Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5006652 | Measurement | 2017 | 10 Pages |
Abstract
Previous studies have shown that dielectric properties of biological tissues can be imaged at high frequencies (50 MHz-20 GHz) to detect abnormalities such as tumors. While evidence suggests that imaging these properties at low frequencies (e.g. below 1 MHz) holds a good potential in medical applications, less research efforts have been dedicated to explore these properties at such frequencies for medical imaging. This study uses a recently developed technique to measure tissue dielectric properties of normal and corresponding cancerous tissue at low frequencies. This was accomplished by using a preclinical animal tumor model. To develop this animal model, human breast cancer cell line (MDA-MB-231) was injected into hind legs of severely compromised immunodeficient (SCID) mice. As a result, tumors were developed while they were permitted to grow to the size of 8-10 mm in 8 weeks. The electrical conductivity and permittivity (EC and EP) of the grown xenograft tumors and their surrounding normal tissue were measured at 100 Hz-1 MHz frequency using a measurement method which includes using a custom-made experimental setup in conjunction with an inverse finite element framework. Histological analysis was performed on the tumor and normal tissue specimens to assess differences in their micro-structure. Results indicated that both conductivity and permittivity of the tumors have significantly greater values than those of the surrounding normal tissue with average ratio values of 3.5:1 and 10.9:1 for the EC and EP, respectively. Results obtained in this study are consistent with micro-structural changes observed by histological assessment. The substantially high EP ratios measured in this study suggests that electrical permittivity at low frequencies can potentially be used as a powerful biomarker for the detection of breast malignancies.
Related Topics
Physical Sciences and Engineering
Engineering
Control and Systems Engineering
Authors
Seyyed M. Hesabgar, Ali Sadeghi-Naini, Gregory Czarnota, Abbas Samani,