Spherical measurement-based analysis of gradient nonlinearity in magnetic resonance imaging_Journal of Biomedical Engineering

Authors：

YANG Xiaoli ^1,2 , WANG Zhaolian ^1,3 , WANG Qian ^1,3 , ZHANG Yiting ¹ , SONG Zixuan ¹ , ZHANG Yuchang ¹ , QI Yafei ⁴ ,  MA Xiaopeng ²

1. Weifang Xinli Superconducting Magnet Technology Co., Ltd., Weifang, Shandong 261071, P. R. China;
2. School of Control Science and Engineering, Shandong University, Jinan 250061, P. R. China;
3. Shandong Huate Magnet Technology Co., Ltd., Weifang, Shandong 262619, P. R. China;
4. Department of Radiology, Qilu Hospital of Shandong University, Jinan 250012, P. R. China;

Corresponding author：

MA Xiaopeng, Email: xiaopeng.ma@sdu.edu.cn

Keywords：

Magnetic resonance imaging; Gradient coils; Gradient magnetic field calculation; Gradient nonlinearity

DOI：

10.7507/1001-5515.202401068

Video：

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The gradient field, one of the core magnetic fields in magnetic resonance imaging (MRI) systems, is generated by gradient coils and plays a critical role in spatial encoding and the generation of echo signals. The uniformity or linearity of the gradient field directly impacts the quality and distortion level of MRI images. However, traditional point measurement methods lack accuracy in assessing the linearity of gradient fields, making it difficult to provide effective parameters for image distortion correction. This paper introduced a spherical measurement-based method that involved measuring the magnetic field distribution on a sphere, followed by detailed magnetic field calculations and linearity analysis. This study, applied to assess the nonlinearity of asymmetric head gradient coils, demonstrated more comprehensive and precise results compared to point measurement methods. This advancement not only strengthens the scientific basis for the design of gradient coils but also provides more reliable parameters and methods for the accurate correction of MRI image distortions.

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13.	Retif P, Djibo Sidikou A, Mathis C, et al. Evaluation of the ability of the brainlab elements cranial distortion correction algorithm to correct clinically relevant MRI distortions for cranial SRT. Strahlenther Onkol, 2022, 198(10): 907‐918.
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1. 杨正汉, 冯逢, 郑卓肇, 等. 磁共振成像技术指南. 第2版. 北京: 中国协和医科大学出版社, 2023.
2. 张宇翔, 何为, 杨磊, 等. 移动式无屏蔽超低场磁共振成像系统研究. 生物医学工程学杂志, 2023, 40(5): 829-836.
3. Rodríguez-Soto A E, Fang L K, Holland D, et al. Correction of artifacts induced by B0 inhomogeneities in breast MRI using reduced-field-of-view echo-planar imaging and enhanced reversed polarity gradient method. J Magn Reson Imaging, 2021, 53(5): 1581-1591.
4. Dai E, Zhu A, Yang G K, et al. Frequency-dependent diffusion kurtosis imaging in the human brain using an oscillating gradient spin echo sequence and a high-performance head-only gradient. Neuroimage, 2023, 279: 120328.
5. Bardwell Speltz L J, Shu Y, Watson R E, et al. Evaluation of a compact 3 T MRI scanner for patients with implanted devices. Magn Reson Imaging, 2023, 103: 109-118.
6. Zhu M, Xia L, Liu F, et al. A finite difference method for the design of gradient coils in MRI—An initial framework. IEEE Trans Biomed Eng, 2012, 59(9): 2412-2421.
7. Zheng S, Li X, Yan W Q, et al. Gradient coils design with regularization method for superconducting magnetic resonance imaging// 2018 International Conference on Image and Vision Computing New Zealand (IVCNZ). Auckland: IEEE, 2018: 1-5.
8. Hidalgo‐Tobon S S. Theory of gradient coil design methods for magnetic resonance imaging. Concept Magn Reson A, 2010, 36(4): 223-242.
9. 贺红艳, 魏树峰, 王慧贤, 等. 矩阵梯度线圈研究现状与发展趋势. 波谱学杂志, 2021, 38(1): 140-153.
10. Winkler S A, Schmitt F, Landes H, et al. Gradient and shim technologies for ultra high field MRI. Neuroimage, 2018, 168: 59-70.
11. Langlois S, Desvignes M, Constans J M, et al. MRI geometric distortion: a simple approach to correcting the effects of non-linear gradient fields. J Magn Reson Imaging, 1999, 9(6): 821-831.
12. Janke A, Zhao H, Cowin G J, et al. Use of spherical harmonic deconvolution methods to compensate for nonlinear gradient effects on MRI images. Magn Reson Med, 2004, 52(1): 115-122.
13. Retif P, Djibo Sidikou A, Mathis C, et al. Evaluation of the ability of the brainlab elements cranial distortion correction algorithm to correct clinically relevant MRI distortions for cranial SRT. Strahlenther Onkol, 2022, 198(10): 907‐918.
14. Tao S, Trzasko J D, Gunter J L, et al. Gradient nonlinearity calibration and correction for a compact, asymmetric magnetic resonance imaging gradient system. Phys Med Biol, 2017, 62(2): N18-N31.
15. 王秋良. 磁共振成像系统的电磁理论与构造方法. 第1版. 北京: 科学出版社, 2018.
16. Yarach U, Luengviriya C, Danishad A, et al. Correction of gradient nonlinearity artifacts in prospective motion correction for 7T MRI. Magn Reson Med, 2015, 73(4): 1562-1569.
17. Koori N, Kamekawa H, Mukawa N, et al. Relationship between imaging parameters and distortion in magnetic resonance images for gamma knife treatment planning. J Appl Clin Med Phys, 2023, 24(12): e14205.
18. Eccles C D, Crozier S, Westphal M, et al. Temporal spherical-harmonic expansion and compensation of eddy-current fields produced by gradient pulses. J Magn Reson, 1993, 103(2): 135-141.
19. 俎栋林. 核磁共振成像仪-构造原理和物理设计. 第1版. 北京: 科学出版社, 2015.
20. Weavers P T, Tao S, Trzasko J D, et al. Image-based gradient non-linearity characterization to determine higher-order spherical harmonic coefficients for improved spatial position accuracy in magnetic resonance imaging. Magn Reson Imaging, 2017, 38: 54-62.

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