Skip to main content

Advertisement

SpringerLink
Log in

A multi-vertebrae CT to US registration of the lumbar spine in clinical data

  • Original Article
  • Published:
International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Spinal needle injections are widely applied to alleviate back pain and for anesthesia. Current treatment is performed either blindly with palpation or using fluoroscopy or computed tomography (CT). Both fluoroscopy and CT guidance expose patients to ionizing radiation. Ultrasound (US) guidance for spinal needle procedures is becoming more prevalent as an alternative. It is challenging to use US as the sole imaging modality for intraoperative guidance of spine needle injections due to the acoustic shadows created by the bony structures of the vertebra that limit visibility of the target areas for injection. We propose registration of CT and the US images to augment anatomical visualization for the clinician during spinal interventions guided by US.

Methods

The proposed method involves automatic global and multi-vertebrae registration to find the closest alignment between CT and US data. This is performed by maximizing the similarity between the two modalities using voxel intensity information as well as features extracted from the input volumes. In our method, the lumbar spine is first globally aligned between the CT and US data using intensity-based registration followed by point-based registration. To account for possible curvature change of the spine between the CT and US volumes, a multi-vertebrae registration step is also performed. Springs are used to constrain the movement of the individually transformed vertebrae to ensure the optimal alignment is a pose of the lumbar spine that is physically possible.

Results

Evaluation of the algorithm is performed on 10 clinical patient datasets. The registration approach was able to align CT and US datasets from initial misalignments of up to 25 mm, with a mean TRE of 1.37 mm. These results suggest that the proposed approach has the potential to offer a sufficiently accurate registration between clinical CT and US data.

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. Balki M, Lee Y, Halpern S, Carvalho J (2009) Ultrasound imaging of the lumbar spine in the transverse plane: the correlation between estimated and actual depth to the epidural space in obese parturients. Anesth Analg 108(6):1876–1881

    Article  PubMed  Google Scholar 

  2. Conroy P, Luyet C, McCartney C, McHardy P (2013) Real-time ultrasound-guided spinal anaesthesia: a prospective observational study of a new approach. Anesthesiol Res Pract 2013:525 818–525 824

    CAS  Google Scholar 

  3. Falco F, Manchikanti L, Datta S, Sehgal N, Geffert S, Onyewu O, Zhu J, Coubarous S, Hameed M, Ward S, Sharma M, Hameed H, Singh V, Boswell M (2012) An update of the effectiveness of therapeutic lumbar facet joint interventions. Pain Physician 15:E909–E953

    PubMed  Google Scholar 

  4. Fedorov A, Tuncali K, Fennessy FM, Tokuda J, Hata N, Wells WM, Kikinis R, Tempany CM, Tempany CM (2012) Image registration for targeted MRI-guided transperineal prostate biopsy. J Magn Reson Imaging 36(4):987–9926

    Article  PubMed Central  PubMed  Google Scholar 

  5. Foroughi P, Boctor E, Swartz M, Taylor R, Fichtinger G (2007) P6d–2 ultrasound bone segmentation using dynamic programming. In: Ultrasonics symposium New York, NY, USA, pp 2523–2526

  6. Gill S, Abolmaesumi P, Fichtinger G, Boisvert J, Pichora D, Borshneck D, Mousavi P (2012) Biomechanically constrained groupwise ultrasound to CT registration of the lumbar spine. Med Image Anal 16(3):662–674

    Article  PubMed  Google Scholar 

  7. Hacihaliloglu I, Rasoulian A, Rohling R, Abolmaesumi P (2013) Statistical shape model to 3D ultrasound registration for spine interventions using enhanced local phase features. In: Medical image computing and computer-assisted intervention-MICCAI, pp 361–368

  8. Herring J, Dawant B, Maurer C, Muratore D, Galloway R Jr, Fitzpatrick J (1998) Surface-based registration of CT images to physical space for image-guided surgery of the spine: a sensitivity study. IEEE Trans Med Imaging 17(5):743–752

    Article  CAS  PubMed  Google Scholar 

  9. Johnson H, Harris G, Williams K (2007) Brainsfit: mutual information registrations of whole-brain 3D images, using the insight toolkit. Insight J

  10. Lasso A, Heffter T, Pinter C, Ungi T, Fichtinger G (2012) Implementation of the plus open-source toolkit for translational research of ultrasound-guided intervention systems. In: MICCAI workshop on systems and architectures for computer assisted interventions, Nice, France, pp 1–12

  11. Moore J, Clarke C, Bainbridge D, Wedlake C, Wiles A, Pace D, Peters T (2009) Image guidance for spinal facet injections using tracked ultrasound. In: Yang GZ, Hawkes D, Rueckert D, Noble A, Taylor C (eds) MICCAI 2009. LNCS 5761, pp 516–523

  12. Muratore DM, Russ JH, Dawant BM, Galloway R Jr (2002) Three-dimensional image registration of phantom vertebrae for image-guided surgery: a preliminary study. Comput Aided Surg 7(6):342–352

