We present a pilot study using a microwave tomography system in which we image the forearms of 5 adult male and female volunteers between the ages of 30 and 48. Microwave scattering data were collected at 0.8 to 1.2？GHz with 24 transmitting and receiving antennas located in a matching fluid of deionized water and table salt. Inversion of the microwave data was performed with a balanced version of the multiplicative-regularized contrast source inversion algorithm formulated using the finite-element method (FEM-CSI). T1-weighted MRI images of each volunteer’s forearm were also collected in the same plane as the microwave scattering experiment. Initial “blind” imaging results from the utilized inversion algorithm show that the image quality is dependent on the thickness of the arm’s peripheral adipose tissue layer; thicker layers of adipose tissue lead to poorer overall image quality. Due to the exible nature of the FEM-CSI algorithm used, prior information can be readily incorporated into the microwave imaging inversion process. We show that by introducing prior information into the FEM-CSI algorithm the internal anatomical features of all the arms are resolved, significantly improving the images. The prior information was estimated manually from the blind inversions using an ad hoc procedure. 1. Introduction Microwave imaging (MWI) is an alternative imaging modality that promises several advantages over more established modalities such as X-ray, ultrasound, or MRI. Advantages include low cost, use of safer nonionizing radiation, the ability to image bulk-electrical tissue properties, and the ability to provide functional imaging without the use of contrast agents [1]. Microwave imaging applications have primarily focused on breast cancer [2–7], although extremity (arm and leg) imaging has also received attention [1, 8–12]. While standard X-ray imaging gives reliable indication of bone injury, some researchers have indicated that diagnosing the condition of soft tissue is important for the final outcome of treatment [8], and microwaves may potentially be used to assess the soft tissue component of an injured extremity. Despite the potential advantages of microwaves as an imaging modality, the technology has not yet seen widespread use in clinics outside of research labs (e.g., the largest study involves 400 volunteers [13]). We believe that the best argument for the use of microwave imaging is that it promises to fill a niche within the medical imaging world, providing a nonionizing, inexpensive imaging modality which is capable of imaging soft tissue
References
[1]
S. Semenov, J. Kellam, B. Nair et al., “Microwave tomography of extremities: 2. Functional fused imaging of flow reduction and simulated compartment syndrome,” Physics in Medicine and Biology, vol. 56, no. 7, pp. 2019–2030, 2011.
[2]
P. M. Meaney, M. W. Fanning, T. Raynolds et al., “Initial clinical experience with microwave breast imaging in women with normal mammography,” Academic Radiology, vol. 14, no. 2, pp. 207–218, 2007.
[3]
S. P. Poplack, T. D. Tosteson, W. A. Wells et al., “Electromagnetic breast imaging: results of a pilot study in women with abnormal mammograms,” Radiology, vol. 243, no. 2, pp. 350–359, 2007.
[4]
E. C. Fear, P. M. Meaney, and M. A. Stuchly, “Microwaves for breast cancer detection?” IEEE Potentials, vol. 22, no. 1, pp. 12–18, 2003.
[5]
M. Lazebnik, D. Popovic, L. McCartney 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, pp. 6093–6115, 2007.
[6]
D. W. Winters, J. D. Shea, P. Kosmas, B. D. Van Veen, and S. C. Hagness, “Three-dimensional microwave breast imaging: dispersive dielectric properties estimation using patient-specific basis functions,” IEEE Transactions on Medical Imaging, vol. 28, no. 7, pp. 969–981, 2009.
[7]
M. Klemm, I. Craddock, J. Leendertz et al., “Clinical trials of a UWB imaging radar for breast cancer,” in Proceedings of the 4th European Conference on Antennas and Propagation (EuCAP '10), pp. 1–4, April 2010.
[8]
S. Semenov, J. Kellam, Y. Sizov et al., “Microwave tomography of extremities: 1. Dedicated 2D system and physiological signatures,” Physics in Medicine and Biology, vol. 56, no. 7, pp. 2005–2017, 2011.
[9]
S. Y. Semenov, A. E. Bulyshev, A. Abubakar et al., “Microwave-tomographic imaging of the high dielectric-contrast objects using different image-reconstruction approaches,” IEEE Transactions on Microwave Theory and Techniques, vol. 53, no. 7, pp. 2284–2293, 2005.
[10]
S. Semenov, “Microwave tomography: review of the progress towards clinical applications,” Philosophical Transactions of the Royal Society A, vol. 367, no. 1900, pp. 3021–3042, 2009.
[11]
S. Semenov, J. Kellam, P. Althausen et al., “Microwave tomography for functional imaging of extremity soft tissues: feasibility assessment,” Physics in Medicine and Biology, vol. 52, no. 18, pp. 5705–5719, 2007.
[12]
S. Salvador, E. Fear, M. Okoniewski, and J. Matyas, “Exploring joint tissues with microwave imaging,” IEEE Transactions on Microwave Theory and Techniques, vol. 58, no. 8, pp. 2307–2313, 2010.
