targeted to cancer cells.

Extended arrays for nonlinear susceptibility magnitude imaging

This study implements nonlinear susceptibility magnitude imaging (SMI) with multifrequency intermodulation and phase encoding. An imaging grid was constructed of cylindrical wells of 3.5-mm diameter and 4.2-mm height on a hexagonal two-dimensional 61-voxel pattern with 5-mm spacing. Patterns of sample wells were filled with 40-μl volumes of Fe3O4 starch-coated magnetic nanoparticles (mNPs) with a hydrodynamic diameter of 100 nm and a concentration of 25 mg/ml. The imaging hardware was configured with three excitation coils and three detection coils in anticipation that a larger imaging system will have arrays of excitation and detection coils. Hexagonal and bar patterns of mNP were successfully imaged (R2>0.9) at several orientations. This SMI demonstration extends our prior work to feature a larger coil array, enlarged field-of-view, effective phase encoding scheme, reduced mNP sample size, and more complex imaging patterns to test the feasibility of extending the method beyond the pilot scale. The results presented in this study show that nonlinear SMI holds promise for further development into a practical imaging system for medical applications.