Abstract
Objective
Percutaneous stimulation of the auricular branch of the vagus nerve (pVNS) by miniaturized needle electrodes in the auricle gained importance as a treatment for acute and chronic pain. The objective is to establish a realistic numerical model of pVNS and investigate the effects of stimulation waveform, electrodes’ depth, and electrodes’ position on nerve excitation threshold and the percentage of stimulated nerves.
Methods
Simulations were performed with Sim4Life. An electrostatic solver and neural tissue models were combined for electromagnetic and neural simulation. The numerical model consisted of a realistic high-resolution model of a human ear, blood vessels, nerves, and three needle electrodes.
Results
A novel 3D ear model was established, including blood vessels and nerves. The electric field distribution was extracted and evaluated. Maximum sensitivity to needles’ depth and displacement was evaluated to be 9.8 and 15.5% per 0.1 mm, respectively. Stimulation was most effective using biphasic compared to mono-phasic pulses.
Conclusion
The established model allows easy and quantitative evaluation of various stimulation setups, enabling optimization of pVNS in experimental settings. Results suggest a high sensitivity of pVNS to the electrodes’ position and depth, implying the need for precise electrode positioning. Validation of the model needs to be performed.
Similar content being viewed by others
References
Groves D, Brown V (2005) Vagal nerve stimulation: a review of its applications and potential mechanisms that mediate its clinical effects. Neurosci Biobehav Rev 29(3):493–500
De Ferrari G, Crijns H, Borggrefe M et al (2011) Chronic vagus nerve stimulation: a new and promising therapeutic approach for chronic heart failure. Eur Heart J 32(7):847–855
Ellrich J (2011) Transcutaneous vagus nerve stimulation. Eur Neurol Rev 6(4):254
Kampusch S, Kaniusas E, Széles J (2013) New approaches in multi-punctual percutaneous stimulation of the auricular vagus nerve. In: Proceedings of the 6th international IEEE EMBS conference on neural engineering, pp 263–266
Peuker E, Filler T (2002) The nerve supply of the human auricle. Clin Anat 15(1):35–37
Kaniusas E, Varoneckas G, Mahr B, Széles J (2011) Optic visualization of auricular nerves and blood vessels: optimisation and validation. IEEE Trans Instrum Meas 60(10):3253–3258
Sator-Katzenschlager S, Széles J, Scharbert G, Michalek-Sauberer A, Kober A, Heinze G, Kozek-Langenecker S (2003) Electrical stimulation of auricular acupuncture points is more effective than conventional manual auricular acupuncture in chronic cervical pain: a pilot study. Anesth Anal 97(5):1469–1473
Payrits T et al (2011) Vagal stimulation—a new possibility for conservative treatment of peripheral arterial occlusion disease. Zentralblatt für Chirurgie 136:431–435
Berthoud H, Neuhuber W (2000) Functional and chemical anatomy of the afferent vagal system. Auton Neurosci 85(1–3):1–17
Kaniusas E (2012) Biomedical signals and sensors I. Springer, Berlin
Zamotrinsky A, Kondratiev B, de Jong J (2001) Vagal neurostimulation in patients with coronary artery disease. Auton Neurosci 88(1–2):109–116
Széles J, Litscher G (2004) Objectivation of cerebral effects with a new continuous electrical auricular stimulation technique for pain management. Neurol Res 26(7):797–800
Tracey K (2009) Reflex control of immunity. Nat Rev Immunol 9(6):418–428
Zhao Y, He W, Jing X, Liu J, Rong P, Ben H et al (2012) Transcutaneous auricular vagus nerve stimulation protects endotoxemic rat from lipopolysaccharide-induced inflammation. Evid Based Complem Altern Med 2012:1–10
Shammas N (2007) Epidemiology, classification, and modifiable risk factors of peripheral arterial disease. Vasc Health Risk Manag 3(2):229–234
