Skip to main content

The Frontiers of Neurosurgery

  • Chapter
  • First Online:
Fundamentals of Neurosurgery
  • 1347 Accesses

Abstract

Neurological surgery is a rapidly evolving medical field. Although relatively new, this medical specialty has experienced an unprecedented technological development. As we live the so-called fourth industrial revolution, neurosurgery seems to be following this revolution closely. It consists of robotics, artificial intelligence, nanotechnology, extensive study of epigenetics, tridimensional printing, big computer data, and automated machines, among others. This fascinating era has been reviewed in light of the fourth human revolution. The chapter is divided into various topics corresponding to different neurosurgical fields. Many recent advancements are presented, as well as what might be expected for doctors and patients. This chapter is based on current medical and technical literature, as we present today’s developments. Some topics allow us to predict what may be expected for us in the near future, since knowledge and technology have never developed so quickly.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 99.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 129.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Suggested Readings and References

  1. Burkhardt JK, Zinn PO, Bozinov O, et al. Neurosurgical education in Europe and the United States of America. Neurosurg Rev. 2010;33(4):409–17.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Schwab K. The fourth industrial revolution. New York: Crown Business, Crown Publishing Group; 2016.

    Google Scholar 

  3. D’Andrea G, Trillo G, Picotti V, Raco A. Functional Magnetic Resonance Imaging (fMRI), pre-intraoperative tractography in neurosurgery: the experience of Sant’ Andrea Rome University Hospital. Acta Neurochir Suppl. 2017;124:241–50.

    Article  PubMed  Google Scholar 

  4. D’Andrea G, Familiari P, Di Lauro A, et al. Safe resection of gliomas of the dominant angular gyrus availing of preoperative FMRI and intraoperative DTI: preliminary series and surgical technique. World Neurosurg. 2016;87:627–39.

    Article  PubMed  Google Scholar 

  5. Nakagawa S, Murai Y, Matano F, et al. Evaluation video angiography of patency after vascular anastomosis using quantitative evaluation of visualization time in indocyanine green. World Neurosurg. 2018;110:e699–709.

    Article  PubMed  Google Scholar 

  6. Roessler K, Krawagna M, Dörfler A, et al. Essentials in intraoperative indocyanine green videoangiography assessment for intracranial aneurysm surgery: conclusions from 295 consecutively clipped aneurysms and review of the literature. Neurosurg Focus. 2014;36(2):E7.

    Article  PubMed  Google Scholar 

  7. Wright JM, Huang CL, Sharma R, et al. Cardiac standstill and circulatory flow arrest in surgical treatment of intracranial aneurysms: a historical review. Neurosurg Focus. 2014;36(4):E10.

    Article  PubMed  Google Scholar 

  8. Intarakhao P, Thiarawat P, Rezai Jahromi B, et al. Adenosine-induced cardiac arrest as an alternative to temporary clipping during intracranial aneurysm surgery. J Neurosurg. 2018;129(3):684–90.

    Article  PubMed  Google Scholar 

  9. Coelho G, Chaves TMF, Goes AF, et al. Multimaterial 3D printing preoperative planning for frontoethmoidal meningoencephalocele surgery. Childs Nerv Syst. 2017; https://doi.org/10.1007/s00381-017-3616-6.

  10. Govsa F, Karakas AB, Ozer MA, Eraslan C. Development of life-size patient-specific 3D-printed Dural venous models for preoperative planning. World Neurosurg. 2018;110:e141–9.

    Article  PubMed  Google Scholar 

  11. Choque-Velasquez J, Colasanti R, Collan J, et al. Virtual reality glasses and “Eye-hands blind technique” for microsurgical training in Neurosurgery. World Neurosurg. 2018;112:126–30. pii: S1878–8750(18)30110–4.

    Article  PubMed  Google Scholar 

  12. Gmeiner M, Dirnberger J, Fenz W, et al. Virtual cerebral aneurysm clipping with real-time haptic force feedback in neurosurgical education. World Neurosurg. 2018;112:e313–23. pii: S1878–8750(18)30082–2.

    Article  PubMed  Google Scholar 

  13. Rhoton AL Jr. Cranial anatomy and surgical approaches. The Congress of Neurological Surgeons ed. Schaumberg; 2003.

    Google Scholar 

  14. Tang Y, Sun W, Toga AW, et al. A probabilistic atlas of human brainstem pathways based on connectome imaging data. NeuroImage. 2018;169:227–39.

