Skip to main content

Image-Guided Neurosurgical Planning

  • Chapter
  • First Online:
Intraoperative Imaging and Image-Guided Therapy

Abstract

Preoperative planning for neurosurgery may be enhanced by the availability of imaging methods capable of capturing information relating to both structure and function of pathological and adjacent tissue. High-resolution structural images may be augmented with functional MRI (fMRI) to delineate eloquent brain regions; diffusion tensor imaging (DTI) to capture white matter macrostructure organization and potential disruption; and positron emission tomography (PET) imaging to assess metabolic activity and response. Other techniques including magnetoencephalography (MEG) and transcranial magnetic stimulation (TMS) are discussed in relation to presurgical functional assessment. Composition of these pieces of information into a clinically useful plan via image processing and registration is important both for the preoperative plan and for intraoperative guidance. Identification and highlighting of clinically relevant features from separate modalities facilitates integrated review of complementary information. As surgeon comfort with this approach increases, it is likely to help achieve safer and more complete surgical resections.

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 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
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

References

  1. Ogawa S, Lee TM, Kay AR, Tank DW. Brain magnetic resonance imaging with contrast dependent on blood oxygenation. Proc Natl Acad Sci U S A. 1990;87(24):9868–72.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  2. Worsley KJ, Friston KJ. Analysis of fMRI time-series revisited – again. Neuroimage. 1995;2(3):173–81.

    Article  CAS  PubMed  Google Scholar 

  3. Fernández G, Specht K, Weis S, et al. Intrasubject reproducibility of presurgical language lateralization and mapping using fMRI. Neurology. 2003;60(6):969–75.

    Article  PubMed  Google Scholar 

  4. Ruff IM, Petrovich Brennan NM, Peck KK, et al. Assessment of the language laterality index in patients with brain tumor using functional MR imaging: effects of thresholding, task selection, and prior surgery. AJNR Am J Neuroradiol. 2008;29(3):528–35.

    Article  CAS  PubMed  Google Scholar 

  5. Suarez RO, Whalen S, O’Shea JP, Golby AJ. A surgical planning method for functional MRI assessment of language dominance: influences from threshold, region-of-interest, and stimulus mode. Brain Imaging Behav. 2008;2:59–73.

    Article  Google Scholar 

  6. Cabeza R, Nyberg L. Imaging cognition II: an empirical review of 275 PET and fMRI studies. J Cogn Neurosci. 2000;12(1):1–47.

    Article  CAS  PubMed  Google Scholar 

  7. Binder JR, Desai RH, Graves WW, Conant LL. Where is the semantic system? A critical review and meta-analysis of 120 functional neuroimaging studies. Cereb Cortex. 2009;19(12):2767–96.

    Article  PubMed  Google Scholar 

  8. Bookheimer S. Pre-surgical language mapping with functional magnetic resonance imaging. Neuropsychol Rev. 2007;17(2): 145–55.

    Article  PubMed  Google Scholar 

  9. American College of Radiology. ACR–ASNR Practice Guidelines for the Performance of Functional Magnetic Resonance Imaging of the Brain (fMRI). 2007. ACR Practice Guidelines: http://www.acr.org/Quality-Safety/Standards-Guidelines/Practice-Guidelines-by-Modality/MRI. fMRI guidelines: http://www.acr.org/~/media/ACR/Documents/PGTS/guidelines/FMRI.pdf.

  10. Ulmer J, Holodny AI. Functional neuroradiology: a call to action. AJNR Am J Neuroradiol. 2005;26(1):2–3.

    PubMed  Google Scholar 

  11. Sundgren PC, Dong Q, Gómez-Hassan D, et al. Diffusion tensor imaging of the brain: review of clinical applications. Neuroradiology. 2004;46(5):339–50.

    Article  CAS  PubMed  Google Scholar 

  12. Lutsep HL, Albers GW, DeCrespigny A, et al. Clinical utility of diffusion-weighted magnetic resonance imaging in the assessment of ischemic stroke. Ann Neurol. 1997;41(5):574–80.

    Article  CAS  PubMed  Google Scholar 

  13. Kawamata T, Katayama Y, Aoyama N, Mori T. Heterogeneous mechanisms of early edema formation in cerebral contusion: diffusion MRI and ADC mapping study. Acta Neurochir Suppl. 2000;76:9–12.

    CAS  PubMed  Google Scholar 

  14. Mori S, Barker PB. Diffusion magnetic resonance imaging: its principle and applications. Anat Rec. 1999;257(3):102–9.

