Research Progress of Quantitative Susceptibility Mapping in MRI_Journal of Biomedical Engineering

Authors：

 WANGShuai ¹ , DUANChang ¹ , ZHANGPing ² , WANGChunmei ³ , LIUXiang ¹ , LIHongsheng ¹ , CHENGJian ¹

1. School of Electronic Engineering, University of Electronic Technology and Science of China, Chengdu 611731, China;
2. School of Optoelectronic Information, University of Electronic Technology and Science of China, Chengdu 611731, China;
3. School of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan 430205, China;

Corresponding author：

WANGShuai, Email: wangshuai0601@uestc.edu.cn

Keywords：

quantitative susceptibility mapping; magnetic susceptibility; ill-posed; inverse problem; de-convolution; quantify in vivo

DOI：

10.7507/1001-5515.20150200

Video：

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Abstract Full text Figures/Tables Video References Cited by

Magnetic susceptibility is an intrinsic physical quantity which describes the relationship between material magnetization and applied external magnetic field. Quantitative susceptibility mapping (QSM) is an MRI technology which can quantify the buck magnetic susceptibility of tissue in vivo. It is particularly effective at elucidating anatomy with paramagnetic or diamagnetic components. QSM technology is a method for solving the ill-pose problem of un-conventional de-convolution of the measured tissue magnetic field with the unit magnetic dipole field to obtain the susceptibility source map. Many multi orientation scan based QSM and clinically acceptable single orientation QSM methods have been proposed to solve this ill-posed problem. In this paper, the QSM concept is introduced and the various QSM methods are systematically categorized and discussed. The aim of this paper is to summarize the current research progress of QSM, popularize the knowledge of QSM and promote the improvements and the rational application of QSM in clinical field.

Citation： WANGShuai, DUANChang, ZHANGPing, WANGChunmei, LIUXiang, LIHongsheng, CHENGJian. Research Progress of Quantitative Susceptibility Mapping in MRI. Journal of Biomedical Engineering, 2015, 32(5): 1131-1134. doi: 10.7507/1001-5515.20150200 Copy

1.	LANGKAMMER C, SCHWESER F, KREBS N, et al. Quantitative susceptibility mapping (QSM) as a means to measure brain iron? A post mortem validation study[J]. Neuroimage, 2012, 62(3):1593-1599.
2.	LIU T, SRAPANENI K, LOU M, et al. Cerebral microbleeds:burden assessment by using quantitative susceptibility mapping[J]. Radiology, 2012, 262(1):269-278.
3.	LIU T, SPINCEMAILLE P, DE ROCHEFORT L, 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[J]. Magn Reson Med, 2009, 61(1):196-204.
4.	LIU J, LIU T, DE ROCHEFORT L, et al. Morphology enabled dipole inversion for quantitative susceptibility mapping using structural consistency between the magnitude image and the susceptibility map[J]. Neuroimage, 2012, 59(3):2560-2568.
5.	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?[J]. Neuroimage, 2011, 54(4):2789-2807.
6.	KRESSLER B, DE ROCHEFORT L, Liu T, et al. Nonlinear regularization for per voxel estimation of magnetic susceptibility distributions from MRI field maps[J]. IEEE Trans Med Imaging, 2010, 29(2):273-281.
7.	LIU T, KHALIDOV I, DE ROCHEFORT L, et al. A novel background field removal method for MRI using projection onto dipole fields (PDF)[J]. NMR Biomed, 2011, 24(9):1129-1136.
8.	WEN Y, ZHOU D, LIU T, et al. An iterative spherical mean value method for background field removal in MRI[J]. Magnet Reson Med, 2013,.
9.	SUN H, WILMAN A H. Background field removal using spherical mean value filtering and Tikhonov regularization[J]. Magnet Reson Med, 2013,.
10.	TOPFER R, SCHWESER F, DEISTUNG A, et al. SHARP edges:Recovering cortical phase contrast through harmonic extension[J]. Magnet Reson Med, 2014,.
11.	ZHOU D, LIU T, SPINCEMAILLE P, et al. Background field removal by solving the Laplacian boundary value problem[J]. NMR in Biomedicine, 2014,.
12.	SHMUELI K, DE ZWART J A, VAN GELDEREN P, et al. Magnetic susceptibility mapping of brain tissue in vivo using MRI phase data[J]. Magnet Reson Med, 2009, 62(6):1510-1522.
13.	LI W, WU B, LIU C. Quantitative susceptibility mapping of human brain reflects spatial variation in tissue composition[J]. Neuroimage, 2011, 55(4):1645-1656.
14.	DE ROCHEFORT L, LIU T, KRESSLER B, et al. Quantitative susceptibility map reconstruction from MR phase data using bayesian regularization:validation and application to brain imaging[J]. Magn Reson Med, 2010, 63(1):194-206.
15.	WANG S, LIU T, CHEN W, et al. Noise effects in various quantitative susceptibility mapping methods[J]. IEEE Trans Biomed Eng, 2013, 70(12):8.
16.	WU B, LI W, GUIDON A, et al. Whole brain susceptibility mapping using compressed sensing[J]. Magn Reson Med, 2012, 67(1):137-147.
17.	LIU T, WISNIEFF C, LOU M, et al. Nonlinear formulation of the magnetic field to source relationship for robust quantitative susceptibility mapping[J]. Magn Reson Med, 2013, 69(2):467-476.
18.	LIU T, XU W, SPINCEMAILLE P, et al. Accuracy of the morphology enabled dipole inversion (MEDI) algorithm for quantitative susceptibility mapping in MRI[J]. IEEE Trans Med Imaging, 2012, 31(3):816-824.
19.	范敬争, 李冠武, 田亚楠, et al. MR磁量图对自发性脑出血患者脑铁过量沉积的定量研究[J]. 磁共振成像, 2013, 4(2):99-103.
20.	CHEN W, ZHU W, KOVANLIKAYA I, et al. Intracranial calcifications and hemorrhages:characterization with quantitative susceptibility mapping[J]. Radiology, 2014, 270(2):496-505.
21.	WANG S, LOU M, LIU T, et al. Hematoma volume measurement in gradient echo MRI using quantitative susceptibility mapping[J]. Stroke, 2013, 44(8):2315-2317.
22.	REICHENBACH J R. The future of susceptibility contrast for assessment of anatomy and function[J]. Neuroimage, 2012, 62(2):1311-1315.