[13]
T. M. Grzegorczyk, P. M. Meaney, P. M. Kaufman, R. M. di Florio Alexander, and K. D. Paulsen, “Fast 3-D tomographic microwave imaging for breast cancer detection,” IEEE Transactions on Medical Imaging, vol. 31, no. 8, pp. 1584–1592, 2012.
[14]
E. J. Hall, “Lessons we have learned from our children: cancer risk from diagnostic radiology,” Pediatric Radiology, vol. 32, no. 10, pp. 700–706, 2002.
[15]
S. Gabriel, R. W. Lau, and C. Gabriel, “The dielectric properties of biological tissues: III. Parametric models for the dielectric spectrum of tissues,” Physics in Medicine and Biology, vol. 41, no. 11, pp. 2271–2293, 1996.
[16]
C. Kaye, J. LoVetri, A. Zakaria, and M. Osadrahimi, “Feasibility study of microwave tomography for in vivo characteristic of tissue as a diagnostic technique for human disease,” in Proceedings of IEEE International Symposium on Antennas and Propagation and USNC/URSI National Radio Science Meeting (AP-S/USNC-URSI '12), July 2012.
[17]
C. Gilmore, P. Mojabi, A. Zakaria et al., “A wideband microwave tomography system with a novel frequency selection procedure,” IEEE Transactions on Biomedical Engineering, vol. 57, no. 4, pp. 894–904, 2010.
[18]
C. Gilmore, A. Zakaria, J. LoVetri, and S. Pistorius, “A study of matching fluid loss in a biomedical microwave tomography system,” Medical Physics, vol. 40, no. 2, Article ID 023101, 14 pages, 2012.
[19]
P. M. Meaney, S. A. Pendergrass, M. W. Fanning, D. Li, and K. D. Paulsen, “Importance of using a reduced contrast coupling medium in 2D microwave breast imaging,” Journal of Electromagnetic Waves and Applications, vol. 17, no. 2, pp. 333–355, 2003.
[20]
J. Jin, The Finite Element Method in Electromagnetics, John Wiley & Sons, New York, NY, USA, 2002.
[21]
A. Zakaria, The finite-element contrast source inversion method for microwave imaging applications [Ph.D. dissertation], University of Manitoba, 2012.
[22]
A. Abubakar, P. M. van den Berg, and J. J. Mallorqui, “Imaging of biomedical data using a multiplicative regularized contrast source inversion method,” IEEE Transactions on Microwave Theory and Techniques, vol. 50, no. 7, pp. 1761–1771, 2002.
[23]
T. Rubk, P. M. Meaney, P. Meincke, and K. D. Paulsen, “Nonlinear microwave imaging for breast-cancer screening using Gauss-Newton's method and the CGLS inversion algorithm,” IEEE Transactions on Antennas and Propagation, vol. 55, no. 8, pp. 2320–2331, 2007.
[24]
R. K. Amineh, M. Ravan, A. Trehan, and N. K. Nikolova, “Near-field microwave imaging based on aperture raster scanning with TEM horn antennas,” IEEE Transactions on Antennas and Propagation, vol. 59, no. 3, pp. 928–940, 2011.
[25]
M. Ostadrahimi, P. Mojabi, A. Zakaria, J. LoVetri, and L. Shafai, “Enhancement of Gauss-Newton inversion method for biomedical tissue imaging,” IEEE Transactions on Microwave Theory and Techniques. Accepted.
[26]
M. Klemm, I. J. Craddock, J. A. Leendertz, A. Preece, and R. Benjamin, “Radar-based breast cancer detection using a hemispherical antenna array—experimental results,” IEEE Transactions on Antennas and Propagation, vol. 57, no. 6, pp. 1692–1704, 2009.
[27]
D. Flores-Tapia, M. O'Halloran, and S. Pistorius, “A bimodal reconstruction method for breast cancer imaging,” Progress in Electromagnetics Research, vol. 118, pp. 461–486, 2011.
[28]
D. Kurrant and E. Fear, “Defining regions of interest for microwave imaging using near-field reflection data,” IEEE Microwave Theory and Techniques Society, vol. 61, no. 5, pp. 2137–2145, 2013.
[29]
M. El-Shenawee and E. L. Miller, “Spherical harmonics microwave algorithm for shape and location reconstruction of breast cancer tumor,” IEEE Transactions on Medical Imaging, vol. 25, no. 10, pp. 1258–1271, 2006.
[30]
P. M. van den Berg and R. E. Kleinman, “A contrast source inversion method,” Inverse Problems, vol. 13, no. 6, pp. 1607–1620, 1997.
[31]
A. Zakaria, C. Gilmore, and J. LoVetri, “Finite-element contrast source inversion method for microwave imaging,” Inverse Problems, vol. 26, no. 11, Article ID 115010, 2010.
