Quality of neurosurgical care and patient outcomes are inextricably linked to surgical and technical proficiency and a thorough working knowledge of microsurgical anatomy. Simulated neurosurgical training is essential for the development and refinement of technical skills prior to their use on a living patient. Recent biotechnological advances—including 3D microscopy and endoscopy, 3D printing, virtual reality, surgical simulation, surgical robotics, and advanced neuroimaging—have proved to reduce the learning curve, improve conceptual understanding of complex anatomy, and enhance visuospatial skills in neurosurgical training. For developing neurosurgeons, such tools can reduce the learning curve, improve conceptual understanding of complex anatomy, and enhance visuospatial skills. We explore the current and future roles and application of virtual reality and simulation in neurosurgical training.
- Virtual reality
- Surgical training
- Augmented reality
This is a preview of subscription content, access via your institution.
Apparent diffusion coefficient
Augmented reality and artificial intelligence
Computed tomography angiography
Functional magnetic resonance
Magnetic resonance angiography
Red green blue
Simulation markup language
Visualization tool kit
Cappabianca P, Magro F. The lesson of anatomy. Surg Neurol. 2009;71:597–89.
Moon K, Filis AK, Cohen AR. The birth and evolution of neuroscience through cadaveric dissection. Neurosurgery. 2010;67:799–810.
Aboud E, Al-Mefty O, Yaşargil MG. New laboratory model for neurosurgical training that simulates live surgery. J Neurosurg. 2002;97:1367–72.
Kockro RA, Stadie A, Schwandt E, et al. A collaborative virtual reality environment for neurosurgical planning and training. Neurosurgery. 2007;61:379–91.
Kin T, Nakatomi H, Shojima M, et al. A new strategic neurosurgical planning tool for brainstem cavernous malformations using interactive computer graphics with multimodal fusion images. J Neurosurg. 2012;117(1):78–88.
Abhari K, Baxter JSH, Chen ECS, et al. Training for planning tumour resection: augmented reality and human factors. IEEE Trans Biomed Eng. 2015;62(6):1466–77.
Moisi M, Tubbs RS, Page J, et al. Training medical novices in spinal microsurgery: does the modality matter? A pilot study comparing traditional microscopic surgery and a novel robotic optoelectronic visualization tool. Cureus. 2016;8(1):e469.
Ruisoto P, Juanes JA, Contador I, Mayoral P, Prats-Galino A. Experimental evidence for improved neuroimaging interpretation using three-dimensional graphic models. Anat Sci Educ. 2012;5(3):132–7.
Weigl M, Stefan P, Abhari K. Intra-operative disruptions, surgeon’s mental workload, and technical performance in a full-scale simulated procedure. Surg Endosc. 2015;30(2):559–66.
Valdés PA, Roberts DW, Lu F-K, Golby A. Optical technologies for intraoperative neurosurgical guidance. Neurosurg Focus. 2016;40(3):E8.
Healey AN, Sevdalis N, Vincent CA. Measuring intra-operative interference from distraction and interruption observed in the operating theatre. Ergonomics. 2006;49:589–604.
Christian CK, Gustafson ML, Roth EM, et al. A prospective study of patient safety in the operating room. Surgery. 2006;139:159–73.
Etchells E, O’Neill C, Bernstein M. Patient safety in surgery: error detection and prevention. World J Surg. 2003;27:936–42.
Schreuder HW, Wolswijk R, Zweemer RP, Schijven MP, Verheijen RH. Training and learning robotic surgery, time for a more structured approach: a systematic review. BJOG. 2012;119:137–49.
Maertens H, Madani A, Landry T, Vermassen F, Van Herzeele I, Aggarwal R. Systematic review of e-learning for surgical training. Br J Surg. 2016;103:1428–37.
Urgun K, Toktas ZO, Akakin A, Yilmaz B, Sahin S, Kilic TA. Very quickly prepared, colored silicone material for injecting into cerebral vasculature for anatomical dissection: a novel and suitable material for both fresh and non-fresh cadavers. Turk Neurosurg. 2016;26(4):568–73.
O’Donnell RD, Eggemeier FT. Workload assessment methodology. In: Handbook of perception and human performance. Cognitive processes and performance, vol. 2. New York: Wiley; 1986. p. 42.1–4.
Selye H. The evolution of the stress concept. Am Sci. 1973;61:692–9.
Satava RM. Historical review of surgical simulation-a personal prospective. World J Surg. 2008;32:141.
