VP15-01 Shortening of Pre-data Acquisition Time in Magnetic Particle Imaging Using AC Susceptometry
Creators: Teruyoshi Sasayama
Naoya Futagawa and Takashi Yoshida
Publisher: name: IEEE
Year: 2025

Magnetic particle imaging (MPI) that employs magnetic nanoparticles (MNPs) to detect tumors, has attracted attention in recent years. Previously, we proposed MPI using a detection coil array that estimates the position of MNPs by obtaining a harmonic magnetic field from nonlinear magnetic responses and solving the inverse problem using a system matrix [1]. The time-consuming acquisition of the system matrix, for example, pre-data, affects the accuracy of the inverse problem analysis, mainly owing to temperature fluctuations in the excitation coils and electric circuits. In this study, we propose to reduce the acquisition time by fitting the system matrix computed using AC susceptometry (ACS) to the measured system matrix [2] and reducing the number of measurement points. Fig. 1 shows MPI using the detection coil array. A sinusoidal current with an amplitude of 1, 2, ..., 20 Apeak and a frequency of 5400 Hz was applied to the excitation coil to generate a magnetic field. Sixteen detection coils detected the third harmonic magnetic field from an MNP sample (Resovist, 100 μgFe), and a system matrix was constructed from the measured values. The spatial resolution was set to 5 mm × 5 mm, and the number of pixels was 39 × 25. Subsequently, the spatial resolution of the system matrix was reduced to 1/d times (d: natural number) in the x- and y-axis directions and fitted with a numerically computed system matrix. The results of the inverse problem analysis using nonnegative least squares were compared with the system matrices before and after reduction. Fig. 2 shows the results of the inverse problem before and after reduction. The results demonstrated that the position estimation performance of the MNPs was nearly maintained even after reduction. ACKNOWLEDGEMENTS This study was supported by the Japan Society for the Promotion of Science (JSPS) KAKENHI Grant Numbers JP23K20939 and JP20H05652.References: [1] T. Sasayama, T. Yoshida, and K. Enpuku, “Two-dimensional magnetic nanoparticle imaging using multiple magnetic sensors based on amplitude modulation,” J. Magn. Magn. Mater., vol. 505, Jul. 2020, Art. no. 166765. [2] N. Futagawa, M. Fujimoto, K. Higashino, T. Sasayama, and T. Yoshida, “Imaging of magnetic nanoparticles using AC susceptibility data,” IEEE Trans. Magn., vol. 59, no. 11, Nov. 2023, Art. no. 5101205.
Magnetic particle imaging (MPI) that employs magnetic nanoparticles (MNPs) to detect tumors, has attracted attention in recent years. Previously, we proposed MPI using a detection coil array that estimates the position of MNPs by obtaining a harmonic magnetic field from nonlinear magnetic responses and solving the inverse problem using a system matrix [1]. The time-consuming acquisition of the system matrix, for example, pre-data, affects the accuracy of the inverse problem analysis, mainly owing to temperature fluctuations in the excitation coils and electric circuits. In this study, we propose to reduce the acquisition time by fitting the system matrix computed using AC susceptometry (ACS) to the measured system matrix [2] and reducing the number of measurement points. Fig. 1 shows MPI using the detection coil array. A sinusoidal current with an amplitude of 1, 2, ..., 20 Apeak and a frequency of 5400 Hz was applied to the excitation coil to generate a magnetic field. Sixteen detection coils detected the third harmonic magnetic field from an MNP sample (Resovist, 100 μgFe), and a system matrix was constructed from the measured values. The spatial resolution was set to 5 mm × 5 mm, and the number of pixels was 39 × 25. Subsequently, the spatial resolution of the system matrix was reduced to 1/d times (d: natural number) in the x- and y-axis directions and fitted with a numerically computed system matrix. The results of the inverse problem analysis using nonnegative least squares were compared with the system matrices before and after reduction. Fig. 2 shows the results of the inverse problem before and after reduction. The results demonstrated that the position estimation performance of the MNPs was nearly maintained even after reduction. ACKNOWLEDGEMENTS This study was supported by the Japan Society for the Promotion of Science (JSPS) KAKENHI Grant Numbers JP23K20939 and JP20H05652.References: [1] T. Sasayama, T. Yoshida, and K. Enpuku, “Two-dimensional magnetic nanoparticle imaging using multiple magnetic sensors based on amplitude modulation,” J. Magn. Magn. Mater., vol. 505, Jul. 2020, Art. no. 166765. [2] N. Futagawa, M. Fujimoto, K. Higashino, T. Sasayama, and T. Yoshida, “Imaging of magnetic nanoparticles using AC susceptibility data,” IEEE Trans. Magn., vol. 59, no. 11, Nov. 2023, Art. no. 5101205.