Skip to main content
SpringerLink
Log in

Preoperative Planning of DBS Surgery with MRI

  • Chapter
  • First Online:
Magnetic Resonance Imaging in Deep Brain Stimulation

  • 342 Accesses

Abstract

The preoperative planning of deep brain stimulation surgery is essential in maximizing therapeutic outcomes. Previously, planning was based on indirect targeting methods; however, improvements in neuroimaging have permitted the direct visualization of target structures. We summarize and evaluate MRI sequences that have been used to improve the visualization of common DBS targets, highlight existing limitations, and discuss the potential future of DBS target planning. Studies describing the MRI visualization of common DBS targets were identified following a comprehensive MEDLINE database search. The development of novel MRI sequences—such as quantitative susceptibility mapping, which exploits the amount of tissue iron in target structures—has allowed direct targeting to become more clinically feasible through improved visualization of subcortical structures. Common limitations within the literature were the technical challenges associated with implementing certain sequences, the relative dearth of imaging in clinical populations, and the lack of prospective studies designed to objectively determine which visualization techniques are optimal for any given target. Future targeting may leverage higher field strengths (e.g., 7 Tesla) and may move beyond the targeting of discrete anatomical structures and toward the engagement of larger networks, as visualized by tractography and functional MRI.

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

Access this chapter

Log in via an institution
eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
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. Lemaire J-J, Coste J, Ouchchane L, et al. Brain mapping in stereotactic surgery: a brief overview from the probabilistic targeting to the patient-based anatomic mapping. NeuroImage. 2007;37(Suppl 1):S109–15.

    Article  PubMed  Google Scholar 

  2. Patel NK, Khan S, Gill SS. Comparison of atlas- and magnetic-resonance-imaging-based stereotactic targeting of the subthalamic nucleus in the surgical treatment of Parkinson’s disease. Stereotact Funct Neurosurg. 2008;86:153–61.

    Article  PubMed  Google Scholar 

  3. Bejjani BP, Dormont D, Pidoux B, et al. Bilateral subthalamic stimulation for Parkinson’s disease by using three-dimensional stereotactic magnetic resonance imaging and electrophysiological guidance. J Neurosurg. 2000;92:615–25.

    Article  CAS  PubMed  Google Scholar 

  4. Zrinzo L, Hariz M, Hyam JA, Foltynie T, Limousin P. Letter to the editor: a paradigm shift toward MRI-guided and MRI-verified DBS surgery. J Neurosurg. 2016;124:1135–7.

    Article  PubMed  Google Scholar 

  5. Boutet A, Gramer R, Steele CJ, Elias GJB, Germann J, Maciel R, Kucharczyk W, Zrinzo L, Lozano AM, Fasano A. Neuroimaging technological advancements for targeting in functional neurosurgery. Curr Neurol Neurosci Rep. 2019;19:42.

    Article  PubMed  Google Scholar 

  6. Zerroug A, Gabrillargues J, Coll G, Vassal F, Jean B, Chabert E, et al. Personalized mapping of the deep brain with a white matter attenuated inversion recovery (WAIR) sequence at 1.5-tesla: experience based on a series of 156 patients. Neurochirurgie. 2016;62:183–9.

    Article  CAS  PubMed  Google Scholar 

  7. Benabid AL, Koudsie A, Benazzouz A, Le Bas J-F, Pollak P. Imaging of subthalamic nucleus and ventralis intermedius of the thalamus. Mov Disord. 2002;17(Suppl 3):S123–9.

    Article  PubMed  Google Scholar 

  8. Lozano AM, Lipsman N. Probing and regulating dysfunctional circuits using deep brain stimulation. Neuron. 2013;77:406–24.

