Skip to main content

Advertisement

SpringerLink
Log in

An Investigation of 2D Spine Magnetic Resonance Imaging (MRI) with Compressed Sensing (CS)

  • Scientific Article
  • Published:
Skeletal Radiology Aims and scope Submit manuscript

Abstract

Objective

To investigate the feasibility of compressed sensing MRI (CS-MRI) in the application of 2D spinal imaging and compare its performance with conventional MR imaging (non-CS-MRI).

Methods

The CS imaging protocol was optimized on 5 volunteers. Non-CS-MRI and CS-MRI of 2D sagittal T1 weighted imaging (WI), Sag T2WI, and axial T2WI were performed for 71 patients (22 cervical, 8 thoracic, 41 lumbar MRI). Paired t tests were conducted to compare the total scan time. Three radiologists assessed image quality and lesion diagnosis independently. A Kendall W test was performed to assess interobserver agreement of the image quality scores and lesion diagnosis between readers. A nonparametric test (Wilcoxon test) was performed to compare the image quality. For lesion diagnosis, the interobserver and interstudy agreements were evaluated by kappa analysis. Paired t tests were conducted for SNR and CNR comparison.

Results

The mean scan time for spine CS-MRI (4 min 28.7 s ± 34.6 s) was significantly shorter than that with non-CS-MRI (7 min 21.3 s ± 38.7 s, t =  − 47.464, P < 0.0001). CS-MRI achieved higher SNR and CNR than Non-CS-MRI in image quality assessment. Interobserver agreements of lesion diagnosis were excellent between non-CS-MRI and CS-MRI (kappa value from 0.913 to 1.000, P < 0.001). Interstudy agreements of lesion assessments were also excellent (kappa value = 1.000, with P < 0.001).

Conclusion

CS-MRI spine imaging can significantly reduce the scan time, while maintaining comparable imaging quality to non-CS-MRI.

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. Taber KH, Herrick RC, Weathers SW, Kumar AJ, Hayman LA. Pitfalls and artifacts encountered in clinical MR imaging of the spine. Radiographics. 1998;18(6):1499–521. https://doi.org/10.1148/radiographics.18.6.9821197.

    Article  CAS  PubMed  Google Scholar 

  2. Hermann KGA, Althoff CE, Schneider U, Zühlsdorf S, Lembcke A, Hamm B, et al. Spinal changes in patients with spondyloarthritis: comparison of MR imaging and radiographic appearances. Radiographics. 2005;25(3):570–569. https://doi.org/10.1023/A:1015523611397.

    Article  Google Scholar 

  3. Groves CJ, Cassarpullicino VN, Tins BJ, Tyrrell PN, Mccall IW. Chance-type flexion-distraction injuries in the thoracolumbar spine: MR imaging characteristics. Radiology. 2005;236(2):601–8. https://doi.org/10.1148/radiol.2362040281.

    Article  PubMed  Google Scholar 

  4. Arnbak B, Jensen TS, Egund N, Zejden A, Hørslev-Petersen K, Manniche C, et al. Prevalence of degenerative and spondyloarthritis-related magnetic resonance imaging findings in the spine and sacroiliac joints in patients with persistent low back pain. Eur Radiol. 2016;26(4):1191–203. https://doi.org/10.1007/s00330-015-3903-0.

    Article  PubMed  Google Scholar 

  5. Lyu FJ, Cui H, Pan H, Mc Cheung K, Cao X, Iatridis JC, et al. Painful intervertebral disc degeneration and inflammation: from laboratory evidence to clinical interventions. Bone Res. 2021;9(1):7. https://doi.org/10.1038/s41413-020-00125-x.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Pillastrini P, Gardenghi I, Bonetti F, Capra F, Guccione A, Mugnai R, et al. An updated overview of clinical guidelines for chronic low back pain management in primary care. Joint Bone Spine. 2012;79(2):176–85. https://doi.org/10.1016/j.jbspin.2011.03.019.

