Method for patient-specific finite element modeling and simulation of deep brain stimulation
- 636 Downloads
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.
KeywordsDeep brain stimulation Patient-specific Simulation Finite element Glyph
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.
- 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/
- 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)CrossRefGoogle Scholar
- 9.Cheng DK (1989) Field and wave electromagnetics. Addison-Wesley, New York. ISBN 0-201-52820-7Google Scholar
- 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 259:1516–1523Google 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 1036:949–955Google Scholar
- 15.Holsheimer J (2003) Principles of neurostimulation. In: Pain BA (ed) Electrical stimulation and the relief of Simpson. Elsevier, Amsterdam, pp 17–36Google 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-ECrossRefGoogle Scholar
- 27.Polk C, Postow E (1996) Biological effects of electromagnetic fields, 2nd edn. CRC Press, Boca Raton, p 67Google 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 2004:55Google 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 371–378Google 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 2006Google Scholar