2019-08-29
Electrically Small Magnetic Probe with PCA for Near-Field Microwave Breast Tumors Detection
By
Progress In Electromagnetics Research M, Vol. 84, 177-186, 2019
Abstract
In this paper, an electrically small magnetic probe combined with principal components analysis (PCA) technique for microwave breast cancer detection is presented. The proposed magnetic probe is designed as an electrically small square loop antenna integrated with a matching network operating at 528 MHz. The concept of the proposed microwave detection is based on the shift in the resonance frequency of the near-field magnetic probe due to the presence of a tumor. The proposed magnetic probe is highly sensitive in detecting any changes or abnormality in the dielectric properties of the female breast tissues. Detecting the existence of the breast tumors is expected by estimating the variations in the scattering parameters of the probe's response. The PCA is a feature extraction technique applied to accentuate the variance in the sensor responses for both healthy and tumorous cases. It is shown that when a numerical realistic breast phantom with and without tumor cells is placed close to the magnetic probe in the near-field region, the probe is capable of distinguishing between healthy and tumorous tissues. In addition, the probe can identify tumors with various sizes placed in a specific location within the breast. As a proof of concept, the magnetic probe was fabricated and used to detect a 9 mm metallic sphere buried at three different locations inside a lump of chicken meat, mimicking both normal and tumorous breast tissues, respectively. The CST numerical simulations and experimental results demonstrate that the presented technique is an emerging modality for detecting breast tumors through an inexpensive and portable way.
Citation
Maged A. Aldhaeebi, Thamer S. Almoneef, Hussein Attia, and Omar M. Ramahi, "Electrically Small Magnetic Probe with PCA for Near-Field Microwave Breast Tumors Detection," Progress In Electromagnetics Research M, Vol. 84, 177-186, 2019.
doi:10.2528/PIERM19061303
References

1. Society, A. C., "Cancer facts and figures 2019 @ONLINE,", [Online]. Available: https://www.cancer.org/content/dam/cancer-org/research/cancer-facts-andstatistics/annual-cancer-facts-and-figures/2019/cancer-facts-and-figures-2019.pdf, 2019.
doi:10.1109/TEMC.2019.2896519        Google Scholar

2. Attaran, A., W. B. Handler, and B. A. Chronik, "2 mm radius loop antenna and linear active balun for near field measurement of magnetic field in MRI-conditional testing of medical devices," IEEE Transactions on Electromagnetic Compatibility, 1-8, 2019.
doi:10.1109/ICEAA.2017.8065655        Google Scholar

3. Radder, J., M. Woo, P. Van de Moortele, G. Metzger, A. Ertürk, J. Strupp, K. Ugurbil, and G. Adriany, "Optimization and simulation of a 16-channel loop and dipole array for head MRI applications at 10.5 tesla," 2017 International Conference on Electromagnetics in Advanced Applications (ICEAA), 1828-1831, Sep. 2017.
doi:10.3390/s17071572        Google Scholar

4. Wang, L., "Early diagnosis of breast cancer," Sensors, Vol. 17, No. 7, 1572, 2017.
doi:10.1049/iet-map.2017.0599        Google Scholar

5. Obermeier, R. and J. A. Martinez-Lorenzo, "Compressive sensing unmixing algorithm for breast cancer detection," IET Microwaves, Antennas & Propagation, Vol. 12, No. 4, 533-541, 2018.
doi:10.1109/TBME.2018.2807799        Google Scholar

6. Yousefnia, M., A. Ebrahimzadeh, M. Dehmollaian, and A. Madannejad, "A time-reversal imaging system for breast screening: Theory and initial phantom results," IEEE Transactions on Biomedical Engineering, Vol. 65, No. 11, 2542-2551, 2018.
doi:10.1007/978-3-319-27866-7        Google Scholar

7. Conceição, R. C., J. J. Mohr, and M. O'Halloran, An Introduction to Microwave Imaging for Breast Cancer Detection, Springer, 2016.
doi:10.1109/6668.990683

8. Fear, E. C., S. C. Hagness, P. M. Meaney, M. Okoniewski, and M. A. Stuchly, "Enhancing breast tumor detection with near-field imaging," IEEE Microwave magazine, Vol. 3, No. 1, 48-56, 2002.
doi:10.1109/22.883861        Google Scholar

9. Meaney, P. M., M. W. Fanning, D. Li, S. P. Poplack, and K. D. Paulsen, "A clinical prototype for active microwave imaging of the breast," IEEE Transactions on Microwave Theory and Techniques, Vol. 48, No. 11, 1841-1853, 2000.
doi:10.1163/156939304774113089        Google Scholar

10. Caorsi, S., M. Donelli, A. Lommi, and A. Massa, "Location and imaging of two-dimensional scatterers by using a particle swarm algorithm," Journal of Electromagnetic Waves and Applications, Vol. 18, No. 4, 481-494, 2004.
doi:10.2528/PIERM11040903        Google Scholar

11. Donelli, M., I. J. Craddock, D. Gibbins, and M. Sarafianou, "A three-dimensional time domain microwave imaging method for breast cancer detection based on an evolutionary algorithm," Progress In Electromagnetics Research, Vol. 18, 179-195, 2011.
doi:10.4218/etrij.10.0109.0626        Google Scholar

