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Accelerated whole brain intracranial vessel wall imaging using black blood fast spin echo with compressed sensing (CS-SPACE)

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Abstract

Objective

Develop and optimize an accelerated, high-resolution (0.5 mm isotropic) 3D black blood MRI technique to reduce scan time for whole-brain intracranial vessel wall imaging.

Materials and methods

A 3D accelerated T1-weighted fast-spin-echo prototype sequence using compressed sensing (CS-SPACE) was developed at 3T. Both the acquisition [echo train length (ETL), under-sampling factor] and reconstruction parameters (regularization parameter, number of iterations) were first optimized in 5 healthy volunteers. Ten patients with a variety of intracranial vascular disease presentations (aneurysm, atherosclerosis, dissection, vasculitis) were imaged with SPACE and optimized CS-SPACE, pre and post Gd contrast. Lumen/wall area, wall-to-lumen contrast ratio (CR), enhancement ratio (ER), sharpness, and qualitative scores (1–4) by two radiologists were recorded.

Results

The optimized CS-SPACE protocol has ETL 60, 20% k-space under-sampling, 0.002 regularization factor with 20 iterations. In patient studies, CS-SPACE and conventional SPACE had comparable image scores both pre- (3.35 ± 0.85 vs. 3.54 ± 0.65, p = 0.13) and post-contrast (3.72 ± 0.58 vs. 3.53 ± 0.57, p = 0.15), but the CS-SPACE acquisition was 37% faster (6:48 vs. 10:50). CS-SPACE agreed with SPACE for lumen/wall area, ER measurements and sharpness, but marginally reduced the CR.

Conclusion

In the evaluation of intracranial vascular disease, CS-SPACE provides a substantial reduction in scan time compared to conventional T1-weighted SPACE while maintaining good image quality.

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References

  1. Gorelick PB, Wong KS, Bae HJ, Pandey DK (2008) Large artery intracranial occlusive disease: a large worldwide burden but a relatively neglected frontier. Stroke J Cereb Circ 39(8):2396–2399

    Article  Google Scholar 

  2. Brown RD Jr, Broderick JP (2014) Unruptured intracranial aneurysms: epidemiology, natural history, management options, and familial screening. Lancet Neurol 13(4):393–404

    Article  PubMed  Google Scholar 

  3. Mandell DM, Mossa-Basha M, Qiao Y, Hess CP, Hui F, Matouk C, Johnson MH, Daemen MJ, Vossough A, Edjlali M, Saloner D, Ansari SA, Wasserman BA, Mikulis DJ (2017) Intracranial vessel wall MRI: principles and expert consensus recommendations of the American Society of Neuroradiology. AJNR Am J Neuroradiol 38(2):218–229

    Article  PubMed  CAS  Google Scholar 

  4. Mossa-Basha M, Hwang WD, De Havenon A, Hippe D, Balu N, Becker KJ, Tirschwell DT, Hatsukami T, Anzai Y, Yuan C (2015) Multicontrast high-resolution vessel wall magnetic resonance imaging and its value in differentiating intracranial vasculopathic processes. Stroke 46(6):1567–1573

    Article  PubMed  Google Scholar 

  5. Qiao Y, Zeiler SR, Mirbagheri S, Leigh R, Urrutia V, Wityk R, Wasserman BA (2014) Intracranial plaque enhancement in patients with cerebrovascular events on high-spatial-resolution MR images. Radiology 271(2):534–542

    Article  PubMed  PubMed Central  Google Scholar 

  6. Yu JH, Kwak HS, Chung GH, Hwang SB, Park MS, Park SH (2015) Association of intraplaque hemorrhage and acute infarction in patients with basilar artery plaque. Stroke 46(10):2768–2772

    Article  PubMed  CAS  Google Scholar 

  7. Kim JM, Jung KH, Sohn CH, Moon J, Shin JH, Park J, Lee SH, Han MH, Roh JK (2016) Intracranial plaque enhancement from high resolution vessel wall magnetic resonance imaging predicts stroke recurrence. Int J Stroke 11(2):171–179

    Article  PubMed  Google Scholar 

  8. Edjlali M, Gentric JC, Regent-Rodriguez C, Trystram D, Hassen WB, Lion S, Nataf F, Raymond J, Wieben O, Turski P, Meder JF, Oppenheim C, Naggara O (2014) Does aneurysmal wall enhancement on vessel wall MRI help to distinguish stable from unstable intracranial aneurysms? Stroke 45(12):3704–3706

    Article  PubMed  Google Scholar 

  9. Teng Z, Peng W, Zhan Q, Zhang X, Liu Q, Chen S, Tian X, Chen L, Brown AJ, Graves MJ, Gillard JH, Lu J (2016) An assessment on the incremental value of high-resolution magnetic resonance imaging to identify culprit plaques in atherosclerotic disease of the middle cerebral artery. Eur Radiol 26(7):2206–2214

    Article  PubMed  Google Scholar 

  10. Zhu C, Haraldsson H, Tian B, Meisel K, Ko N, Lawton M, Grinstead J, Ahn S, Laub G, Hess C, Saloner D (2016) High resolution imaging of the intracranial vessel wall at 3 and 7 T using 3D fast spin echo MRI. Magma 29(3):559–570

