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基于二次谐波的磁性纳米颗粒样品空间定位方法研究

Research on Spatial Localization Method of Magnetic Nanoparticle Samples Based on Second Harmonic Waves.

作者信息

Wang Zheyan, Huang Ping, Zheng Fuyin, Yu Hongli, Li Yue, Qiu Zhichuan, Gai Lingke, Liu Zhiyao, Bai Shi

机构信息

School of Information Science and Engineering, Shenyang University of Technology, Shenyang 110870, China.

出版信息

Micromachines (Basel). 2024 Sep 30;15(10):1218. doi: 10.3390/mi15101218.

DOI:10.3390/mi15101218
PMID:39459091
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11509944/
Abstract

Existing magnetic tracer detection systems primarily rely on fundamental wave signal acquisition using non-differential sensor configurations. These sensors are highly susceptible to external interference and lack tomographic localization capabilities, hindering their clinical application. To address these limitations, this paper presents a novel method for achieving the deep spatial localization of tracers. The method exploits second harmonic signal detection at non-zero field points. By considering the combined nonlinear characteristics of the coil's axial spatial magnetic field distribution and the Langevin function, a correlation model linking the signal peak and bias field is established. This model enables the determination of the tracer's precise spatial location. Building on this framework, a handheld device for localizing magnetic nanoparticle tracers was developed. The device harnesses the second harmonic response generated by coupling an AC excitation field with a DC bias field. Our findings demonstrate that under conditions of reduced coil turns and weak excitation fields, the DC bias field exhibits exclusive dependence on the axial distance of the detection point, independent of particle concentration. This implies that the saturated DC bias field corresponding to the second harmonic signal can be used to determine the magnetic nanoparticle sample detection depth. The experimental results validated the method's high accuracy, with axial detection distance and concentration reduction errors of only 4.8% and 4.1%, respectively. This research paves the way for handheld probes capable of tomographic tracer detection, offering a novel approach for advancing magnetically sensitive biomedical detection technologies.

摘要

现有的磁示踪剂检测系统主要依靠使用非差分传感器配置来采集基波信号。这些传感器极易受到外部干扰,并且缺乏断层定位能力,这阻碍了它们的临床应用。为了解决这些局限性,本文提出了一种实现示踪剂深度空间定位的新方法。该方法利用在非零场点处检测二次谐波信号。通过考虑线圈轴向空间磁场分布和朗之万函数的组合非线性特性,建立了一个将信号峰值与偏置场联系起来的相关模型。该模型能够确定示踪剂的精确空间位置。基于此框架,开发了一种用于定位磁性纳米颗粒示踪剂的手持设备。该设备利用交流激励场与直流偏置场耦合产生的二次谐波响应。我们的研究结果表明,在减少线圈匝数和弱激励场的条件下,直流偏置场仅依赖于检测点的轴向距离,而与颗粒浓度无关。这意味着对应于二次谐波信号的饱和直流偏置场可用于确定磁性纳米颗粒样品的检测深度。实验结果验证了该方法的高精度,轴向检测距离和浓度降低误差分别仅为4.8%和4.1%。这项研究为能够进行断层示踪剂检测的手持探头铺平了道路,为推进磁敏生物医学检测技术提供了一种新方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4f9/11509944/ff83eac4232c/micromachines-15-01218-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4f9/11509944/c40064e34386/micromachines-15-01218-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4f9/11509944/ab8297bf5f36/micromachines-15-01218-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4f9/11509944/283ce6d56cd9/micromachines-15-01218-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4f9/11509944/2d7d680e2cfe/micromachines-15-01218-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4f9/11509944/1ac94726b04a/micromachines-15-01218-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4f9/11509944/63490b1895a5/micromachines-15-01218-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4f9/11509944/118026c337cc/micromachines-15-01218-g007a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4f9/11509944/ec96dd797104/micromachines-15-01218-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4f9/11509944/3a2631e1e673/micromachines-15-01218-g009a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4f9/11509944/ff83eac4232c/micromachines-15-01218-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4f9/11509944/c40064e34386/micromachines-15-01218-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4f9/11509944/ab8297bf5f36/micromachines-15-01218-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4f9/11509944/283ce6d56cd9/micromachines-15-01218-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4f9/11509944/2d7d680e2cfe/micromachines-15-01218-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4f9/11509944/1ac94726b04a/micromachines-15-01218-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4f9/11509944/63490b1895a5/micromachines-15-01218-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4f9/11509944/118026c337cc/micromachines-15-01218-g007a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4f9/11509944/ec96dd797104/micromachines-15-01218-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4f9/11509944/3a2631e1e673/micromachines-15-01218-g009a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4f9/11509944/ff83eac4232c/micromachines-15-01218-g010.jpg

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