volume | PIER Journals

Abstract

Microwave Imaging is one of the most promising emerging imaging technologies for breast cancer detection, and exploits the dielectric contrast between normal and malignant breast tissue at microwave frequencies. The development of many UWB Radar imaging approaches requires the use of accurate numerical models for the propagation and scattering of microwave signals within the breast. The Finite-Difference Time-Domain (FDTD) method is the most commonly used numerical modelling technique used to model the propagation of Electromagnetic (EM) waves in biological tissue. However, it is critical that an FDTD model accurately represents the dielectric properties of the constituent tissues, including tumour tissues, and the highly correlated distribution of these tissues within the breast. This paper presents a comprehensive review of the latest findings regarding dielectric properties of normal and cancerous breast tissue, and the heterogeneity of normal breast tissue. Furthermore, existing FDTD models of the breast described in the literature are examined.

1. American Cancer Society Cancer Facts & Figures, 2008.

2. Nass, S. L., et al. Mammography and Beyond: Developing Technologies for the Early Detection of Breast Cancer, National Academy Press, 2001.

3. Lehman, C. D., et al. "MRI evaluation of the contralateral breast in women with recently diagnosed breast cancer," The New England Journal of Medicine, Vol. 356, No. 13, 1295-1303, 2007. Google Scholar

4. Viehweg, P., et al. "Contrast-enhanced magnetic resonance imaging of the breast: interpretation guidelines," Top Magn Reson Imaging, Vol. 9, No. 1, 17-43, 1998. Google Scholar

5. Maestro, C., et al. "Systematic ultrasonography in asymptomatic dense breasts ," Eur. J. Radiol., Vol. 26, No. 3, 254-256, 1998. Google Scholar

6. Wang, L., et al. "Microwave-induced acoustic imaging of biological tissues," Rev. Sci. Instrum, Vol. 70, No. 9, 3744-3748, 1991. Google Scholar

7. Souvorov, A. E., et al. "Two-dimensional computer analysis of a microwave °at antenna array for breast cancer tomography," IEEE Trans. on Microwave Theory and Tech., Vol. 48, No. 8, 1413-1415, 2000. Google Scholar

8. Bulyshev, A. E., et al. "Computational modeling of three-dimensional microwave tomography of breast cancer," IEEE Trans. on Biomed. Eng., Vol. 48, No. 9, 1053-1056, 2001. Google Scholar

9. Meaney, P. M., et al. "A clinical prototype for active microwave imaging of the breast," IEEE Trans. on Microwave Theory and Tech., Vol. 48, No. 11, 1841-1853, 2000. Google Scholar

10. Meaney, P. M., et al. "Nonactive antenna compensation for fixed-array microwave imaging: Part II|Imaging results," IEEE Trans. on Med. Imag., Vol. 18, No. 6, 508-518, 1999. Google Scholar

11. Liu, Q. H., et al. "Active microwave imaging I|2-D forward and inverse scattering methods," IEEE Trans. on Microwave Theory and Tech., Vol. 50, No. 1, 123-133, 2002. Google Scholar

12. Hagness, S. C., et al. "Two dimensional FDTD analysis of a pulsed microwave confocal system for breast cancer detection: Fixed-focus and antenna-array sensors," IEEE Trans. on Biomed. Eng., Vol. 45, 1470-1479, 1998. Google Scholar

13. Bindu, G., et al. "Active microwave imaging for breast cancer detection," Progress In Electromagnetics Research, Vol. 58, 149-169, 2006. Google Scholar

14. Sha, L., et al. "A review of dielectric properties of normal and malignant breast tissue," IEEE SoutheastCon, 457-462, 2002. Google Scholar

15. Lazebnik, M., et al. "A large-scale study of the ultrawideband microwave dielectric properties of normal breast tissue obtained from reduction surgeries," Phys. Med. Biol., Vol. 52, 2637-2656, 2007. Google Scholar

16. Bland, K. I., et al. The Breast: Comprehensive Management of Benign and Malignant Disorders, Vol. 1, 2004.

17. Jossinet, J., "The impedivity of freshly excised human breast tissue ," Physiol. Meas., Vol. 19, No. 1, 61-75, 1998. Google Scholar

18. Hagness, S. C., et al. "Three-dimensional FDTD analysis of a pulsed microwave confocal system for breast cancer detection: design of an antenna-array element," IEEE Trans. on Antennas and Propagat., Vol. 47, No. 5, 783-791, 1999. Google Scholar

19. Choi, J. W., et al. "Microwave detection of metastasized breast cancer cells in the lymph node; potential application for sentinel lymphadenectomy," Breast Cancer Res. and Treat., Vol. 86, 107-115, 2004. Google Scholar