    Article  CAS  PubMed  Google Scholar 

  15. Mori S, van Zijl PCM. Fiber tracking: principles and strategies – a technical review. NMR Biomed. 2002;15(7–8):468–80.

    Article  PubMed  Google Scholar 

  16. Dauguet J, Peled S, Berezovskii V, et al. Comparison of fiber tracts derived from in-vivo DTI tractography with 3D histological neural tract tracer reconstruction on a macaque brain. Neuroimage. 2007;37(2):530–8.

    Article  PubMed  Google Scholar 

  17. Takahashi E, Dai G, Rosen GD, et al. Developing neocortex organization and connectivity in cats revealed by direct correlation of diffusion tractography and histology. Cereb Cortex. 2011;21(1): 200–11.

    Article  PubMed  Google Scholar 

  18. Hämäläinen M, Hari R, Ilmoniemi RJ, Knuutila J, Lounasmaa OV. Magnetoencephalography-theory, instrumentation, and applications to noninvasive studies of the working human brain. Rev Mod Phys. 1993;65:413–97.

    Article  Google Scholar 

  19. Dale AM, Liu AK, Fischl BR, et al. Dynamic statistical parametric mapping: combining fMRI and MEG for high-resolution imaging of cortical activity. Neuron. 2000;26(1):55–67.

    Article  CAS  PubMed  Google Scholar 

  20. Ganslandt O, Fahlbusch R, Nimsky C, et al. Functional neuronavigation with magnetoencephalography: outcome in 50 patients with lesions around the motor cortex. J Neurosurg. 1999;91(1):73–9.

    Article  CAS  PubMed  Google Scholar 

  21. Grummich P, Nimsky C, Pauli E, Buchfelder M, Ganslandt O. Combining fMRI and MEG increases the reliability of presurgical language localization: a clinical study on the difference between and congruence of both modalities. Neuroimage. 2006;32(4): 1793–803.

    Article  PubMed  Google Scholar 

  22. Mäkelä JP, Forss N, Jääskeläinen J, et al. Magnetoencephalography in neurosurgery. Neurosurgery. 2007;61(1 Suppl):147–64; discussion 164–5.

    PubMed  Google Scholar 

  23. RamachandranNair R, Otsubo H, Shroff MM, et al. MEG predicts outcome following surgery for intractable epilepsy in children with normal or nonfocal MRI findings. Epilepsia. 2007;48(1):149–57.

    Article  PubMed  Google Scholar 

  24. Wheless JW, Willmore LJ, Breier JI, et al. A comparison of magnetoencephalography, MRI, and V‐EEG in patients evaluated for epilepsy surgery. Epilepsia. 1999;40(7):931–41.

    Article  CAS  PubMed  Google Scholar 

  25. Knowlton RC, Elgavish RA, Bartolucci A, et al. Functional imaging: II. Prediction of epilepsy surgery outcome. Ann Neurol. 2008;64(1):35–41.

    Article  PubMed  Google Scholar 

  26. Papanicolaou AC, Simos PG, Castillo EM, et al. Magnetocephalography: a noninvasive alternative to the Wada procedure. J Neurosurg. 2004;100(5):867–76.

    Article  PubMed  Google Scholar 

  27. Phelps ME. Positron emission tomography provides molecular imaging of biological processes. Proc Natl Acad Sci. 2000;97(16):9226–33.

    Article  CAS  PubMed  Google Scholar 

  28. Alavi JB, Alavi A, Chawluk J, et al. Positron emission tomography in patients with glioma a predictor of prognosis. Cancer. 1988;62(6):1074–8.

    Article  CAS  PubMed  Google Scholar 

  29. Pirotte B, Goldman S, Dewitte O, et al. Integrated positron emission tomography and magnetic resonance imaging-guided resection of brain tumors: a report of 103 consecutive procedures. J Neurosurg. 2006;104(2):238–53.

    Article  PubMed  Google Scholar 

  30. Pirotte B, Goldman S, Massager N, et al. Comparison of 18F-FDG and 11C-methionine for PET-guided stereotactic brain biopsy of gliomas. J Nucl Med. 2004;45(8):1293–8.

    CAS  PubMed  Google Scholar 

  31. Chao ST, Suh JH, Raja S, Lee S, Barnett G. The sensitivity and specificity of FDG PET in distinguishing recurrent brain tumor from radionecrosis in patients treated with stereotactic radiosurgery. Int J Cancer. 2001;96(3):191–7.

