Skip to main content
SpringerLink
Log in

Appropriate echo time selection for quantitative susceptibility mapping

  • Published:
Radiological Physics and Technology Aims and scope Submit manuscript

Abstract

The purpose of our study was to clarify the dependence of quantitative susceptibility mapping (QSM) on echo time (TE). We constructed a phantom consisting of six tubes; three tubes were filled with different concentrations (0.5, 1.0, and 2.5 mM) of gadopentetate dimeglumine (Gd-DTPA), and three were filled with different concentrations (100, 200, and 350 mg/mL) of calcium hydroxyapatite. Real and imaginary images from multi-echo spoiled gradient-echo data (12 echoes) were acquired. We then used four datasets with three serial echoes. The QSM procedure consists of four steps: field map estimation, phase unwrapping, background removal, and dipole inversion. For each sample, we compared the measured mean susceptibility value with the theoretical susceptibility value and conducted a linear regression analysis. Accordingly, the relationship between the measured susceptibility and concentration of Gd-DTPA was shown to agree well with the theoretical values (TEs = 16.4, 20.8, and 25.2 ms; slope = 0.24, R2 = 1.00). Furthermore, the relationship between the measured susceptibility and concentration of hydroxyapatite also showed good linearity (TEs = 16.4, 20.8, and 25.2 ms; slope = − 0.00121, R2 = 1.00). In conclusion, the optimization of the TE in QSM makes it possible to obtain more detailed information regarding the susceptibility of biomaterials.

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

Similar content being viewed by others

References

  1. Buch S, Liu S, Ye Y, Cheng YC, Neelavalli J, Haacke EM. Susceptibility mapping of air, bone, and calcium in the head. Magn Reson Med. 2015;73(6):2185–94.

    Article  CAS  PubMed  Google Scholar 

  2. Hopkins JA, Wehrli FW. Magnetic susceptibility measurement of insoluble solids by NMR: magnetic susceptibility of bone. Magn Reson Med. 1997;37(4):494–500.

    Article  CAS  PubMed  Google Scholar 

  3. Haacke EM, Xu Y, Cheng YC, Reichenbach JR. Susceptibility weighted imaging (SWI). Magn Reson Med. 2004;52(3):612–8.

    Article  PubMed  Google Scholar 

  4. Wang Y, Liu T. Quantitative susceptibility mapping (QSM): decoding MRI data for a tissue magnetic biomarker. Magn Reson Med. 2015;73(1):82–101.

    Article  CAS  PubMed  Google Scholar 

  5. Wu Z, Mittal S, Kish K, Yu Y, Hu J, Haacke EM. Identification of calcification with MRI using susceptibility-weighted imaging: a case study. J Magn Reson Imaging. 2009;29(1):177–82.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Chen W, Zhu W, Kovanlikaya I, Kovanlikaya A, Liu T, Wang S, et al. Intracranial calcifications and hemorrhages: characterization with quantitative susceptibility mapping. Radiology. 2014;270(2):496–505.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Schweser F, Deistung A, Lehr BW, Reichenbach JR. Differentiation between diamagnetic and paramagnetic cerebral lesions based on magnetic susceptibility mapping. Med Phys. 2010;37(10):5165–78.

    Article  PubMed  Google Scholar 

  8. Wu B, Li W, Avram AV, Gho SM, Liu C. Fast and tissue-optimized mapping of magnetic susceptibility and T2* with multi-echo and multi-shot spirals. Neuroimage. 2012;59(1):297–305.

    Article  PubMed  Google Scholar 

  9. Hsieh CY, Cheng YC, Neelavalli J, Haacke EM, Stafford RJ. An improved method for susceptibility and radius quantification of cylindrical objects from MRI. Magn Reson Imaging. 2015;33(4):420–36.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Kressler B, de Rochefort L, Liu T, Spincemaille P, Jiang Q, Wang Y. Nonlinear regularization for per voxel estimation of magnetic susceptibility distributions from MRI field maps. IEEE Trans Med Imaging. 2010;29(2):273–81.

    Article  PubMed  Google Scholar 

  11. Wharton S, Schafer A, Bowtell R. Susceptibility mapping in the human brain using threshold-based k-space division. Magn Reson Med. 2010;63(5):1292–304.

    Article  PubMed  Google Scholar 

  12. Cronin MJ, Wang N, Decker KS, Wei H, Zhu WZ, Liu C. Exploring the origins of echo-time-dependent quantitative susceptibility mapping (QSM) measurements in healthy tissue and cerebral microbleeds. Neuroimage. 2017;149:98–113.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Sood S, Urriola J, Reutens D, O’Brien K, Bollmann S, Barth M, et al. Echo time-dependent quantitative susceptibility mapping contains information on tissue properties. Magn Reson Med. 2017;77(5):1946–58.

    Article  CAS  PubMed  Google Scholar 

  14. de Rochefort L, Brown R, Prince MR, Wang Y. Quantitative MR susceptibility mapping using piece-wise constant regularized inversion of the magnetic field. Magn Reson Med. 2008;60(4):1003–9.

