Annelies Coene

Adaptive Control of Excitation Coil Arrays for Targeted Magnetic Nanoparticle Reconstruction Using Magnetorelaxometry

Magnetic nanoparticles are increasingly applied in biomedical diagnostic and therapeutic modalities. Due to their superparamagnetic properties it is possible to sense and manipulate these particles. In order to obtain the most effective operation of biomedical modalities and to achieve the highest comfort for the patients, it is essential to quantitatively assess the spatial distribution of the magnetic nanoparticles. From the various techniques available, magnetorelaxometry has a high potential for the spatial recovery of the concentration of magnetic nanoparticles. Through the correct interpretation of the measurements it is possible to quantitatively determine the spatial distribution of the particles concentration. We investigate an adaptive control technique that activates excitation coil arrays for targeted magnetic nanoparticle reconstruction.

Regarding the Néel relaxation time constant in magnetorelaxometry

Magnetorelaxometry (MRX) is a sensitive measurement technique frequently employed in biomedical applications for imaging magnetic nanoparticles (MNP). In this article, we employ a first principles model to investigate the effects of different iron oxide MNP sample properties on the Neel relaxation time constant τN in magnetorelaxometry. Using this model, we determined that dipolar interactions start to have an impact on the MRX signal from Fe concentrations of 100 mmol/l and result in a smaller τN. Additionally, the micromagnetic damping constant, closely related to τN, was found to be between 0.0005 and 0.002 by comparison to an MRX measurement of iron oxide particles. This is significantly lower compared to the bulk value of 0.07 for this material.

Dynamical Magnetic Response of Iron Oxide Nanoparticles Inside Live Cells

Magnetic nanoparticles exposed to alternating magnetic fields have shown a great potential acting as magnetic hyperthermia mediators for cancer treatment. However, a dramatic and unexplained reduction of the nanoparticle magnetic heating efficiency has been evidenced when nanoparticles are located inside cells or tissues. Recent studies suggest the enhancement of nanoparticle clustering and/or immobilization after interaction with cells as possible causes, although a quantitative description of the influence of biological matrices on the magnetic response of magnetic nanoparticles under AC magnetic fields is still lacking. Here, we studied the effect of cell internalization on the dynamical magnetic response of iron oxide nanoparticles (IONPs). AC magnetometry and magnetic susceptibility measurements of two magnetic core sizes (11 and 21 nm) underscored differences in the dynamical magnetic response following cell uptake with effects more pronounced for larger sizes. Two methodologies have been employed for experimentally determining the magnetic heat losses of magnetic nanoparticles inside live cells without risking their viability as well as the suitability of magnetic nanostructures for in vitro hyperthermia studies. Our experimental results-supported by theoretical calculations-reveal that the enhancement of intracellular IONP clustering mainly drives the cell internalization effects rather than intracellular IONP immobilization. Understanding the effects related to the nanoparticle transit into live cells on their magnetic response will allow the design of nanostructures containing magnetic nanoparticles whose dynamical magnetic response will remain invariable in any biological environments, allowing sustained and predictable in vivo heating efficiency.

Quantitative estimation of magnetic nanoparticle distributions in one dimension using low-frequency continuous wave electron paramagnetic resonance

In recent years, magnetic nanoparticles (MNPs) have gained increased attention due to their superparamagnetic properties. These properties allow the development of innovative biomedical applications such as targeted drug delivery and tumour heating. However, these modalities lack effective operation arising from the inaccurate quantification of the spatial MNP distribution. This paper proposes an approach for assessing the one-dimensional (1D) MNP distribution using electron paramagnetic resonance (EPR). EPR is able to accurately determine the MNP concentration in a single volume but not the MNP distribution throughout this volume. A new approach that exploits the solution of inverse problems for the correct interpretation of the measured EPR signals, is investigated. We achieve reconstruction of the 1D distribution of MNPs using EPR. Furthermore, the impact of temperature control on the reconstructed distributions is analysed by comparing two EPR setups where the latter setup is temperature controlled. Reconstruction quality for the temperature-controlled setup increases with an average of 5% and with a maximum increase of 13% for distributions with relatively lower iron concentrations and higher resolutions. However, these measurements are only a validation of our new method and form no hard limits.

Quantitative reconstruction of a magnetic nanoparticle distribution using a non-negativity constraint.

Magnetorelaxometry (MRX) is a non-invasive method for the specific quantification of magnetic nanoparticles (MNP). Here, we investigate experimentally the reconstruction of the MNP concentration in an extended volume. A phantom with varying but known MNP distribution was subsequently magnetized by 48 planar coils at different locations. The MRX signal was measured using the PTB 304 SQUID-magnetometer system. The inverse problem was solved by means of a non-negative least squares (NNLS) algorithm and compared to a minimum norm estimation (TSVD-MNE). The reconstruction by NNLS shows a deviation of the total MNP amount of less than 3 % (10% by TSVD-MNE). Hence, adapted non-invasive MRX methods can reliable reconstruct the MNP content in extended volumes.

