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Joint intracranial and carotid vessel wall imaging in 5 minutes using compressed sensing accelerated DANTE-SPACE

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Abstract

Objectives

To compare visualization of joint intracranial and carotid vessel walls between 5× compressed sensing accelerated three-dimensional DANTE-SPACE sequence (CS VWI) acquired in 5 min and the same sequence accelerated by 2.7× parallel imaging (PI VWI) which takes 9–10 min currently.

Methods

Following institutional review board approval and informed consent, 28 subjects including 20 stroke patients underwent PI and CS VWI examinations with an acquired spatial resolution of isotropic 0.55 mm and joint coverage of intracranial and carotid arteries. Quantitative wall thickness measurements of CS VWI and PI VWI were compared on healthy volunteers and patients with wall thickening respectively. Subjective wall visualizations of the two VWI methods on patients were scored by two radiologists blindly and independently using a 4-point scale followed by inter-rater reproducibility analysis.

Results

Linear regression analysis of wall thickness measurements showed excellent agreement between CS VWI and PI VWI in both healthy volunteers (r = 0.99) and stroke patients with wall thickening (r = 0.99). Subjective wall visualization score of CS VWI was slightly lower than PI VWI (3.13 ± 0.41 vs. 3.31 ± 0.79) but still had good diagnostic quality (> 3 based on a 4-point scale). The two radiologists’ scores agreed excellently, evidenced by the intraclass correlation coefficient (ICC) values being higher than 0.75 (p < 0.001).

Conclusions

Compressed sensing expedients joint intracranial and carotid VWI acquired at an isotropic resolution of 0.55 mm in 5 min without compromising quantitative vessel wall thickness measurement or diagnostic wall visualization.

Key Points

• CS VWI facilitates comprehensive visualization of intracranial and carotid vessel walls at an acquired isotropic resolution of 0.55 mm in a single 5-min scan.

• CS VWI affords comparable vessel wall visualization and morphology measurement as PI VWI with a shortened acquisition time by 45%.

• CS VWI alleviates the intensive trade-off between imaging resolution and scan time, and benefits the scan efficiency, motion robustness, and patient tolerance of high-resolution joint intracranial and carotid VWI.

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Abbreviations

2D:

Two-dimensional

3D:

Three-dimensional

BA:

Basilar artery

CCA:

Common carotid artery

CE:

Contrast enhanced

CS:

Compressed sensing

DANTE:

Delay alternating with nutation for tailored excitation

ECA:

Extracranial carotid artery

ICA:

Internal carotid artery

MCA:

Middle cerebral artery

MPR:

Multi-planar reconstruction

MRA:

Magnetic resonance angiography

PI:

Parallel imaging

POCS:

Projection onto convex sets

SPACE:

Sampling perfection with application of optimized contrast using different flip angle evolution

SPIRiT:

Iterative self-consistent parallel imaging reconstruction

VA:

Vertebral artery

VWI:

Vessel wall imaging

References

  1. Qureshi A, Caplan L (2014) Intracranial atherosclerosis. Lancet 383:984–998

    Article  Google Scholar 

  2. Boussel L, Arora S, Rapp J et al (2009) Atherosclerotic plaque progression in carotid arteries: monitoring with high-spatial-resolution MR imaging-multicenter trial. Radiology 252:789–796

    Article  Google Scholar 

  3. Mandell DM, Mossa-Basha M, Qiao Y et al (2017) Intracranial vessel wall MRI: principles and expert consensus recommendations of the American Society of Neuroradiology. AJNR Am J Neuroradiol 38:218–229

    Article  CAS  Google Scholar 

  4. Dieleman N, van der Kolk AG, Zwanenburg JJM et al (2014) Imaging intracranial vessel wall pathology with magnetic resonance imaging: current prospects and future directions. Circulation 130:192–201

    Article  Google Scholar 

  5. Choi YJ, Jung SC, Lee DH (2015) Vessel wall imaging of the intracranial and cervical carotid arteries. J Stroke 17:238–255

    Article  Google Scholar 

  6. Lindenholz A, van der Kolk AG, Zwanenburg JJM, Hendrikse J (2018) The use and pitfalls of intracranial vessel wall imaging: how we do it. Radiology 286:12–28