[32]
A. Zakaria and J. LoVetri, “A study of adaptive meshing in FEM-CSI for microwave tomography,” in Proceedings of the 14th International Symposium on Antenna Technology and Applied Electromagnetics and the American Electromagnetics Conference (ANTEM/AMEREM '10), pp. 1–4, Ottawa, Canada, July 2010.
[33]
A. Zakaria, C. Gilmore, S. Pistorius, and J. LoVetri, “Balanced multiplicative regularization for the contrast source inversion method,” in Proceedings of the 28th International Review of Progress in Applied Computational Electromagnetics Conference (ACES '12), Columbus, Ohio, USA, 2012.
[34]
A. Zakaria and J. LoVetri, “Application of multiplicative regularization to the finite-element contrast source inversion method,” IEEE Transactions on Antennas and Propagation, vol. 59, no. 9, pp. 3495–3498, 2011.
[35]
P. M. van den Berg, A. Abubakar, and J. T. Fokkema, “Multiplicative regularization for contrast profile inversion,” Radio Science, vol. 38, no. 2, 2003.
[36]
C. Gilmore, A. Zakaria, P. Mojabi, M. Ostadrahimi, S. Pistorius, and J. LoVetri, “The University of Manitoba microwave imaging repository: a two-dimensional microwave scattering database for testing inversion and calibration algorithms,” IEEE Antennas and Propagation Magazine, vol. 53, no. 5, pp. 126–133, 2011.
[37]
S. Gabriel, R. W. Lau, and C. Gabriel, “The dielectric properties of biological tissues: II. Measurements in the frequency range 10？Hz to 20？GHz,” Physics in Medicine and Biology, vol. 41, no. 11, pp. 2251–2269, 1996.
[38]
R. J. Halter, T. Zhou, P. M. Meaney et al., “The correlation of in vivo and ex vivo tissue dielectric properties to validate electromagnetic breast imaging: initial clinical experience,” Physiological Measurement, vol. 30, no. 6, pp. S121–S136, 2009.
[39]
D. Haemmerich, O. R. Ozkan, J.-Z. Tsai et al., “Changes in electrical resistivity of swine liver after occlusion and postmortem,” Medical and Biological Engineering and Computing, vol. 40, no. 1, pp. 29–33, 2002.
[40]
J. J. Mallorqui, N. Joachimowicz, J. C. Bolomey, and A. P. Broquetas, “Database of “in vivo” measurements for quantitative microwave imaging and reconstruction algorithms available,” IEEE Antennas and Propagation Magazine, vol. 37, no. 5, pp. 87–89, 1995.
[41]
C. Gilmore, P. Mojabi, and J. LoVetri, “Comparison of an enhanced distorted born iterative method and the multiplicative-regularized contrast source inversion method,” IEEE Transactions on Antennas and Propagation, vol. 57, no. 8, pp. 2341–2351, 2009.
[42]
C. Gilmore, A. Abubakar, W. Hu, T. M. Habashy, and P. M. van den Berg, “Microwave biomedical data inversion using the finite-difference contrast source inversion method,” IEEE Transactions on Antennas and Propagation, vol. 57, no. 5, pp. 1528–1538, 2009.
[43]
M. Haynes, J. Stang, and M. Moghaddam, “Microwave breast imaging system prototype with integrated numerical characterization,” International Journal of Biomedical Imaging, vol. 2012, Article ID 706365, 18 pages, 2012.
[44]
A. Golnabi, P. Meaney, S. Geimer, and K. Paulsen, “Comparison of no-prior and soft-prior regularization in biomedical microwave imaging,” Journal of Medical Physics, vol. 36, no. 3, pp. 159–170, 2011.
[45]
A. Fhager and M. Persson, “Using a priori data to improve the reconstruction of small objects in microwave tomography,” IEEE Transactions on Microwave Theory and Techniques, vol. 55, no. 11, pp. 2454–2462, 2007.
[46]
A. Abubakar, W. Hu, P. M. van den Berg, and T. Habashy, “A finite-difference contrast source inversion method,” Inverse Problems, vol. 24, no. 6, Article ID 065004, 17 pages, 2008.
[47]
T. C. Williams, J. Bourqui, T. R. Cameron, M. Okoniewski, and E. C. Fear, “Laser surface estimation for microwave breast imaging systems,” IEEE Transactions on Biomedical Engineering, vol. 58, no. 5, pp. 1193–1199, 2011.
[48]
M. J. Pallone, P. M. Meaney, and K. D. Paulsen, “Surface scanning through a cylindrical tank of coupling fluid for clinical microwave breast imaging exams,” Medical Physics, vol. 39, no. 6, pp. 3102–3111, 2012.
[49]
A. Zakaria, A. Baran, and J. LoVetri, “Estimation and use of prior information in FEM-CSI for biomedical microwave tomography,” IEEE Antennas and Wireless Propagation Letters, vol. 11, pp. 1606–1609, 2012.
