Journal of Radiation Industry (방사선산업학회지)

Korean Society of Radiation Industry (한국방사선산업학회)
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Analysis of Chemical Shift Artifacts Using the TSE Pulse Sequence and Bandwidth at MR Imaging

  • Hong, Mun Hwa (Department of Radiological Science, College of Bioecological Health, Shinhan University) ;
  • Lee, Min Hyeok (Department of Radiological Science, College of Bioecological Health, Shinhan University) ;
  • Lee, Song Yoon (Department of Radiological Science, College of Bioecological Health, Shinhan University) ;
  • Lee, Ju Yeon (Department of Radiological Science, College of Bioecological Health, Shinhan University) ;
  • Lee, Jin Gyung (Department of Radiological Science, College of Bioecological Health, Shinhan University) ;
  • Han, Jin (Department of Radiological Science, College of Bioecological Health, Shinhan University) ;
  • Kweon, Dae Cheol (Department of Radiological Science, College of Bioecological Health, Shinhan University)
  • Received : 2017.12.29
  • Accepted : 2018.02.12
  • Published : 2018.03.31

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Abstract

In order to experimentally analyze the artifacts of the chemical shift of water and oil, we made a phantom by mixing water and oil to change the turbo spin-echo (TSE) pulse sequence and various bandwidth (BW) and parameters. A phantom made of water and canola oil was prepared, and an eight-channel head coil of MRI 1.5 T and 3.0 T was used. The scan parameters were TR (5069 ms), TE (100 ms), water fat shift (0.999 and 1.891 pix) at 1.5 T and TR (3000 ms), TE (100 ms), and water fat shift (3.836 pix) at 3.0 T. In all sequences, a matrix ($256{\times}256$), field of view (FOV) (240 mm), and slice thickness were scanned at 3 mm; the frequency direction was RL (right-left), and the BW was calculated using the Philips ACR Bandwidth Calculator. The images were analyzed by obtaining the plot profile and the Fourier transform image. The signal-to-noise ratio (SNR), peak signal-to-noise ratio (PSNR), mean square error (MSE), root mean square error (RMSE), and maximum absolute error (MAE) were calculated to evaluate the images according to the 1.5T and 3.0T BWs of MR. In order to compare the image of chemical shift artifact, the layer of the chemical shift artifact was larger than that of 1.5T of BW 114.9 Hz compared to 217.5 Hz, and at 3.0T, 113.2 Hz compared to 218.1 Hz, and chemical shift artifact. The spatial frequency changes due to the Fourier transform were 1.5T and 3.0T. The reference image (BW 55.7 kHz) and the test image (BW 29.4 kHz) had the SNR of 7.753 dB, PSNR of 22.869 dB, RMSE of 26.808, and MAE of 7.758 in the 1.5T MRI. The reference image (BW 55.9 kHz) and the test image (BW 29 kHz) had the SNR of 17.79 dB, PSNR of 34.062 dB, RMSE of 33.401, and MAE of 5.971 in the 3.0 T MRI. The SNR and PSNR were measured at 1.5T and 3.0T when the BW parameter was changed. At the 1.5 T and 3.0 T MRI, there was a statistically significant difference (p-value<.05). The chemical shift artifacts occurred in the phantom of water and oil, and the artifact was less at 1.5 T than at 3.0 T, and the artifact decreased as the BW increased. In order to reduce the chemical shift artifact in MRI, it is considered appropriate to decrease the intensity of the field and to broaden the BW.

