Hostname: page-component-586b7cd67f-rcrh6 Total loading time: 0 Render date: 2024-11-22T07:30:55.409Z Has data issue: false hasContentIssue false

Multi Frequency Assessment of the Electrical Impedance Myography Parameters on 3D Malignant Breast

Published online by Cambridge University Press:  26 December 2018

Md Nurul A. Tarek*
Affiliation:
Department of Electrical & Computer Engineering, Florida International University, Miami, FL33174, U.S.A.
Fahmida Alam
Affiliation:
Department of Electrical & Computer Engineering, Florida International University, Miami, FL33174, U.S.A.
Ahmed Hasnain Jalal
Affiliation:
Department of Electrical & Computer Engineering, Florida International University, Miami, FL33174, U.S.A.
Mohammad A. Ahad
Affiliation:
Department of Electrical & Computer Engineering, Georgia Southern University, Statesboro, GA30460, U.S.A.
*
Get access

Abstract

Electrical properties such as conductivity and permittivity of biological material have notable dependency on frequency. These frequency dependent changes in biomaterial properties can play a prominent role in impedance signature of Electrical Impedance Myography (EIM). EIM is a non-invasive painless four electrode measurement tool, measuring the impedance based on the response of the low amplitude alternating current. In this study, multifrequency Electrical impedance Myography assessment was performed using an applied range of frequencies for getting valuable insight of the biomaterials. In this paper, the objective of our study is to explore the effects of different sized malignant tumor in female breast tissue on the multi-frequency signature of EIM. In this study, a finite element model of a female breast has been developed based on electro-biophysical data for each malignant tissue within a frequency range of 2 GHz to 3 GHz and log frequency vs resistance and log frequency vs reactance of EIM have been analyzed for various sized tumor on breast. It is found that the slope of log reactance vs. frequency and resistance vs log frequency decrease with increasing tumor size. For instance, the percentage deviation of log reactance slope for 8 mm tumor and 6mm tumor from 2 mm (1mm radius) tumor size is 4.12% and 0.412% respectively. The study provides evidence that evaluation of the frequency dependent impedance data can provide rich assessment of the abnormal biological tissue.

Type
Articles
Copyright
Copyright © Materials Research Society 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

U.S. Breast Cancer Statistics: Available at: https://www.breastcancer.org/symptoms..(accessed 19 November 2017)Google Scholar
Chanmugam, A., Hatwar, R. and Herman, C., "Thermal analysis of cancerous breast model," ASME 2012 International Mechanical Engineering Congress and Exposition, (ASME 2012) pp. 135-143.CrossRefGoogle Scholar
Martellosio, A., Espin-Lopez, P. F., Pasian, M., Bozzi, M., Perregrini, L., Mazzanti, A., Svelto, F., Bellomi, M., Preda, L., Renne, G. and Summers, P. E., “Exposure limits and dielectric contrast for breast cancer tissues: Experimental results up to 50 GHz," Antennas and Propagation (EUCAP), (IEEE, 2017) pp. 667-671.Google Scholar
Zou, Y., and Guo, Z.,Med Eng. Phys. 25(2), 79-90, (2003).CrossRefGoogle Scholar
Rutkove, S. B., Muscle & Nerve: Official J. of the American Association of Electrodiagnostic Medicine 40(6), 936946, (2009).Google Scholar
Wang, L. L., Ahad, M., McEwan, A., Li, J., Jafarpoor, M. and Rutkove, S. B., IEEE Trans. on Biomedical Engineering 58(6) ,1585-1591(2011).CrossRefGoogle Scholar
Tarek, M.N.A., Jalal, A. H., Alam, F. and Ahad, M. A., SPIE Smart Biomedical and Physiological Sensor Technology XV 10662,106620I, (2018).Google Scholar
Ortega-Palacios, R., Leija, L., Vera, A. and Cepeda, M. F. J. "Measurement of breast-tumor phantom dielectric properties for microwave breast cancer treatment evaluation, “Electrical Engineering Computing Science and Automatic Control (CCE), (IEEE, 2010) pp. 216-219.Google Scholar
Gabriel, C., Gabriel, S. and Corthout, E., Phys. Med. & Biol. 41(11), 22312249 (1996).CrossRefGoogle Scholar
Gabriel, S., Lau, R. and Gabriel, C., Phys. Med. & Biol. 41(11), 2251(1996).CrossRefGoogle Scholar
Gabriel, C. and Paymen, A., Conn’s Hand. of Mod. for hum.agi. 7, 939-952 (2018).CrossRefGoogle Scholar
Akhtari-Zavare, M. and Latiff, L.A., Asian Pacific J. of Cancer Prevention 16(14), 55955597, (2015).CrossRefGoogle Scholar