    Article  CAS  PubMed  Google Scholar 

  9. Weintraub DB, Zaghloul KA. The role of the subthalamic nucleus in cognition. Rev Neurosci. 2013;24:125–38.

    Article  PubMed Central  PubMed  Google Scholar 

  10. Lambert C, Zrinzo L, Nagy Z, Lutti A, Hariz M, Foltynie T, Draganski B, Ashburner J, Frackowiak R. Confirmation of functional zones within the human subthalamic nucleus: patterns of connectivity and sub-parcellation using diffusion weighted imaging. NeuroImage. 2012;60:83–94.

    Article  PubMed  Google Scholar 

  11. Brunenberg EJL, Platel B, Hofman PAM, ter Haar Romeny BM, Visser-Vandewalle V. Magnetic resonance imaging techniques for visualization of the subthalamic nucleus. J Neurosurg. 2011;115:971–84.

    Article  PubMed  Google Scholar 

  12. Kerl HU, Gerigk L, Pechlivanis I, Al-Zghloul M, Groden C, Nölte I. The subthalamic nucleus at 3.0 tesla: choice of optimal sequence and orientation for deep brain stimulation using a standard installation protocol: clinical article. J Neurosurg. 2012;117:1155–65.

    Article  PubMed  Google Scholar 

  13. Dormont D, Ricciardi KG, Tandé D, Parain K, Menuel C, Galanaud D, Navarro S, Cornu P, Agid Y, Yelnik J. Is the subthalamic nucleus hypointense on T2-weighted images? A correlation study using MR imaging and stereotactic atlas data. AJNR Am J Neuroradiol. 2004;25:1516–23.

    PubMed Central  PubMed  Google Scholar 

  14. Mai JK, Majtanik M, Paxinos G. Atlas of the human brain. Academic Press; 2015.

    Google Scholar 

  15. Danish SF, Jaggi JL, Moyer JT, Finkel L, Baltuch GH. Conventional MRI is inadequate to delineate the relationship between the red nucleus and subthalamic nucleus in Parkinson’s disease. Stereotact Funct Neurosurg. 2006;84:12–8.

    Article  PubMed  Google Scholar 

  16. Rasouli J, Ramdhani R, Panov FE, Dimov A, Zhang Y, Cho C, Wang Y, Kopell BH. Utilization of quantitative susceptibility mapping for direct targeting of the subthalamic nucleus during deep brain stimulation surgery. Oper Neurosurg (Hagerstown). 2018;14:412–9.

    Article  PubMed  Google Scholar 

  17. Zonenshayn M, Rezai AR, Mogilner AY, Beric A, Sterio D, Kelly PJ. Comparison of anatomic and neurophysiological methods for subthalamic nucleus targeting. Neurosurgery. 2000;47(282–92):discussion 292–4.

    PubMed  Google Scholar 

  18. Senova S, Hosomi K, Gurruchaga J-M, et al. Three-dimensional SPACE fluid-attenuated inversion recovery at 3 T to improve subthalamic nucleus lead placement for deep brain stimulation in Parkinson’s disease: from preclinical to clinical studies. J Neurosurg. 2016;125:472–80.

    Article  CAS  PubMed  Google Scholar 

  19. Chandran AS, Bynevelt M, Lind CRP. Magnetic resonance imaging of the subthalamic nucleus for deep brain stimulation. J Neurosurg. 2016;124:96–105.

    Article  PubMed  Google Scholar 

  20. Kitajima M, Korogi Y, Kakeda S, Moriya J, Ohnari N, Sato T, Hayashida Y, Hirai T, Okuda T, Yamashita Y. Human subthalamic nucleus: evaluation with high-resolution MR imaging at 3.0 T. Neuroradiology. 2008;50:675–81.

    Article  PubMed  Google Scholar 

  21. Sudhyadhom A, Haq IU, Foote KD, Okun MS, Bova FJ. A high resolution and high contrast MRI for differentiation of subcortical structures for DBS targeting: the fast gray matter acquisition T1 inversion recovery (FGATIR). NeuroImage. 2009;47(Suppl 2):T44–52.

