Abstract
Deep brain stimulation is a well-established technique for symptomatic treatment of e.g. Parkinson’s disease and essential tremor. Computer simulations using the finite element method (FEM) are widely used to estimate the affected area around the DBS electrodes. For the reliability of the simulations, it is important to match used simulation parameters with experimental data. One such parameter is the electric field magnitude threshold EFt required for axon stimulation. Another is the conductivity of the perielectrode space (PES) around the electrode. At the acute stage after surgery the PES will be characterized by an increased conductivity due to inflammation and edema while the later chronic stage will be characterized by a lower conductivity due to gliosis and minor scar formation. In this study, the EFt and the electric conductivity of the PES have been estimated by comparing FEM simulations with clinical studies of activation distance, pulse length and electrode impedance. The resulting estimates are an EFt of 0.2 V/mm at the common pulse width of 60 µs and a chronaxie of 62 µs. Estimated electric conductivities for the PES are 0.14 S/m in the acute stage and 0.05 S/m in the chronic stage, assuming a PES width of 250 µm. These values are thus experimentally justified to use in FEM simulations of DBS.
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References
Blomstedt, P., Hariz, G. M., and Hariz, M. I., Pallidotomy versus pallidal stimulation, Parkinsonism Relat Disord, 12(5) pp. 296–301, (2006).
Schuurman, P. R., Bosch, D. A., Merkus, M. P., and Speelman, J. D., Long-term follow-up of thalamic stimulation versus thalamotomy for tremor suppression, Mov Disord, 23(8) pp. 1146–53, (2008).
Eltahawy, H. A., Saint-Cyr, J., Giladi, N., Lang, A. E., and Lozano, A. M., Primary dystonia is more responsive than secondary dystonia to pallidal interventions: Outcome after pallidotomy or pallidal deep brain stimulation, Neurosurgery, 54(3) pp. 613–619, (2004).
Marin, C., Jimenez, A., Tolosa, E., Bonastre, M., and Bove, J., Bilateral subthalamic nucleus lesion reverses L-dopa-induced motor fluctuations and facilitates dyskinetic movements in hemiparkinsonian rats, Synapse, 51(2) pp. 140–50, (2004).
Galarreta, M. and Hestrin, S., Frequency-dependent synaptic depression and the balance of excitation and inhibition in the neocortex, Nat Neurosci, 1(7) pp. 587–94, (1998).
Urbano, F. J., Leznik, E., and Llinás, R. R., Cortical activation patterns evoked by afferent axons stimuli at different frequencies: an in vitro voltage-sensitive dye imaging study, Thalamus & Related Systems, 1(4) pp. 371–378, (2002).
Brocker, D. T., Swan, B. D., So, R. Q., Turner, D. A., Gross, R. E., and Grill, W. M., Optimized temporal pattern of brain stimulation designed by computational evolution, Sci Transl Med, 9(371) 2017).
Geddes, L. A., Accuracy limitations of chronaxie values, IEEE Trans Biomed Eng, 51(1) pp. 176–81, (2004).
Rizzone, M., Lanotte, M., Bergamasco, B., Tavella, A., Torre, E., Faccani, G., et al., Deep brain stimulation of the subthalamic nucleus in Parkinson’s disease: effects of variation in stimulation parameters, J Neurol Neurosurg Psychiatry, 71(2) pp. 215–9, (2001).
Gradinaru, V., Mogri, M., Thompson, K. R., Henderson, J. M., and Deisseroth, K., Optical deconstruction of parkinsonian neural circuitry, Science, 324(5925) pp. 354–9, (2009).
Hassler, R., Riechert, T., Mundinger, F., Umbach, W., and Ganglberger, J. A., Physiological observations in stereotaxic operations in extrapyramidal motor disturbances, Brain, 83 pp. 337–50, (1960).
Åström, M., Diczfalusy, E., Martens, H., and Wårdell, K., Relationship between Neural Activation and Electric Field Distribution during Deep Brain Stimulation, IEEE Transactions on Biomedical Engineering, 62(2) pp. 664–672, (2015).
Hemm, S., Pison, D., Alonso, F., Shah, A., Coste, J., Lemaire, J. J., et al., Patient-Specific Electric Field Simulations and Acceleration Measurements for Objective Analysis of Intraoperative Stimulation Tests in the Thalamus, Front Hum Neurosci, 10 p. 577, (2016).
