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Functional Imaging

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CyberKnife NeuroRadiosurgery

Abstract

The incorporation of medical imaging advancements into radiation therapy, has increased the attainable levels of treatment delivery accuracy and precision. This led to a substantial treatment paradigm shift; from three-dimensional conformal radiotherapy (3DCRT), planned on pre-treatment patient image series, to real-time image-guided treatment delivery (IGRT), facilitating the deposition of ablative doses to the target while sparing the surrounding organs at risk (OARs). Besides morphological imaging (e.g., CT, MRI), used either for delineation of target and OARs on pre-treatment images or for in-room beam delivery guidance, functional imaging, including functional MRI (fMRI), may provide a step further into maximizing the therapeutic benefit of stereotactic radiosurgery (SRS) treatments of the central nervous system (CNS). For intracranial critically located lesions, fMRI provides an effective, noninvasive means of identifying functionally eloquent cortical and subcortical areas that would cause significant patient morbidity if compromised and, therefore, should be considered as “functional OARs” (fOARs) during treatment planning and spared. This chapter discusses methodologies for the integration of fMRI into the CyberKnife treatment planning for intracranial SRS applications.

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References

  1. Mehta MP, Tsao MN, Whelan TJ, et al. The American Society for Therapeutic Radiology and Oncology (ASTRO) evidence-based review of the role of radiosurgery for brain metastases. Int J Radiat Oncol. 2005;63:37–46.

    Google Scholar 

  2. Pollock BE, Gorman DA, Brown PD. Radiosurgery for arteriovenous malformations of the basal ganglia, thalamus, and brainstem. J Neurosurg. 2004;100:210–4.

    PubMed  Google Scholar 

  3. Chopra R, Kondziolka D, Niranjan A, et al. Long-term follow-up of acoustic Schwannoma radiosurgery with marginal tumor doses of 12 to 13 Gy. Int J Radiat Oncol Biol Phys. 2007;68:845–51.

    PubMed  Google Scholar 

  4. Choi CYH, Chang SD, Gibbs IC, et al. Stereotactic radiosurgery of the postoperative resection cavity for brain metastases: prospective evaluation of target margin on tumor control. Int J Radiat Oncol Biol Phys. 2012;84:336–42.

    PubMed  Google Scholar 

  5. Chao ST, De Salles A, Hayashi M, et al. Stereotactic radiosurgery in the management of limited (1-4) brain metasteses: systematic review and International Stereotactic Radiosurgery Society practice guideline. Clin Neurosurg. 2018;83:345–53.

    Google Scholar 

  6. Lee CC, Trifiletti DM, Sahgal A, et al. Stereotactic radiosurgery for benign (World Health Organization Grade I) cavernous sinus meningiomas—International Stereotactic Radiosurgery Society (ISRS) practice guideline: a systematic review. Clin Neurosurg. 2018;83:1128–41.

    Google Scholar 

  7. Hadjipanayis CG, Levy EI, Niranjan A, et al. Stereotactic radiosurgery for motor cortex region arteriovenous malformations. Neurosurgery. 2001;48:70–7.

    CAS  PubMed  Google Scholar 

  8. Sasaki T, Kurita H, Saito I, et al. Arteriovenous malformations in the basal ganglia and thalamus: management and results in 101 cases. J Neurosurg. 1998;88:285–92.

    CAS  PubMed  Google Scholar 

  9. Andrade-Souza YM, Zadeh G, Scora D, et al. Radiosurgery for basal ganglia, internal capsule, and thalamus arteriovenous malformation: clinical outcome. Neurosurgery. 2005;56:56–64.

    PubMed  Google Scholar 

  10. Stancanello J, Cavedon C, Francescon P, et al. BOLD fMRI integration into radiosurgery treatment planning of cerebral vascular malformations. Med Phys. 2007;34:1176.

    PubMed  Google Scholar 

  11. Colombo F, Cavedon C, Casentini L, et al. Early results of CyberKnife radiosurgery for arteriovenous malformations. J Neurosurg. 2009;111:807–19.

    PubMed  Google Scholar 

  12. Pantelis E, Papadakis N, Verigos K, et al. Integration of functional MRI and white matter tractography in stereotactic radiosurgery clinical practice. Int J Radiat Oncol Biol Phys. 2010;78:257–67.

    PubMed  Google Scholar 

  13. Conti A, Pontoriero A, Ricciardi GK, et al. Integration of functional neuroimaging in CyberKnife radiosurgery: feasibility and dosimetric results. Neurosurg Focus. 2013;34:1–8.