    Article  CAS  PubMed  Google Scholar 

  32. Young H, Baum R, Cremerius U, et al. Measurement of clinical and subclinical tumour response using [18F]-fluorodeoxyglucose and positron emission tomography: review and 1999 EORTC recommendations. Eur J Cancer. 1999;35(13):1773–82.

    Article  CAS  PubMed  Google Scholar 

  33. Ryvlin P, Bouvard S, Le Bars D, et al. Clinical utility of flumazenil-PET versus [18F]fluorodeoxyglucose-PET and MRI in refractory partial epilepsy. A prospective study in 100 patients. Brain. 1998;121(11):2067–81.

    Article  PubMed  Google Scholar 

  34. Ho SS, Berkovic SF, Berlangieri SU, et al. Comparison of ictal SPECT and interictal PET in the presurgical evaluation of temporal lobe epilepsy. Ann Neurol. 1995;37(6):738–45.

    Article  CAS  PubMed  Google Scholar 

  35. Hallett M. Transcranial magnetic stimulation and the human brain. Nature. 2000;406(6792):147–50.

    Article  CAS  PubMed  Google Scholar 

  36. Boroojerdi B, Foltys H, Krings T, et al. Localization of the motor hand area using transcranial magnetic stimulation and functional magnetic resonance imaging. Clin Neurophysiol. 1999;110(4):699–704.

    Article  CAS  PubMed  Google Scholar 

  37. Maldjian J, Baer A, Kraft R, Laurienti P, Burdette J. Fully automated processing of fMRI data in SPM: from MRI scanner to PACS. Neuroinformatics. 2009;7(1):57–72.

    Article  PubMed  Google Scholar 

  38. Elhawary H, Liu H, Patel P, et al. Intraoperative real-time querying of white matter tracts during frameless stereotactic neuronavigation. Neurosurgery. 2011;68(2):506–16; discussion 516.

    Article  PubMed Central  PubMed  Google Scholar 

  39. Schulze F, Bühler K, Neubauer A, et al. Intra-operative virtual endoscopy for image guided endonasal transsphenoidal pituitary surgery. Int J Comput Assist Radiol Surg. 2009;5:143–54.

    Article  PubMed  Google Scholar 

  40. National Electrical Manufacturers Association, Rosslyn, VA, USA. NEMA PS3 / ISO 12052, Digital Imaging and Communications in Medicine (DICOM) Standard. Available at: http://medical.nema.org.

  41. Archip N, Clatz O, Whalen S, et al. Non-rigid alignment of pre-operative MRI, fMRI, and DT-MRI with intra-operative MRI for enhanced visualization and navigation in image-guided neurosurgery. Neuroimage. 2007;35(2):609–24.

    Article  PubMed Central  PubMed  Google Scholar 

  42. Jenkinson M, Bannister P, Brady M, Smith S. Improved optimization for the robust and accurate linear registration and motion correction of brain images. Neuroimage. 2002;17(2):825–41.

    Article  PubMed  Google Scholar 

  43. Pallud J, Varlet P, Devaux B, et al. Diffuse low-grade oligodendrogliomas extend beyond MRI-defined abnormalities. Neurology. 2010;74(21):1724–31.

    Article  CAS  PubMed  Google Scholar 

  44. Pohl KM, Konukoglu E, Novellas S, et al. A new metric for detecting change in slowly evolving brain tumors: validation in meningioma patients. Neurosurgery. 2011;68(1 Suppl Operative):225–33.

    PubMed Central  PubMed  Google Scholar 

  45. Clark CA, Barrick TR, Murphy MM, Bell BA. White matter fiber tracking in patients with space-occupying lesions of the brain: a new technique for neurosurgical planning? Neuroimage. 2003;20(3):1601–8.

    Article  PubMed  Google Scholar 

  46. Schonberg T, Pianka P, Hendler T, Pasternak O, Assaf Y. Characterization of displaced white matter by brain tumors using combined DTI and fMRI. Neuroimage. 2006;30(4):1100–11.

    Article  PubMed  Google Scholar 

  47. Kamada K, Todo T, Masutani Y, et al. Visualization of the frontotemporal language fibers by tractography combined with functional magnetic resonance imaging and magnetoencephalography. 2007. Available at: http://thejns.org.ezp-prod1.hul.harvard.edu/doi/abs/10.3171/jns.2007.106.1.90. Accessed 7 Oct 2011.

  48. Golby AJ, Kindlmann G, Norton I, et al. Interactive diffusion tensor tractography visualization for neurosurgical planning. Neurosurgery. 2011;68(2):496–505.