20. Gorey, T., et al. "The Breast in Health and Illness --- An Information Guide for Patients and Their Carers (DVD)," AstraZeneca Pharmaceuticals (Irl.) Ltd., 2006. Google Scholar

21. CancerHelp UK Breast Cancer Section Overview, 2007.
doi:http://www.cancerhelp.org.uk/help/default.asp?page=3270

22. Enzinger, F. M., et al. "Soft Tissue Tumors," Mosby, Year Book, Inc.,, 1995. Google Scholar

23. Dixon, J. M., ABC of Breast Diseases, 3rd, Blackwell Publishing Ltd., 2006.

24. CancerHelp UK About Cancer, 2007.
doi:http://www.cancerhelp.org.uk/help/default.asp?page=85

25. Cameron, I. L., et al. The Transformed Cell, Cell Biology, A Series of Monographs, Academic Press, 1981.

26. Bridges, J. E., et al. Microwave Discrimination between Malignant and Benign Breast Tumours, Patent No.: US 6,431,550 B1, Assignee: L.L.C. Interstitial, 2002.

27. Malich, A., et al. "The impact of lesion vascularisation on tumours detection by electrical impedance scanning at 200 Hz," Biomed Imaging Interv J., 2007. Google Scholar

28. Joines, W. T., "Frequency-dependent absorption of electromagnetic energy in biological tissue," IEEE Trans. on Biomed. Eng., Vol. 31, No. 1, 17-20, 1984. Google Scholar

29. Pethig, R., "Dielectric properties of biological materials: Biophysical and medical applications," IEEE Trans. on Electr. Insul., Vol. E1-19, No. 5, 453-474, 1984. Google Scholar

30. Davis, S. K., et al. "Breast tumor characterization based on ultrawideband microwave backscatter," IEEE Trans. on Biomed. Eng., Vol. 55, No. 1, 237-246, 2008. Google Scholar

31. Rangayyan, R. M., et al. "Measures of acutance and shape for classi¯cation of breast tumors," IEEE Trans. on Med. Imag., Vol. 16, No. 6, 799-810, 1997. Google Scholar

32. Bindu, G., et al. "Characterization of benign and malignant breast tissues using 2-D microwave tomographic imaging," Microw. Opt. Technol. Lett., Vol. 49, 2341-2345, 2007. Google Scholar

33. Nguyen, T. M., et al., "Shape analysis of breast masses in mammograms via the fractial dimension," Engineering in Medicine and Biology 27th Annual Conference, 3210-3213, 2005. Google Scholar

34. Guliato, , D., et al., "Polygonal modeling of contours of breast tumors with the preservation of spicules," IEEE Trans. on Biomed. Eng., Vol. 55, No. 1, 14-20, 2008. Google Scholar

35. O'Halloran, , M., et al., "FDTD modeling of the breast: A review," Progress In Electromagnetics Research B, Vol. 18, 1-24, 2009. Google Scholar

36. Joines, , W. T., et al., "The measured electrical properties of normal and malignant human tissues from 50 to 900 MHz," Med. Phys., Vol. 21 , No. 4, 1994. Google Scholar

37. Lazebnik, , M., et al., "A large-scale study of the ultrawideband microwave dielectric properties of normal, benign and malignant breast tissues obtained from cancer surgeries," Phys. Med. Biol., Vol. 52, 6093-6115, 2007. Google Scholar

38. Campbell, , A. M., et al., "dielectric properties of female human breast tissue measured in vitro at 3.2 GHz," breast tissue measured in vitro at 3.2 GHz, Vol. 37, No. 1, 193-210, 1992. Google Scholar

39. Chaudhary, S. S., et al., "Dielectric properties of normal and malignant human breast tissues at radiowave and microwave frequencies," Indian J. Biochem. Biophys., Vol. 21, 76-79, 1984. Google Scholar

40. Surowiec, , A. J., et al., "Dielectric properties of breast carcinoma and the surrounding tissues," IEEE Trans. on Biomed. Eng., Vol. 35, No. 4, 257-263, 1988. Google Scholar

41. Halter, , R. J., et al., "The correlation of in vivo and ex vivo tissue dielectric properties to validate electromagnetic breast imaging: Initial clinical experience," Physiol. Meas., Vol. 30, No. 6, S121-S136, 2009. Google Scholar

42. Jossinet, J., et al., "A review of parameters for the bioelectrical characterization of breast tissue," Ann. N.Y. Acad. Sci.,, Vol. 873, 30-41, 1999. Google Scholar

43. Haemmerich, , D., et al. "Changes in electrical resistivity of swine liver after occlusion and postmortem," Med. Biol. Eng. Comput., Vol. 40, No. 1, 29-33, 2002. Google Scholar

