scholarly journals Magnetic Particle Imaging Using Second-Harmonic Response of Magnetization

2015 ◽  
pp. 1 ◽  
Keyword(s):  
Magnetic Particle ◽  
Second Harmonic ◽  
Harmonic Response ◽  
Magnetic Particle Imaging ◽  
Particle Imaging

scholarly journals Magnetic particle imaging signal acquisition using second harmonic detection of magnetic nanoparticles

2019 ◽  
Vol 15 (1) ◽  
pp. 221
Author(s):  
Muhammad Mahadi Abdul Jamil ◽  
Abdulkadir Abubakar Sadiq ◽  
Muhammad Shukri Ahmad ◽  
Noordin Asimi Mohd Noor ◽  
Nur Adilah Abd Rahman ◽  
...  
Keyword(s):  
Magnetic Particle ◽  
Second Harmonic ◽  
Harmonic Signal ◽  
Signal Amplitude ◽  
Gradient Field ◽  
Pickup Coil ◽  
Harmonic Detection ◽  
Magnetic Particle Imaging ◽  
Particle Imaging ◽  
Second Harmonic Signal

<p class="Abstract">This paper presents an approach for acquiring a magnetic particle imaging (MPI) signal, by utilizing the second harmonic detection of the magnetic nanoparticles tracers. An MPI signal with high signal-to-noise ratio (SNR) is crucial for high spatial resolution images that reveals the distribution of the tracers in a target area. Samples of Resovist and Perimag nanoparticles tracers were prepared in liquid and immobilised form, which were placed at some distances under the receiver coil of the single-sided MPI scanner. The samples were exposed to the excitation magnetic field generated at 22.8 kHz and a static gradient field generated with a direct current of 2 A. The non-linear magnetization response of the tracers for each spatial position is recorded in the form of voltage signal by a gradiometer pickup coil, with the second harmonic signal being extracted by a resonance circuit. The results obtained revealed that a sufficient signal from the tracers is recorded at up to 25 mm under the pickup coil, with Perimag samples inducing higher signals as compared to Resovist. The dependence of the DC gradient field on the second harmonic signal shows that the peak signal amplitude for Resovist and Perimag particles as ±5 mT and ±6 mT respectively. Additionally, the second harmonic signal amplitude increases exponentially with an increase in the excitation magnetic field. Thus, the results obtained shows the potential of this approach in acquiring high SNR MPI signals at low excitation frequency, which could be vital in reconstructing the contour images of the tracers, particularly in sentinel lymph node biopsy (SLNB) for breast cancer diagnosis.</p>

scholarly journals Flow velocity quantification by exploiting the principles of the Doppler effect and magnetic particle imaging

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Dennis Pantke ◽  
Florian Mueller ◽  
Sebastian Reinartz ◽  
Fabian Kiessling ◽  
Volkmar Schulz
Keyword(s):  
Flow Velocity ◽  
Magnetic Particle ◽  
Imaging Techniques ◽  
Radiation Risk ◽  
Medical Application ◽  
Velocity Estimation ◽  
Magnetic Particle Imaging ◽  
Measurable Velocity ◽  
Depth Dependency ◽  
Particle Imaging

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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