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Model-based registration of preprocedure MR and intraprocedure US of the lumbar spine

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Epidural and spinal needle insertions, as well as facet joint denervation and injections are widely performed procedures on the lumbar spine for delivering anesthesia and analgesia. Ultrasound (US)-based approaches have gained popularity for accurate needle placement, as they use a non-ionizing, inexpensive and accessible modality for guiding these procedures. However, due to the inherent difficulties in interpreting spinal US, they yet to become the clinical standard-of-care.

Methods

A novel statistical shape \(+\) pose \(+\) scale (s \(+\) p \(+\) s) model of the lumbar spine is jointly registered to preoperative magnetic resonance (MR) and US images. An instance of the model is created for each modality. The shape and scale model parameters are jointly computed, while the pose parameters are estimated separately for each modality.

Results

The proposed method is successfully applied to nine pairs of preoperative clinical MR volumes and their corresponding US images. The results are assessed using the target registration error (TRE) metric in both MR and US domains. The s \(+\) p \(+\) s model in the proposed joint registration framework results in a mean TRE of 2.62 and 4.20 mm for MR and US images, respectively, on different landmarks.

Conclusion

The joint framework benefits from the complementary features in both modalities, leading to significantly smaller TREs compared to a model-to-US registration approach. The s \(+\) p \(+\) s model also outperforms our previous shape \(+\) pose model of the lumbar spine, as separating scale from pose allows to better capture pose and guarantees equally-sized vertebrae in both modalities. Furthermore, the simultaneous visualization of the patient-specific models on the MR and US domains makes it possible for clinicians to better evaluate the local registration accuracy.

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References

  1. Abdi S, Datta S, Lucas LF (2005) Role of epidural steroids in the management of chronic spinal pain: a systematic review of effectiveness and complications. Pain Phys 8(1):127–143

    Google Scholar 

  2. Ahmed MN, Yamany SM, Mohamed N, Farag AA, Moriarty T (2002) A modified fuzzy C-means algorithm for bias field estimation and segmentation of MRI data. IEEE Trans Med Imaging 21(3):193–199

    Article  PubMed  Google Scholar 

  3. Behnami D, Seitel A, Rasoulian A, Anas EMA, Lessoway VA, Osborn J, Rohling R, Abolmaesumi P (2016) Joint registration of ultrasound, CT and a shape \(+\) pose statistical model of the lumbar spine for guiding anesthesia. Int J Comput Assist Radiol Surg 30(9):1–10

    Google Scholar 

  4. Bø LE, Palomar R, Selbekk T, Reinertsen I (2014) Registration of mr to percutaneous ultrasound of the spine for image-guided surgery. In: Yao J, Klinder T, Li S (eds) Computational methods and clinical applications for spine imaging. Lecture Notes in Computational Vision and Biomechanics, vol 17. Springer, Berlin, pp 209–218

  5. Boisvert J, Cheriet F, Pennec X, Labelle H, Ayache N (2008) Articulated spine models for 3D reconstruction from partial radiographic data. IEEE Trans Biomed Eng 55(11):2565–2574

    Article  PubMed  Google Scholar 

  6. Boswell MV, Colson JD, Spillane WF (2005) Therapeutic facet joint interventions in chronic spinal pain: a systematic review of effectiveness and complications. Pain Phys 8(1):101–114

    Google Scholar 

  7. Brendel B, Winter S, Rick A, Stockheim M, Ermert H (2002) Registration of 3D CT and ultrasound datasets of the spine using bone structures. Comput Aided Surg 7(3):146–155

    Article  CAS  PubMed  Google Scholar 

  8. Brudfors M, Seitel A, Rasoulian A, Lasso A, Lessoway VA, Osborn J, Maki A, Rohling RN, Abolmaesumi P (2015) Towards real-time, tracker-less 3D ultrasound guidance for spine anaesthesia. Int J Comput Assist Radiol Surg 12:1–11

  9. Center P, Covington L, Parr A (2009) Lumbar interlaminar epidural injections in managing chronic low back and lower extremity pain: a systematic review. Pain Phys 12(1):163–188

    Google Scholar 

  10. Chen EC, Mousavi P, Gill S, Fichtinger G, Abolmaesumi P (2010) Ultrasound guided spine needle insertion. In: SPIE medical imaging. International Society for Optics and Photonics, Bellingham, p. 762538

  11. Conroy PH, Luyet C, McCartney CJ, McHardy PG (2013) Real-time ultrasound-guided spinal anaesthesia: a prospective observational study of a new approach. Anesthesiol Res Pract 2013:7. doi:10.1155/2013/525818

  12. 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 

  13. Hacihaliloglu I, Rasoulian A, Rohling RN, Abolmaesumi P (2013) Statistical shape model to 3D ultrasound registration for spine interventions using enhanced local phase features. In: Mori k, Sakuma I, Sato Y, Barillot C, Navab N (eds) Medical image computing and computer-assisted intervention—MICCAI 2013. LNCS, vol. 8150. Springer, Heidelberg, pp 361–368. doi:10.1007/978-3-642-40763-5

  14. Khallaghi S, Mousavi P, Gong RH, Gill S, Boisvert J, Fichtinger G, Pichora D, Borschneck D, Abolmaesumi P (2010) Registration of a statistical shape model of the lumbar spine to 3D ultrasound images. In: Medical image computing and computer-assisted intervention—MICCAI 2010. Springer, Berlin, pp 68–75