    Article  PubMed  Google Scholar 

  22. Xiao Y, Fonov V, Bériault S, Al Subaie F, Chakravarty MM, Sadikot AF, Pike GB, Collins DL. Multi-contrast unbiased MRI atlas of a Parkinson’s disease population. Int J Comput Assist Radiol Surg. 2015;10:329–41.

    Article  PubMed  Google Scholar 

  23. Vertinsky AT, Coenen VA, Lang DJ, Kolind S, Honey CR, Li D, Rauscher A. Localization of the subthalamic nucleus: optimization with susceptibility-weighted phase MR imaging. AJNR Am J Neuroradiol. 2009;30:1717–24.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  24. Thaker AA, Reddy KM, Thompson JA, Gerecht PD, Brown MS, Abosch A, Ojemann SG, Kern DS. Coronal gradient Echo MRI to visualize the zona Incerta for deep brain stimulation targeting in Parkinson’s disease. SFN. 2021;99:443–50.

    Google Scholar 

  25. Watanabe Y, Lee CK, Gerbi BJ. Geometrical accuracy of a 3-tesla magnetic resonance imaging unit in gamma knife surgery. J Neurosurg. 2006;105:190–3.

    Article  PubMed  Google Scholar 

  26. Li J, Chang S, Liu T, et al. Reducing the object orientation dependence of susceptibility effects in gradient echo MRI through quantitative susceptibility mapping. Magn Reson Med. 2012;68:1563–9.

    Article  PubMed Central  PubMed  Google Scholar 

  27. Yu K, Ren Z, Li J, Guo S, Hu Y, Li Y. Direct visualization of deep brain stimulation targets in patients with Parkinson’s disease via 3-T quantitative susceptibility mapping. Acta Neurochir. 2021;163:1335–45.

    Article  PubMed  Google Scholar 

  28. Rashid T, Hwang R, DiMarzio M, Hancu I, Pilitsis JG. Evaluating the role of 1.5 T quantitative susceptibility mapping for subthalamic nucleus targeting in deep brain stimulation surgery. J Neuroradiol. 2021;48:37–42.

    Article  PubMed  Google Scholar 

  29. Schweser F, Deistung A, Reichenbach JR. Foundations of MRI phase imaging and processing for quantitative susceptibility mapping (QSM). Z Med Phys. 2016;26:6–34.

    Article  PubMed  Google Scholar 

  30. Heo YJ, Kim SJ, Kim HS, Choi CG, Jung SC, Lee JK, Lee CS, Chung SJ, Cho SH, Lee GR. Three-dimensional fluid-attenuated inversion recovery sequence for visualisation of subthalamic nucleus for deep brain stimulation in Parkinson’s disease. Neuroradiology. 2015;57:929–35.

    Article  PubMed  Google Scholar 

  31. Ben-Haim S, Gologorsky Y, Monahan A, Weisz D, Alterman RL. Fiducial registration with spoiled gradient-echo magnetic resonance imaging enhances the accuracy of subthalamic nucleus targeting. Neurosurgery. 2011;69:870–5. discussion 875.

    Article  PubMed  Google Scholar 

  32. Liu T, Eskreis-Winkler S, Schweitzer AD, Chen W, Kaplitt MG, Tsiouris AJ, Wang Y. Improved subthalamic nucleus depiction with quantitative susceptibility mapping. Radiology. 2013;269:216–23.

    Article  PubMed Central  PubMed  Google Scholar 

  33. Lefranc M, Derrey S, Merle P, et al. High-resolution 3-dimensional T2*-weighted angiography (HR 3-D SWAN): an optimized 3-T magnetic resonance imaging sequence for targeting the subthalamic nucleus. Neurosurgery. 2014;74:615–26. discussion 627.

    Article  PubMed  Google Scholar 

  34. Nagahama H, Suzuki K, Shonai T, Aratani K, Sakurai Y, Nakamura M, Sakata M. Comparison of magnetic resonance imaging sequences for depicting the subthalamic nucleus for deep brain stimulation. Radiol Phys Technol. 2015;8:30–5.

