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Magnetic Particle Imaging (MPI)

Magnetic Particle Imaging (MPI) is a novel tomographic method for determining the distribution of magnetic material in three dimensions. Similar to Magnetic Particle Spectroscopy (MPS), MPI is based on the nonlinear magnetization response of magnetic iron oxide nanoparticles (MNP) to dynamic magnetic fields. Additional strong magnetic field gradients are used to encode the field of view (FOV) by selectively generating higher harmonics near the encoding scheme. The encoding scheme can have different shapes, such as field-free point (FFP) or field-free line (FFL), which can be moved through the FOV in a variety of ways (trajectories) [1,2,3].

  • innovative 3D imaging
  • dynamic field-free line encoding
  • traveling wave MPI
  • 5 channel transmit system
  • bore size: 15 mm
  • gradient strength: up to 1 T/m
  • AQ time per 3D image: 20 ms
  • open Matlab interface

In 2025 we founded the Spin-Off Phase Vision to focus on the development of MPI, MPS and COMPASS systems.

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Similar to PET or SPECT, MPI is a tracer-based method, which comes with a lot of advantages, such as high spatial resolution [4], high sensitivity [5] and high temporal resolution [6]. These features build a promising new technology for different fields, such as material science, biology, chemistry, and medicine. Especially the latter field shows some interesting developments in the last decade, e.g., MPI as a promising tool for future intervention, such as PTA or stenting [7-12], but also novel scanner designs for human-sized applications [13-17].
Based on one novel scanner design, the pdMPI scanner is based on the traveling wave (TW) approach which uses a dynamic linear gradient array for the generation of the strong magnetic field gradient required for the spatial encoding [18, 19]. With this TWMPI technique, several unique features, such as real parallel MPI [20], superspeed MPI [21], zoom-MPI [22], or hybrid imaging with CT [15, 23] or MRI [24, 25] are connected. This provides new possibilities and new applications for MPI.
A further development of the encoding scheme allows for the first time a fully electrically controlled 3D movement of an FFL [26] in combination with a small and lightweight hardware design [15].

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The pdMPI device

Based on the TW-FFL technology, the pdMPI device provides the first benchtop 3D MPI scanner for research and education and gives an easy entry into the interesting field of MPI.
The pdMPI scanner is a highly flexible system, which comes with a fully 3D simulation framework [27], which not only allows a full emulation of the scanner but also image reconstruction and visualization (2D & 3D) in real-time [28, 29].
With the openMatlab interface, the pdMPI scanner can be easily adapted and integrated into established processes in industry, research, and education.
In the following, only few examples of FFL trajectories covering the data within the FOV of the scanner are shown. Until now, 10 different standard sequences are implemented but with the arbitrary adjustable frequencies, the pdMPI scanner can be set up for your application.

Highly flexible and modular setup:

  • vertical or horizontal scanner design
  • arbitrary sequences & trajectories
  • modular amplifier cabinet
  • gradient strength: up to 15 T/m
  • frequencies: DC…10 kHz
  • scalable bore size: up to 25 cm

