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Human Head Transcranial Magnetic Stimulation Using Finite Element Method

Year 2024, , 62 - 70, 31.05.2024
https://doi.org/10.34088/kojose.1279222

Abstract

Transcranial magnetic stimulation (TMS) is a wearable neuromodulation technique. It is approved for several therapies for various neurological disorders, including major depressive disorder, traumatic brain injury, Parkinson’s disease, and post-traumatic stress disorder. This method became an alternative neuromodulation technique for such brain-related disorders. However, it has shown significant improvement in this alternative approach. Studies based on this technique have shown limited efficacy. They might be associated with current levels, poor coil locality, optimal coil size, and neuromodulator settings. It has been shown in this research that coil heating is related to higher levels of current. Thus, it is required to analyze the impact of the current levels on the induced magnetic distribution to define the optimal current range for the TMS coils. It is not feasible to investigate this research with experimental tests and analytic methods. Alternatively, using an advanced computational model of the coils and accounting for different human head anatomical layers, coil current capacity can be optimized based on finite element magnetic field distribution. This paper aims to investigate the impact of the coil current levels on the induced magnetic field distribution. The current capacity of the coils can be optimized based on the required magnetic field. In this way, the overheating may be reduced and may result in increased efficacy. As a proof-of-concept, a prototype coil and multi-layered geometrical human head models were generated using geometric shapes. The fundamental human head tissue layers were generated based on their average thickness. The model was simulated based on a finite element magnetic simulation using appropriate boundary conditions and neuromodulator settings. The various coil current levels were applied to analyze the outcome. The models were simulated, and the results were recorded based on these current levels. Results showed that there is a direct relation between applied current levels and induced magnetic flux density in the region of interest.

References

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  • [21] Salkim, E., Shiraz, A., & Demosthenous, A., 2018. Influence of cellular structures of skin on fiber activation thresholds and computation cost. Biomedical Physics & Engineering Express, 5(1), pp. 015015.
Year 2024, , 62 - 70, 31.05.2024
https://doi.org/10.34088/kojose.1279222