    Article  PubMed  Google Scholar 

  35. O’Gorman RL, Shmueli K, Ashkan K, Samuel M, Lythgoe DJ, Shahidiani A, Wastling SJ, Footman M, Selway RP, Jarosz J. Optimal MRI methods for direct stereotactic targeting of the subthalamic nucleus and globus pallidus. Eur Radiol. 2011;21:130–6.

    Article  PubMed  Google Scholar 

  36. Ewert S, Plettig P, Li N, Chakravarty MM, Collins DL, Herrington TM, Kühn AA, Horn A. Toward defining deep brain stimulation targets in MNI space: a subcortical atlas based on multimodal MRI, histology and structural connectivity. NeuroImage. 2018;170:271–82.

    Article  PubMed  Google Scholar 

  37. Lozano AM, Lipsman N, Bergman H, et al. Deep brain stimulation: current challenges and future directions. Nat Rev Neurol. 2019;15:148–60.

    Article  PubMed Central  PubMed  Google Scholar 

  38. Nölte IS, Gerigk L, Al-Zghloul M, Groden C, Kerl HU. Visualization of the internal globus pallidus: sequence and orientation for deep brain stimulation using a standard installation protocol at 3.0 tesla. Acta Neurochir. 2012;154:481–94.

    Article  PubMed  Google Scholar 

  39. Hirabayashi H, Tengvar M, Hariz MI. Stereotactic imaging of the pallidal target. Mov Disord. 2002;17(Suppl 3):S130–4.

    Article  PubMed  Google Scholar 

  40. Starr PA, Vitek JL, DeLong M, Bakay RA. Magnetic resonance imaging-based stereotactic localization of the globus pallidus and subthalamic nucleus. Neurosurgery. 1999;44:303–13. discussion 313–4.

    Article  CAS  PubMed  Google Scholar 

  41. Nowacki A, Fiechter M, Fichtner J, Debove I, Lachenmayer L, Schüpbach M, Oertel MF, Wiest R, Pollo C. Using MDEFT MRI sequences to target the GPi in DBS surgery. PLoS One. 2015;10:e0137868.

    Article  PubMed Central  PubMed  Google Scholar 

  42. Beaumont J, Saint-Jalmes H, Acosta O, Kober T, Tanner M, Ferré JC, Salvado O, Fripp J, Gambarota G. Multi T1-weighted contrast MRI with fluid and white matter suppression at 1.5 T. Magn Reson Imaging. 2019;63:217–25.

    Article  CAS  PubMed  Google Scholar 

  43. Ide S, Kakeda S, Ueda I, et al. Internal structures of the globus pallidus in patients with Parkinson’s disease: evaluation with quantitative susceptibility mapping (QSM). Eur Radiol. 2015;25:710–8.

    Article  PubMed  Google Scholar 

  44. Ide S, Kakeda S, Yoneda T, et al. Internal structures of the Globus pallidus in patients with Parkinson’s disease: evaluation with phase difference-enhanced imaging. Magn Reson Med Sci. 2017;16:304–10.

    Article  PubMed  Google Scholar 

  45. Nieuwenhuys R, Voogd J, van Huijzen C. The human central nervous system: a synopsis and atlas. Springer Science & Business Media; 2013.

    Google Scholar 

  46. Hamani C, Schwalb JM, Rezai AR, Dostrovsky JO, Davis KD, Lozano AM. Deep brain stimulation for chronic neuropathic pain: long-term outcome and the incidence of insertional effect. Pain. 2006;125:188–96.

    Article  PubMed  Google Scholar 

  47. Akram H, Dayal V, Mahlknecht P, et al. Connectivity derived thalamic segmentation in deep brain stimulation for tremor. Neuroimage Clin. 2018;18:130–42.

