PDF herunterladen
J Neurol Surg B Skull Base 2022; 83(S 02): e564-e573
DOI: 10.1055/s-0041-1735509
Original Article

Augmented Reality for Retrosigmoid Craniotomy Planning

Christoph Leuze  ‡   *
1   Department of Radiology, Stanford School of Medicine, Stanford, United States
,
Caio A. Neves‡   *
2   Department of Otolaryngology, Stanford School of Medicine, Stanford, United States
3   Faculty of Medicine, University of Brasília, Brasília, Brazil
,
Alejandro M. Gomez
4   Chair for Computer Aided Medical Procedures and Augmented Reality, Department of Informatics, Technical University of Munich, Germany
5   Laboratory for Computer Aided Medical Procedures, Whiting School of Engineering, Johns Hopkins University, Baltimore, United States
,
Nassir Navab
4   Chair for Computer Aided Medical Procedures and Augmented Reality, Department of Informatics, Technical University of Munich, Germany
5   Laboratory for Computer Aided Medical Procedures, Whiting School of Engineering, Johns Hopkins University, Baltimore, United States
,
Nikolas Blevins
2   Department of Otolaryngology, Stanford School of Medicine, Stanford, United States
,
Yona Vaisbuch
2   Department of Otolaryngology, Stanford School of Medicine, Stanford, United States
,
Jennifer A. McNab
1   Department of Radiology, Stanford School of Medicine, Stanford, United States
› Institutsangaben
› Weitere Informationen
Auch verfügbar auf
    Lizenzen und Reprints

Abstract

While medical imaging data have traditionally been viewed on two-dimensional (2D) displays, augmented reality (AR) allows physicians to project the medical imaging data on patient's bodies to locate important anatomy. We present a surgical AR application to plan the retrosigmoid craniotomy, a standard approach to access the posterior fossa and the internal auditory canal. As a simple and accurate alternative to surface landmarks and conventional surgical navigation systems, our AR application augments the surgeon's vision to guide the optimal location of cortical bone removal. In this work, two surgeons performed a retrosigmoid approach 14 times on eight cadaver heads. In each case, the surgeon manually aligned a computed tomography (CT)-derived virtual rendering of the sigmoid sinus on the real cadaveric heads using a see-through AR display, allowing the surgeon to plan and perform the craniotomy accordingly. Postprocedure CT scans were acquired to assess the accuracy of the retrosigmoid craniotomies with respect to their intended location relative to the dural sinuses. The two surgeons had a mean margin of davg = 0.6 ± 4.7 mm and davg = 3.7 ± 2.3 mm between the osteotomy border and the dural sinuses over all their cases, respectively, and only positive margins for 12 of the 14 cases. The intended surgical approach to the internal auditory canal was successfully achieved in all cases using the proposed method, and the relatively small and consistent margins suggest that our system has the potential to be a valuable tool to facilitate planning a variety of similar skull-base procedures.

Keywords

augmented reality - craniotomy - retrosigmoid approach - acoustic neuroma - schwannoma - magicleap

* These authors contributed equally.