    Article  PubMed  Google Scholar 

  15. Henkelman M, Kucharczyk W. Optimization of gradient-echo MR for calcium detection. AJNR Am J Neuroradiol. 1994;15(3):465–72.

    CAS  PubMed  Google Scholar 

  16. Schofield MA, Zhu Y. Fast phase unwrapping algorithm for interferometric applications. Opt Lett. 2003;28(14):1194–6.

    Article  PubMed  Google Scholar 

  17. Zhou D, Liu T, Spincemaille P, Wang Y. Background field removal by solving the Laplacian boundary value problem. NMR Biomed. 2014;27(3):312–9.

    Article  PubMed  Google Scholar 

  18. Liu J, Liu T, de Rochefort L, Ledoux J, Khalidov I, Chen W, et al. Morphology enabled dipole inversion for quantitative susceptibility mapping using structural consistency between the magnitude image and the susceptibility map. Neuroimage. 2012;59(3):2560–8.

    Article  PubMed  Google Scholar 

  19. Liu T, Xu W, Spincemaille P, Avestimehr AS, Wang Y. Accuracy of the morphology enabled dipole inversion (MEDI) algorithm for quantitative susceptibility mapping in MRI. IEEE Trans Med Imaging. 2012;31(3):816–24.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Gilbert G, Savard G, Bard C, Beaudoin G. Quantitative comparison between a multiecho sequence and a single-echo sequence for susceptibility-weighted phase imaging. Magn Reson Imaging. 2012;30(5):722–30.

    Article  PubMed  Google Scholar 

  21. Sun H, Kate M, Gioia LC, Emery DJ, Butcher K, Wilman AH. Quantitative susceptibility mapping using a superposed dipole inversion method: application to intracranial hemorrhage. Magn Reson Med. 2016;76(3):781–91.

    Article  CAS  PubMed  Google Scholar 

  22. Li J, Chang S, Liu T, Jiang H, Dong F, Pei M, et al. Phase-corrected bipolar gradients in multi-echo gradient-echo sequences for quantitative susceptibility mapping. MAGMA. 2015;28(4):347–55.

    Article  PubMed  Google Scholar 

  23. Wang Y. Quantitative susceptibility mapping: magnetic resonance imaging of tissue magnetism. Scotts Valley: CreateSpace Independent Publishing Platform; 2013. p. 57–82.

    Google Scholar 

  24. Blazejewska AI, Wharton S, Gowland PA, Bowtell R. Understanding the effects of oriented susceptibility inclusions on the phase and magnitude of gradient echo signals. In: Proceedings of 19th Annual Meeting ISMRM, Montréal, 2011; p 4511.

  25. Robinson SD, Dymerska B, Bogner W, Barth M, Zaric O, Goluch S, et al. Combining phase images from array coils using a short echo time reference scan (COMPOSER). Magn Reson Med. 2017;77(1):318–27.

    Article  PubMed  Google Scholar 

  26. Shmueli K, de Zwart JA, van Gelderen P, Li TQ, Dodd SJ, Duyn JH. Magnetic susceptibility mapping of brain tissue in vivo using MRI phase data. Magn Reson Med. 2009;62(6):1510–22.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Bilgic B, Fan AP, Polimeni JR, Cauley SF, Bianciardi M, Adalsteinsson E, et al. Fast quantitative susceptibility mapping with L1-regularization and automatic parameter selection. Magn Reson Med. 2014;72(5):1444–59.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Biomedical Sciences, Tokushima University Graduate School, 3-18-15, Kuramoto-Cho, Tokushima, Tokushima, 770-8503, Japan

    Yuki Kanazawa, Masafumi Harada & Hideki Otsuka

  2. Graduate School of Health Science, Tokushima University, 3-18-15, Kuramoto-Cho, Tokushima, Tokushima, 770-8503, Japan

    Yuki Matsumoto

  3. College of Medical, Pharmaceutical and Health Sciences, Kanazawa University, 5-11-80 Kodatsuno, Kanazawa, Ishikawa, 920-0942, Japan

    Hiroaki Hayashi

  4. High-Field MRI Institute, Iwate Medical University, 19-1 Uchimaru, Morioka, Iwate, 020-8505, Japan

    Tsuyoshi Matsuda

Authors
  1. Yuki Kanazawa
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yuki Matsumoto
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Masafumi Harada
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hiroaki Hayashi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Tsuyoshi Matsuda
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Hideki Otsuka
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yuki Kanazawa.

Ethics declarations

Conflict of interest

The authors declare that they have no conflicts of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Additional information

Publisher's Note

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

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kanazawa, Y., Matsumoto, Y., Harada, M. et al. Appropriate echo time selection for quantitative susceptibility mapping. Radiol Phys Technol 12, 185–193 (2019). https://doi.org/10.1007/s12194-019-00513-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12194-019-00513-x

Keywords

Search

Navigation