Implementation of augmented reality support in spine surgery
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To implement a straightforward workflow that allows to establish augmented reality (AR) support in spine surgery.
Intraoperative computed tomography (iCT) applying a 32-slice movable scanner was used for navigation registration in a series of 10 patients who underwent surgery for extra- or intradural spinal lesions. Preoperative multimodal image data were integrated by nonlinear registration with the iCT images. Automatic segmentation was used to delineate the 3-dimensional (3-D) outline of the vertebra, and in addition, the tumor extent, as well as implants, was segmented and visualized.
Automatic patient registration without user interaction resulted in high navigation accuracy with a mean registration error of only about 1 mm. Moreover, the workflow for establishing AR was straightforward and could be easily integrated in the normal surgical procedure. Low-dose iCT protocols resulted in a radiation exposure of 0.35–0.98 mSv for cervical, 2.16–6.92 mSv for thoracic, and 3.55–4.20 mSv for lumbar surgeries, which is a reduction in the effective radiation dose by 70%. The segmented structures were intuitively visualized in the surgical field using the heads-up display of the operating microscope. In parallel, the microscope video was superimposed with the segmented 3-D structures, which were visualized in a semitransparent manner along with various display modes of the image data.
A microscope-based AR environment was successfully implemented for spinal surgery. The application of iCT for registration imaging ensures high navigational accuracy. AR greatly supports the surgeon in understanding the 3-D anatomy thereby facilitating surgery.
KeywordsAugmented reality Intraoperative computed tomography Low-dose computed tomography Navigation registration Spine tumor surgery
We would like to thank J.-W. Bartsch for thoroughly proofreading the manuscript.
Compliance with ethical standards
Conflict of interest
B Carl, M. Bopp, B. Saß and B. Voellger declare that they have no conflict of interest. Ch. Nimsky received speaker fees from Brainlab.
- 4.Nimsky C, Ganslandt O, Kober H, Moller M, Ulmer S, Tomandl B, Fahlbusch R (1999) Integration of functional magnetic resonance imaging supported by magnetoencephalography in functional neuronavigation. Neurosurgery 44(6):1249–1255. https://doi.org/10.1097/00006123-199906000-00044 CrossRefPubMedGoogle Scholar
- 5.Barnett GH, Steiner CP, Weisenberger J (1995) Adaptation of personal projection television to a head-mounted display for intra-operative viewing of neuroimaging. J Image Guided Surg 1(2):109–112. https://doi.org/10.1002/(sici)1522-712x(1995)1:2%3c109:Aid-igs6%3e3.3.Co;2-m CrossRefGoogle Scholar
- 9.Carl B, Bopp M, Chehab S, Bien S, Nimsky C (2018) Preoperative 3-dimensional angiography data and intraoperative real-time vascular data integrated in microscope-based navigation by automatic patient registration applying intraoperative computed tomography. World Neurosurg 113:e414–e425. https://doi.org/10.1016/j.wneu.2018.02.045 CrossRefPubMedGoogle Scholar
- 12.Elmi-Terander A, Skulason H, Soderman M, Racadio J, Homan R, Babic D, van der Vaart N, Nachabe R (2016) Surgical navigation technology based on augmented reality and integrated 3D intraoperative imaging: a spine cadaveric feasibility and accuracy study. Spine (Phila Pa 1976) 41(21):E1303–E1311. https://doi.org/10.1097/brs.0000000000001830 CrossRefGoogle Scholar
- 20.Greffier J, Pereira FR, Viala P, Macri F, Beregi JP, Larbi A (2017) Interventional spine procedures under CT guidance: how to reduce patient radiation dose without compromising the successful outcome of the procedure? Phys Med 35:88–96. https://doi.org/10.1016/j.ejmp.2017.02.016 CrossRefPubMedGoogle Scholar
- 22.Nagpal S, Abolmaesumi P, Rasoulian A, Hacihaliloglu I, Ungi T, Osborn J, Lessoway VA, Rudan J, Jaeger M, Rohling RN, Borschneck DP, Mousavi P (2015) A multi-vertebrae CT to US registration of the lumbar spine in clinical data. Int J Comput Assist Radiol Surg 10(9):1371–1381. https://doi.org/10.1007/s11548-015-1247-5 CrossRefPubMedGoogle Scholar
- 23.Yoon JW, Chen RE, Kim EJ, Akinduro OO, Kerezoudis P, Han PK, Si P, Freeman WD, Diaz RJ, Komotar RJ, Pirris SM, Brown BL, Bydon M, Wang MY, Wharen RE Jr, Quinones-Hinojosa A (2018) Augmented reality for the surgeon: systematic review. Int J Med Robot 14(4):e1914. https://doi.org/10.1002/rcs.1914 CrossRefPubMedGoogle Scholar