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Method for patient-specific finite element modeling and simulation of deep brain stimulation

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Abstract

Deep brain stimulation (DBS) is an established treatment for Parkinson’s disease. Success of DBS is highly dependent on electrode location and electrical parameter settings. The aim of this study was to develop a general method for setting up patient-specific 3D computer models of DBS, based on magnetic resonance images, and to demonstrate the use of such models for assessing the position of the electrode contacts and the distribution of the electric field in relation to individual patient anatomy. A software tool was developed for creating finite element DBS-models. The electric field generated by DBS was simulated in one patient and the result was visualized with isolevels and glyphs. The result was evaluated and it corresponded well with reported effects and side effects of stimulation. It was demonstrated that patient-specific finite element models and simulations of DBS can be useful for increasing the understanding of the clinical outcome of DBS.

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References

  1. Andreuccetti D, Fossi R, Petrucci C (2005) Dielectric properties of body tissue. Italian National Research Council, Institute for Applied Physics, Florence, Italy. http://niremf.ifac.cnr.it/tissprop/

  2. Astrom M, Johansson JD, Hariz MI et al (2006) The effect of cystic cavities on deep brain stimulation in the basal ganglia: a simulation-based study. J Neural Eng 32:132–138. doi:10.1088/1741-2560/3/2/007

    Article  Google Scholar 

  3. Benabid AL, Chabardes S, Seigneuret E et al (2006) Surgical therapy for Parkinson’s disease. J Neural Transm Suppl 70:383–392. doi:10.1007/978-3-211-45295-0_58

    Article  Google Scholar 

  4. Burchiel KJ, Anderson VC, Favre J et al (1999) Comparison of pallidal and subthalamic nucleus deep brain stimulation for advanced Parkinson’s disease: results of a randomized, blinded pilot study. Neurosurgery 456:1375–1382. doi:10.1097/00006123-199912000-00024 (discussion 1382–1384)

    Article  Google Scholar 

  5. Butson CR, McIntyre CC (2006) Role of electrode design on the volume of tissue activated during deep brain stimulation. J Neural Eng 31:1–8. doi:10.1088/1741-2560/3/1/001

    Article  Google Scholar 

  6. Butson CR, McIntyre CC (2007) Differences among implanted pulse generator waveforms cause variations in the neural response to deep brain stimulation. Clin Neurophysiol 1188:1889–1894. doi:10.1016/j.clinph.2007.05.061

    Article  Google Scholar 

  7. Butson CR, Maks CB, McIntyre CC (2006) Sources and effects of electrode impedance during deep brain stimulation. Clin Neurophysiol 1172:447–454. doi:10.1016/j.clinph.2005.10.007

    Article  Google Scholar 

  8. Butson CR, Cooper SE, Henderson JM et al (2007) Patient-specific analysis of the volume of tissue activated during deep brain stimulation. Neuroimage 342:661–670. doi:10.1016/j.neuroimage.2006.09.034

    Article  Google Scholar 

  9. Cheng DK (1989) Field and wave electromagnetics. Addison-Wesley, New York. ISBN 0-201-52820-7

  10. Dormont D, Ricciardi KG, Tande D et al (2004) Is the subthalamic nucleus hypointense on T2-weighted images? A correlation study using MR imaging and stereotactic atlas data. AJNR Am J Neuroradiol 259:1516–1523

    Google Scholar 

  11. Gallay MN, Jeanmonod D, Liu J, Morel A (2008) Human pallidothalamic and cerebellothalamic tracts: anatomical basis for functional stereotactic neurosurgery. Brain Struct Funct 212(6):443–463

    Article  Google Scholar 

  12. Gimsa U, Schreiber U, Habel B et al (2006) Matching geometry and stimulation parameters of electrodes for deep brain stimulation experiments—numerical considerations. J Neurosci Methods 1502:212–227. doi:10.1016/j.jneumeth.2005.06.013

    Article  Google Scholar 

  13. Hemm S, Vayssiere N, Mennessier G et al (2004) Evolution of brain impedance in dystonic patients treated by GPi electrical stimulation. Neuromodulation 7(2):67–75

    Article  Google Scholar 

  14. Hemm S, Mennessier G, Vayssiere N et al (2005) Deep brain stimulation in movement disorders: stereotactic coregistration of two-dimensional electrical field modeling and magnetic resonance imaging. J Neurosurg 1036:949–955

    Google Scholar 

  15. Holsheimer J (2003) Principles of neurostimulation. In: Pain BA (ed) Electrical stimulation and the relief of Simpson. Elsevier, Amsterdam, pp 17–36

    Google Scholar 

  16. Kleiner-Fisman G, Herzog J, Fisman DN et al (2006) Subthalamic nucleus deep brain stimulation: summary and meta-analysis of outcomes. Mov Disord 21(Suppl 14):S290–S304. doi:10.1002/mds.20962

    Article  Google Scholar 

  17. Krack P, Pollak P, Limousin P et al (1998) Subthalamic nucleus or internal pallidal stimulation in young onset Parkinson’s disease. Brain 121:451–457. doi:10.1093/brain/121.3.451

    Article  Google Scholar 

  18. Kuncel AM, Grill WM (2004) Selection of stimulus parameters for deep brain stimulation. Clin Neurophysiol 11511:2431–2441. doi:10.1016/j.clinph.2004.05.031

    Article  Google Scholar 

  19. Laitinen LV, Chudy D, Tengvar M et al (2000) Dilated perivascular spaces in the putamen and pallidum in patients with Parkinson’s disease scheduled for pallidotomy: a comparison between MRI findings and clinical symptoms and signs. Mov Disord 156:1139–1144 doi:10.1002/1531-8257(200011)15:6<1139::AID-MDS1012>3.0.CO;2-E

