Discussion and improvement methods of quantitative susceptibility mapping reconstruction_Journal of Biomedical Engineering

Authors：

 GUO Hongyu ^1,2 , YU Zhongnan ¹ , MA Gaochao ^1,2 , LI Chunsheng ¹

1. Institute of Biomedical Electromagnetic Engineering, Shenyang University of Technology, Shenyang 110870, P.R.China;
2. Neusoft Medical System, Shenyang 110167, P.R.China;

Corresponding author：

GUO Hongyu, Email: iuhongguo@163.com

Keywords：

quantitative susceptibility mapping; sophisticated harmonic artifact reduction for phase data; regularization enable of sophisticated harmonic artifact reduction for phase data; laplacian boundary value; truncated k-space division

DOI：

10.7507/1001-5515.201812014

Video：

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Abstract Full text Figures/Tables Video References Cited by

To assess the background field removal method usually used in quantitative susceptibility mapping (QSM), and to analyze the cause of serious artifacts generated in the truncated k-space division (TKD) method, this paper discusses a variety of background field removal methods and proposes an improved method to suppress the artifacts of susceptibility inversion. Firstly, we scanned phase images with the gradient echo sequence and then compared the quality and the speed of reconstructed images of sophisticated harmonic artifact reduction for phase data (SHARP), regularization enable of SHARP (RESHARP) and laplacian boundary value (LBV) methods. Secondly, we analyzed the reasons for reconstruction artifacts caused by the multiple truncations and discontinuity of the TKD method, and an improved TKD method was proposed by increasing threshold truncation range and improving data continuity. Finally, the result of susceptibility inversion from the improved and original TKD method was compared. The results show that the reconstruction of SHARP and RESHARP are very fast, but SHARP reconstruction artifacts are serious and the reconstruction precision is not high and implementation of RESHARP is complicated. The reconstruction speed of LBV method is slow, but the detail of the reconstructed image is prominent and the precision is high. In the QSM inversion methods, the reconstruction artifact of the original TKD method is serious, while the improved method obtains good artifact suppression image and good inversion result of artifact regions.

Citation： GUO Hongyu, YU Zhongnan, MA Gaochao, LI Chunsheng. Discussion and improvement methods of quantitative susceptibility mapping reconstruction. Journal of Biomedical Engineering, 2019, 36(6): 930-937. doi: 10.7507/1001-5515.201812014 Copy

1.	Bilgic B, Pfefferbaum A, Rohlfing T, et al. MRI estimates of brain iron concentration in normal aging using quantitative susceptibility mapping. Neuroimage, 2012, 59(3): 2625-2635.
2.	Haacke E M, Tang J, Neelavalli J, et al. Susceptibility mapping as a means to visualize veins and quantify oxygen saturation. J Magn Reson Imaging, 2010, 32(3): 663-676.
3.	Langkammer C, Schweser F, Krebs N A, et al. Quantitative susceptibility mapping (QSM) as a means to measure brain iron? A post mortem validation study. Neuroimage, 2012, 62(3): 1593-1599.
4.	Wang M, Li C F. Quantitative susceptibility mapping and its development in brain iron quantification. Chin Imaging J Integrat Traditional West Med, 2016, 14(1): 105-108.
5.	Chen Weiwei, Zhu Wenzhen, Kovanlikaya I I, et al. Intracranial calcifications and hemorrhages: characterization with quantitative susceptibility mapping. Radiology, 2014, 270(2): 496-505.
6.	王阿莉, 林建忠, 刘伟骏, 等. 定量磁化率成像重建方法及其应用. 波谱学杂志, 2014, 31(1): 133-154.
7.	Rauscher A, Barth M, Herrmann K H, et al. Improved elimination of phase effects from background field inhomogeneities for susceptibility weighted imaging at high magnetic field strengths. Magn Reson Imaging, 2008, 26(8): 1145-1151.
8.	Schweser F, Deistung A, Lehr B W, et al. Quantitative imaging of intrinsic magnetic tissue properties using MRI signal phase: an approach to in vivo brain iron metabolism?. Neuroimage, 2011, 54(4): 2789-2807.
9.	Sun Hongfu, Wilman A H. Background field removal using spherical mean value filtering and tikhonov regularization. Magnetic Resonance in Medicine, 2014, 71(3): 1151-1157.
10.	Zhou Dong, Liu Tian, Spincemaille P, et al. Background field removal by solving the Laplacian boundary value problem. NMR Biomed, 2014, 27(3): 312-319.
11.	Liu Tian, Khalidov I, de Rochefort L A, et al. A novel background field removal method for MRI using projection onto dipole fields (PDF). NMR Biomed, 2011, 24(9): 1129-1136.
12.	Liu Tian, Spincemaille P, de Rochefort L A, et al. Calculation of susceptibility through multiple orientation sampling (COSMOS): a method for conditioning the inverse problem from measured magnetic field map to susceptibility source image in MRI. Magnetic Resonance in Medicine, 2009, 61(1): 196-204.
13.	Shmueli K, de Zwart J A, van Gelderen P, et al. Magnetic susceptibility mapping of brain tissue in vivo using MRI phase data. Magnetic Resonance in Medicine, 2009, 62(6): 1510-1522.
14.	郑志伟, 蔡聪波, 蔡淑惠, 等. 定量磁化率成像的基本原理及方法概述. 磁共振成像, 2016, 7(6): 454-460.
15.	Abdul-Rahman H S, Gdeisat M A, Burton D R, et al. Fast and robust three-dimensional best path phase unwrapping algorithm. Appl Opt, 2007, 46(26): 6623-6635.
16.	Cusack R, Papadakis N. New robust 3-D phase unwrapping algorithms: application to magnetic field mapping and undistorting echoplanar images. Neuroimage, 2002, 16(3): 754-764.
17.	de Rochefort L, Liu Tian, Kressler B, et al. Quantitative susceptibility map reconstruction from MR phase data using bayesian regularization: validation and application to brain imaging. Magnetic Resonance in Medicine, 2010, 63(1): 194-206.
18.	Hallgren B, Sourander P. The effect of age on the non-haemin iron in the human brain. J Neurochem, 1958, 3(1): 41-51.

