Simple and practical method for correcting the inhomogeneous sensitivity of a receiving coil in magnetic particle imaging

Murase, Kenya; Banura, Natsuo; Mimura, Atsushi; Nishimoto, Kohei

doi:10.7567/jjap.54.038001

Cited by 14 publications

(16 citation statements)

References 9 publications

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“…Each projection data set was then transformed into 64 bins by linear interpolation. Both the inhomogeneous sensitivity of the receiving coil and feed through interference were corrected using the method described in [12]. Transverse images were reconstructed from the projection data using the ML-EM algorithm over 15 iterations, in which the initial concentration of MNPs was assumed to be uniform [7] [8].…”

Section: Magnetic Particle Imagingmentioning

confidence: 99%

Application of Magnetic Particle Imaging to Pulmonary Imaging Using Nebulized Magnetic Nanoparticles

Nishimoto¹,

Mimura²,

Aoki

et al. 2015

OJMI

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Purpose: To investigate the feasibility of applying magnetic particle imaging (MPI) to pulmonary imaging using nebulized magnetic nanoparticles (MNPs) and to quantify the mucociliary clearance in the lung, using small animal experiments. Materials and Methods: Intrapulmonary administration of MNPs was performed in seven-week-old male ICR (Institute of Cancer Research) mice (n = 8) using a nebulized microsprayer connected to a high-pressure syringe containing 50 μL of MNPs (500 mM Resovist®). We imaged the lungs using our MPI scanner 2.5 hours, 1 day, 3 days, and 7 days after the intrapulmonary administration of MNPs. The average MPI value was calculated by drawing a region of interest (ROI) on the lungs by taking the threshold value for extracting the contour as 20% of the maximum MPI value within the ROI. The MPI value was defined as the pixel value of the transverse image reconstructed from the third-harmonic signals. Mice were sacrificed immediately after the last MPI and X-ray CT studies on day 7, and 5 lobes of the lung in each mouse were extracted to confirm the accumulation of iron using Berlin blue staining. Results: We could visualize the distribution of MNPs in the lungs as positive contrast using MPI with use of nebulized MNPs. The presence of iron in the lung was confirmed by Berlin blue staining. The average MPI value decreased with time and tended to saturate. The clearance rate was calculated to be 0.505 day −1 from the time course of the average MPI value in the lungs. Conclusion: Our preliminary results suggest that MPI can be applied to pulmonary imaging by nebulizing MNPs and can be useful for quantifying the mucociliary clearance in the lung.

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Section: Magnetic Particle Imagingmentioning

confidence: 99%

Application of Magnetic Particle Imaging to Pulmonary Imaging Using Nebulized Magnetic Nanoparticles

Nishimoto¹,

Mimura²,

Aoki

et al. 2015

OJMI

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“…Each projection data set was then transformed into 64 bins by linear interpolation. Both the inhomogeneous sensitivity of the receiving coil and feed through interference were corrected using the method described in [13]. Transverse images were reconstructed from the projection data using the ML-EM algorithm over 15 iterations, in which the initial concentration of MNPs was assumed to be uniform [9] [10].…”

Section: System For Magnetic Particle Imagingmentioning

confidence: 99%

Visualization of Magnetic Nanofibers Using Magnetic Particle Imaging

Murase

Mimura²,

Banura³

et al. 2015

OJMI

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Purpose: Magnetic nanofibers (MNFs) are nanofibers impregnated with magnetic nanoparticles (MNPs). Magnetic particle imaging (MPI) is a recently introduced imaging method that allows imaging of the spatial distribution of MNPs. The purpose of this study was to develop MNFs and to investigate the feasibility of visualizing them using MPI and of heating them using an alternating magnetic field (AMF). Materials and Methods: First, chitosan nanofibers were cross-linked with glutaraldehyde vapor in a sealed vial for 24 hours. Next, they were mixed with various concentrations of MNPs and the mixture was stirred for 1 hour using a magnetic stirrer. After the mixture was refrigerated at -80˚C for 24 hours, it was freeze-dried for 24 hours. The morphology of the resultant MNFs was characterized by scanning electron microscopy, and the magnetic properties were measured using a vibrating sample magnetometer. After these measurements, we imaged the MNFs using our MPI scanner, and investigated the correlation between the pixel values of the MPI image and the concentration of MNPs or the number of MNF sheets. We also heated the MNFs using AMF, and measured the temperature rise using an infrared thermometer. Results: The MNFs were successfully visualized using our MPI scanner, and the pixel values of the MPI image showed excellent correlation with the concentration of MNPs (r = 0.992) and the number of MNF sheets (r = 0.997). A significant temperature rise was observed under AMF, and the initial slope of the time-dependent temperature rise showed excellent correlation with the concentration of MNPs (r = 0.994) and the number of MNF sheets (r = 0.979). Conclusion: The MNFs developed in this study can be visualized using MPI and can be applied to magnetic hyperthermia. They will be useful in biomedicine including cancer therapy and tissue regeneration.

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“…A serious issue regarding signal detection in MPI is that the signal generated by MNPs is superimposed with the direct feed through interference of the excitation signal derived from the excitation coil generating the DMF, which directly couples with the receiving coil [9] [10]. Graeser et al proposed the combined use of a band-stop filter and the cancellation technique using a gradiometer coil to improve the MPI image quality [10].…”

Section: Introductionmentioning

confidence: 99%

“…Graeser et al proposed the combined use of a band-stop filter and the cancellation technique using a gradiometer coil to improve the MPI image quality [10]. We developed a simple and practical me-thod for correcting the inhomogeneous sensitivity of a receiving coil together with the feed through interference using a blank scan [9]. By combining the filtering method adopted by Graeser et al [10] and our method [9], we would expect that the reliability of our MPI system can be further enhanced.…”

Section: Introductionmentioning

confidence: 99%

“…We developed a simple and practical me-thod for correcting the inhomogeneous sensitivity of a receiving coil together with the feed through interference using a blank scan [9]. By combining the filtering method adopted by Graeser et al [10] and our method [9], we would expect that the reliability of our MPI system can be further enhanced. In this study, we investigated the effect of signal filtering with various analog filter modes on the image quality and quantitativity of the MPI images obtained by our projection-based MPI system using phantom studies.…”

Section: Introductionmentioning

confidence: 99%

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Effect of Signal Filtering on Image Quality of Projection-Based Magnetic Particle Imaging

Shimada¹,

Murase²

2017

OJMI

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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 backprojection (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.

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Simple and practical method for correcting the inhomogeneous sensitivity of a receiving coil in magnetic particle imaging

Cited by 14 publications

References 9 publications

Application of Magnetic Particle Imaging to Pulmonary Imaging Using Nebulized Magnetic Nanoparticles

Application of Magnetic Particle Imaging to Pulmonary Imaging Using Nebulized Magnetic Nanoparticles

Visualization of Magnetic Nanofibers Using Magnetic Particle Imaging

Effect of Signal Filtering on Image Quality of Projection-Based Magnetic Particle Imaging

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