MPI Hardware and Instrumentation

At the Institute of Biomedical Imaging, a wide variety of instrumentation projects are carried out in the field of MPI research. Among others, various MPI subfields are investigated, such as the generation of efficient static magnetic fields, as well as the excitation of magnetic nanoparticles with arbitrary signals and their reception and hardware processing. In addition, a human-sized head scanner is operated and further developed, which is intended for long-term monitoring of patients with strokes.

Low-Power Iron Magnetic Field Generator

A major issue for human-sized magnetic particle imaging scanners is the generation of magnetic fields with sufficiently large magnetic field gradients. By exploiting the field enhancement properties of soft iron, a significant amount of power can be saved. Many different concepts for selection field generators have been introduced for Magnetic Particle Imaging. In this project, an optimized iron core selection field generator consisting of two coil arrays with a total of 18 coils was built ("Low-Power Iron Selection and Focus Field Generator"). Due to the high number of degrees of freedom, a wide variety of field configurations are possible with significantly less demands on infrastructure and cooling design. The setup allows the generation of arbitrarily shaped fields, including standard magnetic particle imaging fields such as field-free points and field-free lines ("Flexible Selection Field Generation using Iron Core Coil Arrays"). Due to the non-linear magnetization properties of the coil cores, the simulation of such generators is particular challenging. In practice, very specific fields must be set using the coil currents as degrees of freedom. Finding the correct currents for the given field constellation is a nonlinear inverse problem. This field generator serves the purpose of investigating the inverse problem within the context of MPI, magnetic manipulation of microdevices, and targeted drug delivery.

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Magnetic field measurement in our Low-Power Iron Magnetic Field Generator.

(Arbitrary) Magnetic Particle Spectroscopy

State-of-the-art systems utilize a sinusoidal excitation to drive superparamagnetic nanoparticles into the non-linear part of their magnetization curve, which creates a spectrum with a clear separation of direct feed-through and higher harmonics caused by the particles response. One challenge for arbitrary waveform excitation is the discrimination of particle and excitation signals, both broad-band. Another is the drive-field sequence itself, as particles that are not placed at the same spatial position, may react simultaneously and are not separable by their signal phase or shape. To overcome this potential loss of information in spatial encoding for high amplitudes, a superposition of shifting fields and drive-field rotations is proposed in "System Matrix Based Reconstruction for Pulsed Sequences in Magnetic Particle Imaging". Generating arbitrary excitation fields poses a new challenge in MPI hardware design. In the study "Model-based voltage predictions for arbitrary waveform excitation in Magnetic Particle Imaging", a method which models the excitation chain as a linear system and predicts the required input voltage for the desired output field. The initial prediction is then iteratively improved to compensate for inaccuracies of the model.

In order to calibrate the receive path, the recorded voltage is transferred to the device-indepedent domain of the magnetic moment. This enables the comparison of MPI signals from different devices and can be used to normalize measurements and system functions in devices with exchangeable receive coils. To achieve high accuracy, the transfer function is measured using a calibration procedure with a network analyzer and a well known calibration coil. A general description of the underlying calibration model and methodology is provided in "On the Receive Path Calibration of Magnetic Particle Imaging Systems", including a general multi-channel calibration procedure for inductive receive paths in MPI and a blueprint to investigate model and method uncertainties. We generalized the calibration procedure to also cover non-orthogonal and non-homogeneous receive coils, as well as present an uncertainty analysis on our custom MPS system and use the MPI transfer functions of misaligned receive coils.

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Cross sectional view of our pulsed MPS with the measurement chamber (top) and the gradiometer for feedthrough compensation (bottom).

Project Publications

[183663]
Title: The pitfalls of receive path calibration.
Written by: F. Thieben, T. Knopp, M. Boberg, F. Foerger, M. Graeser, and M. Möddel
in: <em>International Journal on Magnetic Particle Imaging IJMPI</em>. mar (2023).
Volume: <strong>9</strong>. Number: (1 Suppl 1),
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URL: https://www.journal.iwmpi.org/index.php/iwmpi/article/view/606
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Note: inproceedings, instrumentation

Abstract: In Magnetic Particle Imaging (MPI) and magnetic particle spectroscopy (MPS) magnetic nanoparticles (MNPs) are exposed to static and dynamic fields. These cause a dynamic magnetization response that is typically measured with inductive coils. The signal acquisition generally occurs in parallel with the excitation. This has the consequence that the excitation field couples into each receive path. The feed-through signal is commonly dampened by advanced passive filtering, at the cost of a distorted particle signal. Consequently, the measurement signals of different MPI or MPS devices will differ, even if the underlying magnetization response of the MNPs is the same. Receive path calibration can be used to address this issue by reverting these distortions and transforming the signal into a device independent domain. The authors of this abstract studied a general calibration procedure for multi-channel, non-orthogonal and non-homogeneous receive coils along with an analytical calibration model. Furthermore, method and model uncertainties were investigated and a systematic model error that had not been accounted for in previous calibration methods has been identified. This systematic model error could be attributed to the approximation of the mutual inductance between receive and calibration coil and it becomes non-negligible in experimental setups with small inductive receivers. Suggestionswere made for estimating and reducing its influence. Finally, the method was used to calibrate the receive path of an MPS system and of a multi-channel, non-orthogonal MPI receive coil setup.