Navigation in surgery

Uli Mezger, Claudia Jendrewski, Michael Bartels, Uli Mezger, Claudia Jendrewski, Michael Bartels

Abstract

Introduction: "Navigation in surgery" spans a broad area, which, depending on the clinical challenge, can have different meanings. Over the past decade, navigation in surgery has evolved beyond imaging modalities and bulky systems into the rich networking of the cloud or devices that are pocket-sized.

Discussion: This article will review various aspects of navigation in the operating room and beyond. This includes a short history of navigation, the evolution of surgical navigation, as well as technical aspects and clinical benefits with examples from neurosurgery, spinal surgery, and orthopedics.

Conclusion: With improved computer technology and a trend towards advanced information processing within hospitals, navigation is quickly becoming an integral part in the surgical routine of clinicians.

Figures

Fig. 1
Fig. 1
Spinal OR setup: The common OR setup involving surgical navigation consists of a stereotactic camera (upper right corner) and a computer screen (center)—both are mounted at the ceiling in the OR here. Further marker spheres are rigidly attached via a reference array to the patient and to surgical instruments
Fig. 2
Fig. 2
Basic workflows of image-based and model-based navigation. Image-based navigation requires preoperative images which need to be registered to the patient setup, typically employed for cranial or spinal surgery. Model-based navigation requires no imaging data and the process of registration matches the patients anatomy to a virtual model, typically employed for orthopedic surgery
Fig. 3
Fig. 3
The Brainlab platform family serves the needs of each discipline: Curve in two different configurations: a ceiling-mounted and b dual display; c Kick, more portable and with a smaller footprint; and d Dash, the smart mobile solution. Copyright: Brainlab AG
Fig. 4
Fig. 4
Multimodal image fusion is an important preoperative planning step to combine various imaging information for optimal surgical route planning. Copyright: Brainlab AG
Fig. 5
Fig. 5
Exemplary neuronavigation screenshot showing microscope-based navigation and the overlay of functional information, e.g., eloquent cortical areas (light blue outline), subcortical fibers (colorful fibers) in relation to the tumor (yellow outline) allowing to navigate to the tumor avoiding critical risk structures. Copyright: Brainlab AG
Fig. 6
Fig. 6
Intraoperative imaging of the future with a portable, multi-slice CT scanner tightly integrated with navigation optimized for use in surgery. Copyright: Brainlab AG
Fig. 7
Fig. 7
Knee navigation screenshot showing how navigation adds valuable information for orthopedic surgeons. It enables a gap optimization and delivers information on the laxity of the knee joint over the whole range-of-motion. This allows an analysis of the initial and final biomechanical situation during a knee replacement surgery (graph on bottom of image; purple: initial situation, yellow: final situation). Copyright: Brainlab AG
Fig. 8
Fig. 8
Use of Brainlab® Dash navigation system during total knee replacement surgery: the surgeon can intuitively navigate the bone resection with the iPod screen alongside the surgical field
Fig. 9
Fig. 9
Typical partitioning of needs in an integrated OR
Fig. 10
Fig. 10
A clinical online network like Quentry™ enables uploading of medical images into the cloud to single user or defined departmental accounts, the so-called CareTeams. The uploaded medical data can then be accessed on mobile, desktop, and surgical navigation devices

References

    1. Enchev Y. Neuronavigation: geneology, reality, and prospects. Neurosurg Focus. 2009;27(3):E11. doi: 10.3171/2009.6.FOCUS09109.
    1. Paleologos TS, Wadley JP, Kitchen ND, Thomas DG. Clinical utility and cost-effectiveness of interactive image-guided craniotomy: clinical comparison between conventional and image-guided meningioma surgery. Neurosug. 2000;47(1):40–48.
    1. Omay SB, Barnett GH. Surgical navigation for meningioma surgery. J Neurooncol. 2010;99(3):357–364. doi: 10.1007/s11060-010-0359-6.
    1. Maciuanas RJ. Computer-assisted neurosurgery. Clin Neurosurg. 2006;53:267–271.
    1. Kraus MD, Krischak G, Keppler P, Gebhard FT, Schuetz UH. Can computer-assisted surgery reduce the effective dose for spinal fusion and sacroiliac screw insertion? Clin Orthop Relat Res. 2010;468(9):2419–2429. doi: 10.1007/s11999-010-1393-6.
    1. Ferroli P, Tringali G, Acerbi F, Schiariti M, Broggi M, Aquino D, Broggi G. Advanced 3-dimensional planning in neurosurgery. Neurosurg Suppl. 2013;1:A54–A62. doi: 10.1227/NEU.0b013e3182748ee8.
    1. Jung TY, Jung S, Kim IY, Park SJ, Kang SS, Kim S, Lim SC. Application of neuronavigation system to brain tumor surgery with clinical experience of 420 cases. Minim Invasive Neurosurg. 2006;49(4):210–215. doi: 10.1055/s-2006-948305.
    1. Wadley J, Dorward N, Kitchen N, Thomas D. Pre-operative planning and intra-operative guidance in modern neurosurgery: a review of 300 cases. Ann R Coll Surg Engl. 1999;81(4):217–225.
    1. Kurimoto M, Hayashi N, Kamiyama H, Nagai S, Shibata T, Asahi T, Matsumura N, Hirashima Y, Endo S. Impact of neuronavigation and image-guided extensive resection for adult patients with supratentorial malignant astrocytomas: a single-institution retrospective study. Minim Invasive Neurosurg. 2004;47(5):278–283. doi: 10.1055/s-2004-830093.
    1. Wirtz CR, Albert FK, Schwaderer M, Heuer C, Staubert A, Tronnier VM, Knauth M, Kunze S. The benefit of neuronavigation for neurosurgery analyzed by its impact on glioblastoma surgery. Neurol Res. 2000;22(4):354–360.
    1. Sanai N, Berger MS. Glioma extent of resection and its impact on patient outcome. Neurosurg. 2008;62(4):753–766. doi: 10.1227/.
    1. Schulz C, Waldeck S, Mauer UM (2012) Intraoperative image guidance in neurosurgery: development, current indications, and future trends. Radiol Res Pract 197364. doi:10.1155/2012/197364
    1. Nimsky C, Ganslandt O, Fahlbusch R. Implementation of fiber tract navigation. Neurosurg. 2006;58(4 Suppl 2):ONS-292–ONS-303.
    1. Hatiboglu MA, Weinberg JS, Suki D, Rao G, Prabhu SS, Shah K, Jackson E, Sawaya R. Impact of intraoperative high-field magnetic resonance imaging guidance on glioma surgery: a prospective volumetric analysis. Neurosurg. 2009;64(6):1073–1081. doi: 10.1227/01.NEU.0000345647.58219.07.
    1. Nimsky C, Ganslandt O, Hastreiter P, Wang R, Benner T, Sorensen AG, Fahlbusch R. Preoperative and intraoperative diffusion tensor imaging-based fiber tracking in glioma surgery. Neurosurg. 2005;56(1):130–138.
    1. Scheufler KM, Franke J, Eckardt A, Dohmen H. Accuracy of image-guided pedicle screw placement using intraoperative computed tomography-based navigation with automated referencing, part I: cervicothoracic spine. Neurosurg. 2011;69(4):782–795. doi: 10.1227/NEU.0b013e318222ae16.
    1. Fehring TK, Odum S, Griffin WL, Mason JB, Nadaud M. Early failures in total knee arthroplasty. Clin Orthop Relat Res. 2001;392:315–318. doi: 10.1097/00003086-200111000-00041.
    1. Sharkey PF, Hozack WJ, Rothman RH, Shastri S, Jacoby SM (2002) Why are total knee arthroplasties failing today? Clin Orthop Relat Res (404)7-13.
    1. Upadhyay A, York S, Macaulay W, McGrory B, Robbennolt J, Bal BS. Medical malpractice in hip and knee arthroplasty. J Arthroplasty. 2007;22(6 Suppl 2):2–7. doi: 10.1016/j.arth.2007.05.003.
    1. Kelley TC, Swank ML. Role of navigation in total hip arthroplasty. J Bone Joint Surg Am. 2009;91(Suppl 1):153–158. doi: 10.2106/JBJS.H.01463.
    1. Mason JB, Fehring TK, Estok R, Banel D, Fahrbach K. Meta-analysis of alignment outcomes in computer-assisted total knee arthroplasty surgery. J Arthroplasty. 2007;8:1097–1106. doi: 10.1016/j.arth.2007.08.001.
    1. Blakeney WG, Khan RJ, Wall SJ. Computer-assisted techniques versus conventional guides for component alignment in total knee arthroplasty: a randomized controlled trial. J Bone Joint Surg Am. 2011;93:1377–1384. doi: 10.2106/JBJS.I.01321.