    Article  Google Scholar 

  20. Lang AE, Houeto JL, Krack P et al (2006) Deep brain stimulation: preoperative issues. Mov Disord 21(Suppl 14):S171–S196. doi:10.1002/mds.20955

    Article  Google Scholar 

  21. Mayberg HS, Lozano AM, Voon V et al (2005) Deep brain stimulation for treatment-resistant depression. Neuron 455:651–660. doi:10.1016/j.neuron.2005.02.014

    Article  Google Scholar 

  22. McIntyre CC, Grill WM, Sherman DL et al (2004) Cellular effects of deep brain stimulation: model-based analysis of activation and inhibition. J Neurophysiol 914:1457–1469. doi:10.1152/jn.00989.2003

    Article  Google Scholar 

  23. McIntyre CC, Mori S, Sherman DL et al (2004) Electric field and stimulating influence generated by deep brain stimulation of the subthalamic nucleus. Clin Neurophysiol 1153:589–595. doi:10.1016/j.clinph.2003.10.033

    Article  Google Scholar 

  24. McNeal DR (1976) Analysis of a model for excitation of myelinated nerve. IEEE Trans Biomed Eng 234:329–337

    Article  Google Scholar 

  25. Miocinovic S, Parent M, Butson CR et al (2006) Computational analysis of subthalamic nucleus and lenticular fasciculus activation during therapeutic deep brain stimulation. J Neurophysiol 963:1569–1580. doi:10.1152/jn.00305.2006

    Article  Google Scholar 

  26. Plaha P, Ben-Shlomo Y, Patel NK et al (2006) Stimulation of the caudal zona incerta is superior to stimulation of the subthalamic nucleus in improving contralateral parkinsonism. Brain 129(Pt 7):1732–1747. doi:10.1093/brain/awl127

    Article  Google Scholar 

  27. Polk C, Postow E (1996) Biological effects of electromagnetic fields, 2nd edn. CRC Press, Boca Raton, p 67

    Google Scholar 

  28. Pollak P, Fraix V, Krack P et al (2002) Treatment results: Parkinson’s disease. Mov Disord 17(Suppl 3):S75–S83. doi:10.1002/mds.10146

    Article  Google Scholar 

  29. Ranck JB Jr (1963) Specific impedance of rabbit cerebral cortex. Exp Neurol 7:144–152. doi:10.1016/S0014-4886(63)80005-9

    Article  Google Scholar 

  30. Rattay F (1986) Analysis of models for external stimulation of axons. IEEE Trans Biomed Eng 3310:974–977. doi:10.1109/TBME.1986.325670

    Article  Google Scholar 

  31. Sekino M, Inoue Y, Ueno S (2004) Magnetic resonance imaging of mean values and anisotropy of electrical conductivity in the human brain. Neurol Clin Neurophysiol 2004:55

    Google Scholar 

  32. Sigfridsson A, Ebbers T, Heiberg E et al (2002) Tensor field visualisation using adaptive filtering of noise fields combined with glyph rendering. In: Proceedings of IEEE visualization 2002, Boston, MA, October 27– November 1, 2002, pp 371–378

  33. Ulla M, Thobois S, Lemaire JJ et al (2006) Manic behaviour induced by deep-brain stimulation in Parkinson’s disease: evidence of substantia nigra implication? J Neurol Neurosurg Psychiatry 7712:1363–1366. doi:10.1136/jnnp.2006.096628

    Article  Google Scholar 

  34. Volkmann J (2004) Deep brain stimulation for the treatment of Parkinson’s disease. J Clin Neurophysiol 211:6–17. doi:10.1097/00004691-200401000-00003

    Article  Google Scholar 

  35. Volkmann J, Moro E, Pahwa R (2006) Basic algorithms for the programming of deep brain stimulation in Parkinson’s disease. Mov Disord 21(Suppl 14):S284–S289. doi:10.1002/mds.20961

    Article  Google Scholar 

  36. Wei XF, Grill WM (2005) Current density distributions, field distributions and impedance analysis of segmented deep brain stimulation electrodes. J Neural Eng 24:139–147. doi:10.1088/1741-2560/2/4/010

    Article  Google Scholar 

  37. Wiklund J, Nicolas V, Alface PR, et al (2006) T-flash: tensor visualization in medical studio. In: Similar NoE tensor workshop, Las Palmas, Spain, November 2006

Download references

Acknowledgments

This work was supported by the Swedish Foundation for Strategic Research (SSF), Swedish Research Council (VR) and Swedish Governmental Agency for Innovation Systems (VINNOVA). The authors would like to thank Johannes Johansson for valuable discussions, Johan Tervald for graphical advice and Göran Salerud for valuable comments on the manuscript.

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Authors and Affiliations

  1. Department of Biomedical Engineering, Linköping University, 581 85, Linköping, Sweden

    Mattias Åström & Karin Wårdell

  2. Institute of Neurology, University College London, Queen Square, London, UK

    Ludvic U. Zrinzo, Stephen Tisch, Elina Tripoliti & Marwan I. Hariz

  3. Department of Neurosurgery, University Hospital, Umeå, Sweden

    Marwan I. Hariz

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  1. Mattias Åström
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  2. Ludvic U. Zrinzo
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Correspondence to Mattias Åström.

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Åström, M., Zrinzo, L.U., Tisch, S. et al. Method for patient-specific finite element modeling and simulation of deep brain stimulation. Med Biol Eng Comput 47, 21–28 (2009). https://doi.org/10.1007/s11517-008-0411-2

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  • DOI: https://doi.org/10.1007/s11517-008-0411-2

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