1. LANGKAMMER C, SCHWESER F, KREBS N, et al. Quantitative susceptibility mapping (QSM) as a means to measure brain iron? A post mortem validation study[J]. Neuroimage, 2012, 62(3):1593-1599.
2. LIU T, SRAPANENI K, LOU M, et al. Cerebral microbleeds:burden assessment by using quantitative susceptibility mapping[J]. Radiology, 2012, 262(1):269-278.
3. LIU T, SPINCEMAILLE P, DE ROCHEFORT L, 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[J]. Magn Reson Med, 2009, 61(1):196-204.
4. LIU J, LIU T, DE ROCHEFORT L, et al. Morphology enabled dipole inversion for quantitative susceptibility mapping using structural consistency between the magnitude image and the susceptibility map[J]. Neuroimage, 2012, 59(3):2560-2568.
5. 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?[J]. Neuroimage, 2011, 54(4):2789-2807.
6. KRESSLER B, DE ROCHEFORT L, Liu T, et al. Nonlinear regularization for per voxel estimation of magnetic susceptibility distributions from MRI field maps[J]. IEEE Trans Med Imaging, 2010, 29(2):273-281.
7. LIU T, KHALIDOV I, DE ROCHEFORT L, et al. A novel background field removal method for MRI using projection onto dipole fields (PDF)[J]. NMR Biomed, 2011, 24(9):1129-1136.
8. WEN Y, ZHOU D, LIU T, et al. An iterative spherical mean value method for background field removal in MRI[J]. Magnet Reson Med, 2013,.
9. SUN H, WILMAN A H. Background field removal using spherical mean value filtering and Tikhonov regularization[J]. Magnet Reson Med, 2013,.
10. TOPFER R, SCHWESER F, DEISTUNG A, et al. SHARP edges:Recovering cortical phase contrast through harmonic extension[J]. Magnet Reson Med, 2014,.
11. ZHOU D, LIU T, SPINCEMAILLE P, et al. Background field removal by solving the Laplacian boundary value problem[J]. NMR in Biomedicine, 2014,.
12. SHMUELI K, DE ZWART J A, VAN GELDEREN P, et al. Magnetic susceptibility mapping of brain tissue in vivo using MRI phase data[J]. Magnet Reson Med, 2009, 62(6):1510-1522.
13. LI W, WU B, LIU C. Quantitative susceptibility mapping of human brain reflects spatial variation in tissue composition[J]. Neuroimage, 2011, 55(4):1645-1656.
14. DE ROCHEFORT L, LIU T, KRESSLER B, et al. Quantitative susceptibility map reconstruction from MR phase data using bayesian regularization:validation and application to brain imaging[J]. Magn Reson Med, 2010, 63(1):194-206.
15. WANG S, LIU T, CHEN W, et al. Noise effects in various quantitative susceptibility mapping methods[J]. IEEE Trans Biomed Eng, 2013, 70(12):8.
16. WU B, LI W, GUIDON A, et al. Whole brain susceptibility mapping using compressed sensing[J]. Magn Reson Med, 2012, 67(1):137-147.
17. LIU T, WISNIEFF C, LOU M, et al. Nonlinear formulation of the magnetic field to source relationship for robust quantitative susceptibility mapping[J]. Magn Reson Med, 2013, 69(2):467-476.
18. LIU T, XU W, SPINCEMAILLE P, et al. Accuracy of the morphology enabled dipole inversion (MEDI) algorithm for quantitative susceptibility mapping in MRI[J]. IEEE Trans Med Imaging, 2012, 31(3):816-824.
19. 范敬争, 李冠武, 田亚楠, et al. MR磁量图对自发性脑出血患者脑铁过量沉积的定量研究[J]. 磁共振成像, 2013, 4(2):99-103.
20. CHEN W, ZHU W, KOVANLIKAYA I, et al. Intracranial calcifications and hemorrhages:characterization with quantitative susceptibility mapping[J]. Radiology, 2014, 270(2):496-505.
21. WANG S, LOU M, LIU T, et al. Hematoma volume measurement in gradient echo MRI using quantitative susceptibility mapping[J]. Stroke, 2013, 44(8):2315-2317.
22. REICHENBACH J R. The future of susceptibility contrast for assessment of anatomy and function[J]. Neuroimage, 2012, 62(2):1311-1315.

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