    1. Choong PF, Dowsey MM, Stoney JD. Does accurate anatomical alignment result in better function and quality of life? Comparing conventional and computer-assisted total knee arthroplasty. J Arthroplasty. 2009;24(4):560–569. doi: 10.1016/j.arth.2008.02.018.
    1. Peterlein CD, Schofer MD, Fuchs-Winkelmann S, Scherf FG. Clinical outcome and quality of life after computer-assisted total knee arthroplasty: results from a prospective, single-surgeon study and review of the literature. Chir Organi Mov. 2009;93(3):115–122.
    1. Luring C, Oczipka F, Grifka J, Perlick L (2008) The computer-assisted sequential lateral soft-tissue release in total knee arthroplasty for valgus knees. 32(2):229–235.
    1. Ryan JA, Jamali AA, Bargar WL. Accuracy of computer navigation for acetabular component placement in THA. Clin Orthop Relat Res. 2010;468(1):169–177. doi: 10.1007/s11999-009-1003-7.
    1. Petrella AJ, Stowe JQ, D’Lima DD, Rullkoetter PJ, Laz PJ. Computer-assisted versus manual alignment in THA—a probabilistic approach to range of motion. Clin Orthop Relat Res. 2009;467:50–55. doi: 10.1007/s11999-008-0561-4.
    1. Kalteis T, Handel M, Baethis H, Perlick L, Tingart M, Grifka J. Imageless navigation for insertion of the acetabular component in total hip arthroplasty—is it as accurate as CT-based navigation? J Bone Joint Surg Br. 2006;88(2):163–167. doi: 10.1302/0301-620X.88B2.17163.
    1. Reininga IH, Zijlstra W, Wagenmakers R, Boerboom AL, Huijbers BP, Groothoff JW, Bulstra SK, Stevens M. Minimally invasive and computer-navigated total hip arthroplasty: a qualitative and systematic review of the literature. BMC Musculoskelet Disord. 2010;11:92. doi: 10.1186/1471-2474-11-92.
    1. Wixson RL, MacDonald MA. Total hip arthroplasty through a minimal posterior approach using imageless computer-assisted hip navigation. J Arthroplasty. 2005;20(7 suppl 3):51–56. doi: 10.1016/j.arth.2005.04.024.
    1. Manzotti A, Cerveri P, De Momi E, Pullen C, Confalonieri N. Does computer-assisted surgery benefit leg length restoration in THA? Navigation versus conventional freehand. Int Orthop. 2009;35(1):19–24. doi: 10.1007/s00264-009-0903-1.
    1. Murphy SB, Ecker TM. Evaluation of a new leg length measurement algorithm in hip arthroplasty. Clin Orthop Relat Res. 2007;463:85–89.
    1. Renkawitz T, Schuster T, Grifka J, Kalteis E, Sendtner E. Leg length and offset measures with a pinless femoral reference array during THA. Clin Orthop Relat Res. 2010;468(7):1862–1868. doi: 10.1007/s11999-009-1086-1.
    1. Lehnen K, Giesinger K, Warschkow R, Porter M, Koch E, Kuster MS. Clinical outcome using a ligament referencing technique in CAS versus conventional technique. Knee Surg Sports Traumatol Arthrosc. 2010;19(6):887–892. doi: 10.1007/s00167-010-1264-4.
    1. Rivkin G, Liebergall M. Challenges of technology integration and computer-assisted surgery. J Bone Joint Surg Am. 2009;91(Suppl 1):13–16. doi: 10.2106/JBJS.H.01410.
    1. Schnurr C, Eysel P, König DP. Displays mounted on cutting blocks reduce the learning curve in navigated total knee arthroplasty. Comput Aided Surg. 2011;16:249–256. doi: 10.3109/10929088.2011.603750.
    1. Kuhnt D, Becker A, Ganslandt O, Bauer M, Buchfelder M, Nimsky C. Correlation of the extent of tumor volume resection and patient survival in surgery of glioblastoma multiforme with high-field intraoperative MRI guidance. Neuro Oncol. 2011;13(12):1339–1348. doi: 10.1093/neuonc/nor133.
    1. Senft C, Bink A, Franz K, Vatter H, Gasser T, Seifert V. Intraoperative MRI guidance and extent of resection in glioma surgery: a randomised, controlled trial. Lancet Oncol. 2011;12(11):997–1003. doi: 10.1016/S1470-2045(11)70196-6.
    1. Stryker. On . Accessed 5 May 2012.
    1. Denzler DN (2010) Brainlab AG, internal analysis of functionalities and user surveys of “Brainsuite Net” (Brainlab 1st generation OR integration) vs “Digital Lightbox” (Brainlab OR-optimized surgical DICOM viewer with intuitive user interface and intelligent algorithms), Mar 2010
    1. de Yang L, Xu QW, Che XM, Wu JS, Sun B. Clinical evaluation and follow-up outcome of presurgical plan by Dextroscope: a prospective controlled study in patients with skull base tumors. Surg Neurol. 2009;72(6):682–689. doi: 10.1016/j.surneu.2009.07.040.
    1. Thani NB, Bala A, Swann GB, Lind CR. Accuracy of postoperative computed tomography and magnetic resonance image fusion for assessing deep brain stimulation electrodes. Neurosurg. 2011;69(1):207–214. doi: 10.1227/NEU.0b013e318218c7ae.

Source: PubMed

3
Suscribir