Quantitative susceptibility mapping of ultra-high resolution monkey brain in vivo at 9.4 T_Journal of Biomedical Engineering

Authors：

WEN Qingqing ^1,2 , YANG Hongyi ¹ ,  ZHONG Kai ^1,3,4

1. High Magnetic Field Laboratory, Chinese Academy of Sciences, Hefei 230031, P.R.China;
2. University of Chinese Academy of Sciences, Beijing 100049, P.R.China;
3. Key Laboratory of High Field Magnetic Resonance Imaging of Anhui Province, Hefei 230031, P.R.China;
4. CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, P.R.China;

Corresponding author：

ZHONG Kai, Email: kzhong@hmfl.ac.cn

Keywords：

high resolution; monkey brain in vivo; quantitative susceptibility mapping

DOI：

10.7507/1001-5515.201809009

Video：

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Quantitative susceptibility mapping (QSM) can provide tissue susceptibility information and has been adapted for clinical research and diagnosis. QSM of monkey brain in vivo at 9.4 T has not been demonstrated so far. In this study 9.4 T in vivo monkey brain QSM was performed with 200 μm isotropic high-resolution. It was found that the inherent singularity problem for QSM diverged significantly at ultra-high image resolution during regularization process and resulted in severe image artifacts. The K-space division (TKD) was applied to eliminate the artifacts, with an optimal threshold level between 0.2 and 0.3. High resolution QSM of monkey brain in vivo can thus provide a novel tool for brain research.

Citation： WEN Qingqing, YANG Hongyi, ZHONG Kai. Quantitative susceptibility mapping of ultra-high resolution monkey brain in vivo at 9.4 T. Journal of Biomedical Engineering, 2019, 36(3): 349-355. doi: 10.7507/1001-5515.201809009 Copy

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4.	Li Wei, Avram A V, Wu Bing, et al. Integrated Laplacian-based phase unwrapping and background phase removal for quantitative susceptibility mapping. NMR Biomed, 2014, 27(2): 219-227.
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8.	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. Magn Reson Med, 2009, 61(1): 196-204.
9.	Liu Tian, Xu Weiyu, Spincemaille P, et al. Accuracy of the morphology enabled dipole inversion (MEDI) algorithm for quantitative susceptibility mapping in MRI. IEEE Trans Med Imaging, 2012, 31(3): 816-824.
10.	Li Wei, Wu Bing, Liu Chunlei. Quantitative susceptibility mapping of human brain reflects spatial variation in tissue composition. Neuroimage, 2011, 55(4): 1645-1656.
11.	Schweser F, Deistung A, Sommer K. Toward online reconstruction of quantitative susceptibility maps: Superfast dipole inversion. Magn Reson Med, 2013, 69(6): 1581-1593.
12.	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.
13.	Magness C L, Fellin P C, Thomas M J, et al. Analysis of the Macaca mulatta transcriptome and the sequence divergence between Macaca and human. Genome Biol, 2005, 6(7): R60.
14.	Shively C A, Clarkson T B. The unique value of primate models in translational research. Am J Primatol, 2009, 71(9): 715-721.
15.	Haacke E M, Liu Saifeng, Buch S, et al. Quantitative susceptibility mapping: Current status and future directions. Magn Reson Imaging, 2015, 33(1): 1-25.
16.	Bilgic B, Chatnuntawech I, Fan A P, et al. Fast image reconstruction with L2-regularization. J Magn Reson Imaging, 2014, 40(1): 181-191.
17.	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.
18.	Persson N, Wu Jianlin, Zhang Qing, et al. Age and sex related differences in subcortical brain iron concentrations among healthy adults. Neuroimage, 2015, 122: 385-398.
19.	Liu Chunlei, Li Wei, Tong K A, et al. Susceptibility-weighted imaging and quantitative susceptibility mapping in the brain. J Magn Reson Imaging, 2015, 42(1): 23-41.
20.	Wang D M, Doddrell D M. A segmentation-based and partial-volume-compensated method for an accurate measurement of lateral ventricular volumes on T-1-weighted magnetic resonance images. Magn Reson Imaging, 2001, 19(2): 267-273.

1. De Rochefort L, Brown R, Prince M R, et al. Quantitative MR susceptibility mapping using piece-wise constant regularized inversion of the magnetic field. Magn Reson Med, 2008, 60(4): 1003-1009.
2. Haacke E M, Cheng N Y, House M J, et al. Imaging iron stores in the brain using magnetic resonance imaging. Magn Reson Imaging, 2005, 23(1): 1-25.
3. 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.
4. Li Wei, Avram A V, Wu Bing, et al. Integrated Laplacian-based phase unwrapping and background phase removal for quantitative susceptibility mapping. NMR Biomed, 2014, 27(2): 219-227.
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?. Neuroimage, 2011, 54(4): 2789-2807.
6. Liu T, Khalidov I, De Rochefort L, et al. A novel background field removal method for MRI using projection onto dipole fields (PDF). NMR Biomed, 2011, 24(9): 1129-1136.
7. 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. Magn Reson Med, 2010, 63(1): 194-206.
8. 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. Magn Reson Med, 2009, 61(1): 196-204.
9. Liu Tian, Xu Weiyu, Spincemaille P, et al. Accuracy of the morphology enabled dipole inversion (MEDI) algorithm for quantitative susceptibility mapping in MRI. IEEE Trans Med Imaging, 2012, 31(3): 816-824.
10. Li Wei, Wu Bing, Liu Chunlei. Quantitative susceptibility mapping of human brain reflects spatial variation in tissue composition. Neuroimage, 2011, 55(4): 1645-1656.
11. Schweser F, Deistung A, Sommer K. Toward online reconstruction of quantitative susceptibility maps: Superfast dipole inversion. Magn Reson Med, 2013, 69(6): 1581-1593.
12. 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.
13. Magness C L, Fellin P C, Thomas M J, et al. Analysis of the Macaca mulatta transcriptome and the sequence divergence between Macaca and human. Genome Biol, 2005, 6(7): R60.
14. Shively C A, Clarkson T B. The unique value of primate models in translational research. Am J Primatol, 2009, 71(9): 715-721.
15. Haacke E M, Liu Saifeng, Buch S, et al. Quantitative susceptibility mapping: Current status and future directions. Magn Reson Imaging, 2015, 33(1): 1-25.
16. Bilgic B, Chatnuntawech I, Fan A P, et al. Fast image reconstruction with L2-regularization. J Magn Reson Imaging, 2014, 40(1): 181-191.
17. 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.
18. Persson N, Wu Jianlin, Zhang Qing, et al. Age and sex related differences in subcortical brain iron concentrations among healthy adults. Neuroimage, 2015, 122: 385-398.
19. Liu Chunlei, Li Wei, Tong K A, et al. Susceptibility-weighted imaging and quantitative susceptibility mapping in the brain. J Magn Reson Imaging, 2015, 42(1): 23-41.
20. Wang D M, Doddrell D M. A segmentation-based and partial-volume-compensated method for an accurate measurement of lateral ventricular volumes on T-1-weighted magnetic resonance images. Magn Reson Imaging, 2001, 19(2): 267-273.

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