    Article  PubMed  Google Scholar 

  7. Robertson WD, Jarvik JG, Tsuruda JS, Koepsell TD, Maravilla KR. The comparison of a rapid screening MR protocol with a conventional MR protocol for lumbar spondylosis. AJR. 1996;166:909–16. https://doi.org/10.2214/AJR.15.15764.

    Article  CAS  PubMed  Google Scholar 

  8. Iida T, Abumi K, Kotani Y, Kaneda K. Effects of aging and spinal degeneration on mechanical properties of lumbar supraspinous and interspinous ligaments. Spine J. 2002;2(2):95–100. https://doi.org/10.1016/s1529-9430(02)00142-0.

    Article  PubMed  Google Scholar 

  9. Urban JP, Roberts S. Degeneration of the intervertebral disc. Arthritis Res Ther. 2003;5(3):120–30. https://doi.org/10.1186/ar629.

    Article  PubMed  PubMed Central  Google Scholar 

  10. European Society of Skeletal Radiology. Guidelines for MR imaging of sports injuries. https://essr.org/content-essr/uploads/2016/10/ ESSR-MRI-Protocols-Spine.pdf. Accessed May 31, 2018.

  11. Taron J, Weiss J, Notohamiprodjo M, Kuestner T, Bamberg F, Weiland E, et al. Acceleration of magnetic resonance cholangiopancreatography using compressed sensing at 1.5 and 3 T. Investigative Radiology 2018;53(11): 681–688. https://doi.org/10.1097/RLI.0000000000000489.

  12. Lohöfer FK, Kaissis GA, Rasper M, Katemann C, Hock A, Peeters JM, et al. Magnetic resonance cholangiopancreatography at 3 Tesla: image quality comparison between 3D compressed sensing and 2D single-shot acquisitions. Eur J Radiol. 2019;115:53–8. https://doi.org/10.1016/j.ejrad.2019.04.002.

    Article  PubMed  Google Scholar 

  13. Garwood ER, Recht MP, White LM. Advanced imaging techniques in the knee: Benefits and limitations of new rapid acquisition strategies for routine knee MRI. AJR Am J Roentgenol. 2017;209:552–60. https://doi.org/10.2214/AJR.17.18228.

    Article  PubMed  Google Scholar 

  14. Lin Z, Zhang X, Guo L, Wang K, Jiang Y, Hu X, et al. Clinical feasibility study of 3D intracranial magnetic resonance angiography using compressed sensing. J Magn Reson Imaging. 2019;50:1843–51. https://doi.org/10.1002/jmri.26752.

    Article  PubMed  Google Scholar 

  15. Vranic JE, Cross NM, Wang Y, Hippe DS, de Weerdt E, Mossa-Basha M. Compressed sensing-sensitivity encoding (CS-SENSE) accelerated brain imaging: reduced scan time without reduced image quality. AJNR Am J Neuroradiol. 2019;40(1):92–8. https://doi.org/10.3174/ajnr.A5905.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Bratke G, Rau R, Weiss K, Kabbasch C, Sircar K, Morelli JN, et al. Accelerated MRI of the lumbar spine using compressed sensing: quality and efficiency. J Magn Reson Imaging. 2019;49(7):e164–75. https://doi.org/10.1002/jmri.26526.

    Article  PubMed  Google Scholar 

  17. Morita K, Nakaura T, Maruyama N, Iyama Y, Oda S, Utsunomiya D, et al. Hybrid of compressed sensing and parallel imaging applied to three-dimensional isotropic T2-weighted Turbo spin-echo MR imaging of the lumbar spine. Magn Reson Med Sci. 2020;19(1):48–55. https://doi.org/10.2463/mrms.mp.2018-0132.

