Abstract
The electrode structure in micro-electrical impedance tomography (MEIT) highly influences the measurement sensitivity and therefore the reconstructed image quality. Hence, optimizing the electrode structure leads to the improvement of image quality in the reconstruction procedure. Although there have been many investigations on electrical impedance tomography (EIT) electrodes, there is no comprehensive study on their influence on images of the peripheral nerve. In this paper, we present a simulation method to study the effects of the electrode structure in the density measurement system of the peripheral nerve based on MEIT. The influence of the electrode structure such as dimensions, material and the number of electrodes and also the recognition feature of different radii of fascicle and different locations of fascicles has been studied. Data were reconstructed from the real and imaginary parts of complex conductivity data, respectively. It has been shown that the material of the electrodes had no effect on the reconstructed images, while the dimensions of the electrodes significantly affected the image sensitivity and thus the image quality. An increase in the number of electrodes increased the amount of data and information content. However, as the number of electrodes increased due to the given perimeter of the peripheral nerve, the area of the electrodes was reduced. This reduction affects the reconstructed image quality. The real and imaginary parts of the data were separately reconstructed for each case. Although, in real EIT systems, the reconstructed images using the real part of the signal have a better signal-to-noise ratio (SNR), this study proved that for a density measuring system of the peripheral nerve, the reconstructed images using the imaginary part of the signal had better quality. This simulation study proposes the effects of the electrode size and material and obtained spatial resolution that was high enough to reconstruct fascicles in a peripheral nerve.
Research funding: Authors state no funding involved.
Conflict of interest: Authors state no conflict of interest.
References
[1] Adler A, Lionheart WR. Minimizing EIT image artefacts from mesh variability in finite element models. Physiol Meas 2011; 32: 823.10.1088/0967-3334/32/7/S07Search in Google Scholar PubMed
[2] Bohnert J. Effects of time-varying magnetic fields in the frequency range 1 khz to 100 khz upon the human body: Numerical studies and stimulation experiment. Vol. 15. Karlsruhe, Germany: KIT Scientific Publishing 2014.Search in Google Scholar
[3] Brown BH. Medical impedance tomography and process impedance tomography: a brief review. Meas Sci Technol 2001; 12: 991.10.1088/0957-0233/12/8/301Search in Google Scholar
[4] Brown B, Barber D, Seagar A. Applied potential tomography: possible clinical applications. Clin Phys Physiol Meas 1985; 6: 109.10.1088/0143-0815/6/2/002Search in Google Scholar PubMed
[5] Choi AQ, Cavanaugh JK, Durand DM. Selectivity of multiple-contact nerve cuff electrodes: a simulation analysis. IEEE Trans Biomed Eng 2001; 48: 165–172.10.1109/10.909637Search in Google Scholar PubMed
[6] Daube JR, Rubin DI. Nerve conduction studies. In: Aminoff, Michael J, editor. Aminoff’s Electrodiagnosis in Clinical Neurology. Amsterdam, the Netherlands: Elsevier Health Sciences 2012: 289–325.10.1016/B978-1-4557-0308-1.00013-3Search in Google Scholar
[7] Dharia S, Ayliffe HE, Rabbitt RD. Single cell electric impedance topography: Mapping membrane capacitance. Lab Chip 2009; 9: 3370–3377.10.1039/b912881fSearch in Google Scholar PubMed PubMed Central