    Article  Google Scholar 

  7. Saba L, Yuan C, Hatsukami TS et al (2018) Carotid artery wall imaging: perspective and guidelines from the ASNR Vessel Wall Imaging Study Group and expert consensus recommendations of the American Society of Neuroradiology. AJNR Am J Neuroradiol 39:9–31

    Article  Google Scholar 

  8. Qiao Y, Steinman DA, Qin Q et al (2011) Intracranial arterial wall imaging using three-dimensional high isotropic resolution black blood MRI at 3.0 tesla. J Magn Reson Imaging 34:22–30

    Article  Google Scholar 

  9. Zhang L, Zhang N, Wu J et al (2015) High resolution three dimensional intracranial arterial wall imaging at 3T using T1 weighted SPACE. Magn Reson Imaging 33:1026–1034

    Article  Google Scholar 

  10. Fan Z, Yang Q, Deng Z et al (2017) Whole-brain intracranial vessel wall imaging at 3 tesla using cerebrospinal fluid-attenuated T1-weighted 3D turbo spin echo. Magn Reson Med 77:1142–1150

    Article  Google Scholar 

  11. Balu N, Yarnykh VL, Chu B, Wang J, Hatsukami T, Yuan C (2011) Carotid plaque assessment using fast 3D isotropic resolution black-blood MRI. Magn Reson Med 65:627–637

    Article  Google Scholar 

  12. Fan Z, Zhang Z, Chung YC et al (2010) Carotid arterial Wall MRI at 3T using 3D variable-flip-angle turbo spin-echo (TSE) with flow-sensitive dephasing (FSD). J Magn Reson Imaging 31:645–654

    Article  Google Scholar 

  13. Li L, Chai J, Biasiolli L et al (2014) Black-blood multicontrast imaging of carotid arteries with DANTE-prepared 2D and 3D MR imaging. Radiology 273:560–569

    Article  Google Scholar 

  14. Edjlali M, Roca P, Rabrait C, Naggara O, Oppenheim C (2014) 3D fast spin-echo T1 black-blood imaging for the diagnosis of cervical artery dissection. AJNR Am J Neuroradiol 34:103–106

    Article  Google Scholar 

  15. Cuvinciuc V, Viallon M, Momjian-Mayor I, (2013) 3D fat-saturated T1 SPACE sequence for the diagnosis of cervical artery dissection. Neuroradiology 55:595–602

  16. Han M, Rim NJ, Lee JS, Kim SY, Choi JW (2014) Feasibility of high-resolution MR imaging for the diagnosis of intracranial vertebrobasilar artery dissection. Eur Radiol 24:3017–3024

    Article  Google Scholar 

  17. Xu Y, Yuan C, Zhou Z et al (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 18:90–97

    Article  Google Scholar 

  18. Zhou Z, Li R, Zhao X et al (2015) Evaluation of 3D multi-contrast joint intra- and extracranial vessel wall cardiovascular magnetic resonance. J Cardiovasc Magn Reson 17:41–51

    Article  Google Scholar 

  19. Xu Y, Li D, Yuan C et al (2018) Association of severity between carotid and intracranial artery atherosclerosis. Ann Clin Transl Neurol 5:843–849

    Article  Google Scholar 

  20. Xie Y, Yang Q, Xie G, Pang J, Fan Z, Li D (2016) Improved black-blood imaging using DANTE-SPACE for simultaneous carotid and intracranial vessel wall evaluation. Magn Reson Med 75:2286–2294

    Article  Google Scholar 

  21. Hu X, Li Y, Zhang L, Zhang X, Liu X, Chung YC (2016) A 32-channel coil system for MR vessel wall imaging of intracranial and extracranial arteries at 3T. Magn Reson Imaging 36:86–92

    Article  Google Scholar 

  22. Zhang L, Zhang N, Wu J, Liu X, Chung YC (2017) High resolution simultaneous imaging of intracranial and extracranial arterial wall with improved cerebrospinal fluid suppression. Magn Reson Imaging 44:65–71

    Article  Google Scholar 

  23. Murphy M, Alley M, Demmel J, Keutzer K, Vasanawala S, Lustig M (2012) Fast l(1)-SPIRiT compressed sensing parallel imaging MRI: scalable parallel implementation and clinically feasible runtime. IEEE Trans Med Imaging 31:1250–1262

    Article  Google Scholar 

  24. Zhang T, Chowdhury S, Lustig M et al (2014) Clinical performance of contrast enhanced abdominal pediatric MRI with fast combined parallel imaging compressed sensing reconstruction. J Magn Reson Imaging 40:13–25

