Abstract

Magnetic Particle Imaging (MPI) is a quantitative imaging modality with promising features for several biomedical applications. Here, we study quantitatively the raw data obtained during MPI measurements. We present a method for the calibration of the MPI scanner output using measurements from a magnetic particle spectrometer (MPS) to yield data in units of magnetic moments. The calibration technique is validated in a simplified MPI mode with a 1D excitation field. Using the calibrated results from MPS and MPI, we determine and compare the detection limits for each system. The detection limits were found to be 5·10-12 Am2 for MPS and 3.6·10-10 Am2 for MPI. Finally, the quantitative information contained in a standard MPI measurement with a 3D excitation is analyzed and compared to the previous results, showing a decrease in signal amplitudes of the odd harmonics related to the case of 1D excitation. We propose physical explanations for all acquired results; and discuss the possible benefits for the improvement of MPI technology.

Highlights

  • Magnetic Particle Imaging (MPI) is an emerging imaging modality with great potential for biomedical applications.[1]

  • The resulting calibration factor λ was used to scale all frequency components for each MPI measurement

  • A comparison of the calibrated A3 values measured with MPI and magnetic particle spectrometer (MPS) is displayed in figure 1a)

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Summary

Introduction

Magnetic Particle Imaging (MPI) is an emerging imaging modality with great potential for biomedical applications.[1] The technique utilizes the spectral response of magnetic nanoparticles (MNP) to oscillating magnetic excitation fields, in combination with a static gradient field, to generate a 3D image of the MNP distribution in an organism. The raw data obtained during an MPI measurement contain information on the amount of particles present at each location within the volume imaged. The impact of the different reconstruction algorithms and parameters on the quantities of the reconstructed particle distributions is not yet fully understood. To exclude potential influences of the reconstruction algorithms, we here focus on the quantitative information contained in the raw data of MPI measurements

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