Publikationsverlauf

Eingereicht: 04. Dezember 2020

Angenommen: 28. Juli 2021

Artikel online veröffentlicht:
10. September 2021

© 2021. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 

  • References

  • 1 Vávra P, Roman J, Zonča P. et al. Recent development of augmented reality in surgery: a review. J Healthc Eng 2017; 2017: 4574172
    CrossrefPubMedGoogle Scholar
  • 2 Rolland JP, Fuchs H. Optical versus video see-through head-mounted displays in medical visualization. Presence Teleoperators Virtual Environ 2000; 9 (03) 287-309
    CrossrefPubMedGoogle Scholar
  • 3 Cho J, Rahimpour S, Cutler A, Goodwin CR, Lad SP, Codd P. Enhancing reality: a systematic review of augmented reality in neuronavigation and education. World Neurosurg 2020; 139: 186-195
    CrossrefPubMedGoogle Scholar
  • 4 Perkins S, Lin M, Srinivasan S, Wheeler A, Hargreves B, Daniel B. A Mixed-Reality System for Breast Surgical Planning. Presented at IEEE International Symposium on Mixed and Augmented Reality (ISMAR-Adjunct); October 30, 2017; Nantes, France:
    PubMedGoogle Scholar
  • 5 Fuchs H, Livingston MA, Raskar R. et al. Augmented reality visualization for laparoscopic surgery. In: Wells WM, Colchester A, Delp S. eds. Medical Image Computing and Computer-Assisted Intervention—MICCAI'98. Cambridge, MA: : irst International Conference Cambridge Proceedings; 1998:1496: 934-943
    Google Scholar
  • 6 Bajura M, Fuchs H, Ohbuchi R. Merging virtual objects with the real world: seeing ultrasound imagery within the patient. Comput Graph 1992; 26 (02) 203-210
    CrossrefPubMedGoogle Scholar
  • 7 Jackler R. Atlas of Skull Base Surgery and Neurotology. New York: Thieme; 2008: 2
    Google Scholar
  • 8 Arnold H, Schulze M, Wolpert S. et al. Positioning a novel transcutaneous bone conduction hearing implant: a systematic anatomical and radiological study to standardize the retrosigmoid approach, correlating navigation-guided, and landmark-based surgery. Otol Neurotol 2018; 39 (04) 458-466
    CrossrefPubMedGoogle Scholar
  • 9 Heermann R, Schwab B, Issing PR, Haupt C, Lenarz T. Navigation with the StealthStation™ in skull base surgery: an otolaryngological perspective. Skull Base 2001; 11 (04) 277-285 DOI: 10.1055/s-2001-18634.
    Artikel in Thieme ConnectPubMedGoogle Scholar
  • 10 Ledderose GJ, Hagedorn H, Spiegl K, Leunig A, Stelter K. Image guided surgery of the lateral skull base: testing a new dental splint registration device. Comput Aided Surg 2012; 17 (01) 13-20
    CrossrefPubMedGoogle Scholar
  • 11 Birkfellner W, Watzinger F, Wanschitz F, Ewers R, Bergmann H. Calibration of tracking systems in a surgical environment. IEEE Trans Med Imaging 1998; 17 (05) 737-742 DOI: 10.1109/42.736028.
    CrossrefPubMedGoogle Scholar
  • 12 Fischer GS. Electromagnetic tracker characterization and optimal tool design [dissertation]. Baltimore, MD: Johns Hopkins University; 2005: 233
    Google Scholar
  • 13 Eggers G, Mühling J, Marmulla R. Image-to-patient registration techniques in head surgery. Int J Oral Maxillofac Surg 2006; 35 (12) 1081-1095
    CrossrefPubMedGoogle Scholar
  • 14 Azimi E, Qian L, Navab N, Kazanzides P. Alignment of the virtual scene to the 3D display space of a mixed reality head-mounted display. Accessed August 13, 2021 at: https://arxiv.org/pdf/1703.05834.pdf
    PubMedGoogle Scholar
  • 15 Kruijff E, Swan JE, Feiner S. Perceptual issues in augmented reality revisited. Presented at Presented at IEEE International Symposium on Mixed and Augmented Reality (ISMAR-Adjunct); November 22, 2010: 3–12 Seoul, Korea (South)
    PubMedGoogle Scholar
  • 16 Mitsuno D, Ueda K, Hirota Y, Ogino M. Effective Application of Mixed Reality Device HoloLens: Simple Manual Alignment of Surgical Field and Holograms. Plast Reconstr Surg 2019; 143 (02) 647-651
    CrossrefPubMedGoogle Scholar
  • 17 Li Y, Chen X, Wang N. et al. A wearable mixed-reality holographic computer for guiding external ventricular drain insertion at the bedside. J Neurosurg 2018; 131 (05) 1-8
    CrossrefPubMedGoogle Scholar
  • 18 Besharati Tabrizi L, Mahvash M. Augmented reality-guided neurosurgery: accuracy and intraoperative application of an image projection technique. J Neurosurg 2015; 123 (01) 206-211
    CrossrefPubMedGoogle Scholar
  • 19 Incekara F, Smits M, Dirven C, Vincent A. Clinical feasibility of a wearable mixed-reality device in neurosurgery. World Neurosurg 2018; 118: e422-e427
    CrossrefPubMedGoogle Scholar
  • 20 McJunkin JL, Jiramongkolchai P, Chung W. et al. Development of a mixed reality platform for lateral skull base anatomy. Otol Neurotol 2018; 39 (10) e1137-e1142
    CrossrefPubMedGoogle Scholar
