Skip to main content
SpringerLink
Log in

Simulation and Optimization Study of an Ultra-Low-Field Bell-Shaped Head MRI Electromagnet

  • Original Paper
  • Published:
Applied Magnetic Resonance Aims and scope Submit manuscript

Abstract

Ultra-low magnetic field systems have attracted increasing attention in recent years because they lack cryocoolers and exhibit lightweight, low cost, and mobilization convenience. In contrast to permanent magnet systems, electromagnetic systems can easily vary background magnetic fields, thus offering opportunities on multiple scales of time and distance to characterize the molecular dynamics and transport properties of complex liquids in bulk or embedded in confined environments. An unconventional ultra-low field bell-shaped head MRI magnet with a dedicated compact structure is needed for applications in clinics, intensive care units, and mobile vans and evaluating stroke in the hyperacute and acute stages. In this work, we use the discrete minimum energy (DME) method to design the ultra-low field bell-shaped head MRI electromagnet. This method involves obtaining a DME current map, initial coil extraction, and coil adjustment. The DME map is used to determine the initial current distribution of the MRI electromagnet over a predefined domain subject to constraints. Then, initial coil extraction aims to extract the initial regularized rectangle coil layout from the DME map. Considering that the extraction process decreases magnetic field homogeneity in the region of interest (ROI), coil adjustment is then implemented. This step adjusts the position and volume of the initial coil layout to meet the homogeneity requirement. A bell-shaped electromagnet (\(< 20\) mT, 2 MA/m\(^2\)) with a homogeneity of 7 ppm over 260 mm DSV is designed in this work.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. M. Zhou, H. Wang, J. Zhu, W. Chen, L. Wang, S. Liu, Y. Li, L. Wang, Y. Liu, P. Yin, J. Liu, S. Yu, F. Tan, R.M. Barber, M.M. Coates, D. Dicker, M. Fraser, D. González-Medina, H. Hamavid, Y. Hao, G. Hu, G. Jiang, H. Kan, A.D. Lopez, M.R. Phillips, J. She, T. Vos, X. Wan, G. Xu, L.L. Yan, C. Yu, Y. Zhao, Y. Zheng, X. Zou, M. Naghavi, Y. Wang, C.J.L. Murray, G. Yang, X. Liang, Cause-specific mortality for 240 causes in China during 1990–2013: a systematic subnational analysis for the Global Burden of Disease Study 2013. The Lancet 387(10015), 251–272 (2016). https://doi.org/10.1016/S0140-6736(15)00551-6

    Article  Google Scholar 

  2. H. Wang, Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015. The Lancet 388, 86 (2016)

    Article  Google Scholar 

  3. K.J. Becker, A.B. Baxter, H.M. Bybee, D.L. Tirschwell, T. Abouelsaad, W.A. Cohen, Extravasation of radiographic contrast is an independent predictor of death in primary intracerebral hemorrhage. Stroke 30(10), 2025–2032 (1999). https://doi.org/10.1161/01.STR.30.10.2025

    Article  Google Scholar 

  4. C.J. van Asch, M.J. Luitse, G.J. Rinkel, I. van der Tweel, A. Algra, C.J. Klijn, Incidence, case fatality, and functional outcome of intracerebral haemorrhage over time, according to age, sex, and ethnic origin: a systematic review and meta-analysis. Lancet Neurol. 9(2), 167–176 (2010). https://doi.org/10.1016/S1474-4422(09)70340-0

    Article  Google Scholar 

  5. S. Makkat, J.E. Vandevenne, G. Verswijvel, T. Ijsewijn, M. Grieten, Y. Palmers, A.M. De Schepper, P.M. Parizel, Signs of acute stroke seen on fluid-attenuated inversion recovery MR imaging. Am. J. Roentgenol. 179(1), 237–243 (2002). https://doi.org/10.2214/ajr.179.1.1790237

    Article  Google Scholar 

  6. L.L. Wald, P.C. McDaniel, T. Witzel, J.P. Stockmann, C.Z. Cooley, Low-cost and portable MRI. J. Magn. Reson. Imaging 52(3), 686–696 (2020). https://doi.org/10.1002/jmri.26942

    Article  Google Scholar 

  7. S. Geethanath, J.T. Vaughan, Accessible magnetic resonance imaging: a review. J. Magn. Reson. Imaging 49(7), e65–e77 (2019). https://doi.org/10.1002/jmri.26638

    Article  Google Scholar 

  8. J.P. Marques, F.F. Simonis, A.G. Webb, Low-field MRI: an MR physics perspective. J. Magn. Reson. Imaging 49(6), 1528–1542 (2019). https://doi.org/10.1002/jmri.26637

    Article  Google Scholar 

  9. T. O’Reilly, W. Teeuwisse, A. Webb, Three-dimensional MRI in a homogenous 27 cm diameter bore Halbach array magnet. J. Magn. Reson. 307, 106578 (2019). https://doi.org/10.1016/j.jmr.2019.106578

    Article  Google Scholar 

  10. C.Z. Cooley, P.C. McDaniel, J.P. Stockmann, S.A. Srinivas, S. Cauley, M. Śliwiak, C.R. Sappo, C.F. Vaughn, B. Guerin, M.S. Rosen, M.H. Lev, L.L. Wald, A portable brain MRI scanner for underserved settings and point-of-care imaging (2019), p. 18

  11. Y. He, W. He, L. Tan, F. Chen, F. Meng, H. Feng, Z. Xu, Use of 2.1 MHz MRI scanner for brain imaging and its preliminary results in stroke. J. Magn. Reson. 319, 106829 (2020). https://doi.org/10.1016/j.jmr.2020.106829