    Article  PubMed Central  PubMed  Google Scholar 

  49. O’Donnell LJ, Kubicki M, Shenton ME, et al. A method for clustering white matter fiber tracts. AJNR Am J Neuroradiol. 2006;27(5):1032–6.

    PubMed Central  PubMed  Google Scholar 

  50. O’Donnell LJ, Westin C-F. Automatic tractography segmentation using a high-dimensional white matter atlas. IEEE Trans Med Imaging. 2007;26(11):1562–75.

    Article  PubMed  Google Scholar 

  51. Zhang Y, Zhang J, Oishi K, et al. Atlas-guided tract reconstruction for automated and comprehensive examination of the white matter anatomy. Neuroimage. 2010;52(4):1289–301.

    Article  PubMed Central  PubMed  Google Scholar 

  52. Baciu M, Le Bas JF, Segebarth C, Benabid AL. Presurgical fMRI evaluation of cerebral reorganization and motor deficit in patients with tumors and vascular malformations. Eur J Radiol. 2003;46(2):139–46.

    Article  CAS  PubMed  Google Scholar 

  53. Rossini PM, Caltagirone C, Castriota-Scanderbeg A, et al. Hand motor cortical area reorganization in stroke: a study with fMRI. MEG and TCS maps. Neuroreport. 1998;9(9):2141–6.

    Article  CAS  PubMed  Google Scholar 

  54. Liégeois F, Connelly A, Cross JH, et al. Language reorganization in children with early‐onset lesions of the left hemisphere: an fMRI study. Brain. 2004;127(6):1229–36.

    Article  PubMed  Google Scholar 

  55. Bonelli SB, Powell RHW, Yogarajah M, et al. Imaging memory in temporal lobe epilepsy: predicting the effects of temporal lobe resection. Brain. 2010;133(4):1186–99.

    Article  PubMed  Google Scholar 

  56. Wu W, Rigolo L, O’Donnell LJ, et al. Visual pathway study using in vivo DTI tractography to complement classical anatomy. Neurosurgery. 2012;70(1 Suppl):145–56; discussion 156. doi: 10.1227/NEU.0b013e31822efcae. http://www.ncbi.nlm.nih.gov/pubmed/21808220.

    Google Scholar 

  57. Hirsch J, Ruge MI, Kim KH, et al. An integrated functional magnetic resonance imaging procedure for preoperative mapping of cortical areas associated with tactile, motor, language, and visual functions. Neurosurgery. 2000;47(3):711–21; discussion 721–2.

    CAS  PubMed  Google Scholar 

  58. Krishnan R, Raabe A, Hattingen E, et al. Functional magnetic resonance imaging-integrated neuronavigation: correlation between lesion-to-motor cortex distance and outcome. Neurosurgery. 2004;55(4):904–14; discussion 914–5.

    Article  PubMed  Google Scholar 

  59. Giussani C, Roux F-E, Ojemann J, et al. Is preoperative functional magnetic resonance imaging reliable for language areas mapping in brain tumor surgery? Review of language functional magnetic resonance imaging and direct cortical stimulation correlation studies. Neurosurgery. 2010;66(1):113–20.

    Article  PubMed  Google Scholar 

  60. Woermann FG, Jokeit H, Luerding R, et al. Language lateralization by Wada test and fMRI in 100 patients with epilepsy. Neurology. 2003;61(5):699–701.

    Article  CAS  PubMed  Google Scholar 

  61. Benke T, Köylü B, Visani P, et al. Language lateralization in temporal lobe epilepsy: a comparison between fMRI and the Wada test. Epilepsia. 2006;47(8):1308–19.

    Article  PubMed  Google Scholar 

  62. Wu J-S, Zhou L-F, Tang W-J, et al. Clinical evaluation and follow-up outcome of diffusion tensor imaging-based functional neuronavigation. Neurosurgery. 2007;61:935–49.

    Article  PubMed  Google Scholar 

  63. Bello L, Gambini A, Castellano A, et al. Motor and language DTI Fiber Tracking combined with intraoperative subcortical mapping for surgical removal of gliomas. Neuroimage. 2008;39(1):369–82.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Isaiah H. Norton BS .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer Science+Business Media New York

About this chapter

Cite this chapter

Norton, I.H., Orringer, D.A., Golby, A.J. (2014). Image-Guided Neurosurgical Planning. In: Jolesz, F. (eds) Intraoperative Imaging and Image-Guided Therapy. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7657-3_37

Download citation

  • DOI: https://doi.org/10.1007/978-1-4614-7657-3_37

  • Published:

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-7656-6

  • Online ISBN: 978-1-4614-7657-3

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics