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生物医学微波热声成像

王雨 张慧敏 覃欢

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生物医学微波热声成像

王雨, 张慧敏, 覃欢

Biomedical microwave-induced thermoacoustic imaging

Wang Yu, Zhang Hui-Min, Qin Huan
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  • 微波热声成像是一种以生物组织电特性差异为原理基础的多物理场耦合成像方法. 其采用脉冲微波作为激发源, 通过热弹性效应产生的超声波呈递深层生物组织的结构与功能信息, 融合了微波成像高对比度和超声成像高分辨率的优点. 目前已在无损脑结构成像、乳腺肿瘤筛查、人体关节炎成像、肝脂肪含量检测等方面展现出了广阔的医学应用前景, 有望成为新的物理医学影像方法. 本文对微波热声成像技术的物理原理、系统装置以及近来的代表性研究进展进行了系统性的介绍, 并分析探讨了微波热声成像技术值得关注的发展方向以及面临的挑战.
    Microwave thermoacoustic imaging (MTAI) is an exciting imaging technique rooted from the underlying principle of exploiting the distinct electrical properties of biological tissues. By using short-pulsed microwaves as a stimulation source and their interaction with the human body, MTAI has paved the way for revolutionary advancements in medical imaging. When microwaves are absorbed by polar molecules and ions within the tissues, an ingenious thermoelastic effect gives rise to ultrasound waves. These ultrasound waves, brimming with invaluable pathological and physiological insights, propagate outward, carrying the essence of the composition and functionality of biological tissue. Through a meticulous collection of ultrasound signals from all directions surrounding the tissue, it becomes possible to reconstruct intricate internal structures and visualize the tissue's functional dynamics. The MTAI excels in non-invasiveness, capable of delving several centimeters beneath the surface with a microscopic resolution on the order of micrometers. The magic lies in converting microwave energy into ultrasound waves, entering into the hidden depths of tissues without causing harm. This groundbreaking imaging modality unlocks a realm of possibilities for acquiring profound insights into the intricate structures and functionality of deep-seated tissues. Furthermore, the inherent polarization characteristics of microwaves empower MTAI to capture additional dimensions of information, unraveling the intricate polarization properties and illuminating a richer understanding of the tissue's complexity. The great potential of MTAI extends far and wide within the medicine field. It has made remarkable achievements in non-invasive imaging of brain structures, screening breast tumors, visualizing human arthritis, and detecting liver fat content. These accomplishments have laid a solid foundation, firmly establishing MTAI as a trailblazing medical imaging technique. The present study offers a comprehensive and in-depth exploration of the physical principles underpinning MTAI, the sophisticated system devices involved, and the recent groundbreaking research breakthroughs. Moreover, it delves into the exciting prospects and challenges that lie ahead in the future development of MTAI. As the technology continues to progress by leaps and bounds, MTAI is ready to break down barriers, and usher in a new era of unmatched imaging quality and performance. This, in turn, will open the floodgates for transformative innovations and applications in medical diagnosis and treatment. The anticipation is palpable as MTAI strives to make substantial contributions to the ever-developing medical imaging field, bestowing upon humanity more accurate, reliable, and life-enhancing diagnostic capabilities.
      通信作者: 覃欢, qinghuan@scnu.edu.cn
    • 基金项目: 国家自然科学基金(批准号: 62075066 )、广东省基础与应用基础研究基金(批准号: 2023A1515010824)和广州市科技计划(批准号: 202201010718)资助的课题.
      Corresponding author: Qin Huan, qinghuan@scnu.edu.cn
    • Funds: Project supported by the National Natural Science Foundation of China (Grant No. 62075066), the Basic and Applied Basic Research Foundation of Guangdong Province, China (Grant No. 2023A1515010824), and the Science and Technology Program of Guangzhou, China (Grant No. 202201010718).
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  • 图 1  热声效应示意图

    Fig. 1.  Schematic diagram of TA effect.

    图 2  微波热声信号延时叠加算法示意图

    Fig. 2.  Schematic diagram of the thermoacoustic signal delay superposition algorithm.

    图 3  微波热声成像技术典型实现方案 (a)微波乳腺热声成像一体化探头装置图[16]; (b)微波热声脑成像装置图[15]; (c)微波乳腺热声成像装置[66]; (d)微波热声关节成像装置图[17]

    Fig. 3.  Typical implementation scheme of microwave thermoacoustic imaging technology: (a) Microwave-induced breast thermoacoustic imaging integrated probe device[16]; (b) diagram of a Microwave-induced brain thermoacoustic imaging device[15]; (c) microwave-induced breast thermoacoustic imaging system[66]; (d) microwave-induced thermoacoustic joint imaging device[17].

    图 4  微波热声成像乳腺成像 (a) Kruger等[74]的乳腺成像图; (b) 微波热声乳腺成像实操图[16]; (c) 乳房的解剖结构示意图[16]; (d) 覃欢团队[16]乳腺成像图

    Fig. 4.  MTAI breast imaging: (a) Kruger et al.[74] breast imaging; (b) microwave thermoacoustic breast imaging actual operation diagram[16]; (c) anatomical diagram of the breast[16]; (d) breast imaging of Professor Qin Huan’s team[16].

    图 5  微波热声脑成像[15] (a) 两只新生小鼠脑出血的热声图像及出血区域标注(白色区域); (b) 脑出血组织切片与相应热声图像对照

    Fig. 5.  MTAI brain imaging[15]: (a) MTAI image and bleeding area (white area) of cerebral hemorrhage in two newborn mice; (b) comparison of cerebral hemorrhage tissue slices with corresponding MTAI images.

    图 6  受试者中指的热声图像 (T0-T30)和MRI (M2-M30)的比较[17]

    Fig. 6.  Comparison of MTAI (T0-T30) and MRI (M2-M30) of subjects’ middle fingers[17].

    图 7  偏振微波热声心梗模型成像[93] (a) 偏振微波热声成像系统的示意图和用于计算异质性参数(DOMA)的偏振微波热声成像机制; (b) 超声图像及相应的DOMA图像

    Fig. 7.  P-MTAI myocardial infarction model detection[93]: (a) Schematic diagram of the P-MTAI imaging system and the P-MTAI mechanism used to calculate DOMA; (b) ultrasonic images and corresponding DOMA images.

    表 1  微波源各参数对成像影响

    Table 1.  Influence of various parameters of microwave source on imaging.

    成像影响微波源参数
    分辨率脉冲宽度、
    脉冲波形
    信噪比脉冲重复频率、
    脉冲能量强度
    对比度中心频率、
    脉冲能量强度
    成像深度中心频率、
    脉冲能量强度
    下载: 导出CSV

    表 2  主要脑组织在3.05 GHz下的电导率[15]

    Table 2.  Conductivity property of major brain tissues at 3.05 GHz[15].

    物质 电导率/(S·m–1)
    脑灰质 2.2588
    脑白质 1.5393
    血液 3.0991
    脑脊液 4.0592
    小脑 2.5189
    血管壁 1.8444
    硬膜 2.0485
    脊髓 1.3530
    下载: 导出CSV

    表 3  关节各组织在3 GHz下的电导率和介电常数[85]

    Table 3.  Conductivity and permittivity of each tissue of the joint at 3 GHz[85].

    物质相对介电常数电导率/(S·m–1)
    肌腱/韧带42.132.17
    软骨37.612.21
    骨松质17.941.01
    下载: 导出CSV
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    Ketcham R A, Carlson W D 2001 Comput. Geosci. 27 381Google Scholar

    [2]

    Bushong S C, Clarke G 2003 Magnetic Resonance Imaging: Physical and Biological Principles (Amsterdam: Elsevier Health Sciences) pp58–65

    [3]

    Bushberg J T, Boone J M 2011 The Essential Physics of Medical Imaging (Philadelphia: Lippincott Williams & Wilkins) pp171–202

    [4]

    Haribabu V, Girigoswami K, Sharmiladevi P, Girigoswami A 2020 ACS Biomater. Sci. Eng. 6 4377Google Scholar

    [5]

    Chan V, Perlas A 2011 Atlas of Ultrasound-guided Procedures in Interventional Pain Management (New York: Springer) p13

    [6]

    Nguyen K C T, Le L H, Kaipatur N R, Zheng R, Lou E H, Major P W 2016 Ann. Biomed. Eng. 44 2874Google Scholar

    [7]

    Wang H, Liu N 2020 J. Med. Imaging Health Inf. 10 918Google Scholar

    [8]

    Xu M H, Ku G, Jin X, Wang L V, Fornage B D, Hunt K K 2005 The Sixth Conference on Biomedical Thermoacoustics, Optoacoustics, and Acousto-optics 5697 45

    [9]

    Behari J 2019 Radio Frequency and Microwave Effects on Biological Tissues (New York: CRC Press) pp63–82

    [10]

    Chen H, Tang X, Nie G, Wang Z, Hu J, Hu J, Qin H 2023 J. Innovative Opt. Health Sci. 16 2243002Google Scholar

    [11]

