|
|
|
| Magnetoacoustic Magnetic Particle Concentration Imaging Based on Improved Helical Gradient Coil |
| Yan Xiaoheng, Zhang Weiguang, Chen Weihua, Hou Xiaohan, Wang Zhiren |
| Faculty of Electrical and Control Engineering Liaoning Technology University Huludao 125000 China |
|
|
|
Abstract Magneto-acoustic concentration tomography of magnetic nanoparticles (MNPs) using magnetic induction (MACT-MI) represents a novel approach for MNPs concentration tomography.However, existing MACT-MI research is confronted with two major issues: “excessively high excitation current amplitude and poor uniformity of the gradient magnetic field”, which restrict the system′s miniaturization and clinical application. To address the above issues, this study starts with reducing current excitation and improving magnetic field uniformity, and designs a gradient coil to enhance the quality of the gradient magnetic field in the imaging area, thereby promoting experimental research. Firstly, this study proposed an “improved helical gradient coil” design method. Based on the discrete flow technique, it combines the existing helical coil with the circular coil to form an improved helical coil system. The external coil of this system can improve the problem of magnetic field non-uniformity at the imaging boundary. The Artificial lemming algorithm (ALA) was applied to the model, with the root mean square error of the magnetic flux density at 4 147 discrete points in the imaging area as the fitness function, and optimization was carried out under multiple physical constraints such as current, radius, and spacing. Compared with the traditional Maxwell, matrix, and improved target field method (TFM) gradient coils under the same gradient magnetic field conditions, the current excitation amplitude of the improved helical gradient coil was reduced by 67%, 64%, and 54% respectively, and the non-uniformity of the magnetic field in the imaging area was reduced by 70%, 65%, and 31% respectively. In addition, to evaluate the performance of the improved gradient coil, a multi-physical field forward problem simulation model of MACT-MI was built in COMSOL, nine sets of magnetite nanoparticles, identical in size and uniformly distributed, were constructed within the imaging region,and the physical process was solved. Under the gradient magnetic fields generated by the traditional Maxwell, matrix, and improved TFM gradient coils, the average relative deviations of the magnetic force were 7.56%, 2.95%, and 1.68% respectively, and the average relative deviations of the acoustic pressure signals were 5.64%, 2.79%, and 2.37% respectively; under the gradient magnetic field generated by the improved helical gradient coil, the average relative deviations of the magnetic force and acoustic pressure signal were 1.36% and 2.34% respectively. The average deviations of the magnetic force and acoustic pressure compared to the other three gradient coils have decreased, and the standard deviations have also decreased. To evaluate coil stability, analysis was conducted using standard deviation and 95% confidence intervals. The coil designed in this study exhibited the smallest standard deviation and no overlap within the 95% confidence interval, thereby validating the high stability of the gradient coil. The results show that the improved helical coil proposed in this paper is superior to the Maxwell coil, matrix coil, and improved TFM coil in both the amplitude of the pulse excitation and the non-uniformity of the gradient magnetic field. Moreover, magnetic nanoparticles experience lower magnetic force and acoustic pressure deviations compared to other coils, resulting in greater stability in the magnetic field generated by the coil.
|
|
Received: 24 June 2025
|
|
|
|
|
|
[1] 闫孝姮, 李政兴, 潘也, 等. 相同极性永磁体对感应式磁声磁粒子浓度成像过程影响的仿真[J]. 电工技术学报, 2022, 37(8): 1926-1937. Yan Xiaoheng, Li Zhengxing, Pan Ye, et al.Simulation of the influence of permanent magnets of the same polarity on the magneto-acoustic concentration tomography of magnetic nanoparticles with magnetic induction process[J]. Transactions of China Electro-technical Society, 2022, 37(8): 1926-1937. [2] Shi Xiaoyu, Liu Guoqiang, Yan Xiaoheng, et al.Simulation research on magneto-acoustic concentration tomography of magnetic nanoparticles with magnetic induction[J]. Computers in Biology and Medicine, 2020, 119: 103653. [3] 闫孝姮, 李政兴, 孙迪, 等. 基于矩阵式线圈的感应式磁声磁粒子浓度成像研究[J]. 电工技术学报, 2022, 37(17): 4269-4283. Yan Xiaoheng, Li Zhengxing, Sun Di, et al.Magnetoacoustic concentration tomography of magnetic nanoparticles with magnetic induction based on matrix coil[J]. Transactions of China Electro-technical Society, 2022, 37(17): 4269-4283. [4] 闫孝姮, 淡新贤, 陈伟华, 等. 基于改进目标场法梯度线圈的感应式磁声磁粒子浓度成像研究[J]. 电工技术学报, 2024, 39(14): 4305-4316. Yan Xiaoheng, Dan Xinxian, Chen Weihua, et al.Magneto-acoustic magnetic particle concentration imaging based on improved target field method gradient coil[J]. Transactions of China Electro-technical Society, 2024, 39(14): 4305-4316. [5] 张宇翔, 何为, 孔晓涵, 等. 