Skip to main content

Advertisement

SpringerLink
Log in

3D true-phase polarity recovery with independent phase estimation using three-tier stacks based region growing (3D-TRIPS)

  • Research Article
  • Published:
Magnetic Resonance Materials in Physics, Biology and Medicine Aims and scope Submit manuscript

Abstract

Objectives

A postprocessing technique termed 3D true-phase polarity recovery with independent phase estimation using three-tier stacks based region growing (3D-TRIPS) was developed, which directly reconstructs phase-sensitive inversion-recovery images without acquisition of phase-reference images. The utility of this technique is demonstrated in myocardial late gadolinium enhancement (LGE) imaging.

Materials and methods

A data structure with three tiers of stacks was used for 3D-TRIPS to directly achieve reliable region growing for successful background-phase estimation. Fifteen patients undergoing postgadolinium 3D phase-sensitive inversion recovery (PSIR) cardiac LGE magnetic resonance imaging (MRI) were recruited, and 3D-TRIPS LGE reconstructions were compared with standard PSIR. Objective voxel-by-voxel comparison was performed. Additionally, blinded review by two radiologists compared scar visibility, clinical acceptability, voxel polarity error, or groups and blurring.

Results

3D-TRIPS efficiently reconstructed postcontrast phase-sensitive myocardial LGE images. Objective analysis showed an average 95% voxel-by-voxel agreement between 3D-TRIPS and PSIR images. Blinded radiologist review demonstrated similar image quality between 3D-TRIPS and PSIR reconstruction.

Conclusion

3D-TRIPS provided similar image quality to PSIR for phase-sensitive myocardial LGE MRI reconstruction. 3D-TRIPS does not require acquisition of a reference image and can therefore be used to accelerate phase-sensitive LGE imaging.

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
Fig. 8
Fig. 9

Similar content being viewed by others

References

  1. Kellman P, Arai AE, McVeigh ER, Aletras AH (2002) Phase-sensitive inversion recovery for detecting myocardial infarction using gadolinium-delayed hyperenhancement. Magn Reson Med 47(2):372–383

    Article  PubMed  PubMed Central  Google Scholar 

  2. Mugler JP 3rd, Brookeman JR (1990) Three-dimensional magnetization-prepared rapid gradient-echo imaging (3D MP RAGE). Magn Reson Med 15(1):152–157

    Article  PubMed  Google Scholar 

  3. Sethi V, Yousry TA, Muhlert N, Ron M, Golay X, Wheeler-Kingshott C, Miller DH, Chard DT (2012) Improved detection of cortical MS lesions with phase-sensitive inversion recovery MRI. J Neurol Neurosurg Psychiatry 83(9):877–882

    Article  PubMed  Google Scholar 

  4. Xiang QS (1996) Inversion recovery image reconstruction with multiseed region-growing spin reversal. J Magn Reson Imaging 6(5):775–782

    Article  CAS  PubMed  Google Scholar 

  5. Wang J, Chen H, Maki JH, Zhao X, Wilson GJ, Yuan C, Bornert P (2014) Referenceless acquisition of phase-sensitive inversion-recovery with decisive reconstruction (RAPID) imaging. Magn Reson Med 72(3):806–815

    Article  PubMed  Google Scholar 

  6. Hou P, Hasan KM, Sitton CW, Wolinsky JS, Narayana PA (2005) Phase-sensitive T1 inversion recovery imaging: a time-efficient interleaved technique for improved tissue contrast in neuroimaging. AJNR Am J Neuroradiol 26(6):1432–1438

    PubMed  Google Scholar 

  7. Wang J, Bornert P, Zhao H, Hippe DS, Zhao X, Balu N, Ferguson MS, Hatsukami TS, Xu J, Yuan C, Kerwin WS (2013) Simultaneous noncontrast angiography and intraplaque hemorrhage (SNAP) imaging for carotid atherosclerotic disease evaluation. Magn Reson Med 69(2):337–345

    Article  PubMed  Google Scholar 

  8. Borrello JA, Chenevert TL, Aisen AM (1990) Regional phase correction of inversion-recovery MR images. Magn Reson Med 14(1):56–67

    Article  CAS  PubMed  Google Scholar 

  9. Kim RJ, Wu E, Rafael A, Chen EL, Parker MA, Simonetti O, Klocke FJ, Bonow RO, Judd RM (2000) The use of contrast-enhanced magnetic resonance imaging to identify reversible myocardial dysfunction. N Engl J Med 343(20):1445–1453

    Article  CAS  PubMed  Google Scholar 

  10. Bucciarelli-Ducci C, Wu E, Lee DC, Holly TA, Klocke FJ, Bonow RO (2006) Contrast-enhanced cardiac magnetic resonance in the evaluation of myocardial infarction and myocardial viability in patients with ischemic heart disease. Curr Probl Cardiol 31(2):128–168

    Article  PubMed  Google Scholar 

  11. Lloyd SG, Gupta H (2005) Assessment of myocardial viability by cardiovascular magnetic resonance. Echocardiography 22(2):179–193

    Article  PubMed  Google Scholar 

  12. Peukert D, Laule M, Taupitz M, Kaufels N, Hamm B, Dewey M (2007) 3D and 2D delayed-enhancement magnetic resonance imaging for detection of myocardial infarction: Preclinical and clinical results. Acad Radiol 14(7):788–794