Abstract

References

  • [1] L. M. Koponen, J. O. Nieminen, T. P. Mutanen, M. Stenroos, and R. J. Ilmoniemi, 2017. Coil optimisation for transcranial magnetic stimulation in realistic head geometry. Brain Stimulation, 4, pp. 795–805.
  • [2] M. Ghannad-Rezaie, P. M. Eimon, Y. Wu, and M. F. Yanik, 2019. Engineering brain activity patterns by neuromodulator polytherapy for treatment of disorders. Nature Communications, 10, pp. 1–13.
  • [3] J. J. Mahoney, C. A. Hanlon, P. J. Marshalek, A. R. Rezai, and L. Krinke, 2020. Transcranial magnetic stimulation, deep brain stimulation, and other forms of neuromodulation for substance use disorders: Review of modalities and implications for treatment. Journal of the neurological sciences, 418, p. 117-149.
  • [4] T. Denison and M. J. Morrell, 2022. Neuromodulation in 2035. Neurology, 98, pp. 65–72.
  • [5] P. Rastogi, E. G. Lee, R. L. Hadimani, and D. C. Jiles, 2017. Transcranial Magnetic Stimulation-coil design with improved focality. Aip Advances, 7.
  • [6] Kraus, Karl H., et al., 1993. The use of a cap-shaped coil for transcranial magnetic stimulation of the motor cortex. Journal of Clinical Neurophysiology, 10.3, pp. 353-362.
  • [7] Roth, Y., Zangen, A., & Hallett, M., 2002. A coil design for transcranial magnetic stimulation of deep brain regions. Journal of Clinical Neurophysiology, 19, pp. 361-370.
  • [8] Lontis, E. R., Voigt, M., & Struijk, J. J., 2006. Focality assessment in transcranial magnetic stimulation with double and cone coils. Journal of Clinical Neurophysiology, 23, pp. 463-472.
  • [9] Maeda, F., Keenan, J. P., Tormos, J. M., Topka, H., & Pascual-Leone, A., 2000. Interindividual variability of the modulatory effects of repetitive transcranial magnetic stimulation on cortical excitability. Experimental brain research, 133, pp. 425-430.
  • [10] Kumru, H., Benito-Penalva, J., Valls-Sole, J., Murillo, N., Tormos, J. M., Flores, C., & Vidal, J., 2016. Placebo-controlled study of rTMS combined with Lokomat gait training for treatment in subjects with motor incomplete spinal cord injury. Experimental brain research, 234, pp. 3447-3455.
  • [11] Mosayebi-Samani, M., Jamil, A., Salvador, R., Ruffini, G., Haueisen, J., & Nitsche, M. A., 2021. The impact of individual electrical fields and anatomical factors on the neurophysiological outcomes of tDCS: A TMS-MEP and MRI study. Brain stimulation, 14(2), pp. 316-326.
  • [12] Pascual-Leone, A., Rubio, B., Pallardó, F., & Catalá, M. D., 1996. Rapid-rate transcranial magnetic stimulation of left dorsolateral prefrontal cortex in drug-resistant depression. The Lancet, 348(9022), pp. 233-237.
  • [13] Lu, C., Deng, Z. D., & Choa, F. S., 2022. Augmenting Transcranial Magnetic Stimulation Coil with Magnetic Material: An Optimization Approach, 01.
  • [14] Salkim, E., Shiraz, A., & Demosthenous, A., 2019. Impact of neuroanatomical variations and electrode orientation on stimulus current in a device for migraine: A computational study. Journal of neural engineering, 17(1), pp., 016006.
  • [15] Salkim, E., 2022. Analysis of tissue electrical properties on bio-impedance variation of upper limps. Turkish Journal of Electrical Engineering and Computer Sciences, 30(5), pp. 1839-1850.
  • [16] Salkim, E., Zamani, M., Jiang, D., Saeed, S. R., & Demosthenous, A., 2022. Insertion guidance based on impedance measurements of a cochlear electrode array. Frontiers in Computational Neuroscience, 16, pp. 862126.
  • [17] Ruohonen, J., Virtanen, J., & Ilmoniemi, R. J., 1997. Coil optimization for magnetic brain stimulation. Annals of Biomedical Engineering, 25, pp. 840-849.
  • [18] Gutierrez, M. I., Poblete-Naredo, I., Mercado-Gutierrez, J. A., Toledo-Peral, C. L., Quinzaños-Fresnedo, J., Yanez-Suarez, O., & Gutierrez-Martinez, J., 2022. Devices and Technology in Transcranial Magnetic Stimulation: A Systematic Review. Brain Sciences, 12(9), pp. 1218.
  • [19] Xu, Y., Zhang, J., Xia, S., Qiu, J., Qiu, J., Yang, X., ... & Yu, Y., 2022. Optimal design of transcranial magnetic stimulation coil with iron core. Journal of Neural Engineering, 19(2), pp. 026046.
  • [20] Dannhauer, M., Huang, Z., Beynel, L., Wood, E., Bukhari-Parlakturk, N., & Peterchev, A. V., 2022. TAP: Targeting and analysis pipeline for optimization and verification of coil placement in transcranial magnetic stimulation. Journal of neural engineering, 19(2), pp. 026050.
  • [21] Salkim, E., Shiraz, A., & Demosthenous, A., 2018. Influence of cellular structures of skin on fiber activation thresholds and computation cost. Biomedical Physics & Engineering Express, 5(1), pp. 015015.
There are 21 citations in total.

Details

Primary Language English
Subjects Biomedical Engineering
Journal Section Articles
Authors

Enver Salkım 0000-0002-7342-8126

Tayfun Abut 0000-0003-4646-3345

Early Pub Date May 31, 2024
Publication Date May 31, 2024
Acceptance Date December 13, 2023
Published in Issue Year 2024

Cite

APA Salkım, E., & Abut, T. (2024). Human Head Transcranial Magnetic Stimulation Using Finite Element Method. Kocaeli Journal of Science and Engineering, 7(1), 62-70. https://doi.org/10.34088/kojose.1279222