44. Chen, , Y., et al. "Application of the mimo radar technique for lesion classi¯cation in UWB breast cancer detection," 17th EUSIPCO, 759-763, 2009. Google Scholar

45. Chen, Y., et al., "Effect of lesion morphology on microwave signature in ultra-wideband breast imaging: A preliminary two-dimensional investigation," IEEE Antennas and Propagation Society International Symposium, 2168-2171, 2007. Google Scholar

46. Chen, , Y., et al., "Effect of lesion morphology on microwave signature in 2-D ultra-wideband breast imaging," IEEE Trans. on Biomed. Eng., Vol. 55, No. 8, 2011-2021, 2008. Google Scholar

47. Chen, Y., et al., "Multiple-input multiple-output radar for lesion classi¯cation in ultrawideband breast imaging," IEEE Journal of Selected Topics in Signal Processing, Vol. 4, No. 1, 187-201, 2010. Google Scholar

48. Chen, , Y., et al., "Feasibility study of lesion classification via contrast-agent-aided uwb breast imaging," IEEE Trans. on Biomed. Eng., Vol. 57, No. 5, 1003-1007, 2010. Google Scholar

49. Teo, , J., et al., "Breast lesion classification using ultrawideband early time breast lesion response," IEEE Trans. on Antennas and Propagat., Vol. 58, No. 8, 2604-2613, 2010. Google Scholar

50. Conceicao, R. C., et al., "Antenna configurations for ultra wide band radar detection of breast cancer," SPIE BIOS West, Vol. 7169, No. 9, 2009. Google Scholar

51. Conceicao, R. C., et al., "Support vector machines for the classi¯cation of early-stage breast cancer based on radar target signatures," Progress In Electromagnetics Research B, Vol. 23, 311-327, 2010. Google Scholar

52. Conceicao, R. C., et al., "Evaluation of features and classifiers for classi¯cation of early-stage breast cancer," Journal of Electromagnetic Waves and Applications, Vol. 25, No. 1, 1-14, 2011. Google Scholar

53. Conceicao, R. C., M. O'Halloran, D. Byrne, E. Jones, and M. Glavin, "Tumor classi¯cation using radar target signatures," PIERS Proceedings, 346-349, July 2010. Google Scholar

54. Conceicao, R. C., et al., "Effects of dielectric heterogeneity in the performance of breast tumour classifiers," Progress In Electromagnetics Research M, Vol. 17, 73-86, 2011. Google Scholar

55. Conceicao, R. C., et al., "Investigation of classifiers for early-stage breast cancer based on radar target signatures," Progress In Electromagnetics Research In Electromagnetics Research, 295-311, 2010. Google Scholar

56. McGinley, , B., et al., "Spiking neural networks for breast cancer classification using radar target signatures," Progress In Electromagnetics Research C, Vol. 17, 79-94, 2010. Google Scholar

57. O'Halloran, , M., et al., "Spiking neural networks for breast cancer classi¯cation in a dielectrically heterogeneous breast," Progress In Electromagnetics Research, Vol. 113, 413-428, 2011. Google Scholar

58. Bond, E. , J., et al., "Microwave imaging via space-time beamforming for early detection of breast cancer," IEEE Trans. on Antennas and Propagat., Vol. 51 , No. 8, 1690-1705, 2003. Google Scholar

59. Muinonen, , K., "Introducing the gaussian shape hypothesis for asteroids and comets," Astron. and Astrophys., Vol. 332, 1087-1098, 1998. Google Scholar

60. Muinonen, K., "Chapter 11: Light scattering by stochastically shaped particles ," Light Scattering by Nonspherical Particles: Theory, Measurements, and Applications, 2000. Google Scholar

61. Muinonen, , K., Gaussian Random Sphere Program G-sphere, 2002.
doi:www.astro.helsinki.fi/psr/

62. University of Wisconsin | Computational Electromagnetics Laboratory (UWCEM).
doi:http://uwcem.ece.wisc.edu/.

63. Zastrow, , E., et al., "Database of 3D Grid-Based Numerical Breast Phantoms for Use in Computational Electromagnetics Simulations,".
doi:http://uwcem.ece.wisc.edu/home.htm. Google Scholar

64. Alshehri, , S. A., et al., "3D experimental detection and discrimination of malignant and benign breast tumor using NN-based UWB imaging system ," Progress In Electromagnetics Research, Vol. 116, 221-237, 2011. Google Scholar

11. "Geppert: The Lognormal Distribution, Engr 323 Notes,". Google Scholar

Dr. Raquel Cruz Conceicao

Dr. Martin O'Halloran

Dr. Martin Glavin

Dr. Edward Jones