Hohl BL, Neal DW, Kleinhenz DT, Hoh DJ, Mocco J, Barker FGII. Higher complications and no improvement in mortality in the ACGME resident duty-hour restriction era: an analysis of more than 107.000 neurosurgical trauma patients in Nationwide inpatient sample database. Neurosurgery. 2012;70:1369–82.
Selden NR, Barbaro N, Origitano TC, Burchiel KJ. Fundamental skills for entering neurosurgery residents: report of a Pacific region “boot camp” pilot course, 2009. Neurosurgery. 2011;68:759–64.
Bohnen HG, Gaillard AW. The effects of sleep loss in a combined tracking and time estimation task. Ergonomics. 1994;37:1021–30.
Mascord DJ, Heath RA. Behavioral and physiological indices of fatigue in a visual tracking task. J Saf Res. 1992;23:19–25.
Borghini G, Astolfi L, Vecchiato G, Mattia D, Babiloni F. Measuring neurophysiological signals in aircraft pilots and car drivers for the assessment of mental workload, fatigue and drowsiness. Neurosci Biobehav Rev. 2014;44:58–75.
Muns A, Meixensberger J, Lindner D. Evaluation of a novel phantom-based neurosurgical training system. Surg Neurol Int. 2014;5:173.
Patel A, Koshy N, Ortega-Barnett J, Chan HC, Kuo Y, Luciano C, et al. Neurological tactile discrimination training with haptic-based virtual reality simulation. Neurol Res. 2014;36:1035–9.
Ofek E, Pizov R, Bitterman N. From a radial operating theatre to a self-contained operating table. Anaesthesia. 2006;61:548–52.
Ganju A, Aoun SG, Daou MR, Ahmadieh TY, Chang Wang L, et al. The role of simulation in neurosurgical education: a survey of 99 United States neurosurgery program directors. World Neurosurg. 2013;80:e1–8.
Kshettry VR, Mullin JP, Schlenk R, Recinos PF, Benzel EC. The role of laboratory dissection training in neurosurgical residency: results of a national survey. World Neurosurg. 2014;82:554–9.
Wehbe-Janek H, Colbert CY, Govednik-Horny C, White BAA, Thomas S, Shabahang M. Residents’ perspectives of the value of a simulation curriculum in a general surgery residency program: a multimethod study of stakeholder feedback. Surgery. 2012;151(6):815–21.
Breimer GE, Bodani V, Looi T, Drake JM. Design and evaluation of a new synthetic brain simulator for endoscopic third ventriculostomy. J Neurosurg. 2015;15(1):82–8.
Congress of Neurological Surgeons. Congress Quarterly. https://www.cns.org/news-advocacy/congress-quarterly; 2016 Accessed 1 Dec 2016.
Cleary DR, Siler DA, Whitney N, Selden NR. A microcontroller-based simulation of dural venous sinus injury for neurosurgical training. J Neurosurg. 2017:1–7.
Grandjean E. Fatigue in industry. Br J Ind Med. 1979;36:175–86.
Grandjean E. Fitting the task to the man: a textbook of occupational ergonomics. 4th ed: Taylor & Francis; 1988. philadelphia, PA
Johns MW, Chapman R, Crowley K, Tucker A. A new method for assessing the risks of drowsiness while driving. Somnologie. 2008;12:66–74.
Hull L, Arora S, Kassab E, Kneebone R, Sevdalis N. Assessment of stress and teamwork in the operating room: an exploratory study. Am J Surg. 2011;201:24–30.
Arora S, Sevdalis N, Nestel D, Woloshynowych M, Darzi A, Kneebone R. The impact of stress on surgical performance: a systematic review of the literature. Surgery. 2010;147:318–30. e1-e6
Wetzel CM, Kneebone RL, Woloshynowych M, et al. The effects of stress on surgical performance. Am J Surg. 2006;191:5–10.
Cinaz B, La Marca R, Arnrich B, Tröster G Monitoring of mental workload levels. Proceedings of the IADIS International Conference e-Healt. pp. 189–193. 2010.
Yurko YY, Scerbo MW, Prabhu AS, Acker CE, Stefanidis D. Higher mental workload is associated with poorer laparoscopic performance as measured by the NASA-TLX tool. Sim Healthcare. 2010;5:267–71.
Zheng B, Cassera MA, Martinec DV, Spaun GO, Swanstrom LL. Measuring mental workload during the performance of advanced laparoscopic tasks. Surg Endosc. 2010;24:45–50.
Hart SG, Staveland LE. Development of NASA-TLX: results of empirical and theoretical research. In: Human Mental Workload. Amsterdam: Elsevier; 1988. p. 139–83.