1. Bilgic B, Pfefferbaum A, Rohlfing T, et al. MRI estimates of brain iron concentration in normal aging using quantitative susceptibility mapping. Neuroimage, 2012, 59(3): 2625-2635.
2. Haacke E M, Tang J, Neelavalli J, et al. Susceptibility mapping as a means to visualize veins and quantify oxygen saturation. J Magn Reson Imaging, 2010, 32(3): 663-676.
3. Langkammer C, Schweser F, Krebs N A, et al. Quantitative susceptibility mapping (QSM) as a means to measure brain iron? A post mortem validation study. Neuroimage, 2012, 62(3): 1593-1599.
4. Wang M, Li C F. Quantitative susceptibility mapping and its development in brain iron quantification. Chin Imaging J Integrat Traditional West Med, 2016, 14(1): 105-108.
5. Chen Weiwei, Zhu Wenzhen, Kovanlikaya I I, et al. Intracranial calcifications and hemorrhages: characterization with quantitative susceptibility mapping. Radiology, 2014, 270(2): 496-505.
6. 王阿莉, 林建忠, 刘伟骏, 等. 定量磁化率成像重建方法及其应用. 波谱学杂志, 2014, 31(1): 133-154.
7. Rauscher A, Barth M, Herrmann K H, et al. Improved elimination of phase effects from background field inhomogeneities for susceptibility weighted imaging at high magnetic field strengths. Magn Reson Imaging, 2008, 26(8): 1145-1151.
8. Schweser F, Deistung A, Lehr B W, et al. Quantitative imaging of intrinsic magnetic tissue properties using MRI signal phase: an approach to in vivo brain iron metabolism?. Neuroimage, 2011, 54(4): 2789-2807.
9. Sun Hongfu, Wilman A H. Background field removal using spherical mean value filtering and tikhonov regularization. Magnetic Resonance in Medicine, 2014, 71(3): 1151-1157.
10. Zhou Dong, Liu Tian, Spincemaille P, et al. Background field removal by solving the Laplacian boundary value problem. NMR Biomed, 2014, 27(3): 312-319.
11. Liu Tian, Khalidov I, de Rochefort L A, et al. A novel background field removal method for MRI using projection onto dipole fields (PDF). NMR Biomed, 2011, 24(9): 1129-1136.
12. Liu Tian, Spincemaille P, de Rochefort L A, et al. Calculation of susceptibility through multiple orientation sampling (COSMOS): a method for conditioning the inverse problem from measured magnetic field map to susceptibility source image in MRI. Magnetic Resonance in Medicine, 2009, 61(1): 196-204.
13. Shmueli K, de Zwart J A, van Gelderen P, et al. Magnetic susceptibility mapping of brain tissue in vivo using MRI phase data. Magnetic Resonance in Medicine, 2009, 62(6): 1510-1522.
14. 郑志伟, 蔡聪波, 蔡淑惠, 等. 定量磁化率成像的基本原理及方法概述. 磁共振成像, 2016, 7(6): 454-460.
15. Abdul-Rahman H S, Gdeisat M A, Burton D R, et al. Fast and robust three-dimensional best path phase unwrapping algorithm. Appl Opt, 2007, 46(26): 6623-6635.
16. Cusack R, Papadakis N. New robust 3-D phase unwrapping algorithms: application to magnetic field mapping and undistorting echoplanar images. Neuroimage, 2002, 16(3): 754-764.
17. de Rochefort L, Liu Tian, Kressler B, et al. Quantitative susceptibility map reconstruction from MR phase data using bayesian regularization: validation and application to brain imaging. Magnetic Resonance in Medicine, 2010, 63(1): 194-206.
18. Hallgren B, Sourander P. The effect of age on the non-haemin iron in the human brain. J Neurochem, 1958, 3(1): 41-51.

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