14 May 2018 Detection of the breast cancer based on the electrical impedance myography parameters using finite element method
Author Affiliations +
Abstract
Electrical Impedance Myography (EIM) is a painless, non-invasive electrophysiological technique for the assessment of different disease status of the human body. In EIM, high frequency, low-intensity electrical current is injected via the surface electrode to the localized area and resulting voltage patterns are analyzed using the voltage sensing electrode to access three major parameters-resistance(R), reactance(X), and phase(θ). This method detects the abnormalities in the biological tissue based on differences in values of these three parameters between normal and malignant tissue. In this study, a finite element model of the human breast has been developed in an attempt to analyze the EIM parameters for the detection of malignant tissue. Simulations were carried out for a frequency range of 2 to 3 GHz and electrical properties of breast tissue were used. For example, at 2.45 GHz, normal breast tissue has a resistance of .961 Ω and a reactance of 4.462 Ω. At this particular frequency, malignant breast tissue with a tumor size of 7 mm had a resistance of .945 ohm and reactance of 4.365 ohm. The percentage deviation of the normal breast tissue from the 7mm malignant tissue for resistance and reactance is 1.665% and 2.174% respectively. This paper attempts to illustrate the behavior of EIM parameters for different size and location of the tumor in the breast tissue. The ultimate goal of the paper is to investigate EIM’s ability to detect early cancer cell in the breast tissue.
Conference Presentation
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Md Nurul A. Tarek, Ahmed H. Jalal, Fahmida Alam, Mohammad A. Ahad, "Detection of the breast cancer based on the electrical impedance myography parameters using finite element method", Proc. SPIE 10662, Smart Biomedical and Physiological Sensor Technology XV, 106620I (14 May 2018); doi: 10.1117/12.2307198; https://doi.org/10.1117/12.2307198
PROCEEDINGS
6 PAGES + PRESENTATION

SHARE
Back to Top