Montero PN, Acker CE, Heniford BT, et al. Single incision laparoscopic surgery (SILS) is associated with poorer performance and increased surgeon workload compared with standard laparoscopy. Am Surg. 2011;77:73–7.
Carswell C, Clarke D, Seales W. Assessing mental workload during laparoscopic surgery. Surg Innov. 2005;12:80–90.
Carter FJ, Schijven MP, Aggarwal R, et al. Consensus guidelines for validation of virtual reality surgical simulators. Surg Endosc. 2005;19(12):1523–32.
Das P, Goyal T, Xue A, Kalatoor S, Guillaume D. Simulation training in neurological surgery. Austin Neurosurg Open Access. 2014;1(1):1004–10.
Anichini G, Evins AI, Boeris D, Stieg PE, Bernardo A. Three-dimensional endoscope-assisted surgical approach to the foramen magnum and craniovertebral junction: minimizing bone resection with the aid of the endoscope. World Neurosurg. 2014;82(6):e797–805.
Raspelli S, Pallavicini F, Carelli L, et al. Validating the neuro VR-based virtual version of the multiple errands test: preliminary results. Presence Teleop Virt. 2012;21(1):31–42.
UIC BVIS Students. Surgical simulation and augmented reality. https://uicbvisstudents.wordpress.com/tag/immersive-touch/; 2016 Accessed 1 Dec 2016.
Willaert WIM, Aggarwal R, Van Herzeele I, Cheshire NJ, Vermassen FE. Recent advancements in medical simulation: patient-specific virtual reality simulation. World J Surg. 2012;36(7):1703–12.
Kockro RA, Reisch R, Serra L, Goh LC, Lee E, Stadie AT. Image-guided neurosurgery with 3-dimensional multimodal imaging data on a stereoscopic monitor. Neurosurgery. 2013;72:A78–88.
Barsom EZ, Graafland M, Schijven MP. Systematic review on the effectiveness of augmented reality applications in medical training. Surg Endosc. 2016;30:4174–83.
Doulgeris JD, Gonzalez-Blohm SA, Filis AK, Shea Thomas M, Aghayev K, Vrionis FD. Robotics in neurosurgery: evolution, current challenges, and compromises. Cancer Control. 2015;22(3):352–9.
Goetz J, Engineering. New technology may help surgeons save lives. https://uanews.arizona.edu/story/new-technology-may-help-surgeons-save-lives. Accessed 1 Dec 2016.
Espadaler JM, Conesa G. (2011) Navigated repetitive transcranial magnetic stimulation (TMS) for language mapping: a new tool for surgical planning. In: Duffau H. (eds) Brain Mapp. Springer, Vienna.
De Notaris M, Palma K, Serra L, et al. A three-dimensional computer-based perspective of the skull base. World Neurosurg. 2014;82(6):S41–8.
Christian E, Yu C, Apuzzo MLJ. Focused ultrasound: relevant history and prospects for the addition of mechanical energy to the neurosurgical armamentarium. World Neurosurg. 2014;82(3–4):354–65.
Robison RA, Liu CY, Apuzzo MLJ. Man, mind, and machine: the past and future of virtual reality simulation in neurologic surgery. World Neurosurg. 2011;76(5):419–30.
Hochman JB, Kraut J, Kazmerik K, Unger BJ. Generation of a 3D printed temporal bone model with internal fidelity and validation of the mechanical construct. Otolaryngol Head Neck Surg. 2013;150(3):448–54.
Lobel DA, Elder JB, Schirmer CM, Bowyer MW, Rezai AR. A novel craniotomy simulator provides a validated method to enhance education in the management of traumatic brain injury. Neurosurgery. 2013;73(Suppl 1):57–65.
Hooten KG, Lister JR, Lombard G, et al. Mixed reality ventriculostomy simulation. Neurosurgery. 2014;10:576–81.
Ramaswamy A, Monsuez B, Tapus A. Saferobots: a model-driven approach for designing robotic software architectures. Collab Technolog Syst. 2014:131–4.
Dharmendra, La G, Saxena K. AUC based software defect prediction for object-oriented systems. e-Learning. 2016;64(57)
Lee B, Liu CY, Apuzzo MLJ. Quantum computing: a prime modality in Neurosurgery’s future. World Neurosurg. 2012;78(5):404–8. 3
Sabbadin M. Interaction and rendering with harvested 3D data. 2016.
Kurzhals K, Burch M, Pfeiffer T, Weiskopf D. Eye tracking in computer-based visualization. Comput Sci Eng. 2015;17(5):64–71.