    Article  PubMed  Google Scholar 

  15. Abdallah CG, Averill LA, Collins KA, et al. Ketamine treatment and global brain connectivity in major depression. Neuropsychopharmacology. 2017;42(6):1210–9.

    Article  CAS  PubMed  Google Scholar 

  16. Li T, Wang Q, Zhang J, et al. Brain-wide analysis of functional connectivity in first-episode and chronic stages of schizophrenia. Schizophr Bull. 2017;43(2):436–48.

    PubMed  Google Scholar 

  17. Lu FM, Dai J, Couto TA, et al. Diffusion tensor imaging tractography reveals disrupted white matter structural connectivity network in healthy adults with insomnia symptoms. Front Hum Neurosci. 2017;11:583.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Ji GJ, Yu Y, Miao HH, Wang ZJ, Tang YL, Liao W. Decreased network efficiency in benign epilepsy with centrotemporal spikes. Radiology. 2017;283(1):186–94.

    Article  PubMed  Google Scholar 

  19. Whelan CD, Altmann A, Botía JA, et al. Structural brain abnormalities in the common epilepsies assessed in a worldwide ENIGMA study. Brain. 2018;141(2):391–408.

    Article  PubMed  PubMed Central  Google Scholar 

  20. T Vu A, Jamison K, Glasser MF, et al. Tradeoffs in pushing the spatial resolution of fMRI for the 7T human connectome project. NeuroImage. 2017;154:23–32.

    Article  PubMed  Google Scholar 

  21. Bari AA, Thum J, Babayan D, Lozano AM. Current and expected advances in deep brain stimulation for movement disorders. Prog Neurol Surg. 2018;33:222–9.

    Article  PubMed  Google Scholar 

  22. Martinez-Ramirez D, Jimenez-Shahed J, et al. Efficacy and safety of deep brain stimulation in Tourette syndrome: the international Tourette syndrome deep brain stimulation public database and registry. JAMA Neurol. 2018;75(3):353–9. https://doi.org/10.1001/jamaneurol.2017.4317.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Lozano CS, Tam J, Lozano AM. The changing landscape of surgery for Parkinson’s disease. Mov Disord. 2018;33(1):36–47.

    Article  PubMed  Google Scholar 

  24. Bari AA, Thum J, Babayan D, Lozano AM. Current and expected advances in deep brain stimulation for movement disorders. Prog Neurol Surg. 2018;33:222–9.

    Article  PubMed  Google Scholar 

  25. Elias GJB, Namasivayam AA, Lozano AM. Deep brain stimulation for stroke: current uses and future directions. Brain Stimul. 2018;11(1):3–28.

    Article  PubMed  Google Scholar 

  26. Beckett LA, Harvey DJ, Gamst A, et al. The Alzheimer’s disease neuroimaging initiative: annual change in biomarkers and clinical outcomes. Alzheimers Dement. 2010;6(3):257–64.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Ponce FA, Asaad WF, Foote KD, et al. Bilateral deep brain stimulation of the fornix for Alzheimer’s disease: surgical safety in the advance trial. J Neurosurg. 2016;125(1):75–84.

    Article  PubMed  Google Scholar 

  28. Dalton B, Bartholdy S, Campbell IC, Schmidt U. Neurostimulation in clinical and sub-clinical eating disorders: a systematic update of the literature. Curr Neuropharmacol. 2018;16(8):1174–92. https://doi.org/10.2174/1570159X16666180108111532.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Lipsman N, Lam E, Volpini M, et al. Deep brain stimulation of the subcallosal cingulate for treatment-refractory anorexia nervosa: 1 year follow-up of an open-label trial. Lancet Psychiatry. 2017;4(4):285–94.

    Article  PubMed  Google Scholar 

  30. de Oliveira Souza C, de Lima-Pardini AC, Coelho DB, et al. Peduncolopontine DBS improves balance in progressive supranuclear palsy: instrumental analysis. Clin Neurophysiol. 2016;127(11):3470–1.

    Article  PubMed  Google Scholar 

  31. Thevathasan W, Debu B, Aziz T, et al. Pedunculopontine nucleus deep brain stimulation in Parkinson’s disease: a clinical review. Mov Disord. 2018;33(1):10–20.

    Article  PubMed  Google Scholar 

  32. Lizarraga KJ, Gorgulho A, Chen W, De Salles AA. Molecular imaging of movement disorders. World J Radiol. 2016;8(3):226–39.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Spetzler RF, Zabramski JM, McDougall CG, et al. Analysis of saccular aneurysms in the Barrow Ruptured Aneurysm Trial. J Neurosurg. 2018;128(1):120–5.

