From narrow-band to ultra-wide-band microwave sensors in direct skin contact for breast cancer detection
- 93 Downloads
In this paper, the design and test of different microwave antennas and sensors for breast cancer detection are presented. The sensors are designed and optimized to be used in direct skin contact, and for this purpose a specific breast phantom model is proposed. First, a miniaturized microstrip back-cavity Hilbert fractal antenna, operating in the ISM band (2.4–2.5 GHz), was designed. Then, this antenna was used to investigate the possibility of detecting the presence of breast tumors based on a narrowband frequency method that monitors the shift of the antenna frequency response. The antenna prototype was fabricated and tested in real in vivo measurement conditions on two different patients diagnosed with breast cancer. Measurement results have led after a comparison with the retro-simulation results of the structure to a more realistic breast model and to draw the limitations of this narrowband frequency method. As a time domain study seems to be more relevant, an UWB monopole antenna of dimensions 3 cm × 3 cm, to be used in direct contact with the breast model was designed. This antenna was optimized to both enhance the antenna/human body matching and to maximize the transfer of energy into the breast phantom by using a cavity, increasing by this way the detection potential. In order to improve the sensor’s directivity and enhance the electromagnetic field level inside the breast, a balanced antipodal Vivaldi antenna was also designed and optimized for a direct breast contact to operate in the 3.1–10.6 GHz band. A mono static and a bi static study in the time domain are finally proposed to investigate the presence of the tumor.
KeywordsBreast tumor Back-cavity Hilbert fractal antenna In vivo and ex vivo measurements UWB antenna Dispersive breast model BAVA
The authors would like to thank Mr. Alexis Chevalier from the lab-STICC UBO for his help in tissue permittivity measurements and also Dr Pierre-François Dupré from the CHRU of Brest.
- 1.Sajjadieh, M., Foroozan, F., & Asif, A. (2009). Breast cancer detection using time reversal signal processing. In IEEE 13th international multi-optic conference, INMIC.Google Scholar
- 2.Hossain, M. D., & Mohan, A. S. (2013). Breast cancer detection in highly dense numerical breast phantoms using time reversal. In IEEE electromagnetics in advanced applications (ICEAA).Google Scholar
- 4.Hossain, M. D., & Mohan, A. S. (2012). Breast cancer localization in three dimensions using time reversal DORT method. In IEEE antennas and propagation (ISAP).Google Scholar
- 7.Lazebnik, M., Popovic, D., McCartney, L., Watkins, C. B., Lindstrom, M. J., Harter, J., et al. (2007). A large-scale study of the ultrawideband microwave dielectric properties of normal, benign and malignant breast tissues obtained from cancer surgeries. Physics in Medicine and Biology, 52(20), 6093.CrossRefGoogle Scholar
- 8.Larsen, L., & Jacobi, J. (1986). Medical applications of microwave imaging (pp. 148–212). New York: IEEE press.Google Scholar
- 9.Karli, R., & Ammor, H. (2014). Evaluation of a microstrip patch antenna for breast tumor detection. International Journal of Innovation and Scientific Research, 5(2), 128–135.Google Scholar
- 11.Sanpanich, A., Phasukkit, P., Pairoch, S., Sueaseenak, D., Kajornpreedanon, Y., Hamamoto, K., & Pintavirooj C. (2012). A basic investigation of cancerous breast microwave ablation using opened-tip applicator and ex vivo experiment. In Proceedings of 31th JSST, Kobe.Google Scholar
- 12.Stang, J. (2008). A 3D active microwave imaging system for breast cancer screening. Ph.D. dissertation, Department of Electrical and Computer Engineering, Duke University, Durham, NC.Google Scholar
- 13.Katbay, Z., Sadek, S., Le Roy, M., Lababidi, R., & Perennec, A. (2016). Microstrip back-cavity Hilbert fractal antenna for experimental detection of breast tumors. In IEEE MECAP conference.Google Scholar
- 14.Shahira Banu, M. A., Vanaja, S., & Poonguzhali, S. (2013). UWB microwave detection of breast cancer using SAR. 978-1-4673-6150-7/13/IEEE.Google Scholar
- 16.Tuovinen, T., Kumpuniemi, T., Yazdandoost, K. Y., Hämäläinen, M., & Iinatti, J. (2013). Effect of the antenna-human body distance on the antenna matching in UWB WBAN applications. In 7th international symposium on medical information and communication technology (ISMICT).Google Scholar
- 19.Zastrow, E., Davis, S. K., Lazebnik, M., Kelcz, F., Van Veen, B. D., & Hagness, S. C. (2008). Development of anatomically realistic numerical breast phantoms with accurate dielectric properties for modeling microwave interactions with the human breast. IEEE Transactions on Biomedical Engineering, 55(12), 2792–2800.CrossRefGoogle Scholar
- 20.Porter, E., Fakhoury, J., Oprisor, R., Coates, M., & Popović, M. (2010). Improved tissue phantoms for experimental validation of microwave breast cancer detection. In Proceedings of the fourth European conference on antennas and propagation (pp. 1–5).Google Scholar
- 21.Lazebnik, M., Okoniewski, M., Booske, J. H., & Hagness, S. C. (2007). Highly accurate debye models for normal and malignant breast tissue dielectric properties at microwave frequencies. IEEE MWCL, 17(12), 822–824.Google Scholar
- 22.Zastrow, E., Davis, S. K., Lazebnik, M., Kelcz, F., Van Veen, B. D., & Hagness, S. C. (2008). Database of 3D grid-based numerical breast phantoms for use in computational electromagnetics simulations. http://uwcem.ece.wisc.edu/home.htm.
- 24.Zhang, H. (2014). Microwave imaging for ultra-wideband antenna based cancer detection. Edinburgh: University of Edinburgh.Google Scholar
- 25.Karli, R., & Ammor, H. (2014). Evaluation of a microstrip patch antenna for breast tumor detection. International Journal of Innovation and Scientific Research, 5(2), 128–135.Google Scholar
- 27.Katbay, Z., Sadek, S., Le Roy, M., Lababidi, R., & Perennec, A. (2017). A UWB antenna in direct breast contact for cancer detection. In IEEE SENSET conference.Google Scholar
- 32.Li, Q., Xiao, X., Song, H., & Liang, W. (2014). Tumor response extraction based on ensemble empirical mode decomposition for early breast cancer detection by UWB. In IEEE.Google Scholar