Gao X, Zhang S, Zhu B, Zhang H (2008) Investigation of specificity of auricular acupuncture points in regulation of autonomic function in anesthetized rats. Auton Neurosci 138(1–2):50–56
Miocinovic S (2006) Computational analysis of subthalamic nucleus and lenticular fasciculus activation during therapeutic deep brain stimulation. J Neurophysiol 96(3):1569–1580
Schmidt C, van Rienen U (2012) Modeling the field distribution in deep brain stimulation: the influence of anisotropy of brain tissue. IEEE Trans Biomed Eng 59(6):1583–1592
Danner SM et al (2014) Potential distribution and nerve fiber responses in transcutaneous lumbosacral spinal cord stimulation. In: International conference on advancements of medicine and health care through technology; IFBME 44, pp 203–208
Samoudi A, Vermeeren G, Tanghe E, Van Holen R, Martens L, Josephs W (2016) Numerically simulated exposure of children and adults to pulsed gradient fields in MRI. J Magn Reson Imaging 44:1360–1367
De Lucia M, Parker G, Embleton K, Newton J, Walsh V (2007) Diffusion tensor MRI-based estimation of the influence of brain tissue anisotropy on the effects of transcranial magnetic stimulation. Neuroimage 36(4):1159–1170
Lu M, Ueno S (2013) Calculating the induced electromagnetic fields in real human head by deep transcranial magnetic stimulation. Conf Proc IEEE Eng Med Biol Soc 2013:795–798
Choi C, Lee Y, Tsou Y (2011) Modeling deep brain stimulation based on current steering scheme. IEEE Trans Magn 47(5):890–893
Chaturvedi A, Foutz T, McIntyre C (2012) Current steering to activate targeted neural pathways during deep brain stimulation of the subthalamic region. Brain Stimul 5(3):369–377
Sim4Life, Zurich Med Tech. www.zurichmedtech.com/sim4life/. Visited on September 2016
Neufeld E, Cassará A, Montanaro H, Kuster N, Kainz W (2016) Functionalized anatomical models for EM-neuron interaction modeling. Phys Med Biol 61(12):4390–4401
Neufeld E, Vogiatzis Oikonomidis I, Ida Iacono M, Angelone L, Kainz W, Kuster N (2016) Investigation of assumptions underlying current safety guidelines on EM-induced nerve stimulation. Phys Med Biol 61(12):4466–4478
Reilly J, Freeman V, Larkin W (1985) Sensory effects of transient electrical stimulation—evaluation with a neuroelectric model. IEEE Trans Biomed Eng 32(12):1001–1011
McNeal D (1976) Analysis of a model for excitation of myelinated nerve. IEEE Trans Biomed Eng 23(4):329–337
Santis V, Chen X, Laakso I, Hirata A (2015) An equivalent skin conductivity model for low-frequency magnetic field dosimetry. Biomed Phys Eng Express 1(1):1–10
Tilotta F, Lazaroo B, Laujac M, Gaudy J (2009) A study of the vascularization of the auricle by dissection and diaphanization. Surg Radiol Anat 31(4):259–265
Alvord L, Farmer B (1997) Anatomy and orientation of the human external ear. J Am Acad Audiol 8(6):383–390
Reilly J, Diamant A (2011) Electrostimulation-theory applications, and computational model. Artech House, Boston
Safi S, Ellrich J, Neuhuber W (2016) Myelinated axons in the auricular branch of the human vagus nerve. Anat Rec 299(9):1184–1191
Sandby-Møller J, Poulsen T, Wulf H (2003) Epidermal thickness at different body sites: relationship to age, gender, pigmentation, blood content, skin type and smoking habits. Acta Dermato-Venereol 83(6):410–413
Acknowledgements
The research was supported by COST Action BM1309 (COST EMF-MED) and the FWO G003415N project. E. Tanghe is a postdoctoral fellow of the Research Foundation-Flanders (FWO-V).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Samoudi, A.M., Kampusch, S., Tanghe, E. et al. Numerical modeling of percutaneous auricular vagus nerve stimulation: a realistic 3D model to evaluate sensitivity of neural activation to electrode position. Med Biol Eng Comput 55, 1763–1772 (2017). https://doi.org/10.1007/s11517-017-1629-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11517-017-1629-7