Abstract
Purpose: Magnetic particle imaging (MPI) allows for imaging of the spatial distribution of magnetic nanoparticles (MNPs) in positive contrast, with high sensitivity, high spatial resolution, and high imaging speed. It is necessary to increase the signal-to-noise ratio to enhance the reliability of MPI. The purpose of this study was to investigate the effect of signal filtering on the image quality and quantitativity in projection-based MPI using phantoms. Materials and Methods: We fabricated two kinds of phantom (cylindrical tube phantom with a diameter of 6 mm and A-shaped phantom) and evaluated the effect of signal filtering in terms of root-mean-square (RMS) granularity and the correlation coefficient between iron concentrations of MNPs and average MPI values for four filter modes (THRU, BPF, BEF, and LPF). In the THRU mode, the signal input was output without passing through the filter. In the BPF mode, only the third-harmonic signal was passed using a band-pass filter (central frequency: 1200 Hz, band width: 1/3 octave). In the BEF mode, the first-harmonic signal was eliminated using a band-elimination filter (central frequency: 400 Hz, band width: 1/3 octave). In the LPF mode, only the signal with a frequency less than the third-harmonic frequency was passed using a low-pass filter (cut-off frequency: 1200 Hz, -24 ± 2 dB/octave). The RMS granularity was obtained by calculating standard deviations of the pixel values in the MPI image without MNPs, whereas average MPI values were obtained by drawing a circular region of interest with a diameter of 6 mm on the MPI image of the cylindrical tube phantom. Results: When using the filtered back-projection (FBP) method with a ramp filter for image reconstruction, the RMS granularity and correlation coefficient decreased in the order of THRU, BPF, BEF, and LPF. In the BPF mode, however, some artifacts were observed. When using the maximum likelihood-expectation maximization (ML-EM) algorithm with an iteration number of 15, the correlation coefficient decreased in the order of THRU, BPF, BEF, and LPF, whereas the RMS granularity did not largely depend on the filter mode and was significantly (p < 0.05) lower than that for the FBP method for all the filter modes. Conclusion: The BEF mode is adequate for the FBP method in projection-based MPI, whereas THRU is a best option in use of the ML-EM algorithm.
Highlights
In 2005, a new imaging method called magnetic particle imaging (MPI) was introduced [1]
The BEF mode is adequate for the filtered backprojection (FBP) method in projection-based Magnetic particle imaging (MPI), whereas THRU is a best option in use of the maximum likelihood-expectation maximization (ML-EM) algorithm
There were excellent linear correlations between the iron concentration of magnetic nanoparticles (MNPs) and the average MPI value and the correlation coefficients exceeded 0.996 in all cases, the correlation coefficient slightly decreased in the order of THRU, BPF, BEF, and LPF (Table 1 and Table 2)
Summary
In 2005, a new imaging method called magnetic particle imaging (MPI) was introduced [1]. MPI uses the nonlinear magnetization response of magnetic nanoparticles (MNPs) to an alternating magnetic field called the drive magnetic field (DMF) and allows for imaging of the spatial distribution of MNPs in positive contrast, with high sensitivity, high spatial resolution, and high imaging speed [1]. When MNPs are located within the FFP or FFL, odd-harmonic signals are observed. When they are located outside the FFP or FFL, odd-harmonic signals are attenuated and alternatively even-harmonic signals are increased. Based on these phenomena, the spatial distribution of MNPs can be imaged by moving the position of the FFP or FFL, while receiving odd-harmonic signals. Since the third-harmonic signal is the largest of the odd-harmonic signals except for the first-harmonic signal, it is commonly used for signal detection in MPI [3]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