Keywords

References

  1. Ann HW, Moon JH, Lee DI, Lee TH, Jeong JG and Kweon DC. 2017. Measurement of MR pulse sequence for acoustic noise and image quality of opening and closing door in 1.5 T and 3.0 T MRI scanning room. J. Radiat. Indt. 11(4):227-233.
  2. Antoine JP, Coron A and Dereppe JM. 2000. Water peak suppression: time-frequency vs time-scale approach. J. Magn. Reson. 144:189-194. https://doi.org/10.1006/jmre.1999.2011
  3. Cabanes E, Confort-Gouny S, Le Fur Y, Simond G and Cozzone PJ. 2001. Optimization of residual water signal removal by HLSVD on simulated short echo time proton MR spectra of the human brain. J. Magn. Reson. 150:116-125. https://doi.org/10.1006/jmre.2001.2318
  4. Douis H, Davies AM, Jeys L and Sian P. 2016. Chemical shift MRI can aid in the diagnosis of indeterminate skeletal lesions of the spine. Eur. Radiol. 26:932-940. https://doi.org/10.1007/s00330-015-3898-6
  5. Ghrare SE, Ali MAM, Ismail M and Jumari K. 2008. The effect of image data compression on the clinical information quality of compressed computed tomography images for teleradiology applications. Eur. J. Sci. Res. 23:6-12.
  6. Gonzalez RC and Woods RE. 2008. Digital image processing, third edition, Prentice Hall.
  7. Goo EH. 2016. The evaluation of image quality in gradient echo MRI of the pancreas: comparison with 2D T1 FFE and 3D T1 THRIVE imaging. J. Korean Soc. Radiol. 10:71-79.
  8. Goo EH and Dong KR. 2016. Quantitative and Qualitative Evaluation of Brain Diffusion Weighted Magnetic Resonance Imaging: Comparison with 1.5 T and 3.0 T Units. J. Radiat. Indt. 10(4):227-230.
  9. Hayes CE and Roemer PB. 1990. Noise correlations in data simultaneously acquired from multiple surface coil arrays. Magn. Reson. Med. 16:181-191. https://doi.org/10.1002/mrm.1910160202
  10. Herrick RC, Hayman LA, Taber KH, Diaz-Marchan PJ and Kuo MD. 1997. Artifacts and pitfalls in MR imaging of the orbit: A clinical review. Radiographics 17:707-724. https://doi.org/10.1148/radiographics.17.3.9153707
  11. Kanematsu M, Hoshi H, Itoh K, Murakami T, Hori M, Kondo H, Yokoyama R and Nakamura H. 1999. Focal hepatic lesion detection: comparison of four fat suppressed T2-weighted MR imaging pulse sequences. Radiology 211:363-371. https://doi.org/10.1148/radiology.211.2.r99ma23363
  12. Keogan MT and Eldelman RR. 2001. Technologic advances in abdominal MR imaging. Radiology 220:310-320. https://doi.org/10.1148/radiology.220.2.r01au22310
  13. Kweon DC. 2016. Experimental study of chemical shift artifacts at 1.5 T and 3.0 T MRI using gradient echo pulse sequence. J. Korean. Soc. Radiol. 10:530-537.
  14. Masuda J, Nabika T and Notsu Y. 2001. Silent stroke: pathogenesis, genetic factors and clinical implications as a risk factor. Curr. Opin. Neurol. 14:77-82. https://doi.org/10.1097/00019052-200102000-00012
  15. Pauleit D, Textor J, Bachmann R, Conrad R, Flacke S, Kreft B and Schild H. 2001. Improving the detectability of focal liver lesions on T2-weighted MR images: ultrafast breath-hold or respiratory-triggered thin-section MRI? J. Magn. Reson. Imaging. 14:128-133. https://doi.org/10.1002/jmri.1162
  16. Priolaa AM, Priolaa SM, Gneda D, Giraudob MT, Fornaric A and Veltria A. 2016. Comparison of CT and chemical-shift MRI for differentiating thymoma from non-thymomatous conditions in myasthenia gravis: value of qualitative and quantitative assessment. Clin. Radiol. 71:157-169. https://doi.org/10.1016/j.crad.2015.12.009
  17. Ragab Y, Emad Y, Gheita T, Mansour M, Abou-Zeid A, Ferrari S and Rasker JJ. 2009. Differentiation of osteoporotic and neoplastic vertebral fractures by chemical shift (in-phase and out-of phase) MR imaging. Eur. J. Radiol. 72:125-133. https://doi.org/10.1016/j.ejrad.2008.06.019
  18. Roemer PB, Edelstein WA, Hayes CE, Souza SP and Mueller OM. 1990. The NMR phased array. Magn. Reson. Med. 16:192-225. https://doi.org/10.1002/mrm.1910160203
  19. Ward J. 2006. New MR techniques for the detection of liver metastases. Cancer Imaging 6:33-42. https://doi.org/10.1102/1470-7330.2006.0007
  20. Zhu C, Haraldsson H, Faraji F, Owens C, Gasper W, Ahn S, Liu J, Laub G, Hope MD and Saloner D. 2016. Isotropic 3D black blood MRI of abdominal aortic aneurysm wall and intraluminal thrombus. Magn. Reson. Imaging 34:18-25. https://doi.org/10.1016/j.mri.2015.10.002