    Google Scholar 

  14. Sun L, Qu B, Wang J, et al. Integration of functional MRI and white matter tractography in CyberKnife radiosurgery. Technol Cancer Res Treat. 2017;16:850–6.

    PubMed  PubMed Central  Google Scholar 

  15. De Martin E, Duran D, Ghielmetti F, et al. Integration of functional magnetic resonance imaging and magnetoencephalography functional maps into a CyberKnife planning system: feasibility study for motor activity localization and dose planning. World Neurosurg. 2017;108:756–62.

    PubMed  Google Scholar 

  16. Faro SH, Mohamed FB. Functional MRI: basic principles and clinical applications: Springer; 2006.

    Google Scholar 

  17. Kim PE, Singh M. Functional magnetic resonance imaging for brain mapping in neurosurgery. Neurosurg Focus. 2003;15:1–7.

    Google Scholar 

  18. Melhem ER, Mori S, Mukundan G, et al. Diffusion tensor MR imaging of the brain and white matter tractography. Am J Roentgenol. 2002;178:3–16.

    Google Scholar 

  19. Petrella JR, Shah LM, Harris KM, et al. Preoperative functional MR imaging localization of language and motor areas: effect on therapeutic decision making in patients with potentially resectable brain tumors. Radiology. 2006;240:793–802.

    PubMed  Google Scholar 

  20. Maruyama K, Kamada K, Shin M, et al. Optic radiation tractography integrated into simulated treatment planning for Gamma Knife surgery. J Neurosurg. 2007;107:721–6.

    PubMed  Google Scholar 

  21. Maruyama K, Kamada K, Ota T, et al. Tolerance of pyramidal tract to gamma knife radiosurgery based on diffusion-tensor tractography. Int J Radiat Oncol Biol Phys. 2008;70:1330–5.

    PubMed  Google Scholar 

  22. Chen JE, Glover GH. Functional magnetic resonance imaging methods. Neuropsychol Rev. 2015;25:289–313.

    PubMed  PubMed Central  Google Scholar 

  23. Ogawa S, Tank DW, Menon R, et al. Intrinsic signal changes accompanying sensory stimulation: functional brain mapping with magnetic resonance imaging. Proc Natl Acad Sci U S A. 1992;89:5951–5.

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Sandrone S, Bacigaluppi M, Galloni MR, et al. Weighing brain activity with the balance: Angelo Mosso’s original manuscripts come to light. Brain. 2014;137:621–33.

    PubMed  Google Scholar 

  25. Buxton RB. The physics of functional magnetic resonance imaging (fMRI). Reports Prog Phys. 2013;76:096601.

    Google Scholar 

  26. Hall EL, Robson SE, Morris PG, Brookes MJ. The relationship between MEG and fMRI. NeuroImage. 2014;102:80–91.

    PubMed  Google Scholar 

  27. Preibisch C, Wallenhorst T, Heidemann R, et al. Comparison of parallel acquisition techniques generalized autocalibrating partially parallel acquisitions (GRAPPA) and modified sensitivity encoding (mSENSE) in functional MRI (fMRI) at 3T. J Magn Reson Imaging. 2008;27:590–8.

    PubMed  Google Scholar 

  28. Glover GH. 3D z-shim method for reduction of susceptibility effects in BOLD fMRI. Magn Reson Med. 1999;42:290–9.

    CAS  PubMed  Google Scholar 

  29. Feinberg DA, Setsompop K. Ultra-fast MRI of the human brain with simultaneous multi-slice imaging. J Magn Reson. 2013;229:90–100.

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Amaro E, Barker GJ. Study design in fMRI: basic principles. Brain Cogn. 2006;60:220–32.

    PubMed  Google Scholar 

  31. Dale AM. Optimal experimental design for event-related fMRI. Hum Brain Mapp. 1999;8:109–14.

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Huettel SA. Event-related fMRI in cognition. NeuroImage. 2012;62:1152–6.

    PubMed  Google Scholar 

  33. Maus B, van Breukelen GJP, Goebel R, Berger MPF. Optimization of blocked designs in fMRI studies. Psychometrika. 2010;75:373–90.

    Google Scholar 

  34. Baldwin LN, Wachowicz K, Thomas SD, et al. Characterization, prediction, and correction of geometric distortion in 3T MR images. Med Phys. 2007;34:388–99.

    PubMed  Google Scholar 

  35. Baldwin LN, Wachowicz K, Fallone BG. A two-step scheme for distortion rectification of magnetic resonance images. Med Phys. 2009;36:3917–26.