    Article  PubMed  Google Scholar 

  34. Spetzler RF, McDougall CG, Zabramski JM, et al. The Barrow Ruptured Aneurysm Trial: 6-year results. J Neurosurg. 2015;123(3):609–17.

    Article  PubMed  Google Scholar 

  35. Bijlenga P, Gondar R, Schilling S, et al. PHASES score for the management of intracranial aneurysm a cross-sectional population-based retrospective study. Stroke. 2017;48:1–8.

    Article  Google Scholar 

  36. Greving JP, Wermer MJ, Brown RD Jr, et al. Development of the PHASES score for prediction of risk of rupture of intracranial aneurysms: a pooled analysis of six prospective cohort studies. Lancet Neurol. 2014;13(1):59–66.

    Article  PubMed  Google Scholar 

  37. Pexman JH, Barber PA, Hill MD, et al. Use of the Alberta Stroke Program Early CT Score (ASPECTS) for assessing CT scans in patients with acute stroke. AJNR Am J Neuroradiol. 2001;22(8):1534–42.

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Bal S, Bhatia R, Menon BK, et al. Time dependence of reliability of noncontrast computed tomography in comparison to computed tomography angiography source image in acute ischemic stroke. Int J Stroke. 2015;10(1):55–60.

    Article  PubMed  Google Scholar 

  39. Fransen PS, Beumer D, Berkhemer OA, et al. MR CLEAN, a multicenter randomized clinical trial of endovascular treatment for acute ischemic stroke in the Netherlands: study protocol for a randomized controlled trial. Trials. 2014;15:343.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Goyal M, Dermchuk AM, Menon BK, et al. Randomized assessment of rapid endovascular treatment of ischemic stroke. N Engl J Med. 2015;372:1019–30.

    Article  CAS  PubMed  Google Scholar 

  41. Saver JL, Goyal M, Bonafe A, et al. Stent-retriever Thrombectomy after intravenous t-PA, vs. t-PA alone in acute stroke. N Engl J Med. 2015;372:2285–95.

    Article  CAS  PubMed  Google Scholar 

  42. Campbell BCV, Mitchell PJ, Kleinig PJ, et al. Endovascular therapy for ischemic stroke with perfusion-imaging selection. N Engl J Med. 2015;372:1009–18.

    Article  CAS  PubMed  Google Scholar 

  43. Jovin TG, Bonafe A, Cobo E, et al. Thrombectomy within 8 hours onset of acute stroke. N Engl J Med. 2015;372:2296–306.

    Article  CAS  PubMed  Google Scholar 

  44. Nogueira RG, Jadhav DC, Haussen DC, et al. Thrombectomy 6-24 hours after stroke with mismatch between deficit and infarct. N Engl J Med. 2018;378(1):11–21.

    Article  PubMed  Google Scholar 

  45. Albers GW, Kemp MS, Christensen JP, et al. Thrombectomy for stroke at 6 to 16 hours with selection by perfusion imaging. N Engl J Med. 2018;378:708–18. https://doi.org/10.1056/NEJMoa1713973.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Hacke W. A new DAWN for imaging-based selection in the treatment of acute stroke. N Engl J Med. 2018;378(1):81–3.

    Article  PubMed  Google Scholar 

  47. van der Hoeven EJ, Schonewille WJ, Vos JA, et al. The basilar artery international cooperation study (BASICS): study protocol for a randomised controlled trial. Trials. 2013;14:200.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Bashkar S, Stanwell P, Cordato D, et al. Reperfusion therapy in acute ischemic stroke: dawn of a new era? BMC Neurol. 2018:18–8.

    Google Scholar 

  49. Oliveira Magaldi M, Nicolato A, Godinho JV, et al. Human placenta aneurysm model for training neurosurgeons in vascular neurosurgery. Neurosurgery. 2014;10(Suppl 4):592–600.

    Article  PubMed  Google Scholar 

  50. De Oliveira MMR, Ferrarez CE, Ramos TM, et al. Learning brain aneurysm microsurgical skills in a human placenta model: predictive validity. J Neurosurg. 2017;128(3):846–52.

    Article  PubMed  Google Scholar 

  51. Ostrom QT, Guttleman H, Fulop J, et al. CBTRUS statistical report: primary brain and central nervous system tumors diagnosed in the United States in 2008–2012. Neuro-Oncology. 2015;17:iv1–iv62.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Louis DN, Perry A, Reifenberger G, von Deimling A, Figarella-Branger D, Cavenee WK, Ohgaki H, Wiestler OD, Kleihues P, Ellison DW. The 2016 World Health Organization classification of tumors of the central nervous system: a summary. Acta Neuropathol. 2016;131:803–20.

    Article  PubMed  Google Scholar 

  53. Font-Burgada J, Reina O, Rossell D, Azorín F. chroGPS, a global chromatin positioning system for the functional analysis and visualization of the epigenome. Nucleic Acids Res. 2014;42(4):2126–3.

    Article  CAS  PubMed  Google Scholar 

  54. Chikawa K, Morishita S. A linear time algorithm for detecting long genomic regions enriched with a specific combination of epigenetic states. BMC Genomics. 2015;16(Suppl 2):S8.

    Article  Google Scholar 

  55. Hortobágyi T, Bencze J, Varkoly G, et al. Meningioma recurrence. Open Med (Wars). 2016;11(1):168–73.

    Google Scholar 

  56. De la Garza-Ramos R, Flores-Rodríue JV, Martínez-Gutierrez JC, Ruiz-Valls A, Caroso-Rio E. Current standing and frontiers of gene therapy for meningiomas. Neurosurg Focus. 2013;35(6):E4.

    Article  Google Scholar 

  57. Bi WL, Abedalthagafi M, Horowitz P, et al. Genomic landscape of intracranial meningiomas. J Neurosurg. 2016;125:525–35.

    Article  CAS  PubMed  Google Scholar 

  58. Galani V, Lampri E, Varouktsi A, et al. Genetic and epigenetic alterations in meningiomas. Clin Neurol Neurosurg. 2017;158:119–25.

    Article  PubMed  Google Scholar 

  59. Tang M, Wei H, Han L, et al. Whole-genome sequencing identifies new genetic alterations in meningiomas. Oncotarget. 2017;8(10):17070–80.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Olar A, Wani KM, Wilson CD, et al. Global epigenetic profiling identifies methylation subgroups associated with recurrence-free survival in meningioma. Acta Neuropathol. 2017;133(3):431–44.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. NNI Supplement to the President’s 2018 Budget. NSTC/COT/NSET. Nov 30, 2017.

    Google Scholar 

  62. Peng C, Gao X, Xu J, et al. Targeting orthotopic gliomas with renal-clearable luminescent gold nanoparticles. Nano Res. 2017;10(4):1366–76.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Ferber S, Tiram G, Sousa-Herves A, et al. Co-targeting the tumor endothelium and P-selectin-expressing glioblastoma cells leads to a remarkable therapeutic outcome. Elife. 2017;6:pii: e25281.

    Article  Google Scholar 

  64. Zhang B, Wang H, Jin K, Jiang T, Shen S, Luo Z. BQ123 selectively improved tumor perfusion and enhanced nanomedicine delivery for glioblastomas treatment. Pharmacol Res. 2017;132:211–9. pii: S1043–6618(17)31332–4.

    Article  PubMed  Google Scholar 

  65. Panek WK, Khan OF, Yu D, Lesniak MS. Multiplexed nanomedicine for brain tumors: nanosized Hercules to tame our Lernaean Hydra inside? Nanomedicine (Lond). 2017; https://doi.org/10.2217/nnm-2017-0260.

  66. Játiva P, Ceña V. Use of nanoparticles for glioblastoma treatment: a new approach. Nanomedicine (Lond). 2017;12(20):2533–54.

    Article  Google Scholar 

  67. Zhang B, Jiang T, Tuo Y, et al. Captopril improves tumor nanomedicine delivery by increasing tumor blood perfusion and enlarging endothelial gaps in tumor blood vessels. Cancer Lett. 2017;410:12–9.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgement

The author would like to express his gratitute for the input and feedback from Dr. Robert F, Spetzler, from the Barrow Neurological Institute, Phoenix, AZ.

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Ferreira, M.A.T. (2019). The Frontiers of Neurosurgery. In: Joaquim, A., Ghizoni, E., Tedeschi, H., Ferreira, M. (eds) Fundamentals of Neurosurgery. Springer, Cham. https://doi.org/10.1007/978-3-030-17649-5_20

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-17649-5_20

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-17648-8

  • Online ISBN: 978-3-030-17649-5

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics