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Simulation research on magneto-acoustic concentration tomography of magnetic nanoparticles based on truncated singular value decomposition (TSVD)

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Abstract

The existing magneto-acoustic concentration tomography with magnetic induction (MACT-MI) inverse problem algorithm has some problems such as the singularity of reconstructed boundary and poor anti-noise performance, which make it difficult to be applied to recognition of early breast cancer tumor. Therefore, a system matrix linking the concentration distribution information of magnetic nanoparticles (MNPs) to the ultrasonic signal was built in this paper, and a truncated singular value decomposition (TSVD) based MNPS concentration reconstruction algorithm was proposed. Firstly, a simulation model was established. Secondly, the magnetic field and acoustic field simulation data were substituted into the inverse problem algorithm based on TSVD for concentration reconstruction. Finally, the effects of the number of singular values, SNR and radius of MNPs on the reconstruction results were studied. The simulation results show that, the inverse problem algorithm based on TSVD proposed in this paper can maximize the use of ultrasonic signals, and has a good reconstruction effect on 1 mm small-radius MNPs, high resolution reconstructed images can also be obtained under the condition of low SNR, which can effectively promote the clinical application of this imaging method.

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References

  1. Diaby V et al (2015) A review of systematic reviews of the cost-effectiveness of hormone therapy, chemotherapy, and targeted therapy for breast cancer. Breast Cancer Res Treat 151(1):27–40. https://doi.org/10.1007/s10549-015-3383-6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Gampenrieder SP, Gabriel R, Richard G (2013) Neoadjuvant chemotherapy and targeted therapy in breast Cancer: past, present, and future. J Oncol 2013(2013):732047. https://doi.org/10.1155/2013/732047

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Grser M, Thieben F, Szwargulski P, Werner F, Gdaniec N, Boberg M et al Human-sized magnetic particle imaging for brain applications. Nat Commun. https://doi.org/10.1038/s41467-019-09704-x

  4. Borgert J, Schmidt JD, Schmale I, Rahmer J, Bontus C, Gleich B et al (2012) Fundamentals and applications of magnetic particle imaging. J Cardiovasc Comp Tomogr 6(3):149–153. https://doi.org/10.1016/j.jcct.2012.04.007

    Article  Google Scholar 

  5. Parkins KM, Melo KP, Ronald JA & Foster, P. J.. (2020). Visualizing tumour self-homing with magnetic particle imaging. https://doi.org/10.1039/D0NR07983A

  6. Finas D, Baumann K, Sydow L, Heinrich K, Grafe K, Rody A et al (2013) Lymphatic tissue and superparamagnetic nanoparticles - magnetic particle imaging for detection and distribution in a breast cancer model. Biomedizinische Technik/Biomed Eng. https://doi.org/10.1515/bmt-2013-4262

  7. Zhu J , Yang,W , Wei S , Wang Z , & Lv X. (2018). Progress of Electromagnetic Detection and Imaging of Magnetic Nanoparticles.https://doi.org/10.3969/j.issn.0258-8021.2018.03.012

  8. Yan X, Xu Z, Chen W, Pan Y (2021) Implementation method for magneto-acoustic concentration tomography with magnetic induction (mact-mi) based on the method of moments. Comput Biol Med 128:104105. https://doi.org/10.1016/j.compbiomed.2020.104105

    Article  CAS  PubMed  Google Scholar 

  9. Yan X, He B (2005) Magnetoacoustic tomography with magnetic induction (mat-mi). Phys Med Biol 50(2005):5175–5187. https://doi.org/10.1088/0031-9155/50/21/015

    Article  Google Scholar 

  10. Wang H, Liu G, Jiang L, Zhang Y, Xia H, Yanhong LI et al (2008) Three dimensional electromagnetic forward/inverse problems in magnetoacoustic tomography with magnetic induction. Beijing Biomed Eng 2009(11):2292–2295. https://doi.org/10.3969/j.issn.1002-3208.2008.06.006

    Article  Google Scholar 

  11. Sun X, Fang D, Dong Z, Ma Q (2013) Acoustic dipole radiation based electrical impedance contrast imaging approach of magnetoacoustic tomography with magnetic induction. Med Phys 40(5):052902. https://doi.org/10.1118/1.4800639

    Article  PubMed  Google Scholar 

  12. Jing C, Liu G, Hui X (2013) Conductivity reconstruction for magnetoacoustic tomography based on the system matrix. Modern Sci Instruments. http://qikan.cqvip.com/Qikan/Article/Detail?id=45856363. Accessed 8 Oct 2021

  13. Xia R, Li X, He B (2009) Reconstruction of vectorial acoustic sources in time-domain tomography. IEEE Trans Med Imaging 28(5):669–675. https://doi.org/10.1109/TMI.2008.2008972

    Article  PubMed  PubMed Central  Google Scholar 

  14. Mariappan L, He B (2013) Magnetoacoustic tomography with magnetic induction: bioimepedance reconstruction through vector source imaging. IEEE Trans Med Imaging 32(3):619–627. https://doi.org/10.1109/TMI.2013.2239656

    Article  PubMed  Google Scholar 

  15. Mariappan L, Hu G, He B (2014) Magnetoacoustic tomography with magnetic induction for high-resolution bioimepedance imaging through vector source reconstruction under the static field of mri magnet. Med Phys 41(2):022902. https://doi.org/10.1118/1.4862836

    Article  PubMed  PubMed Central  Google Scholar 

  16. Ren MA, Yang M, Zhang S, Zhou X, Yin T, Liu Z (2019) Magneto-acoustic tomography with magnetic induction reconstruction algorithm based on singular value decomposition method. J Biomed Eng Res. https://doi.org/10.19529/j.cnki.1672-6278.2019.02.01

  17. Ma R, Zhou X, Zhang S, Yin T, Liu Z (2016) A 3d reconstruction algorithm for magneto-acoustic tomography with magnetic induction based on ultrasound transducer characteristics. Phys Med Biol 61(24):8762. https://doi.org/10.1088/1361-6560/61/24/8762

    Article  PubMed  Google Scholar 

  18. Ma R , Yang M , Zhang S , Zhou X, & Liu Z.. (2020). Analysis of the singular values for conductivity reconstruction in magneto-acoustic tomography with magnetic induction. IEEE Access, PP(99), 1–1. https://doi.org/10.1109/ACCESS.2020.2980250

  19. Xu W, Chen Y, You W (2016) Application of SVD method in ill-posed problem. Bull Surv Map 466(01):74–75+101. http://qikan.cqvip.com/Qikan/Article/Detail?id=667782835. Accessed 8 Oct 2021

  20. Kong HL (2021) Truncated singular value decomposition in ripped photo recovery. ITM Web of Conf 36(4):04008. https://doi.org/10.1051/itmconf/20213604008

    Article  Google Scholar 

  21. Hansen, P. C.. (1998). Rank-deficient and discrete ill-posed problems. american mathematical monthly. https://doi.org/10.1137/1.9780898719697

  22. Wu Y Numerical solution of discrete ill-posed problems. (Doctoral dissertation, Lanzhou university). https://doi.org/10.7666/d.D01299561

  23. Li Y (2017) The unit integral calculation method of defective material’s forward question of magnetic flux leakage detection based on the magnetic dipole model. Trans Electrotech Soc 21(v.32):180–189. https://doi.org/10.19595/j.cnki.1000-6753.tces.170430

    Article  Google Scholar 

  24. Hansen PC (1987) The truncated svd as a method for regularization. BIT 27(4):534–553. https://doi.org/10.1007/BF01937276

    Article  Google Scholar 

  25. Hanson R (1971) A numerical method for solving Fredholm integral equations of the first kind using singular values. SIAM J Numer Anal 8:616–622. https://doi.org/10.1137/0708058

    Article  Google Scholar 

  26. Yan X, Pan Y, Chen W, Xu Z, Li Z (2021) Simulation research on the forward problem of magnetoacoustic concentration tomography for magnetic nanoparticles with magnetic induction in a saturation magnetization state. J Phys D Appl Phys 54(7):075002 (10pp). https://doi.org/10.1088/1361-6463/abc27c

    Article  CAS  Google Scholar 

  27. Kellnberger S, Rosenthal A, Myklatun A et al (2016) Magnetoacoustic sensing of magnetic nanoparticles. Phys Rev Lett 116(10):108103. https://doi.org/10.1103/PhysRevLett.116.108103

    Article  CAS  PubMed  Google Scholar 

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Acknowledgments

This research was supported by the Natural Science Foundation of Liaoning Province (No. 2019-ZD-0039), and Basic Research Project of Liaoning Provincial Department of Education (No. LJ2020JCL003).

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Correspondence to Yu Hu.

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Yan, X., Hu, ., Guang, S. et al. Simulation research on magneto-acoustic concentration tomography of magnetic nanoparticles based on truncated singular value decomposition (TSVD). Med Biol Eng Comput 59, 2383–2396 (2021). https://doi.org/10.1007/s11517-021-02450-7

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