    Article  PubMed  Google Scholar 

  13. Myronenko A, Song X (2010) Point set registration: coherent point drift. IEEE Trans Pattern Anal Mach Intell 32(12):2262–2275

  14. Nagpal S, Abolmaesumi P, Rasoulian A, Ungi T, Hacihaliloglu I, Osborn J, Borschneck D, Lessoway V, Rohling RN, Mousavi P (2014) CT to US registration of the lumbar spine: a clinical feasibility study. In: Stoyanov D, Collins L, Sakuma I, Abolmaesumi P, Jannin P (eds) IPCAI 2014. LNCS 8498, pp 108–117

  15. Pieper S, Halle M, Kikinis R (2004) 3D Slicer. In: IEEE symposium on biomedical imaging: nano to macro 2004, pp 632–635

  16. Pieper S, Lorensen B, Schroeder W, Kikinis R (2006) The NA-MIC kit: Itk, vtk, pipelines, grids and 3D slicer as an open platform for the medical image computing community. In: IEEE symposium on biomedical imaging: nano to macro 2006, pp 698–701

  17. Rajpoot K, Grau V, Noble JA (2009) Local-phase based 3D boundary detection using monogenic signal and its application to real-time 3D echocardiography images. In: IEEE symposium on biomedical imaging: from nano to macro 2009, pp 783–786

  18. Rasoulian A, Rohling R, Abolmaesumi P (2012) Probabilistic registration of an unbiased statistical shape model to ultrasound images of the spine. In: proceedings of SPIE medical imaging, Orlando, Florida, USA, pp 8316:83161P-1-83161P-6

  19. Rasoulian A, Abolmaesumi P, Mousavi P (2012) Feature-based multibody rigid registration of CT and ultrasound images of lumbar spine. Med Phys 39(6):3154–3166

    Article  PubMed  Google Scholar 

  20. Rasoulian A, Rohling R, Abolmaesumi P (2013) Lumbar spine segmentation using a statistical multi-vertebrae anatomical shape+pose model. IEEE Trans Med Imaging 32(10):1890–1900

    Article  PubMed  Google Scholar 

  21. Ungi T, Abolmaesumi P, Jalal R, Welch M, Ayukawa I, Nagpal S, Lasso A, Jaeger M, Borschneck DP, Fichtinger G, Mousavi P (2012) Spinal needle navigation by tracked ultrasound snapshots. IEEE Trans Biomed Eng 59(10):2766–2772

    Article  PubMed  Google Scholar 

  22. Winter S, Brendel B, Pechlivanis I, Schmieder K, Igel C (2008) Registration of CT and intraoperative 3D ultrasound images of the spine using evolutionary and gradient-based methods. IEEE Trans Evolut Comput 12(3):284–296

    Article  Google Scholar 

  23. Yan CXB, Goulet B, Pelletier J, Chen SJ-S, Tampieri D, Collins DL (2011) Towards accurate, robust and practical ultrasound-CT registration of vertebrae for image-guided spine surgery. Int J Comput Assist Radiol Surg 6(4):523–537

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

This work was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC), Canadian Institutes of Health Research (CIHR) and the NSERC Collaborative Research and Training Experience (CREATE) program. We would like to thank Kingston General Hospital Imaging Department, and the Human Mobility Research Centre, specifically Fiona Howells, Leone Ploeg, Karen Pearson, Barbara Delaney, and Catherine Logan Munro for their assistance with patient recruitment, and data acquisition.

Author information

Authors and Affiliations

  1. School of Computing, Queen’s University, Kingston, ON, Canada

    Simrin Nagpal, Tamas Ungi & Parvin Mousavi

  2. The University of British Columbia, Vancouver, BC, Canada

    Purang Abolmaesumi, Abtin Rasoulian & Robert N. Rohling

  3. Rutgers-The State University of New Jersey, Newark, NJ, USA

    Ilker Hacihaliloglu

  4. St. Paul’s Hospital, Vancouver, BC, Canada

    Jill Osborn

  5. BC Women’s Hospital, Vancouver, BC, Canada

    Victoria A. Lessoway

  6. Kingston General Hospital, Kingston, ON, Canada

    John Rudan, Melanie Jaeger & Dan P. Borschneck

Authors
  1. Simrin Nagpal
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Purang Abolmaesumi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Abtin Rasoulian
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ilker Hacihaliloglu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Tamas Ungi
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Jill Osborn
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Victoria A. Lessoway
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. John Rudan
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Melanie Jaeger
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Robert N. Rohling
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Dan P. Borschneck
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Parvin Mousavi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Parvin Mousavi.

Ethics declarations

Conflicts of interest

The authors declare that they have no conict of interest.

Ethical standard

The study was approved by the institutional Research Ethics Board.

Informed consent

All participants provided informed consent to be part of the study.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nagpal, S., Abolmaesumi, P., Rasoulian, A. et al. A multi-vertebrae CT to US registration of the lumbar spine in clinical data. Int J CARS 10, 1371–1381 (2015). https://doi.org/10.1007/s11548-015-1247-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11548-015-1247-5

Keywords

Search

Navigation