    Article  CAS  Google Scholar 

  25. Hansen SM, Sørensen TS (2013) Gadgetron: an open source framework for medical image reconstruction. Magn Reson Med 69:1768–1776

    Article  Google Scholar 

  26. Zhang N, Fan Z, Deng Z et al (2018) 3D whole-brain vessel wall cardiovascular magnetic resonance imaging: a study on the reliability in the quantification of intracranial vessel dimensions. J Cardiovasc Magn Reson 20:39–50

    Article  Google Scholar 

  27. Okuchi S, Fushimi Y, Okada T et al (2019) Visualization of carotid vessel wall and atherosclerotic plaque: T1-SPACE vs. compressed sensing T1-SPACE. Eur Radiol 29:1452–1459

    Article  Google Scholar 

  28. Zhu C, Tian B, Chen L et al (2017) Accelerated whole brain intracranial vessel wall imaging using black blood fast spin echo with compressed sensing (CS-SPACE). MAGMA 31:457–467

    Article  Google Scholar 

  29. Li L, Miller KL, Jezzard P (2012) DANTE-prepared pulse trains: a novel approach to motion-sensitized and motion-suppressed quantitative magnetic resonance imaging. Magn Reson Med 68:1423–1438

    Article  Google Scholar 

  30. Wang J, Helle M, Zhou Z, Börnert P, Hatsukami TS, Yuan C (2016) Joint blood and cerebrospinal fluid suppression for intracranial vessel wall MRI. Magn Reson Med 75:831–838

    Article  Google Scholar 

  31. Xue H, Inati S, Sørensen TS, Kellman P, Hansen MS (2015) Distributed MRI reconstruction using Gadgetron-based cloud computing. Magn Reson Med 73:1015–1025

    Article  Google Scholar 

  32. Qiao Y, Zeiler SR, Mirbagheri S et al (2014) Intracranial plaque enhancement in patients with cerebrovascular events on high-spatial-resolution MR images. Radiology 271:534–542

    Article  Google Scholar 

  33. Mossa-Basha M, Hwang WD, Havenon AD et al (2015) Multicontrast high-resolution vessel wall magnetic resonance imaging and its value in differentiating intracranial vasculopathic proces. Stroke 46:1567–1573

    Article  Google Scholar 

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

    Article  Google Scholar 

Download references

Funding

This study has received funding from the State Key Program of National Natural Science Foundation of China (Grant No. 81830056), the National Natural Science Foundation of China (Grant No. 81801691), and the Natural Science Foundation of Guangdong Province (Grant No. 2018A030313204).

Author information

Author notes

  1. Sen Jia and Lei Zhang contributed equally to this work.

Authors and Affiliations

  1. Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, Guangdong, China

    Sen Jia, Lei Zhang, Na Zhang, Ye Li, Xin Liu, Hairong Zheng & Dong Liang

  2. University of Chinese Academy of Sciences, Beijing, China

    Sen Jia

  3. Department of Neurology, Shenzhen No.2 People’s Hospital, Shenzhen, Guangdong, China

    Lijie Ren

  4. Department of Radiology, Beijing University Shenzhen Hospital, Shenzhen, Guangdong, China

    Yulong Qi

  5. Department of Radiology, Chinese People’s Liberation Army General Hospital, Beijing, China

    Jinhao Ly

  6. Siemens Healthcare Pte. Ltd, Singapore, Singapore

    Yiu-cho Chung

Authors
  1. Sen Jia
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  2. Lei Zhang
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  7. Ye Li
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  8. Xin Liu
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Corresponding author

Correspondence to Dong Liang.

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Guarantor

The scientific guarantor of this publication is Xin Liu, MD.

Conflict of interest

Dr. Yiu-cho Chung is an employee of Siemens Healthcare Pte. Ltd., Singapore. Other authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was obtained from all subjects (patients) in this study.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• retrospective

• cross-sectional

• performed at one institution

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Jia, S., Zhang, L., Ren, L. et al. Joint intracranial and carotid vessel wall imaging in 5 minutes using compressed sensing accelerated DANTE-SPACE. Eur Radiol 30, 119–127 (2020). https://doi.org/10.1007/s00330-019-06366-7

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  • DOI: https://doi.org/10.1007/s00330-019-06366-7

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