[8] Geddes L, Baker L. The specific resistance of biological material –a compendium of data for the biomedical engineer and physiologist. Med Biol Eng 1967; 5: 271–293.10.1007/BF02474537Search in Google Scholar PubMed
[9] Golombeck M-A, Riedel C, Dössel O. Calculation of the dielectric properties of biological tissue using simple models of cell patches. Biomed Eng 2002; 47: 253–256.10.1515/bmte.2002.47.s1a.253Search in Google Scholar PubMed
[10] Goodall EV, Kosterman L, Holsheimer J, Struijk JJ. Modeling study of activation and propagation delays during stimulation of peripheral nerve fibers with a tripolar cuff electrode. IEEE Trans Rehabil Eng 1995; 3: 272–282.10.1109/86.413200Search in Google Scholar
[11] Griffin JW, Hogan MV, Chhabra AB, Deal DN. Peripheral nerve repair and reconstruction. J Bone Joint Surg 2013; 95: 2144–2151.10.2106/JBJS.L.00704Search in Google Scholar PubMed
[12] Holder D, Gardner-Medwin A. Some possible neurological applications of applied potential tomography. Clin Phys Physiol Meas 1988; 9:111.10.1088/0143-0815/9/4A/019Search in Google Scholar
[13] Ichihara S, Inada Y, Nakamura T. Artificial nerve tubes and their application for repair of peripheral nerve injury: an update of current concepts. Injury 2008; 39: 29–39.10.1016/j.injury.2008.08.029Search in Google Scholar PubMed
[14] Jiang X, Lim SH, Mao H-Q, Chew SY. Current applications and future perspectives of artificial nerve conduits. Exp Neurol 2010; 223: 86–101.10.1016/j.expneurol.2009.09.009Search in Google Scholar PubMed
[15] Kaufmann S, Moray T, Latif A, Saputra W, Henschel J, Ryschka M. A micro electrical impedance tomography system for vessel studies. World Congress on Medical Physics and Biomedical Engineering May 26–31, 2012, Beijing, China, 2013, pp. 964–966.10.1007/978-3-642-29305-4_253Search in Google Scholar
[16] Linderholm P, Marescot L, Loke MH, Renaud P. Cell culture imaging using microimpedance tomography. IEEE Trans Biomed Eng 2008; 55: 138–146.10.1109/TBME.2007.910649Search in Google Scholar PubMed
[17] Lundborg G, Gelberman RH, Longo FM, Powell HC, Varon S. In vivo regeneration of cut nerves encased in silicone tubes. J Neuropathol Exp Neurol 1982; 41: 412–422.10.1097/00005072-198207000-00004Search in Google Scholar PubMed
[18] Mimura T, Dezawa M, Kanno H, Sawada H, Yamamoto I. Peripheral nerve regeneration by transplantation of bone marrow stromal cell-derived Schwann cells in adult rats. J Neurosurg 2004; 101: 806–812.10.3171/jns.2004.101.5.0806Search in Google Scholar PubMed
[19] Negredo P, Castro J, Lago N, Navarro X, Avendano C. Differential growth of axons from sensory and motor neurons through a regenerative electrode: a stereological, retrograde tracer, and functional study in the rat. Neuroscience 2004; 128: 605–615.10.1016/j.neuroscience.2004.07.017Search in Google Scholar PubMed
[20] Noble J, Munro CA, Prasad VS, Midha R. Analysis of upper and lower extremity peripheral nerve injuries in a population of patients with multiple injuries. J Trauma 1998; 45: 116–122.10.1097/00005373-199807000-00025Search in Google Scholar PubMed
[21] Perez-Orive J; Durund D. Modeling study of peripheral nerve recording selectivity. IEEE Trans Rehabil Eng 2000; 8: 320–329.10.1109/86.867874Search in Google Scholar PubMed
[22] Pfister BJ, Gordon T, Loverde JR, Kochar AS, Mackinnon SE, Cullen DK. Biomedical engineering strategies for peripheral nerve repair: surgical applications, state of the art, and future challenges. Crit Rev Biomed Eng 2011; 39: 81–124.10.1615/CritRevBiomedEng.v39.i2.20Search in Google Scholar