    Article  PubMed Central  PubMed  Google Scholar 

  48. Grewal SS, Middlebrooks EH, Kaufmann TJ, Stead M, Lundstrom BN, Worrell GA, Lin C, Baydin S, Van Gompel JJ. Fast gray matter acquisition T1 inversion recovery MRI to delineate the mammillothalamic tract for preoperative direct targeting of the anterior nucleus of the thalamus for deep brain stimulation in epilepsy. Neurosurg Focus. 2018;45:E6.

    Article  PubMed  Google Scholar 

  49. Buentjen L, Kopitzki K, Schmitt FC, Voges J, Tempelmann C, Kaufmann J, Kanowski M. Direct targeting of the thalamic anteroventral nucleus for deep brain stimulation by T1-weighted magnetic resonance imaging at 3 T. Stereotact Funct Neurosurg. 2014;92:25–30.

    Article  PubMed  Google Scholar 

  50. Bender B, Wagner S, Klose U. Optimized depiction of thalamic substructures with a combination of T1-MPRAGE and phase: MPRAGE. Clin Neuroradiol. 2017;27:511–8.

    Article  PubMed  Google Scholar 

  51. Middlebrooks EH, Okromelidze L, Lin C, Jain A, Westerhold E, Ritaccio A, Quiñones-Hinojosa A, Gupta V, Grewal SS. Edge-enhancing gradient echo with multi-image co-registration and averaging (EDGE-MICRA) for targeting thalamic centromedian and parafascicular nuclei. Neuroradiol J. 2021;19714009211021781

    Google Scholar 

  52. Spiegelmann R, Nissim O, Daniels D, Ocherashvilli A, Mardor Y. Stereotactic targeting of the ventrointermediate nucleus of the thalamus by direct visualization with high-field MRI. Stereotact Funct Neurosurg. 2006;84:19–23.

    Article  PubMed  Google Scholar 

  53. Morrison MA, Lee AT, Martin AJ, Dietiker C, Brown EG, Wang DD. DBS targeting for essential tremor using intersectional dentato-rubro-thalamic tractography and direct proton density visualization of the VIM: technical note on 2 cases. J Neurosurg. 2021;135:806–14.

    Article  Google Scholar 

  54. Sidiropoulos C, Mubita L, Krstevska S, Schwalb JM. Successful vim targeting for mixed essential and parkinsonian tremor using intraoperative MRI. J Neurol Sci. 2015;358:488–9.

    Article  PubMed  Google Scholar 

  55. Alterman RL, Reiter GT, Shils J, Skolnick B, Arle JE, Lesutis M, Simuni T, Colcher A, Stern M, Hurtig H. Targeting for thalamic deep brain stimulator implantation without computer guidance: assessment of targeting accuracy. Stereotact Funct Neurosurg. 1999;72:150–3.

    Article  CAS  PubMed  Google Scholar 

  56. Yamada K, Akazawa K, Yuen S, Goto M, Matsushima S, Takahata A, Nakagawa M, Mineura K, Nishimura T. MR imaging of ventral thalamic nuclei. AJNR Am J Neuroradiol. 2010;31:732–5.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  57. Jiltsova E, Möttönen T, Fahlström M, Haapasalo J, Tähtinen T, Peltola J, Öhman J, Larsson E-M, Kiekara T, Lehtimäki K. Imaging of anterior nucleus of thalamus using 1.5T MRI for deep brain stimulation targeting in refractory epilepsy. Neuromodulation. 2016;19:812–7.

    Article  PubMed  Google Scholar 

  58. Möttönen T, Katisko J, Haapasalo J, Tähtinen T, Kiekara T, Kähärä V, Peltola J, Öhman J, Lehtimäki K. Defining the anterior nucleus of the thalamus (ANT) as a deep brain stimulation target in refractory epilepsy: delineation using 3 T MRI and intraoperative microelectrode recording. Neuroimage Clin. 2015;7:823–9.