    Article  PubMed  Google Scholar 

  18. Yang AC, Kretzler M, Sudarski S, Gulani V, Seiberlich N. Sparse reconstruction techniques in magnetic resonance imaging: methods, applications, and challenges to clinical adoption. Invest Radiol. 2016;51(6):349–64. https://doi.org/10.1097/RLI.0000000000000274.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Hollingsworth KG. Reducing acquisition time in clinical MRI by data undersampling and compressed sensing reconstruction. Phys Med Biol. 2015;60(21):R297-322. https://doi.org/10.1088/0031-9155/60/21/R297.

    Article  PubMed  Google Scholar 

  20. Fan X, Lian Q, Shi B. Compressed sensing MRI based on image decomposition model and group sparsity. Magn Reson Imaging. 2019;60:101–9. https://doi.org/10.1016/j.mri.2019.03.011.

    Article  PubMed  Google Scholar 

  21. Feng L, Benkert T, Block KT, Sodickson DK, Otazo R, Chandarana H. Compressed sensing for body MRI. J Magn Reson Imaging. 2017;45(4):966–87. https://doi.org/10.1002/jmri.25547.

    Article  PubMed  Google Scholar 

  22. Jaspan ON, Fleysher R, Lipton ML. Compressed sensing MRI: a review of the clinical literature. Br J Radiol. 2015;88(1056):20150487. https://doi.org/10.1259/bjr.20150487.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Ikeda H, Ohno Y, Murayama K, Yamamoto K, Iwase A, Fukuba T, et al. Compressed sensing and parallel imaging accelerated T2 FSE sequence for head and neck MR imaging: comparison of its utility in routine clinical practice. Eur J Radiol. 2021;135: 109501. https://doi.org/10.1016/j.ejrad.2020.109501.

    Article  PubMed  Google Scholar 

  24. Mo ̈nch S, Sollmann N, Hock A, Zimmer C, Kirschke JS, Hedderich DM. Magnetic resonance imaging of the brain using compressed sensing - quality assessment in daily clinical routine. Clin Neuroradiol. 2020;30(2):279–86. https://doi.org/10.1007/s00062-019-00789-x.

    Article  Google Scholar 

  25. Uecker M, Lai P, Murphy MJ, Virtue P, Elad M, Pauly JM, et al. ESPIRiT—an eigenvalue approach to autocalibrating parallel MRI: where SENSE meets GRAPPA. Magn Reson Med. 2014;71:990–1001. https://doi.org/10.1002/mrm.24751.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Lustig M, Donoho D, Pauly JM. Sparse MRI: the application of compressed sensing for rapid MR imaging. Magn Reson Med. 2007;58:1182–95. https://doi.org/10.1002/mrm.21391.

    Article  PubMed  Google Scholar 

  27. Obyn C, Cleemput I. The capital cost and productivity of MRI in a Belgian setting. JBR-BTR. 2010;93(2):92–6. https://doi.org/10.1016/j.jcmg.2010.01.003.

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Radiology, Peking University First Hospital, XiCheng District, 8 XiShiKu Avenue, Beijing, 100034, China

    Jianxing Qiu, Jing Liu, Zhongxu Bi, Xiaowei Sun & Naishan Qin

  2. Philips Healthcare, Beijing, China

    Qingping Gu & Geli Hu

Authors
  1. Jianxing Qiu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jing Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zhongxu Bi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xiaowei Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Qingping Gu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Geli Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Naishan Qin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Naishan Qin.

Ethics declarations

Conflict of interest

The authors declare no competing interests.

Additional information

Publisher's note

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

Jianxing Qiu and Jing Liu contributed equally to this work

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 593 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Qiu, J., Liu, J., Bi, Z. et al. An Investigation of 2D Spine Magnetic Resonance Imaging (MRI) with Compressed Sensing (CS). Skeletal Radiol 51, 1273–1283 (2022). https://doi.org/10.1007/s00256-021-03954-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00256-021-03954-x

Keywords

Search

Navigation