  15. Liu SS, Strodtbeck WM, Richman JM, Wu CL (2005) A comparison of regional versus general anesthesia for ambulatory anesthesia: a meta-analysis of randomized controlled trials. Anesth Analg 101(6):1634–1642

    Article  PubMed  Google Scholar 

  16. Loizides A, Peer S, Plaikner M, Spiss V, Galiano K, Obernauer J, Gruber H (2011) Ultrasound-guided injections in the lumbar spine. Med Ultrason 13(1):54–58

    PubMed  Google Scholar 

  17. 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: Medical image computing and computer-assisted intervention—MICCAI 2009. Springer, Berlin, pp 516–523

  18. Niazi A, Chin K, Jin R, Chan V (2014) Real-time ultrasound-guided spinal anesthesia using the SonixGPS ultrasound guidance system: a feasibility study. Acta Anaesthesiol Scand 58(7):875–881

    Article  CAS  PubMed  Google Scholar 

  19. de Oliveira Filho GR (2002) The construction of learning curves for basic skills in anesthetic procedures: an application for the cumulative sum method. Anesth Analg 95(2):411–416

    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. Rasoulian A, Rohling RN, Abolmaesumi P (2013) Augmentation of paramedian 3D ultrasound images of the spine. In: Information processing in computer-assisted interventions. Springer, Berlin, pp 51–60

  22. Rasoulian A, Seitel A, Osborn J, Sojoudi S, Nouranian S, Lessoway VA, Rohling RN, Abolmaesumi P (2015) Ultrasound-guided spinal injections: a feasibility study of a guidance system. Int J Comput Assist Radiol Surg 10(9):1417–1425

  23. Rodgers A, Walker N, Schug S, McKee A, Kehlet H, Van Zundert A, Sage D, Futter M, Saville G, Clark T, MacMahon S (2000) Reduction of postoperative mortality and morbidity with epidural or spinal anaesthesia: results from overview of randomised trials. BMJ 321(7275):1493

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Rubin DI (2007) Epidemiology and risk factors for spine pain. Neurol Clin 25(2):353–371

    Article  PubMed  Google Scholar 

  25. Schumann S (2016) State of the art of ultrasound-based registration in computer assisted orthopedic interventions. In: Computational radiology for orthopaedic interventions. Springer, Berlin, pp 271–297

  26. Seitel A, Sojoudi S, Osborn J, Rasoulian A, Nouranian S, Lessoway VA, Rohling RN, Abolmaesumi P (2016) Ultrasound-guided spine anesthesia: feasibility study of a guidance system. Ultrasound Med Biol 42(12):3043–3049

    Article  PubMed  Google Scholar 

  27. Sprigge J, Harper S (2008) Accidental dural puncture and post dural puncture headache in obstetric anaesthesia: presentation and management: a 23-year survey in a district general hospital. Anaesthesia 63(1):36–43

    Article  CAS  PubMed  Google Scholar 

  28. Suhm N, Jacob A, Nolte LP, Regazzoni P, Messmer P (2000) Surgical navigation based on fluoroscopy clinical application for computer-assisted distal locking of intramedullary implants. Comput Aided Surg 5(6):391–400

    Article  CAS  PubMed  Google Scholar 

  29. Suzani A, Rasoulian A, Fels S, Rohling RN, Abolmaesumi P (2014) Semi-automatic segmentation of vertebral bodies in volumetric MR images using a statistical shape \(+\) pose model. In: SPIE medical imaging. International Society for Optics and Photonics, Bellingham, pp 90,360P–90,360P

  30. Tran D, Kamani AA, Al-Attas E, Lessoway VA, Massey S, Rohling RN (2010) Single-operator real-time ultrasound-guidance to aim and insert a lumbar epidural needle. Can J Anesth/Journal canadien d’anesthésie 57(4):313–321

    Article  PubMed  Google Scholar 

  31. 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 

  32. Yan CX, Goulet B, Pelletier J, Chen SJS, 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 

  33. Yoon SH, OBrien SL, Tran M (2013) Ultrasound guided spine injections: advancement over fluoroscopic guidance? Curr Phys Med Rehabil Rep 1(2):104–113

    Article  Google Scholar 

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Acknowledgements

This work was supported in part by the Natural Sciences and Engineering Research and Council of Canada (NSERC) and in part by the Canadian Institutes of Health Research (CIHR).

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada

    Delaram Behnami, Emran Mohammad Abu Anas, Abtin Rasoulian, Alexander Seitel & Purang Abolmaesumi

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

    Alireza Sedghi, Tamas Ungi & Parvin Mousavi

  3. Department of Ultrasound, Women’s Hospital, Vancouver, BC, Canada

    Victoria Lessoway

  4. Kingston General Hospital and Department of Surgery, School of Medicine, Queen’s University, Kinston, PN, Canada

    David Yen

  5. Department of Anesthesia, St. Paul’s Hospital, Vancouver, BC, Canada

    Jill Osborn

  6. Departments of Mechanical Engineering, Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada

    Robert Rohling

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  1. Delaram Behnami
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  2. Alireza Sedghi
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Correspondence to Delaram Behnami.

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The authors declare that they have no conflict of interest.

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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.

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

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Behnami, D., Sedghi, A., Anas, E.M.A. et al. Model-based registration of preprocedure MR and intraprocedure US of the lumbar spine. Int J CARS 12, 973–982 (2017). https://doi.org/10.1007/s11548-017-1552-2

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  • DOI: https://doi.org/10.1007/s11548-017-1552-2

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