    PubMed  Google Scholar 

  36. Cusack R, Papadakis N. New robust 3-D phase unwrapping algorithms: application to magnetic field mapping and Undistorting Echoplanar images. NeuroImage. 2002;16:754–64.

    CAS  PubMed  Google Scholar 

  37. Maclaren J, Herbst M, Speck O, Zaitsev M. Prospective motion correction in brain imaging: a review. Magn Reson Med. 2013;69:621–36.

    PubMed  Google Scholar 

  38. Sladky R, Friston KJ, Tröstl J, et al. Slice-timing effects and their correction in functional MRI. NeuroImage. 2011;58:588–94.

    PubMed  PubMed Central  Google Scholar 

  39. Tanabe J, Miller D, Tregellas J, et al. Comparison of Detrending methods for optimal fMRI preprocessing. NeuroImage. 2002;15:902–7.

    PubMed  Google Scholar 

  40. Monti MM. Statistical analysis of fMRI time-series: a critical review of the GLM approach. Front Hum Neurosci. 2011;5:28.

    PubMed  PubMed Central  Google Scholar 

  41. Poline J-B, Brett M. The general linear model and fMRI: does love last forever? NeuroImage. 2012;62:871–80.

    PubMed  Google Scholar 

  42. Mckeown MJ, Makeig S, Brown GG, et al. Analysis of fMRI data by blind separation into independent spatial components. Hum Brain Mapp. 1998;6:160–88.

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Haxby JV, Gobbini MI, Furey ML, et al. Distributed and overlapping representations of faces and objects in ventral temporal cortex. Science. 2001;293:2425–30.

    CAS  PubMed  Google Scholar 

  44. Mahmoudi A, Takerkart S, Regragui F, et al. Multivoxel pattern analysis for fMRI data: a review. Comput Math Methods Med. 2012;2012:1–14.

    Google Scholar 

  45. Colquhoun D. An investigation of the false discovery rate and the misinterpretation of p-values. R Soc Open Sci. 2014;1:140216.

    PubMed  PubMed Central  Google Scholar 

  46. Engel SA, Burton PC. Confidence intervals for fMRI activation maps. PLoS One. 2013;8:e82419.

    PubMed  PubMed Central  Google Scholar 

  47. Nichols T, Hayasaka S. Controlling the familywise error rate in functional neuroimaging: a comparative review. Stat Methods Med Res. 2003;12:419–46.

    PubMed  Google Scholar 

  48. Klein A, Andersson J, Ardekani BA, et al. Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration. NeuroImage. 2009;46:786–802.

    PubMed  PubMed Central  Google Scholar 

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Author information

Authors and Affiliations

  1. CyberKnife and TomoTherapy Department, IATROPOLIS Private Special Clinic, Athens, Greece

    Argyris Moutsatsos

  2. Medical Physics Laboratory, Medical School, National and Kapodistrian University of Athens, Athens, Greece

    Evangelos Pantelis

  3. CyberKnife and TomoTherapy Radiotherapy Department, IATROPOLIS Private Special Clinic, Athens, Greece

    Evangelos Pantelis

Authors
  1. Argyris Moutsatsos
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  2. Evangelos Pantelis
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Corresponding author

Correspondence to Evangelos Pantelis .

Editor information

Editors and Affiliations

  1. Associate Professor of Neurosurgery, Alma Mater Studiorum University of Bologna, Bologna, Italy

    Alfredo Conti

  2. Scientific Director, AB Medica, Milano, Italy

    Pantaleo Romanelli

  3. Assistant Professor, Medical Physics Laboratory, Medical School, National and Kapodistrian University of Athens, Athens, Greece

    Evangelos Pantelis

  4. Associate Professor, Department of Radiation Oncology, Stanford University Cancer Center, Stanford, CA, USA

    Scott G. Soltys

  5. Associate Professor, Department of Neurosurgery and Radiosurgery Center, Asan Medical Center, University of Ulsan, College of Medicine, Seoul, Korea (Republic of)

    Young Hyun Cho

  6. Department of Neurosurgery, The Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Michael Lim

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Moutsatsos, A., Pantelis, E. (2020). Functional Imaging. In: Conti, A., Romanelli, P., Pantelis, E., Soltys, S., Cho, Y., Lim, M. (eds) CyberKnife NeuroRadiosurgery . Springer, Cham. https://doi.org/10.1007/978-3-030-50668-1_9

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