Xiaoyu Shi1, Guoqiang Liu2, Xiaoheng Yan1, Yanhong Li3. 1. Faculty of Electrical and Control Engineering, Liaoning Technical University, Huludao, 125105, China; Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing, 100190, China. 2. Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing, 100190, China; School of Electronic Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 101407, China. Electronic address: gqliu@mail.iee.ac.cn. 3. Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing, 100190, China.
Abstract
BACKGROUND: Magnetic nanoparticles (MNPs) have been proposed as drug carriers for targeted therapy. Noninvasive imaging methods that can compute the distribution of MNPs have also attracted much attention. METHOD: Based on the Langevin theory, the theoretical relationship between the magnetic force and the concentration of MNPs was derived. The acoustic pressure wave equation containing the concentration of MNPs was established. RESULT: The acoustic pressure waveform reflected the dimension and position of the MNPs region. From reconstructed images, MNPs regions with different concentrations and different sizes were clearly distinguished. CONCLUSION: The concentration of MNPs can be parsed from the acoustic signals generated by particles vibrations. This conclusion indicates that magneto-acoustic concentration tomography of magnetic nanoparticles with magnetic induction (MACT-MI) has potential to detect and reconstruct the concentration of MNPs in biological tissue.
BACKGROUND: Magnetic nanoparticles (MNPs) have been proposed as drug carriers for targeted therapy. Noninvasive imaging methods that can compute the distribution of MNPs have also attracted much attention. METHOD: Based on the Langevin theory, the theoretical relationship between the magnetic force and the concentration of MNPs was derived. The acoustic pressure wave equation containing the concentration of MNPs was established. RESULT: The acoustic pressure waveform reflected the dimension and position of the MNPs region. From reconstructed images, MNPs regions with different concentrations and different sizes were clearly distinguished. CONCLUSION: The concentration of MNPs can be parsed from the acoustic signals generated by particles vibrations. This conclusion indicates that magneto-acoustic concentration tomography of magnetic nanoparticles with magnetic induction (MACT-MI) has potential to detect and reconstruct the concentration of MNPs in biological tissue.