MEMS Based Diagnosis of Breast Cancer
Shobha Gupta1, Vivek Kant Jogi2
1Vivek Kant Jogi*, Associate Professor, Department of Electrical & Electronics, MATS University, Raipur, C.G., India.
2Shobha Gupta, Research Scholar, Department of Electrical & Electronics, MATS University, Raipur, C.G., India.
Manuscript received on January 16, 2020. | Revised Manuscript received on January 22, 2020. | Manuscript published on February 10, 2020. | PP: 2500-2503 | Volume-9 Issue-4, February 2020. | Retrieval Number: D1728029420/2020©BEIESP | DOI: 10.35940/ijitee.D1728.029420
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Based on the fact that the chemical, geometrical and other biophysical characteristics effect the electrical response of cells and tissues, a sensor is proposed which could be utilized for diagnosis and treatment of breast cancer as an economic and easy to use sensor. Endeavor has been made to model an in vitro sensor for early diagnosis of breast cancer considering sample data of normal breast cells (MCF-10A), less invasive cancer breast cells (MCF-7 & T47D) and highly invasive cancer breast cells (MDA-MB-231 & HS-578T). The simulation is done in COMSOL Multiphysics environment to find the impedance and capacitance of the cells with and without culture medium so as to characterize the types of cells. It is found that the impedance decreases sharply from 0.2 to 1 GHz and the normal breast cells could be distinguished from their cancer counter parts by comparing their electrical impedance and capacitance within the given frequency range. Apart from distinguishing normal breast cells from their cancer counterparts, the types of breast cancer cell types could also be determined by the differences in their frequency responses.
Keywords: Breast Cells, Capacitance, COMSOL, Impedance, MEMS.
Scope of the Article: Design and diagnosis