Abstract
Spine needle injections are widely applied to alleviate pain and to remove nerve sensation through analgesia and anesthesia. Currently, spinal injections are performed using either no image guidance or modalities that expose the patient to ionizing radiation such as fluoroscopy or computed tomography (CT). Ultrasound (US) is being investigated as an alternative as it is a non-ionizing and more accessible image modality. An inherent challenge to US imaging of the spine is the acoustic shadows created by the bony structures of the vertebrae limiting visibility. It is possible to enhance the anatomical information in US through its fusion with a pre-operative CT. In this manuscript we propose a clinical feasibility study involving a novel registration pipeline to align CT and US images of the spine. This pipeline involves automatic global and multi-vertebrae registration. We evaluate the proposed methodology on five clinical data sets. The proposed method is able to register the data sets from initial misalignments of up to 25 mm, with a mean TRE of 1.17 mm, sufficient for many spine needle interventions.
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References
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.: An update of the effectiveness of therapeutic lumbar facet joint interventions. Pain Physician 15, E909–E953 (2012)
Conroy, P., Luyet, C., McCartney, C., McHardy, P.: Real-time ultrasound-guided spinal anaesthesia: a prospective observational study of a new approach. Anesthesiology Research & Practice 2013, 525 818–525 824 (2013)
Moghari, M.H., Abolmaesumi, P.: Point-based rigid-body registration using an unscented Kalman filter. IEEE Trans. Med. Imag. 26(12) (2007)
Brounstein, A., Hacihaliloglu, I., Guy, P., Hodgson, A., Abugharbieh, R.: Towards real-time 3D US to CT bone image registration using phase and curvature feature based GMM matching. In: Fichtinger, G., Martel, A., Peters, T. (eds.) MICCAI 2011, Part I. LNCS, vol. 6891, pp. 235–242. Springer, Heidelberg (2011)
Besl, P., McKay, N.: Method for registration of 3-D shapes. IEEE Trans. Pattern Analysis and Machine Intelligence 14(2), 239–256 (1992)
Ma, B., Ellis, R.E.: Robust registration for computer-integrated orthopedic surgery: laboratory validation and clinical experience. Medical Image Analysis 7(3), 237–250 (2003)
Hacihaliloglu, I., Rasoulian, A., Rohling, R.N., Abolmaesumi, P.: 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.) MICCAI 2013, Part II. LNCS, vol. 8150, pp. 361–368. Springer, Heidelberg (2013)
Penney, G.P., Barratt, D.C., Chan, C.S., Slomczykowski, M., Carter, T.J., Edwards, P.J., Hawkes, D.J.: Cadaver validation of intensity-based ultrasound to CT registration. Medical Image Analysis 10(3), 385–395 (2006)
Winter, S., Brendel, B., Pechlivanis, I., Schmieder, K., Igel, C.: Registration of CT and intra-operative 3-D US images of the spine using evolutionary & gradient-based methods. IEEE Trans. Evol. Comp. 12(3), 284–296 (2008)
Yan, C.X.B., Goulet, B., Pelletier, J., Chen, S.J.-S., Tampieri, D., Collins, D.L.: Towards accurate, robust and practical ultrasound-CT registration of vertebrae for image-guided spine surgery. Int. Journal of Computer Assisted Radiology and Surgery 6(4), 523–537 (2011)
Gill, S., Abolmaesumi, P., Fichtinger, G., Boisvert, J., Pichora, D., Borshneck, D., Mousavi, P.: Biomechanically constrained groupwise ultrasound to CT registration of the lumbar spine. Medical Image Analysis 16(3), 662–674 (2012)
Rasoulian, A., Abolmaesumi, P., Mousavi, P.: Feature-based multibody rigid registration of CT and US images of lumbar spine. Medical Physics 39(6), 3154–3166 (2012)
Lasso, A., Heffter, T., Pinter, C., Ungi, T., Fichtinger, G.: Implementation of the plus open-source toolkit for translational research of ultrasound-guided intervention systems. In: Workshop at Medical Image Computing and Computer-Assisted Intervention (MICCAI 2012) - Systems and Architectures for Computer Assisted Interventions, pp. 1–12 (2012)
Johnson, H., Harris, G., Williams, K.: Brainsfit: Mutual information registrations of whole-brain 3D images, using the insight toolkit. Insight Journal (2007)
Myronenko, A., Song, X.: Point set registration: coherent point drift. IEEE Trans. Pattern Analysis and Machine Intelligence 32(12), 2262–2275 (2010)
Foroughi, P., Boctor, E., Swartz, M., Taylor, R., Fichtinger, G.: P6d-2 ultrasound bone segmentation using dynamic programming. In: Ultrasonics Symposium, pp. 2523–2526. IEEE, New York (2007)
Rasoulian, A., Rohling, R., Abolmaesumi, P.: Lumbar spine segmentation using a statistical multi-vertebrae anatomical shape+pose model. IEEE Trans. Medical Imaging 32(10) (2013)
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Nagpal, S. et al. (2014). CT to US Registration of the Lumbar Spine: A Clinical Feasibility Study. In: Stoyanov, D., Collins, D.L., Sakuma, I., Abolmaesumi, P., Jannin, P. (eds) Information Processing in Computer-Assisted Interventions. IPCAI 2014. Lecture Notes in Computer Science, vol 8498. Springer, Cham. https://doi.org/10.1007/978-3-319-07521-1_12
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DOI: https://doi.org/10.1007/978-3-319-07521-1_12
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07520-4
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