AI Article Synopsis

  • Magnetic Particle Imaging (MPI) is a new 3D imaging technique that maps magnetic nanoparticles, but scaling it for human use is difficult due to limitations in the strength of generated magnetic fields.
  • Recent advancements in MPI have led to the development of a human-scale system using superconductors, achieving a magnetic field gradient of 2.5 T/m/μ within a 200 mm bore diameter.
  • This new system, while maintaining similar resolution to earlier animal-scale MPIs, represents a significant advancement toward making MPI viable for clinical applications.

Article Abstract

Magnetic Particle Imaging (MPI) is an emerging tomographic modality that allows for precise three-dimensional (3D) mapping of magnetic nanoparticles (MNPs) concentration and distribution. Although significant progress has been made towards improving MPI since its introduction, scaling it up for human applications has proven challenging. High-quality images have been obtained in animal-scale MPI scanners with gradients up to 7 T/m/μ, however, for MPI systems with bore diameters around 200 mm the gradients generated by electromagnets drop significantly to below 0.5 T/m/μ. Given the current technological limitations in image reconstruction and the properties of available MNPs, these low gradients inherently impose limitations on improving MPI resolution for higher precision medical imaging. Utilizing superconductors stands out as a promising approach for developing a human-scale MPI system. In this study, we introduce, for the first time, a human-scale amplitude-modulated (AM) MPI system with superconductor-based selection coils. The system achieves an unprecedented magnetic field gradient of up to 2.5 T/m/μ within a 200 mm bore diameter, enabling large fields of view of 100 × 130 × 98 mm at 2.5 T/m/μ for 3D imaging. While obtained spatial resolution is in the order of previous animal-scale AM MPIs, incorporating superconductors for achieving such high gradients in a 200 mm bore diameter marks a major step toward clinical MPI.

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http://dx.doi.org/10.1109/TMI.2024.3419427DOI Listing

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