    Article  PubMed  CAS  Google Scholar 

  11. Qiao Y, Steinman DA, Qin Q, Etesami M, Schar M, Astor BC, Wasserman BA (2011) Intracranial arterial wall imaging using three-dimensional high isotropic resolution black blood MRI at 3.0 Tesla. J Magn Reson Imaging JMRI 34(1):22–30

    Article  PubMed  Google Scholar 

  12. Fan Z, Yang Q, Deng Z, Li Y, Bi X, Song S, Li D (2017) Whole-brain intracranial vessel wall imaging at 3 Tesla using cerebrospinal fluid-attenuated T1-weighted 3D turbo spin echo. Magn Reson Med 77(3):1142–1150

    Article  PubMed  Google Scholar 

  13. Harteveld AA, van der Kolk AG, van der Worp HB, Dieleman N, Siero JC, Kuijf HJ, Frijns CJ, Luijten PR, Zwanenburg JJ, Hendrikse J (2017) High-resolution intracranial vessel wall MRI in an elderly asymptomatic population: comparison of 3T and 7T. Eur Radiol 27(4):1585–1595

    Article  PubMed  Google Scholar 

  14. Candes E, Romberg J, Tao T (2006) Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information. IEEE Trans Inf Theory 52(2):489–509

    Article  Google Scholar 

  15. Lustig M, Donoho D, Pauly JM (2007) Sparse MRI: the application of compressed sensing for rapid MR imaging. Magn Reson Med 58(6):1182–1195

    Article  PubMed  Google Scholar 

  16. Makhijani MK, Balu N, Yamada K, Yuan C, Nayak KS (2012) Accelerated 3D MERGE carotid imaging using compressed sensing with a hidden Markov tree model. J Magn Reson Imaging JMRI 36(5):1194–1202

    Article  PubMed  Google Scholar 

  17. Li B, Dong L, Chen B, Ji S, Cai W, Wang Y, Zhang J, Zhang Z, Wang X, Fang J (2013) Turbo fast three-dimensional carotid artery black-blood MRI by combining three-dimensional MERGE sequence with compressed sensing. Magn Reson Med 70(5):1347–1352

    Article  PubMed  Google Scholar 

  18. Yuan J, Usman A, Reid SA, King KF, Patterson AJ, Gillard JH, Graves MJ (2017) Three-dimensional black-blood T2 mapping with compressed sensing and data-driven parallel imaging in the carotid artery. Magn Reson Imaging 37:62–69

    Article  PubMed  Google Scholar 

  19. Feng L, Grimm R, Block KT, Chandarana H, Kim S, Xu J, Axel L, Sodickson DK, Otazo R (2014) Golden-angle radial sparse parallel MRI: combination of compressed sensing, parallel imaging, and golden-angle radial sampling for fast and flexible dynamic volumetric MRI. Magn Reson Med 72(3):707–717

    Article  PubMed  Google Scholar 

  20. Yuan J, Usman A, Reid SA, King KF, Patterson AJ, Gillard JH, Graves MJ (2017) Three-dimensional black-blood multi-contrast carotid imaging using compressed sensing: a repeatability study. Magn Reson Mater Phy. https://doi.org/10.1007/s10334-017-0640-1

    Article  Google Scholar 

  21. Seo N, Park MS, Han K, Kim D, King KF, Choi JY, Kim H, Kim HJ, Lee M, Bae H, Kim MJ (2017) Feasibility of 3D navigator-triggered magnetic resonance cholangiopancreatography with combined parallel imaging and compressed sensing reconstruction at 3T. J Magn Reson Imaging JMRI 46(5):1289–1297

    Article  PubMed  Google Scholar 

  22. Pandit P, Rivoire J, King K, Li X (2016) Accelerated T1rho acquisition for knee cartilage quantification using compressed sensing and data-driven parallel imaging: a feasibility study. Magn Reson Med 75(3):1256–1261

    Article  PubMed  Google Scholar 

  23. Fritz J, Raithel E, Thawait GK, Gilson W, Papp DF (2016) Six-Fold acceleration of high-spatial resolution 3D SPACE MRI of the knee through incoherent k-space undersampling and iterative reconstruction-first experience. Invest Radiol 51(6):400–409

    Article  PubMed  Google Scholar 

  24. Li G, Hennig J, Raithel E, Buchert M, Paul D, Korvink JG, Zaitsev M (2015) An L1-norm phase constraint for half-Fourier compressed sensing in 3D MR imaging. Magma 28(5):459–472

    Article  PubMed  Google Scholar 

  25. Larson AC, Kellman P, Arai A, Hirsch GA, McVeigh E, Li D, Simonetti OP (2005) Preliminary investigation of respiratory self-gating for free-breathing segmented cine MRI. Magn Reson Med 53(1):159–168

    Article  PubMed  PubMed Central  Google Scholar 

  26. Jiang Y, Zhu C, Peng W, Degnan AJ, Chen L, Wang X, Liu Q, Wang Y, Xiang Z, Teng Z, Saloner D, Lu J (2016) Ex-vivo imaging and plaque type classification of intracranial atherosclerotic plaque using high resolution MRI. Atherosclerosis 249:10–16