Quantitative model selection for enhanced magnetic nanoparticle imaging in magnetorelaxometry

PURPOSE The performance of an increasing number of biomedical applications is dependent on the accurate knowledge of the spatial magnetic nanoparticle (MNP) distribution in the body. Magnetorelaxometry (MRX) imaging is a promising and noninvasive technique for the reconstruction of this distribution. To date, no accurate and quantitative measure is available to compare and optimize different MRX imaging models and setups independent of the MNP distribution. In this paper, the authors employ statistical parameters to develop quantitative MRX imaging models. Using these models, a straightforward optimization of setups and models is possible resulting in improved MNP reconstructions. METHODS A MRX imaging setup is considered with different coil configurations, each corresponding to a MRX imaging model. The models can be represented by a sensitivity matrix. These are compared by employing the matrices as inputs to statistical parameters such as conditional entropy and mutual information (MI). These parameters determine the best model to reconstruct the MNP amount for each volume-element (voxel) in the sample. The matrix is transformed by multiplying the columns with different weightings depending on the performance of the MRX imaging model with respect to the other models. This transformed matrix is compared to the original sensitivity matrix without weightings. RESULTS Compared to the original sensitivity matrix, an increased numerical stability and improved noise robustness for the transformed sensitivity matrix are observed. The reconstruction of the MNP shows improvements: a correlation to the actual MNP distribution of 99.2%, whereas the original matrix only had 82.5%. By selecting the MRX models with the smallest MI, the authors are able to reduce the measurement time by 65% and still obtain an improved imaging accuracy and noise robustness. The statistical parameters allow a direct measure of the relative information content within the setup such that the optimal voxel size for the MRX setup is determined to be between 5 and 15 mm, while other sizes show a significant change in the statistical parameters. CONCLUSIONS The use of statistical parameters in MRX imaging models results in quantitative models which can optimize MRX setups in a very fast and elegant way such that improved MNP imaging can be realized. Finally, the presented measure allows to quantitatively and accurately compare different MRX models and setups independent of the MNP distribution.

Thermal effects on transverse domain wall dynamics in magnetic nanowires

Magnetic domain walls are proposed as data carriers in future spintronic devices, whose reliability depends on a complete understanding of the domain wall motion. Applications based on an accurate positioning of domain walls are inevitably influenced by thermal fluctuations. In this letter, we present a micromagnetic study of the thermal effects on this motion. As spin-polarized currents are the most used driving mechanism for domain walls, we have included this in our analysis. Our results show that at finite temperatures, the domain wall velocity has a drift and diffusion component, which are in excellent agreement with the theoretical values obtained from a generalized 1D model. The drift and diffusion component are independent of each other in perfect nanowires, and the mean square displacement scales linearly with time and temperature.

Uncertainty of reconstructions of spatially distributed magnetic nanoparticles under realistic noise conditions

Magnetorelaxometry (MRX) is a measurement technique able to sense the magnetic field originating from magnetic nanoparticles (MNPs). The concentration distribution of MNPs can be recovered by interpreting the MRX measurement data with a numerical model, i.e., by solving an inverse problem. We investigate the actual impact of noise on the MNP reconstruction quality when using distributed excitation coil configurations and how the excitation setup needs to be adapted when prior information on the MRX noise is known. Results show that an approximately 4 times larger sensitivity can be attained when adapting the excitation setup to the known realistic noise. The proposed methodology is able to assess the sensitivity limits of the MRX measurement setup more accurately compared to convenient noise models.

Toward 2D and 3D imaging of magnetic nanoparticles using EPR measurements

PURPOSE Magnetic nanoparticles (MNPs) are an important asset in many biomedical applications. An effective working of these applications requires an accurate knowledge of the spatial MNP distribution. A promising, noninvasive, and sensitive technique to visualize MNP distributions in vivo is electron paramagnetic resonance (EPR). Currently only 1D MNP distributions can be reconstructed. In this paper, the authors propose extending 1D EPR toward 2D and 3D using computer simulations to allow accurate imaging of MNP distributions. METHODS To find the MNP distribution belonging to EPR measurements, an inverse problem needs to be solved. The solution of this inverse problem highly depends on the stability of the inverse problem. The authors adapt 1D EPR imaging to realize the imaging of multidimensional MNP distributions. Furthermore, the authors introduce partial volume excitation in which only parts of the volume are imaged to increase stability of the inverse solution and to speed up the measurements. The authors simulate EPR measurements of different 2D and 3D MNP distributions and solve the inverse problem. The stability is evaluated by calculating the condition measure and by comparing the actual MNP distribution to the reconstructed MNP distribution. Based on these simulations, the authors define requirements for the EPR system to cope with the added dimensions. Moreover, the authors investigate how EPR measurements should be conducted to improve the stability of the associated inverse problem and to increase reconstruction quality. RESULTS The approach used in 1D EPR can only be employed for the reconstruction of small volumes in 2D and 3D EPRs due to numerical instability of the inverse solution. The authors performed EPR measurements of increasing cylindrical volumes and evaluated the condition measure. This showed that a reduction of the inherent symmetry in the EPR methodology is necessary. By reducing the symmetry of the EPR setup, quantitative images of larger volumes can be obtained. The authors found that, by selectively exciting parts of the volume, the authors could increase the reconstruction quality even further while reducing the amount of measurements. Additionally, the inverse solution of this activation method degrades slower for increasing volumes. Finally, the methodology was applied to noisy EPR measurements: using the reduced EPR setups symmetry and the partial activation method, an increase in reconstruction quality of ≈ 80% can be seen with a speedup of the measurements with 10%. CONCLUSIONS Applying the aforementioned requirements to the EPR setup and stabilizing the EPR measurements showed a tremendous increase in noise robustness, thereby making EPR a valuable method for quantitative imaging of multidimensional MNP distributions.

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 types signal can be separated and its spatial distribution reconstructed. By assigning a unique color code and intensity to each particle types 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.