    Article  Google Scholar 

  12. J.P. Korb, Multiscale nuclear magnetic relaxation dispersion of complex liquids in bulk and confinement. Prog. Nucl. Magn. Reson. Spectrosc. 104, 12–55 (2018). https://doi.org/10.1016/j.pnmrs.2017.11.001

    Article  Google Scholar 

  13. M.J. MacLeod, P.J. Ross, G. Guzman-Guttierez, D.J. Lurie, L.M. Broche, Imaging of acute stroke by FFC-MRI: the PUFFINS study (2019), p. 3

  14. S. Lother, S.J. Schiff, T. Neuberger, P.M. Jakob, F. Fidler, Design of a mobile, homogeneous, and efficient electromagnet with a large field of view for neonatal low-field MRI. Magn. Reson. Mater. Phys. Biol. Med. 29(4), 691–698 (2016). https://doi.org/10.1007/s10334-016-0525-8

    Article  Google Scholar 

  15. M. Sarracanie, C.D. LaPierre, N. Salameh, D.E.J. Waddington, T. Witzel, M.S. Rosen, Low-cost high-performance MRI. Sci. Rep. 5(1), 15177 (2015). https://doi.org/10.1038/srep15177

    Article  ADS  Google Scholar 

  16. Y.C.N. Cheng, T.P. Eagan, R.W. Brown, S.M. Shvartsman, M.R. Thompson, Design of actively shielded main magnets: an improved functional method. Magn. Reson. Mater. Phys. Biol. Med. 16(2), 57–67 (2003). https://doi.org/10.1007/s10334-003-0012-x

    Article  Google Scholar 

  17. A. Kalafala, A design approach for actively shielded magnetic resonance imaging magnets. IEEE Trans. Magn. 26(3), 1181–1188 (1990). https://doi.org/10.1109/20.53996

    Article  ADS  Google Scholar 

  18. S. Crozier, Compact MRI magnet design by stochastic optimization (2019), p. 5

  19. N. Shaw, R. Ansorge, Genetic algorithms for MRI magnet design. IEEE Trans. Appl. Supercond. 12(1), 733–736 (2002). https://doi.org/10.1109/TASC.2002.1018506

    Article  ADS  Google Scholar 

  20. M. Thompson, R. Brown, V. Srivastava, An inverse approach to the design of MRI main magnets. IEEE Trans. Magn. 30(1), 108–112 (1994). https://doi.org/10.1109/20.272522

    Article  ADS  Google Scholar 

  21. H. Zhao, S. Crozier, D.M. Doddrell, A hybrid, inverse approach to the design of magnetic resonance imaging magnets. Med. Phys. 27(3), 599–607 (2000). https://doi.org/10.1118/1.598899

    Article  Google Scholar 

  22. H. Zhao, S. Crozier, D.M. Doddrell, Compact clinical MRI magnet design using a multi-layer current density approach (2019), p. 10

  23. Q. Wang, Practical Design of Magnetostatic Structure Using Numerical Simulation: Wang/Practical Design of Magnetostatic Structure Using Numerical Simulation. (Wiley, Singapore, 2013). https://doi.org/10.1002/9781118398159

  24. H. Wheeler, Simple inductance formulas for radio coils. Proc. IRE 16(10), 1398–1400 (1928). https://doi.org/10.1109/JRPROC.1928.221309

    Article  Google Scholar 

  25. J. Nocedal, S.J. Wright, Numerical Optimization, 2nd Ed. Springer Series in Operations Research (Springer, New York, 2006).

    Google Scholar 

  26. N. Otsu, A threshold selection method from gray-level histograms (2019), p. 5

  27. R. Sedgewick, K.D. Wayne, Algorithms, 4th edn. (Addison-Wesley, Upper Saddle River, 2011).

    Google Scholar 

  28. P.E. Gill, W. Murray, M.A. Saunders, SNOPT: an SQP algorithm for large-scale constrained optimization. SIAM Rev. 47(1), 99–131 (2005). https://doi.org/10.1137/S0036144504446096

    Article  ADS  MathSciNet  MATH  Google Scholar 

  29. L. Tsai, R. Mair, M. Rosen, S. Patz, R. Walsworth, An open-access, very-low-field MRI system for posture-dependent 3He human lung imaging. J. Magn. Reson. 193(2), 274–285 (2008). https://doi.org/10.1016/j.jmr.2008.05.016

    Article  ADS  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant no. 52077023) and the Fundamental Research Funds for the Central Universities (nos. 2018CDJDDQ0017, 2019CDYGYB001). (Corresponding author: Zheng Xu and Pan Guo.)

Author information

Authors and Affiliations

  1. School of Electrical Engineering, Chongqing University, Chongqing, 400044, China

    Ye Ding & Zheng Xu

  2. School of Physics and Electronic Engineering, Chongqing Normal University, Chongqing, 401331, China

    Pan Guo

  3. Shenzhen Academy of Aerospace Technology, Shenzhen, 518000, China

    Jiamin Wu & Yucheng He

Authors
  1. Ye Ding
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Pan Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jiamin Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yucheng He
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Zheng Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Pan Guo or Zheng Xu.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ding, Y., Guo, P., Wu, J. et al. Simulation and Optimization Study of an Ultra-Low-Field Bell-Shaped Head MRI Electromagnet. Appl Magn Reson 52, 691–704 (2021). https://doi.org/10.1007/s00723-021-01341-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00723-021-01341-2

Search

Navigation