    Article  PubMed Central  PubMed  Google Scholar 

  59. Vassal F, Coste J, Derost P, Mendes V, Gabrillargues J, Nuti C, Durif F, Lemaire J-J. Direct stereotactic targeting of the ventrointermediate nucleus of the thalamus based on anatomic 1.5-T MRI mapping with a white matter attenuated inversion recovery (WAIR) sequence. Brain Stimul. 2012;5:625–33.

    Article  PubMed  Google Scholar 

  60. Bonneville F, Welter ML, Elie C, et al. Parkinson disease, brain volumes, and subthalamic nucleus stimulation. Neurology. 2005;64:1598–604.

    Article  CAS  PubMed  Google Scholar 

  61. Lee SH, Kim SS, Tae WS, Lee SY, Choi JW, Koh SB, Kwon DY. Regional volume analysis of the Parkinson disease brain in early disease stage: gray matter, white matter, striatum, and thalamus. AJNR Am J Neuroradiol. 2011;32:682–7.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  62. O’Gorman RL, Jarosz JM, Samuel M, Clough C, Selway RP, Ashkan K. CT/MR image fusion in the postoperative assessment of electrodes implanted for deep brain stimulation. Stereotact Funct Neurosurg. 2009;87:205–10.

    Article  PubMed  Google Scholar 

  63. Kraff O, Quick HH. 7T: physics, safety, and potential clinical applications. J Magn Reson Imaging. 2017;46:1573–89.

    Article  PubMed  Google Scholar 

  64. Springer E, Dymerska B, Cardoso PL, Robinson SD, Weisstanner C, Wiest R, Schmitt B, Trattnig S. Comparison of routine brain imaging at 3 T and 7 T. Investig Radiol. 2016;51:469–82.

    Article  Google Scholar 

  65. Cong F, Liu X, Liu C-SJ, Xu X, Shen Y, Wang B, Zhuo Y, Yan L. Improved depiction of subthalamic nucleus and globus pallidus internus with optimized high-resolution quantitative susceptibility mapping at 7 T. NMR Biomed. 2020;33:e4382.

    Article  CAS  PubMed  Google Scholar 

  66. Abosch A, Yacoub E, Ugurbil K, Harel N. An assessment of current brain targets for deep brain stimulation surgery with susceptibility-weighted imaging at 7 tesla. Neurosurgery. 2010;67:1745–56. discussion 1756.

    Article  PubMed  Google Scholar 

  67. Dammann P, Kraff O, Wrede KH, et al. Evaluation of hardware-related geometrical distortion in structural MRI at 7 tesla for image-guided applications in neurosurgery. Acad Radiol. 2011;18:910–6.

    Article  PubMed  Google Scholar 

  68. Hoff MN, McKinney A 4th, Shellock FG, Rassner U, Gilk T, Watson RE Jr, Greenberg TD, Froelich J, Kanal E. Safety considerations of 7-T MRI in clinical practice. Radiology. 2019;292:509–18.

    Article  PubMed  Google Scholar 

  69. Bhusal B, Stockmann J, Guerin B, et al. Safety and image quality at 7T MRI for deep brain stimulation systems: ex vivo study with lead-only and full-systems. PLoS One. 2021;16:e0257077.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  70. Horn A, Fox MD. Opportunities of connectomic neuromodulation. NeuroImage. 2020;221:117180.

    Article  PubMed  Google Scholar 

  71. Yarach U, Luengviriya C, Stucht D, Godenschweger F, Schulze P, Speck O. Correction of B 0-induced geometric distortion variations in prospective motion correction for 7T MRI. MAGMA. 2016;29:319–32.

    Article  PubMed Central  PubMed  Google Scholar 

  72. See AAQ, King NKK. Improving surgical outcome using diffusion tensor imaging techniques in deep brain stimulation. Front Surg. 2017;4:54.

    Article  PubMed Central  PubMed  Google Scholar 

  73. Horn A, Reich M, Vorwerk J, et al. Connectivity predicts deep brain stimulation outcome in Parkinson disease. Ann Neurol. 2017;82:67–78.