    Article  PubMed  Google Scholar 

  13. Kino A, Zuehlsdorff S, Sheehan JJ, Weale PJ, Carroll TJ, Jerecic R, Carr JC (2009) Three-dimensional phase-sensitive inversion-recovery turbo FLASH sequence for the evaluation of left ventricular myocardial scar. AJR Am J Roentgenol 193(5):W381–W388

    Article  PubMed  Google Scholar 

  14. Ma J (2004) Breath-hold water and fat imaging using a dual-echo two-point Dixon technique with an efficient and robust phase-correction algorithm. Magn Reson Med 52(2):415–419

    Article  PubMed  Google Scholar 

  15. Ma J, Son JB, Hazle JD (2016) An improved region growing algorithm for phase correction in MRI. Magn Reson Med 76(2):519–529

    Article  PubMed  Google Scholar 

  16. Hernando D, Kellman P, Haldar JP, Liang ZP (2010) Robust water/fat separation in the presence of large field inhomogeneities using a graph cut algorithm. Magn Reson Med 63(1):79–90

    PubMed  PubMed Central  Google Scholar 

  17. Davison AC, Hinkley DV (1997) Bootstrap methods and their application. Cambridge University Press, Cambridge

    Book  Google Scholar 

  18. Akcakaya M, Rayatzadeh H, Basha TA, Hong SN, Chan RH, Kissinger KV, Hauser TH, Josephson ME, Manning WJ, Nezafat R (2012) Accelerated late gadolinium enhancement cardiac MR imaging with isotropic spatial resolution using compressed sensing: initial experience. Radiology 264(3):691–699

    Article  PubMed  PubMed Central  Google Scholar 

  19. Sodickson DK, Hardy CJ, Zhu Y, Giaquinto RO, Gross P, Kenwood G, Niendorf T, Lejay H, McKenzie CA, Ohliger MA, Grant AK, Rofsky NM (2005) Rapid volumetric MRI using parallel imaging with order-of-magnitude accelerations and a 32-element RF coil array: feasibility and implications. Acad Radiol 12(5):626–635

    Article  PubMed  PubMed Central  Google Scholar 

  20. Sharma SD, Fong CL, Tzung BS, Law M, Nayak KS (2013) Clinical image quality assessment of accelerated magnetic resonance neuroimaging using compressed sensing. Invest Radiol 48(9):638–645

    Article  PubMed  Google Scholar 

  21. Jaspan ON, Fleysher R, Lipton ML (2015) Compressed sensing MRI: a review of the clinical literature. Br J Radiol 88(1056):20150487

    Article  PubMed  PubMed Central  Google Scholar 

  22. Cheng C, Zou C, Liang C, Liu X, Zheng H (2017) Fat-water separation using a region-growing algorithm with self-feeding phasor estimation. Magn Reson Med 77(6):2390–2401

    Article  CAS  PubMed  Google Scholar 

  23. Cui C, Wu X, Newell JD, Jacob M (2015) Fat water decomposition using globally optimal surface estimation (GOOSE) algorithm. Magn Reson Med 73(3):1289–1299

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

This study was supported in part by Grants from the National Institutes of Health R21-EB017514.

Author information

Authors and Affiliations

  1. Department of Bioengineering, University of Washington, 850 Republican Street, Brotman 124, Seattle, WA, 98109-4725, USA

    Haining Liu & Chun Yuan

  2. Department of Radiology, University of Washington, Seattle, WA, USA

    Gregory J. Wilson, Niranjan Balu, Jeffrey H. Maki, Daniel S. Hippe, Jinnan Wang, Martin L. Gunn & Chun Yuan

  3. Department of Radiology, University of Colorado, Aurora, CO, USA

    Jeffrey H. Maki

  4. Department of Radiology, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China

    Wei Wu

  5. Department of Surgery, University of Washington, Seattle, WA, USA

    Hiroko Watase

  6. Department of Bioengineering, Tsinghua University, Beijing, China

    Chun Yuan

Authors
  1. Haining Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gregory J. Wilson
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Niranjan Balu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jeffrey H. Maki
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Daniel S. Hippe
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Wei Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Hiroko Watase
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Jinnan Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Martin L. Gunn
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Chun Yuan
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

HL: Protocol/project development, data collection or management. GJW: Data collection or management, data analysis. NB: Protocol/project development, Data analysis. JHM: Protocol/project development, data analysis. DSH: Data analysis. HW: Data analysis. JW: Protocol/project development. Gunn: Data analysis. WW: Data analysis. CY: Protocol/project development, data collection or management, data analysis.

Corresponding author

Correspondence to Haining Liu.

Ethics declarations

Conflict of interest

D. Hippe has received grants from GE Healthcare and Philips Healthcare. N. Balu has received grants from Philips Healthcare. C. Yuan has received grants from Philips Healthcare and is a Member of Radiology Advisory Network of Philips Healthcare. The other authors declare that they have no conflict of interest.

Research involving human participants

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, H., Wilson, G.J., Balu, N. et al. 3D true-phase polarity recovery with independent phase estimation using three-tier stacks based region growing (3D-TRIPS). Magn Reson Mater Phy 31, 87–99 (2018). https://doi.org/10.1007/s10334-017-0666-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10334-017-0666-4

Keywords

Search

Navigation