Deep brain stimulation (DBS) is a well-established treatment for Parkinson's disease, essential tremor and dystonia. It has also been successfully applied to treat various other neurological and psychiatric conditions including depression and obsessive-compulsive disorder. Numerous computational models, mostly based on the Finite Element Method (FEM) approach have been suggested to investigate the biophysical mechanisms of electromagnetic wave-tissue interaction during DBS. These models, although emphasizing the importance of various electrical and geometrical parameters, mostly have used simplified geometries over a tightly restricted tissue volume in the case of monopolar stimulation. In the present work we show that topological arrangements and geometrical properties of the model have a significant effect on the distribution of voltages in the concerned tissues. The results support reconsidering the current approach for modeling monopolar DBS which uses a restricted cubic area extended a few centimeters around the active electrode to predict the volume of activated tissue. We propose a new technique called multi-resolution FEM modeling, which may improve the accuracy of the prediction of volume of activated tissue and yet be computationally tractable on personal computers.
Alberto Pradas Izquierdo,
Simon J. Graham,
"Effect of Realistic Modeling of Deep Brain Stimulation on the Prediction of Volume of Activated Tissue," Progress In Electromagnetics Research,
Vol. 126, 1-16, 2012. doi:10.2528/PIER12013108
1. Rodriguez-Oroz, M. C., J. A. Obeso, A. E. Lang, J.-L. Houeto, P. Pollak, S. Rehncrona, J. Kulisevsky, A. Albanese, J. Volkmann, M. I. Hariz, N. P. Quinn, J. D. Speelman, J. Guridi, I. Zamarbide, A. Gironell, J. Molet, B. Pascual-Sedano, B. Pidoux, Y. Agid, J. Xie, A.-L. Benabid, A. M. Lozano, J. Saint-Cyr, L. Romito, M. F. Contarino, M. Scerrati, V. Fraix, and N. V. Blercom, "Bilateral deep brain stimulation in Parkinson's disease: A multicentre study with 4 years follow-up," Brain, Vol. 128, No. 10, 2240-2249, Oct. 2005. [Online]., Available: http://dx.doi.org/10.1093/brain/awh571.
2. Wider, C., C. Pollo, J. Bloch, P. R. Burkhard, and F. J. Vingerhoets, "Long-term outcome of 50 consecutive Parkinson's disease patients treated with subthalamic deep brain stimulation," Parkinsonism Relat. Disord., Vol. 14, No. 2, 114-119, 2008. [Online]., http://dx.doi.org/10.1016/j.parkreldis.2007.06.012. doi:10.1016/j.parkreldis.2007.06.012
3. Gabriels, L., P. Cosyns, B. Nuttin, H. Demeulemeester, and J. Gybels, "Deep brain stimulation for treatment-refractory obsessive compulsive disorder: Phsychopathological and neuropsychological outcome in three cases," Acta Psychiatr. Scand., Vol. 107, 275-282, 2003. doi:10.1034/j.1600-0447.2003.00066.x
4. McIntyre, C. C., M. Savasta, L. Kerkerian-Le Goff, and J. L. Vitek, "Uncovering the mechanism(s) of action of deep brain stimulation: Activation, inhibition, or both," Clin. Neurophysiol., Vol. 115, No. 6, 1239-1248, Jun. 2004. [Online]., Available: http://dx.doi.org/10.1016/j.clinph.2003.12.024. doi:10.1016/j.clinph.2003.12.024
5. Moro, E., J. A. Esselink, J. Xie, A. L. Benabid, and P. Pollak, "The impact on parkinsons disease of electrical parameter settings in STN stimulation," Neurology, Vol. 59, 706-713, 2002.
6. McIntyre, C. C., M. Savasta, B. L. Walter, and J. L. Vitek, "How does deep brain stimulation work? Present understanding and future questions," J. Clin. Neurophysiol., Vol. 21, 40-50, 2004.
7. Walckiers, G., B. Fuchs, J.-P. Thiran, J. R. Mosig, and C. Pollo, "Influence of the implanted pulse generator as reference electrode in ¯nite element model of monopolar deep brain stimulation," J. Neurosci. Methods, Vol. 186, No. 1, 90-96, Jan. 2010. [Online]., Available: http://www.ncbi.nlm.nih.gov/pubmed/19895845. doi:10.1016/j.jneumeth.2009.10.012
13. Yousif, N., R. Bayford, S. Wang, and X. Liu, "Quantifying the effects of the electrode-brain interface on the crossing electric currents in deep brain recording and stimulation ," Neuroscience, Vol. 152, No. 68391, 2008. doi:10.1109/TMAG.2010.2082556
14. Yousif, N. and X. Liu, "Investigating the depth electrode-brain interface in deep brain stimulation using finite element models with graded complexity in structure and solution," J. Neurosci. Methods, Vol. 184, No. 1, 142-151, 2009. doi:10.1177/107385840100700207
16. Golestanirad, L., M. Mattes, J. R. Mosig, and C. Pollo, "Effect of model accuracy on the result of computed current densities in the simulation of transcranial magnetic stimulation," IEEE Transactions on Magnetics, Vol. 46, No. 12, 4046-4051, 2010. doi:10.1016/j.clinph.2005.10.007
17. Hines, M. L. and N. T. Carnevale, "Neuron: A tool for neuroscientists," Neuroscientist, Vol. 7, No. 2, 123-135, Apr. 2001.
18. Butson, C. R. and C. C. McIntyre, "Tissue and electrode capacitance reduce neural activation volumes during deep brain stimulation," Clin. Neurophysiol., Vol. 116, No. 10, 2490-2500, Oct. 2005. [Online]., Available: http://dx.doi.org/10.1016/j.clinph.2005.06.023. doi:10.1109/10.605429
19. Butson, C. R., C. B. Maks, and C. C. McIntyre, "Sources and effects of electrode impedance during deep brain stimulation," Clin. Neurophysiol., Vol. 117, No. 2, 447-454, 2006. doi:10.1002/mds.10162
20. Ramon, C., P. Schimpf, and J. Haueisen, "In uence of head models on eeg simulations and inverse source localizations," BioMedical Engineering OnLine, 2006. doi:10.2528/PIER08040504
21. Haueisen, J., C. Ramon, M. Eiselt, H. Brauer, and H. Nowak, "In uence of tissue resistivities on neuromagnetic fields and electric potentials studied with a finite element model of the head," IEEE Trans. Biomed. Eng., Vol. 44, No. 8, 727-735, Aug. 1997. [Online]., Available: http://www.ncbi.nlm.nih.gov/pubmed/9254986. doi: --- Either ISSN/ISBN or Series/Volume title must be supplied.