DeFanti TA, Sandin DJ, Cruz-Neira CA. “Room” with a “view”. IEEE Spectr. 1993;30(10):30–3.
Lemole GM, Banerjee PP, Luciano C, Neckrysh S, Charbel FT. Virtual reality in neurosurgical education. Neurosurgery. 2007;61(1):142–9.
Besharati Tabrizi L, Mahvash M. Augmented reality–guided neurosurgery: accuracy and intraoperative application of an image projection technique. J Neurosurg. 2015;123(1):206–11.
Pun T, Roth P, Bologna G, Moustakas K, Tzovaras D. Image and video processing for visually handicapped people. EURASIP J Image Video Process. 2007;2007:1–12.
Kersten-Oertel M, Gerard I, Drouin S, et al. Augmented reality in neurovascular surgery: feasibility and first uses in the operating room. Int J Comput Assist Radiol Surg. 2015;10(11):1823–36.
Barry Issenberg S, Mcgaghie WC, Petrusa ER, Lee Gordon D, Features SRJ. Uses of high-fidelity medical simulations that lead to effective learning: a BEME systematic review. Med Teach. 2005;27(1):10–28.
Kirkman MA, Ahmed M, Albert AF, Wilson MH, Nandi D, Sevdalis N. The use of simulation in neurosurgical education and training. J Neurosurg. 2014;121(2):228–46. 6
Choudhury N, Gélinas-Phaneuf N, Delorme S, Del Maestro R. Fundamentals of neurosurgery: virtual reality tasks for training and evaluation of technical skills. World Neurosurg. 2013;80(5):e9–e19.
Bajka M, Tuchschmid S, Bachofen D, Fink D, Szekely G, Harders M. Hysteroskopie: Operations training in der Virtuellen Realität. Geburtshilfe Frauenheilkd. 2008;68(S 01). S43.
Morris D, Sewell C, Barbagli F, Salisbury K, Blevins NH, Girod S. Visuohaptic simulation of bone surgery for training and evaluation. IEEE Comput Graph Appl. 2006;26(6):48–57.
Steuer J. Defining virtual reality: dimensions determining telepresence. J Commun. 1992;42(4):73–93.
Burdea GC, Lin MC, Ribarsky W, Watson B. Guest editorial: special issue on Haptics, virtual, and augmented reality. IEEE Trans Vis Comput Graph. 2005;11(6):611–3.
Bernardo A, Preul MC, Zabramski JM, Spetzler RF. A three-dimensional interactive virtual dissection model to simulate Transpetrous surgical avenues. Neurosurgery. 2003;52:499–505.
Evans CH, Schenarts KD. Evolving educational techniques in surgical training. Surg Clin North Am. 2016;96:71–88.
Willis RE, Van Sickle KR. Current status of simulation-based training in graduate medical education. Surg Clin North Am. 2015;95:767–79.
Gasco J, Holbrook TJ, Patel A, et al. Neurosurgery simulation in residency training. Neurosurgery. 2013;73:S39–45.
Schirmer CM, Mocco J, Elder JB. Evolving virtual reality simulation in neurosurgery. Neurosurgery. 2013;73:S127–37.
Dimou S, Battisti RA, Hermens DF, Lagopoulos JA. Systematic review of functional magnetic resonance imaging and diffusion tensor imaging modalities used in presurgical planning of brain tumour resection. Neurosurg Rev. 2012;36(2):205–14.
Romano A, D’Andrea G, Minniti G, et al. Pre-surgical planning and MR-tractography utility in brain tumour resection. Eur Radiol. 2009;19(12):2798–808.
Yoshino M, Kin T, Ito A, et al. Combined use of diffusion tensor tractography and multifused contrast-enhanced FIESTA for predicting facial and cochlear nerve positions in relation to vestibular schwannoma. J Neurosurg. 2015;123(6):1480–8.
Editors and Affiliations
Rights and permissions
© 2018 Springer International Publishing AG, part of Springer Nature
About this chapter
Cite this chapter
Bernardo, A., Evins, A.I. (2018). Neurosurgical Anatomy and Approaches to Simulation in Neurosurgical Training. In: Alaraj, A. (eds) Comprehensive Healthcare Simulation: Neurosurgery. Comprehensive Healthcare Simulation. Springer, Cham. https://doi.org/10.1007/978-3-319-75583-0_17
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-75582-3
Online ISBN: 978-3-319-75583-0
eBook Packages: MedicineMedicine (R0)