Magnetic particle imaging with a planar frequency mixing magnetic detection scanner

2014 ◽  
Vol 85 (1) ◽  
pp. 013705 ◽  
Author(s):  
Hyobong Hong ◽  
Jaeho Lim ◽  
Chel-Jong Choi ◽  
Sung-Woong Shin ◽  
Hans-Joachim Krause
2020 ◽  
Author(s):  
Jaechan Jeong ◽  
Jinsun Kim ◽  
Beomsu Seo ◽  
Hans Krause ◽  
Hyobong Hong

Abstract We present a magnetic particle imaging (MPI) device using a Halbach cuboid magnet and frequency mixing magnetic detection (FMMD) technology. A Field Free Line was formed in the center of a two-piece Halbach cuboid. Then, the cuboid was moved in the sample volume in a T-shaped and circular shape. The sample was exposed to a magnetic excitation field of two different frequencies. Due to the nonlinearity of the superparamagnetic iron oxide nanoparticles (SPIONs), harmonic frequencies and intermodulation products of the excitation frequencies are generated. This characteristic response signal from the particles was acquired by a coil system and demodulated by a FMMD electronics. Images were created by a backprojection method based on Radon and inverse Radon transformation. Using the Halbach cuboid, we were able to generate a stronger magnetic field compared to the previously reported equipment using large permanent magnets.. The results of the experiment showed that the combination of the Halbach cuboid and FMMD can acquire images similar to those of other existing MPI systems, suggesting that it is a method that has advantages in manufacturing and operation of MPI.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Dennis Pantke ◽  
Florian Mueller ◽  
Sebastian Reinartz ◽  
Fabian Kiessling ◽  
Volkmar Schulz

AbstractChanges in blood flow velocity play a crucial role during pathogenesis and progression of cardiovascular diseases. Imaging techniques capable of assessing flow velocities are clinically applied but are often not accurate, quantitative, and reliable enough to assess fine changes indicating the early onset of diseases and their conversion into a symptomatic stage. Magnetic particle imaging (MPI) promises to overcome these limitations. Existing MPI-based techniques perform velocity estimation on the reconstructed images, which restricts the measurable velocity range. Therefore, we developed a novel velocity quantification method by adapting the Doppler principle to MPI. Our method exploits the velocity-dependent frequency shift caused by a tracer motion-induced modulation of the emitted signal. The fundamental theory of our method is deduced and validated by simulations and measurements of moving phantoms. Overall, our method enables robust velocity quantification within milliseconds, with high accuracy, no radiation risk, no depth-dependency, and extended range compared to existing MPI-based velocity quantification techniques, highlighting the potential of our method as future medical application.


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