12. Son, S.-H., N. Simonov, H.-J. Kim, J.-M. Lee, and S.-I. Jeon, "Preclinical prototype development of a microwave tomography system for breast cancer detection," ETRI Journal, Vol. 32, No. 6, 901-910, 2010.        Google Scholar

13. Bridges, J. E., "Non-invasive system for breast cancer detection,", US Patent 5,704, 355, Jan. 6, 1998.
doi:10.1109/TBME.2002.800759        Google Scholar

14. Fear, E. C., X. Li, S. C. Hagness, and M. A. Stuchly, "Confocal microwave imaging for breast cancer detection: Localization of tumors in three dimensions," IEEE Transactions on Biomedical Engineering, Vol. 49, No. 8, 812-822, 2002.
doi:10.2528/PIERM11061206        Google Scholar

15. Donelli, M., "A rescue radar system for the detection of victims trapped under rubble based on the independent component analysis algorithm," Progress In Electromagnetics Research, Vol. 19, 173-181, 2011.
doi:10.3390/s18020655        Google Scholar

16. Wang, L., "Microwave sensors for breast cancer detection," Sensors, Vol. 18, No. 2, 655, 2018.        Google Scholar

17. Klemm, M., I. Craddock, J. Leendertz, A. Preece, and R. Benjamin, "Experimental and clinical results of breast cancer detection using uwb microwave radar," Antennas and Propagation Society International Symposium, 2008. AP-S 2008. IEEE, 1-4, 2008.
doi:10.1109/RBME.2011.2169780        Google Scholar

18. Hassan, A. M. and M. El-Shenawee, "Review of electromagnetic techniques for breast cancer detection," IEEE Reviews in Biomedical Engineering, Vol. 4, 103-118, 2011.
doi:10.1038/s41598-018-31046-9        Google Scholar

19. Aldhaeebi, M. A., T. S. Almoneef, A. Ali, Z. Ren, and O. M. Ramahi, "Near field breast tumor detection using ultra-narrow band probe with machine learning techniques," Scientific Reports, Vol. 8, No. 1, 12607, 2018.        Google Scholar

20. Bourqui, J., J. M. Sill, and E. C. Fear, "A prototype system for measuring microwave frequency reflections from the breast," Journal of Biomedical Imaging, Vol. 2012, 9, 2012.        Google Scholar

21. Gazhonova, V., 3D Automated Breast Volume Sonography: A Practical Guide, Springer, 2016.
doi:10.1016/j.mri.2012.10.022

22. Chen, J.-H., S. Chan, D.-C. Yeh, P. T. Fwu, M. Lin, and M.-Y. Su, "Response of bilateral breasts to the endogenous hormonal uctuation in a menstrual cycle evaluated using 3d mri," Magnetic Resonance Imaging, Vol. 31, No. 4, 538-544, 2013.        Google Scholar

23. CST "Computer simulation technology. cst computer simulation technology ag@ONLINE,", [Online]. Available: http://www.CST.com, Sep. 2017.        Google Scholar

24. UWCEM "Breast phantom repository@ONLINE,", [Online]. Available: http://uwcem.ece.wisc.edu/phantomRepository.html, Aug. 2017.        Google Scholar

25. Zastrow, E., S. Davis, M. Lazebnik, F. Kelcz, B. van Veem, and S. Hagness, "Database of 3D grid-based numerical breast phantoms for use in computational electromagnetics simulations,", [Online]. Available: https://uwcem.ece.wisc.edu/MRIdatabase/InstructionManual.pdf, 2008.
doi:10.1109/TBME.2008.2002130        Google Scholar

26. Zastrow, E., S. K. Davis, M. Lazebnik, F. Kelcz, B. D. Van Veen, and S. C. Hagness, "Development of anatomically realistic numerical breast phantoms with accurate dielectric properties for modeling microwave interactions with the human breast," IEEE Transactions on Biomedical Engineering, Vol. 55, No. 12, 2792-2800, 2008.
doi:10.1088/0031-9155/52/20/002        Google Scholar

27. Lazebnik, M., D. Popovic, L. McCartney, C. B. Watkins, M. J. Lindstrom, J. Harter, S. Sewall, T. Ogilvie, A. Magliocco, T. M. Breslin, et al. "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, Vol. 52, No. 20, 6093, 2007.        Google Scholar

28. Richardson, M., "Principal component analysis,", URL: http://people.maths.ox.ac.uk/richardsonm/SignalProcPCA.pdf (last access: 3.5. 2013), Aleš Hladnik Dr., Ass. Prof., Chair of Information and Graphic Arts Technology, Faculty of Natural Sciences and Engineering, University of Ljubljana, Slovenia, ales.hladnik@ntf. uni-lj.si, 2009.
doi:10.1002/wics.101        Google Scholar

29. Abdi, H. and L. J. Williams, "Principal component analysis," Wiley Interdisciplinary Reviews: Computational Statistics, Vol. 2, No. 4, 433-459, 2010.
doi:10.1098/rsta.2015.0202        Google Scholar

30. Jolliffe, I. T. and J. Cadima, "Principal component analysis: A review and recent developments," Phil. Trans. R. Soc. A, Vol. 374, No. 2065, 20150202, 2016.        Google Scholar