[1]       B. Gleich & J. Weizenecker. Tomographic imaging using the nonlinear response of magnetic particles, Nature, vol. 435(7046), pp. 1217–1217, 2005.
[2]       J. Weizenecker et al. Magnetic Particle Imaging using a Field Free Line, J. Phys. D: Appl Phys, vol. 41:105009, 2008.
[3]       A. Neumann et al., Recent developments in Magnetic Particle Imaging, JMMM, vol. 500: 169037, 2022.
[4]       P. Vogel, et al., Micro-Traveling Wave Magnetic Particle Imaging – sub-millimeter resolution with optimized tracer LS-008, IEEE TMAG, vol. 55(10): 5300207, 2019.
[5]       M. Graeser, et al., Towards Picogram Detection of Superparamagnetic Iron-Oxide Particles Using a Gradiometric Receive Coil, Sci Rep, vol. 7:6872, 2017.
[6]       P. Vogel, et al., Superspeed Bolus Visualization for Vascular Magnetic Particle Imaging, IEEE TMI, vol. 39(6), pp. 2133-9, 2020.[7]       S. Herz, et al., Magnetic Particle Imaging-Guided Stenting, J Endovasc Ther, vol. 26(4), pp. 512-9, 2019.
[8]       S. Herz, et al., Magnetic particle imaging guided real-time percutaneous transluminal angioplasty in a phantom model, Cardiovasc Intervent Radiol, vol. 41(7), pp. 1100–5, 2018.[9]       J. Haegele, et al., Magnetic particle imaging: visualization of instruments for cardiovascular intervention, Radiology, vol. 265(3), pp. 933–8. 2012.
[10]     J. Sedlacik et al., Magnetic particle imaging for high temporal resolution assessment of aneurysm hemodynamics, PLoS ONE, vol. 11(8):e0160097, 2016.
[11]     J. Salamon, et al. Magnetic particle / magnetic resonance imaging: in-vitro MPI-guided real time catheter tracking and 4D angioplasty using a road map and blood pool tracer approach, PLoS ONE, vol. 11(6):e0156899, 2016.
[12]     J. Haegele et al., Toward cardiovascular interventions guided by magnetic particle imaging: first instrument characterization, Magn Reson Med, vol.69(6), pp. 1761-7, 2013.
[13]     M. Graeser et al., Human-sized magnetic particle imaging for brain applications, Nature Comm, vol. 10:1936, 2019.
[14]     E. E. Mason, et al. Design analysis of an MPI human functional brain scanner, Int. J. Magn. Part. Imaging, vol. 3(1):1703008, 2017.
[15]     P. Vogel et al. iMPI – portable human-sized Magnetic Particle Imaging Scanner for real-time endovascular Interventions, PREPRINT (Version 1) available at Research Square, doi:10.21203/rs.3.rs-2294644/v1, 2022
[16]     P. Vogel et al. Realtime iMPI-guided PTA with a lightweight human-sized MPI scanner, Int. J. Magn. Part. Imaging, vol. 9(1):2303024, 2023.
[17]     J. Günther et al. Human-sized Lightweight Head-Scanner Design, Int. J. Magn. Part. Imaging, vol. 8(1):2203064, 2022.
[18]     P. Vogel, et al. Traveling Wave Magnetic Particle Imaging, IEEE Trans Med Imaging., vol. 33(2), pp. 400–407, 2014.
[19]     P. Vogel et al., Dynamic Linear Gradient Array for Traveling Wave Magnetic Particle Imaging, IEEE Trans Magn, vol. 54(2): 5300109, 2018.
[20]     P. Vogel et al. Parallel Magnetic Particle Imaging, Rev. Sci. Instrum., vol. 91(4):045117, 2020.
[21]     P. Vogel et al. Suerspeed Traveling Wave Magnetic Particle Imaging, IEEE Trans Magn, vol. 51(2):6501603, 2015.
[22]     P. Vogel, et al., Adjustable hardware lens for Traveling Wave MPI, IEEE Trans Magn, vol. 56(11):5300506, 2020.
[23]     P. Vogel, et al., Magnetic Particle Imaging meets Computed Tomography: first simultaneous imaging, Sci Rep, vol. 9:12672, 2019.
[24]     P. Vogel et al. MRI meets MPI: a bimodal MPI-MRI tomograph, IEEE TMI, vol. 33(10), pp. 1954-9, 2014.
[25]     P. Klauer et al. Bimodal TWMPI-MRI Hybrid Scanner – Coil Setup and Electronics, IEEE Trans Magn, vol.51(2):5300504, 2015.
[26]     C. Greiner et al. Traveling Wave MPI utilizing a Field-Free Line, Int. J. Magn. Part. Imaging, vol. 8(1):2203027, 2022.
[27]     P. Vogel et al., Highly Flexible and Modular Simulation Framework for Magnetic Particle Imaging, arXiv:2208.13835, 2022.
[28]     P. Vogel, T. Kampf, M.A. Rückert, V.C. Behr, Flexible and Dynamic Patch Reconstruction for Traveling Wave Magnetic Particle Imaging, International Journal on MPI, vol. 2(2):1611001, 2016.
[29]     P. Vogel, et al., Low Latency Real-time Reconstruction for MPI Systems, Int. J. on MPI, vol. 3(2):1707002, 2017.
[30]     S. Herz et al. MPI-guided endovascular therapy of 3D printed human aneurysm, Int. J. on MPI, vol.9(1):2303065, 2023.

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