基于硅钢片均一化的超低场磁共振抗涡流Z梯度线圈设计方法[J]. 电工技术学报, 2025, 40(4): 987-996. Zhang Yuxiang, He Wei, Kong Xiaohan, et al.A design method for eddy current-resistant Z-gradient coil in ultra-low field magnetic resonance imaging systems based on homogeneous of silicon steel sheets[J]. Transactions of China Electrotechnical Society, 2025, 40(4): 987-996. [6] Zhou Weiyong, Han Bangcheng, Wang Jing, et al.Design of uniform magnetic field coil by quasi-elliptic function fitting method with multiple optimizations in miniature atomic sensors[J]. IEEE Transactions on Industrial Electronics, 2022, 69(11): 11755-11764. [7] Forbes L K, Crozier S.A novel target-field method for finite-length magnetic resonance shim coils[J]. Journal of Physics D: Applied Physics, 2001, 34(24): 3447. [8] Zhang Peng, Shi Yikai, Wang Wendong, et al.A spiral, bi-planar gradient coil design for open magnetic resonance imaging[J]. Technology and Health Care, 2018, 26(1): 119-132. [9] Du Xiaoji, Zhu Zian, Zhao Ling, et al.Design of cylindrical transverse gradient coil for 1.5 T MRI system[J]. IEEE Transactions on Applied Superco-nductivity, 2012, 22(3): 4402004. [10] Wang Yaohui, Xin Xuegang, Liu Feng, et al.Spiral gradient coil design for use in cylindrical MRI systems[J]. IEEE Transactions on Biomedical Engineering, 2018, 65(4): 911-920. [11] Wu Wenfeng, Zhou Binquan, Liu Gang, et al.Novel nested saddle coils used in miniature atomic sensors[J]. AIP Advances, 2018, 8(7): 075126. [12] Wang Jing, Song Xinda, Le Yun, et al.Design of self-shielded uniform magnetic field coil via modified pigeon-inspired optimization in miniature atomic sensors[J]. IEEE Sensors Journal, 2021, 21(1): 315-324. [13] Zhou Weiyong, Han Bangcheng, Wang Jing, et al.Design of uniform magnetic field coil by quasi-elliptic function fitting method with multiple optimizations in miniature atomic sensors[J]. IEEE Transactions on Industrial Electronics, 2022, 69(11): 11755-11764. [14] Yan Xiaoheng, Pan Ye, Chen Weihua, et al.Simulation research on the forward problem of magnetoacoustic concentration tomography for magnetic nanoparticles with magnetic induction in a saturation magnetization state[J]. Journal of Physics D: Applied Physics, 2021, 54(7): 075002. [15] 闫孝姮, 王兵, 陈伟华, 等. 基于锥形铁心线圈的感应式磁声磁粒子浓度成像研究[J]. 电工技术学报, 2025, 40(16): 5204-5215. Yan Xiaoheng, Wang Bing, Chen Weihua, et al.Study on induction magneto-acoustic magnetic particle concentration imaging based on conical core coils[J]. Transactions of China Electrotechnical Society, 2025, 40(16): 5204-5215. [16] Wang Yaohui, Xin Xuegang, Liu Feng, et al.Spiral gradient coil design for use in cylindrical MRI systems[J]. IEEE Transactions on Biomedical Engineering, 2018, 65(4): 911-920. [17] Xu Jun, Kang Xiangyu, Fan Zhengkun, et al.Design of highly uniform magnetic field coils with wolf pack algorithm[J]. IEEE Sensors Journal, 2021, 21(4): 4412-4424. [18] Syu S S, Krishna M G, Yadav R, et al.Design of the stable homogeneous magnetic field calibration device generated by the circular coils[J]. IEEE Access, 2022, 10: 103401-103410. [19] Xiao Yaning, Cui Hao, Abu Khurma R, et al.Artificial lemming algorithm: a novel bionic meta-heuristic technique for solving real-world engineering optimization problems[J]. Artificial Intelligence Review, 2025, 58(3): 84. [20] Huang Kaiwen, Chieh J J, Yeh C K, et al.Ultrasound-induced magnetic imaging of tumors targeted by biofunctional magnetic nanoparticles[J]. ACS Nano, 2017, 11(3): 3030-3037. [21] Wang Jing, Song Xinda, Zhou Weiyong, et al.Hybrid optimal design of biplanar coils with uniform magnetic field or field gradient[J]. IEEE Transactions on Industrial Electronics, 2021, 68(11): 11544-11553. [22] Yan Xiaoheng, Sun Di, Li Zhengxing, et al.Simulation research on the forward problem of magneto-acoustic concentration tomography of magnetic nanoparticles with magnetic induction based on the relaxation time of magnetic nanoparticles[J]. IEEE Access, 2022, 10: 56057-56066. [23] 李英顺, 阚宏达, 郭占男, 等. 基于数据预处理和VMD-LSTM-GPR的锂离子电池剩余寿命预测[J]. 电工技术学报, 2024, 39(10): 3244-3258. Li Yingshun, Kan Hongda, Guo Zhannan, et al.Prediction of remaining useful life of lithium-ion battery based on data preprocessing and VMD-LSTM-GPR[J]. Transactions of China Electrotechnical Society, 2024, 39(10): 3244-3258. [24] 黄菁雯, 杜志叶, 徐箭, 等. 计及新能源出力和谐波的变压器热点温度修正模型[J]. 电力系统自动化, 2025, 49(16): 132-141. Huang Jingwen, Du Zhiye, Xu Jian, et al.Modified hotspot temperature model for transformers considering renewable energy output and harmonics[J]. Automation of Electric Power Systems, 2025, 49(16): 132-141. [25] 李奎, 张杰凯, 郭泽, 等. 基于触头电弧侵蚀的直流断路器电性能退化及剩余电寿命预测[J]. 电工技术学报, 2025, 40(16): 5330-5342. Li Kui, Zhang Jiekai, Guo Ze, et al.Model of electrical performance degradation and remaining life prediction for DC circuit breaker based on arc erosion[J]. Transactions of China Electrotechnical Society, 2025, 40(16): 5330-5342. |
|
|
|