Partial FOV Center Imaging (PCI): A Robust X-Space Image Reconstruction for Magnetic Particle Imaging

Abstract

Magnetic Particle Imaging (MPI) is an emerging medical imaging modality that images the spatial distribution of superparamagnetic iron oxide (SPIO) nanoparticles using their nonlinear response to applied magnetic fields. In standard x-space approach to MPI, the image is reconstructed by gridding the speed-compensated nanoparticle signal to the instantaneous position of the field free point (FFP). However, due to safety limits on the drive field, the field-of-view (FOV) needs to be covered by multiple relatively small partial field-of-views (pFOVs). The image of the entire FOV is then pieced together from individually processed pFOVs. These processing steps can be sensitive to non-ideal signal conditions such as harmonic interference, noise, and relaxation effects. In this work, we propose a robust x-space reconstruction technique, Partial FOV Center Imaging (PCI), with substantially simplified pFOV processing. PCI first forms a raw image of the entire FOV by mapping MPI signal directly to pFOV center locations. The corresponding MPI image is then obtained by deconvolving this raw image by a compact kernel, whose fully-known shape solely depends on the pFOV size. We analyze the performance of the proposed reconstruction via extensive simulations, as well as imaging experiments on our in-house FFP MPI scanner. The results show that PCI offers a trade-off between noise robustness and interference robustness,

Magnetic particle imaging: tracer development and the biomedical applications of a radiation-free, sensitive, and quantitative imaging modality

“…Nowadays, x-space processes have received more research attention and are more frequently implemented. 22,[71][72][73] In these processes, a fast reconstruction algorithm computes the MPI image without any requirement for pre-characterisation, modelling, and matrix inversions, 32 resulting in robust, real-time imaging. An x-space MPI image is reconstructed from a raw MPI signal through a simple two-step process of velocity compensation of the received signal, followed by gridding of said signal to the instantaneous position of the FFP.…”

The Reconstruction of Magnetic Particle Imaging: Current Approaches Based on the System Matrix

“…MPI is a new biomedical imaging modality that images the distribution of SPIONs. Some researchers adopt mathematical models to describe the physical process, like the equilibrium model [ 25 ] or its variations, the x-space approach [ 3 , 26 , 27 , 28 ], Chebyshev polynomials [ 29 ], and analytic inversion formulas [ 30 , 31 ]. The state-of-the-art reconstruction techniques adopt the experimentally calibrated forward operators, called the SM-based image reconstruction [ 32 , 33 ].…”

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