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  27. Zhu C, Sadat U, Patterson AJ, Teng Z, Gillard JH, Graves MJ (2014) 3D high-resolution contrast enhanced MRI of carotid atheroma—a technical update. Magn Reson Imaging 32(5):594–597

    Article  PubMed  Google Scholar 

  28. Boussel L, Arora S, Rapp J, Rutt B, Huston J, Parker D, Yuan C, Bassiouny H, Saloner D (2009) Atherosclerotic plaque progression in carotid arteries: monitoring with high-spatial-resolution MR imaging—multicenter trial. Radiology 252(3):789–796

    Article  PubMed  PubMed Central  Google Scholar 

  29. Liu J, Feng L, Shen HW, Zhu C, Wang Y, Mukai K, Brooks GC, Ordovas K, Saloner D (2017) Highly-accelerated self-gated free-breathing 3D cardiac cine MRI: validation in assessment of left ventricular function. Magn Reson Mater Phy. https://doi.org/10.1007/s10334-017-0646-8

    Article  Google Scholar 

  30. Xu Y, Yuan C, Zhou Z, He L, Mi D, Li R, Cui Y, Wang Y, Wang Y, Liu G, Zheng Z, Zhao X (2016) Co-existing intracranial and extracranial carotid artery atherosclerotic plaques and recurrent stroke risk: a three-dimensional multicontrast cardiovascular magnetic resonance study. J Cardiovasc Magn Reson Off J Soc Cardiovasc Magn Reson 18(1):90

    Google Scholar 

  31. Zhou Z, Li R, Zhao X, He L, Wang X, Wang J, Balu N, Yuan C (2015) Evaluation of 3D multi-contrast joint intra- and extracranial vessel wall cardiovascular magnetic resonance. J Cardiovasc Magn Reson Off J Soc Cardiovasc Magn Reson 17:41

    Google Scholar 

  32. Uecker M, Lai P, Murphy MJ, Virtue P, Elad M, Pauly JM, Vasanawala SS, Lustig M (2014) ESPIRiT—an eigenvalue approach to autocalibrating parallel MRI: where SENSE meets GRAPPA. Magn Reson Med 71(3):990–1001

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This study is supported by National Institute of Health (NIH) Grants R01HL114118, R01NS059944 and K99HL136883.

Author information

Authors and Affiliations

  1. Department of Radiology and Biomedical Imaging, University of California, San Francisco (UCSF), San Francisco, CA, USA

    Chengcheng Zhu, Laura Eisenmenger, Jing Liu, Christopher Hess & David Saloner

  2. Department of Radiology, Changhai Hospital, Shanghai, China

    Bing Tian, Luguang Chen, Qi Liu & Jianping Lu

  3. Siemens Healthcare, Erlangen, Germany

    Esther Raithel & Christoph Forman

  4. Siemens Healthcare, San Francisco, CA, USA

    Sinyeob Ahn & Gerhard Laub

Authors
  1. Chengcheng Zhu
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  2. Bing Tian
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  3. Luguang Chen
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  4. Laura Eisenmenger
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  5. Esther Raithel
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  9. Qi Liu
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  10. Jianping Lu
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  11. Jing Liu
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Contributions

Protocol/project development: CZ, SA, GL, ER, CF, JL, CH, DS. Data collection or management: CZ, LC, QL, JL. Data analysis: CZ, BT, LE.

Corresponding authors

Correspondence to Chengcheng Zhu or Jianping Lu.

Ethics declarations

Conflict of interest

Esther Raithel, Christoph Forman, Gerhard Laub and Sinyeob Ahn are employees of Siemens. Other authors declare that they have no conflict of interest.

Ethical approval

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. This study was conducted under IRB approval of the University of California San Francisco (reference number: 10-03248) and Changhai Hospital in Shanghai (reference number: CHEC2013-204).

Informed consent

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

Electronic supplementary material

Below is the link to the electronic supplementary material.

10334_2017_667_MOESM1_ESM.tif

Figure S1. Bar plot showing the image scores of the SPACE and CS-SPACE protocols. Mean and SD are shown in the bar plot (TIFF 335 kb)

10334_2017_667_MOESM2_ESM.tif

Figure S2. Test of high parallel imaging acceleration in a volunteer. A) Sagittal SPACE image (scan time 10:50 s). B) Optimized CS-SPACE image (ETL60-20%, scan time 6:48 s). C) SPACE image with GRAPPA 2x2 (scan time 6:32 s). Red arrows show the internal carotid artery. CS-SPACE has comparable image quality with SPACE, but high GRAPPA factor significantly reduces the SNR (TIFF 1975 kb)

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Zhu, C., Tian, B., Chen, L. et al. Accelerated whole brain intracranial vessel wall imaging using black blood fast spin echo with compressed sensing (CS-SPACE). Magn Reson Mater Phy 31, 457–467 (2018). https://doi.org/10.1007/s10334-017-0667-3

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  • DOI: https://doi.org/10.1007/s10334-017-0667-3

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