    Article  PubMed Central  PubMed  Google Scholar 

  74. Coenen VA, Allert N, Paus S, Kronenbürger M, Urbach H, Mädler B. Modulation of the cerebello-thalamo-cortical network in thalamic deep brain stimulation for tremor: a diffusion tensor imaging study. Neurosurgery. 2014;75:657–69. discussion 669–70.

    Article  PubMed  Google Scholar 

  75. Coenen VA, Sajonz B, Reisert M, Bostroem J, Bewernick B, Urbach H, Jenkner C, Reinacher PC, Schlaepfer TE, Mädler B. Tractography-assisted deep brain stimulation of the superolateral branch of the medial forebrain bundle (slMFB DBS) in major depression. Neuroimage Clin. 2018;20:580–93.

    Article  PubMed Central  PubMed  Google Scholar 

  76. Muller J, Alizadeh M, Matias CM, Thalheimer S, Romo V, Martello J, Liang T-W, Mohamed FB, Wu C. Use of probabilistic tractography to provide reliable distinction of the motor and sensory thalamus for prospective targeting during asleep deep brain stimulation. J Neurosurg. 2021:1–10.

    Google Scholar 

  77. Sajonz BEA, Amtage F, Reinacher PC, Jenkner C, Piroth T, Kätzler J, Urbach H, Coenen VA. Deep brain stimulation for tremor Tractographic versus traditional (DISTINCT): study protocol of a randomized controlled feasibility trial. JMIR Res Protoc. 2016;5:e244.

    Article  PubMed Central  PubMed  Google Scholar 

  78. Gibson WS, Jo HJ, Testini P, Cho S, Felmlee JP, Welker KM, Klassen BT, Min H-K, Lee KH. Functional correlates of the therapeutic and adverse effects evoked by thalamic stimulation for essential tremor. Brain. 2016;139:2198–210.

    Article  PubMed Central  PubMed  Google Scholar 

  79. Younce JR, Campbell MC, Hershey T, et al. Resting-state functional connectivity predicts STN DBS clinical response. Mov Disord. 2021;36:662–71.

    Article  PubMed  Google Scholar 

  80. Edlow BL, Mareyam A, Horn A, et al (2019) 7 tesla MRI of the ex vivo human brain at 100 micron resolution. Sci Data. 2019; https://doi.org/10.1038/s41597-019-0254-8.

Download references

Author information

Authors and Affiliations

  1. University Health Network, Toronto, ON, Canada

    Aaron Loh, Clement T. Chow, Aida Ahrari, Kâmil Uludağ & Sriranga Kashyap

  2. Functional Neurosurgery Unit, Department of Clinical and Movement Neurosciences, University College London, Queen Square Institute of Neurology, London, UK

    Harith Akram & Ludvic Zrinzo

  3. The National Hospital for Neurology and Neurosurgery, London, UK

    Harith Akram & Ludvic Zrinzo

Authors
  1. Aaron Loh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Clement T. Chow
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Aida Ahrari
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Kâmil Uludağ
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Sriranga Kashyap
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Harith Akram
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Ludvic Zrinzo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Aaron Loh .

Editor information

Editors and Affiliations

  1. Joint Department of Medical Imaging, University of Toronto, Toronto, ON, Canada

    Alexandre Boutet

  2. Division of Neurosurgery, University Health Network and University of Toronto, Toronto, ON, Canada

    Andres M. Lozano

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Loh, A. et al. (2022). Preoperative Planning of DBS Surgery with MRI. In: Boutet, A., Lozano, A.M. (eds) Magnetic Resonance Imaging in Deep Brain Stimulation. Springer, Cham. https://doi.org/10.1007/978-3-031-16348-7_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-16348-7_4

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-16347-0

  • Online ISBN: 978-3-031-16348-7

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics

Search

Navigation