[23] Qin J, Wang L, Sun Y, et al. Concentrated growth factor increases Schwann cell proliferation and neurotrophic factor secretion and promotes functional nerve recovery in vivo. Int J Mol Med 2016; 37: 493–500.10.3892/ijmm.2015.2438Search in Google Scholar
[24] Ranck JB, BeMent SL. The specific impedance of the dorsal columns of cat: an anisotropic medium. Exp Neurol 1965; 11: 451–463.10.1016/0014-4886(65)90059-2Search in Google Scholar
[25] Rieger R, Taylor J, Demosthenous A, Donaldson N, Langlois PJ. Design of a low-noise preamplifier for nerve cuff electrode recording. IEEE J Solid-State Circ 2003; 38: 1373–1379.10.1109/ISCAS.2002.1010673Search in Google Scholar
[26] Schmalbruch H. Fiber composition of the rat sciatic nerve. Anat Rec 1986; 215: 71–81.10.1002/ar.1092150111Search in Google Scholar PubMed
[27] Schuettler M, Ulloa M, Ordonez JS, Stieglitz T. Laser-fabrication of neural electrode arrays with sputtered iridium oxide film. in Neural Engineering (NER), 2013 6th International IEEE/EMBS Conference on, 2013, pp. 1171–1173.10.1109/NER.2013.6696147Search in Google Scholar
[28] Seagar A, Barber D, Brown B. Electrical impedance imaging. Piscataway, NJ, USA: IEE Proceedings A (Physical Science, Measurement and Instrumentation, Management and Education, Reviews) 1987; 134: 201–210.10.1049/ip-a-1.1987.0028Search in Google Scholar
[29] Seggio A, Narayanaswamy A, Roysam B, Thompson D. Self-aligned Schwann cell monolayers demonstrate an inherent ability to direct neurite outgrowth. J Neural Eng 2010; 7: 046001.10.1088/1741-2560/7/4/046001Search in Google Scholar PubMed
[30] Tagliafico A, Tagliafico G, Martinoli C. Nerve density: a new parameter to evaluate peripheral nerve pathology on ultrasound. Preliminary study. Ultrasound Med Biol 2010; 36: 1588–1593.10.1016/j.ultrasmedbio.2010.07.009Search in Google Scholar PubMed
[31] van Beek WM, Mandel M. Static relative permittivity of some electrolyte solutions in water and methanol. J Chem Soc Faraday Trans 1 1978; 74: 2339–2351.10.1039/f19787402339Search in Google Scholar
[32] Wang H, Wang C, Yin W. Optimum design of the structure of the electrode for a medical EIT system. Meas Sci Technol 2001; 12: 1020.10.1088/0957-0233/12/8/305Search in Google Scholar
[33] Wang Z, Bovik AC, Sheikh HR, Simoncelli EP. Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 2004; 13: 600–612.10.1109/TIP.2003.819861Search in Google Scholar
[34] Weerasuriya A, Spangler RA, Rapoport SI, Taylor R. AC impedance of the perineurium of the frog sciatic nerve. Biophys J 1984; 46: 167.10.1016/S0006-3495(84)84009-6Search in Google Scholar
[35] Willand MP, Nguyen M-A, Borschel GH, Gordon T. Electrical stimulation to promote peripheral nerve regeneration. Neurorehabil Neural Repair 2016; 30: 490–496.10.1177/1545968315604399Search in Google Scholar PubMed
[36] Yan W, Hong S, Chaoshi R. Optimum design of electrode structure and parameters in electrical impedance tomography. Physiol Meas 2006; 27: 291.10.1088/0967-3334/27/3/007Search in Google Scholar PubMed
[37] Zariffa J, Popovic MR. Localization of active pathways in peripheral nerves: a simulation study. IEEE Trans Neural Sys Rehabil Eng 2009; 17: 53–62.10.1109/TNSRE.2008.2010475Search in Google Scholar PubMed
[38] Zarifi MH, Frounchi J, Jahed N, Tinati M. Finite-element analysis of platinum-based cone microelectrodes for implantable neural recording. in Neural Engineering, 2009. NER’09. 4th International IEEE/EMBS Conference on, 2009, pp. 395–398.10.1109/NER.2009.5109316Search in Google Scholar
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