Alonso, F., Latorre, M. A., Göransson, N., Zsigmond, P., and Wårdell, K., Investigation into Deep Brain Stimulation Lead Designs: A Patient-Specific Simulation Study, Brain Sciences, 6(3) 2016).
Horn, A., Reich, M., Vorwerk, J., Li, N. F., Wenzel, G., Fang, Q. Q., et al., Connectivity Predicts Deep Brain Stimulation Outcome in Parkinson Disease, Annals of Neurology, 82(1) pp. 67–78, (2017).
Perez-Caballero, L., Perez-Egea, R., Romero-Grimaldi, C., Puigdemont, D., Molet, J., Caso, J. R., et al., Early responses to deep brain stimulation in depression are modulated by anti-inflammatory drugs, Mol Psychiatry, 19(5) pp. 607–14, (2014).
Kozai, T. D., Jaquins-Gerstl, A. S., Vazquez, A. L., Michael, A. C., and Cui, X. T., Brain tissue responses to neural implants impact signal sensitivity and intervention strategies, ACS Chem Neurosci, 6(1) pp. 48–67, (2015).
Alonso, F., Hemm-Ode, S., and Wårdell, K., Influence on Deep Brain Stimulation from Lead Design, Operating Mode and Tissue Impedance Changes – A Simulation Study, Brain Disorders & Therapy, 4(3) 2015).
Yousif, N., Bayford, R., Bain, P. G., and Liu, X., The peri-electrode space is a significant element of the electrode-brain interface in deep brain stimulation: A computational study, Brain Research Bulletin, 74(5) pp. 361–368, (2007).
Nielsen, M. S., Bjarkam, C. R., Sorensen, J. C., Bojsen-Moller, M., Sunde, N. A., and Ostergaard, K., Chronic subthalamic high-frequency deep brain stimulation in Parkinson’s disease - a histopathological study, European Journal of Neurology, 14(2) pp. 132–138, (2007).
Haberler, C., Alesch, F., Mazal, P. R., Pilz, P., Jellinger, K., Pinter, M. M., et al., No tissue damage by chronic deep brain stimulation in Parkinson’s disease, Annals of Neurology, 48(3) pp. 372–376, (2000).
Kuncel, A. M., Cooper, S. E., and Grill, W. M., A method to estimate the spatial extent of activation in thalamic deep brain stimulation, Clin Neurophysiol, 119(9) pp. 2148–58, (2008).
Lungu, C., Malone, P., Wu, T., Ghosh, P., McElroy, B., Zaghloul, K., et al., Temporal macrodynamics and microdynamics of the postoperative impedance at the tissue-electrode interface in deep brain stimulation patients, J Neurol Neurosurg Psychiatry, 85(7) pp. 816–9, (2014).
Hemm, S., Mennessier, G., Vayssiere, N., Cif, L., and Coubes, P., Co-registration of stereotactic MRI and isofieldlines during deep brain stimulation, Brain Res Bull, 68(1–2) pp. 59-61, (2005).
McIntyre, C. C., Mori, S., Sherman, D. L., Thakor, N. V., and Vitek, J. L., Electric field and stimulating influence generated by deep brain stimulation of the subthalamic nucleus, Clin Neurophysiol, 115(3) pp. 589–95, (2004).
Liewald, D., Miller, R., Logothetis, N., Wagner, H. J., and Schuz, A., Distribution of axon diameters in cortical white matter: an electron-microscopic study on three human brains and a macaque, Biological Cybernetics, 108(5) pp. 541–557, (2014).
Mathai, A., Wichmann, T., and Smith, Y., More Than Meets the Eye-Myelinated Axons Crowd the Subthalamic Nucleus, Movement Disorders, 28(13) pp. 1811–1815, (2013).
Acknowledgements
This work is funded by the Swedish Research Council (Vetenskapsrådet, Dnr. 2016-03564), the Swedish Foundation for Strategic Research (Project BD15-0032), and the Knut and Alice Wallenberg Foundation (Project Seeing Organ Function). The authors declare that they have no conflicts of interest.
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Johansson, J.D., Alonso, F., Wårdell, K. (2019). Modelling Details for Electric Field Simulations of Deep Brain Stimulation. In: Lhotska, L., Sukupova, L., Lacković, I., Ibbott, G.S. (eds) World Congress on Medical Physics and Biomedical Engineering 2018. IFMBE Proceedings, vol 68/1. Springer, Singapore. https://doi.org/10.1007/978-981-10-9035-6_120
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DOI: https://doi.org/10.1007/978-981-10-9035-6_120
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