    Lin J C 2005 Advances in Electromagnetic Fields in Living Systems (Boston: Springer) p41

    [12]

    Zhao S X, Wang H H, Li Y J, Nie L M, Zhang S X, Xing D, Qin H 2021 IEEE Trans. Biomed. Eng. 69 725

    [13]

    Rahpeima R, Soltani M, Kashkooli F M 2020 Comput. Methods Programs Biomed. 196 105606Google Scholar

    [14]

    Liu Q, Liang X, Li T, Chao W, Qi W Z, Jin T, Gong Y, Jiang H B, Xi L 2023 IEEE Trans. Med. Imaging 42 2425

    [15]

    Zhao Y, Shan T, Chi Z H, Jiang H B 2020 J. Xray Sci. Technol. 28 83

    [16]

    Ren M Y, Cheng Z W, Wu L H, et al. 2023 IEEE Trans. Biomed. Eng. 70 175Google Scholar

    [17]

    Chi Z H, Huang L, Wu D, Long X J, Xu X L, Jiang H B 2022 Med. Phys. 49 84Google Scholar

    [18]

    Vander Vorst A, Rosen A, Kotsuka Y 2006 RF/microwave Interaction With Biological Tissues (Hoboken: John Wiley & Sons) pp30–38

    [19]

    Schwan H P, Foster K R 1980 Proc. IEEE 68 104Google Scholar

    [20]

    Foster K R, Schwan H P 2019 CRC Handbook of Biological Effects of Electromagnetic Fields (Boca Raton: CRC press) pp27–76

    [21]

    Fiedler T M, Ladd M E, Bitz A K 2018 Neuroimage 168 33Google Scholar

    [22]

    Williams J M 2001 arXiv: 0102007 [physics.gen-ph

    [23]

    Bacon C, Guilliorit E, Hosten B, Chimenti D E 2001 J. Acoust. Soc. Am. 110 1398Google Scholar

    [24]

    Dagro A M, Wilkerson J W, Thomas T P, Kalinosky B T, Payne J A 2021 Sci. Adv. 7 eabd8405Google Scholar

    [25]

    Zhang X C, Xu J 2010 Introduction to THz Wave Photonics (Vol. 29) (New York: Springer) pp70–82

    [26]

    Drain L 2019 Laser Ultrasonics: Techniques and Applications (New York: Routledge) pp305–322

    [27]

    Paltauf G, Dyer P E 2003 Chem. Rev. 103 487Google Scholar

    [28]

    Harris C M, Piersol A G 2002 Harris’ Shock and Vibration Handbook (Vol. 5) (New York: McGraw-Hill) p21

    [29]

    Drebushchak V 2020 J. Therm. Anal. Calorim. 142 1097Google Scholar

    [30]

    Gao F, Zheng Q, Zheng Y J 2014 Med. Phys. 41 053302Google Scholar

    [31]

    Luo W L, Ji Z, Yang S H, Xing D 2018 Phys. Rev. Appl. 10 1728

    [32]

    Lou C G, Yang S H, Ji Z, Chen Q, Xing D 2012 Phys. Rev. Lett. 109 218101Google Scholar

    [33]

    Ji Z, Lou C G, Yang S H, Xing D 2012 Med. Phys. 39 6738Google Scholar

    [34]

    Yan J, Tao C J, Wu S Z 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference Shanghai, China, 17–18 January 2006 p1521

    [35]

    Lou C G, Nie L M, Xu D 2011 J. Appl. Phys. 110 083101Google Scholar

    [36]

    Ji Z, Ding W Z, Ye F H, Lou C G, Xing D 2015 Appl. Phys. Lett. 107 094104Google Scholar

    [37]

    Ji Z, Lou C G, Shi Y, Ding W Z, Yang S H, Xing D 2015 Appl. Phys. Lett. 107 839

    [38]

    Wang X, Bauer D R, Vollin J L, Manzi D G, Witte R S, Xin H 2012 IEEE Antennas Wirel. Propag. Lett. 11 1634Google Scholar

    [39]

    Sharif-Khodaei Z, Aliabadi M 2014 Smart Mater. Struct. 23 075007Google Scholar

    [40]

    Berger C R, Demissie B, Heckenbach J, Willett P, Zhou S 2010 IEEE J. Sel. Top. Sign. Proces. 4 226Google Scholar

    [41]

    Li J, Wu R B 1998 IEEE Trans. Sign. Proces. 46 2231Google Scholar

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出版历程
  • 收稿日期:  2023-05-05
  • 修回日期:  2023-06-30
  • 上网日期:  2023-07-18
  • 刊出日期:  2023-10-20

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