  • 21 Neves CA, Vaisbuch Y, Leuze C. et al. Application of holographic augmented reality for external approaches to the frontal sinus. Int Forum Allergy Rhinol 2020; 10 (07) 920-925
    CrossrefPubMedGoogle Scholar
  • 22 Fedorov A, Beichel R, Kalpathy-Cramer J. et al. 3D Slicer as an image computing platform for the Quantitative Imaging Network. Magn Reson Imaging 2012; 30 (09) 1323-1341
    CrossrefPubMedGoogle Scholar
  • 23 Monfared A, Mitteramskogler G, Gruber S, Salisbury Jr JK, Stampfl J, Blevins NH. High-fidelity, inexpensive surgical middle ear simulator. Otol Neurotol 2012; 33 (09) 1573-1577
    CrossrefPubMedGoogle Scholar
  • 24 Chan S, Li P, Locketz G, Salisbury K, Blevins NH. High-fidelity haptic and visual rendering for patient-specific simulation of temporal bone surgery. Comput Assist Surg (Abingdon) 2016; 21 (01) 85-101
    CrossrefPubMedGoogle Scholar
  • 25 Leuze C, Sathyanarayana S, Daniel BL, McNab JA. Landmark-based mixed-reality perceptual alignment of medical imaging data and accuracy validation in living subjects. Presented at Presented at IEEE International Symposium on Mixed and Augmented Reality (ISMAR-Adjunct); December 14, 2020:1333 Porto de Galinhas, Brazil
    PubMedGoogle Scholar
  • 26 Martin-Gomez A, Eck U, Navab N. Visualization techniques for precise alignment in VR: A comparative study. Presented at IEEE Conference on Virtual Reality and 3D User Interfaces (VR); August 15, 2019:735–741 Osaka, Japan
    PubMedGoogle Scholar
  • 27 Jödicke A, Ottenhausen M, Lenarz T. Clinical Use of Navigation in Lateral Skull Base Surgery: Results of a Multispecialty National Survey among Skull Base Surgeons in Germany. J Neurol Surg B Skull Base 2018; 79 (06) 545-553
    Artikel in Thieme ConnectPubMedGoogle Scholar
  • 28 da Silva Jr. EB, Leal AG, Milano JB, da Silva Jr. LFM, Clemente RS, Ramina R. Image-guided surgical planning using anatomical landmarks in the retrosigmoid approach. Acta Neurochir (Wien) 2010; 152 (05) 905-910
    CrossrefPubMedGoogle Scholar
  • 29 Hall S, Peter Gan YC. Anatomical localization of the transverse-sigmoid sinus junction: Comparison of existing techniques. Surg Neurol Int 2019; 10 (186) 186
    CrossrefPubMedGoogle Scholar
  • 30 Wiltfang J, Rupprecht S, Ganslandt O. et al. Intraoperative image-guided surgery of the lateral and anterior skull base in patients with tumors or trauma. Skull Base 2003; 13 (01) 21-29
    Artikel in Thieme ConnectPubMedGoogle Scholar
  • 31 Grauvogel TD, Engelskirchen P, Semper-Hogg W, Grauvogel J, Laszig R. Navigation accuracy after automatic- and hybrid-surface registration in sinus and skull base surgery. PLoS One 2017; 12 (07) e0180975
    CrossrefPubMedGoogle Scholar
  • 32 Mascott CR, Sol JC, Bousquet P, Lagarrigue J, Lazorthes Y, Lauwers-Cances V. Quantification of true in vivo (application) accuracy in cranial image-guided surgery: influence of mode of patient registration. Neurosurgery 2006;59(1, suppl 1) ONS146–ONS156, discussion ONS146–ONS156
    PubMedGoogle Scholar
  • 33 Wolfsberger S, Rössler K, Regatschnig R, Ungersböck K. Anatomical landmarks for image registration in frameless stereotactic neuronavigation. Neurosurg Rev 2002; 25 (1,2): 68-72
    CrossrefPubMedGoogle Scholar
  • 34 Cutting J, Vishton P. Perceiving layout and knowing distances: the integration, relative potency, and contextual use of different information about depth. Percept Sp Motion 1995; 22 (05) 69-117
    CrossrefPubMedGoogle Scholar
  • 35 Krajancich B, Padmanaban N, Wetzstein G. Factored occlusion: single spatial light modulator occlusion-capable optical see-through augmented reality display. IEEE Trans Vis Comput Graph 2020; 26 (05) 1871-1879
    CrossrefPubMedGoogle Scholar
  • 36 Schowengerdt B, Lin D, St Hilaire P. Multi-layer diffractive eyepiece. Accessed August 13, 2021 at: https://patentscope.wipo.int/search/en/detail.jsf?docId=EP321535057
    PubMedGoogle Scholar
  • 37 Konrad R, Angelopoulos A, Wetzstein G. Gaze-contingent ocular parallax rendering for virtual reality. ACM Trans Graph 2020; 39 (02) 10
    CrossrefPubMedGoogle Scholar
  • 38 Fotouhi J, Unberath M, Navab N. et al. Reflective-AR display: an interaction methodology for virtual-to-real alignment in medical robotics. IEEE Robot Autom Lett 2020; 5 (02) 2722-2729
    CrossrefPubMedGoogle Scholar
  • 39 Diaz C, Walker M, Szafir DA, Szafir D. Designing for depth perceptions in augmented reality. IEEE International Symposium on Mixed and Augmented Reality (ISMAR); October 9–13, 2017:111–122 Nantes, France
    PubMedGoogle Scholar
  • 40 NVIDIA Clara documentation. Accessed August 13, 2021 at: https://docs.nvidia.com/clara/tlt-mi/clara-train-sdk-v2.0/index.html
    PubMedGoogle Scholar