Trans-rectal thermo-acoustic computed
tomography: An initial in silico study

• Authors: Sovanlal Mukherjee , Charles Bunting , Daqing Piao
• Languages of publication: EN

Abstracts

EN

Background: The purpose of this in silico study is to
demonstrate thermo-acoustic computed tomography (CT)
based reconstruction of frequency-dependent true electrical
conductivity distribution in a trans-rectal axialimaging
geometry. Since cancerous tissue is expected to
exhibit different conductivity profile compared to normal
tissue, reconstructing conductivity based on thermoacoustic
CT in a trans-rectal geometry has a potential for
prostate cancer detection.Methodology: A trans-rectal axial-imaging geometry is illuminated
by an electromagnetic (EM) point source at a
microwave frequency. The source is located on a transrectal
EM applicator close to the rectal wall. The applicator
also houses a convex-array of point acoustic receivers
that capture the acoustic pressure generated within the geometry
as a result of EM illumination. The finite element
method (FEM) along with an absorbing boundary condition
is applied for solving the electric field (E-field) distribution,
the power loss density and the acoustic pressure.
The Levenberg-Marquardt regularization scheme is
applied to reconstruct the conductivity distribution by decoupling
the E-field from the power loss density.Results: For an excitation frequency of 915 MHz, various
2-D reconstructed images based on a 2:1 conductivity ratio
between the background and object in a trans-rectal
geometry of 40 mm radius are shown. Both single and
double objects of 3 mm radius positioned at 4, 7, 10 and
15 mm depth with respect to the acoustic receiver are considered.
The quality of the reconstructed image is shown
to be object-depth dependent. The effect of different levels
of Gaussian noise on the reconstructed images is shown.
The contrast-to-noise ratios (CNRs) of the reconstructed
images for the objects of different sizes and depths are also
computed.Conclusions: Feasibility of recovering heterogeneous
conductivity distribution in a trans-rectal axial-imaging
geometry by thermo-acoustic CT is demonstrated in silico.
The results implicate an alternative imaging mechanism
for prostate cancer detection.

Keywords

EN

thermo-acoustic CT; trans-rectal geometry; finite-element method; absorbing boundary condition; and conductivity reconstruction

• Publisher: De Gruyter Open
• Journal: X-Acoustics: Imaging and Sensing
• Year: 2014
• Volume: 1
• Issue: 1

Dates

online

10 - 7 - 2014

Contributors

author

Sovanlal Mukherjee

• School of Electrical and Computer
  Engineering, Oklahoma State University, Stillwater, OK, 74078

author

Charles Bunting

• School of Electrical and Computer
  Engineering, Oklahoma State University, Stillwater, OK, 74078

author

Daqing Piao

• School of Electrical and Computer
  Engineering, Oklahoma State University, Stillwater, OK, 74078

References

• [1] R.A. Kruger, K.K. Kopecky, A.M. Aisen, D.R. Reinecke, G.A.Kruger and W. Kiser, Thermoacoustic CT with radio waves: amedical imaging paradigm, Radiology, 211, 1999, 275.[Crossref]
• [2] S.S. Chaudhary, R.K. Mishra, A. Swarup and J.M. Thomas,Dielectric properties of normal & malignant human breasttissues at radiowave & microwave frequencies, Indian J.Biochem. Biophys., 21, 1984, 76.
• [3] W.T. Joines, Y. Zhang, C. Li and R. Jirtle, The measured electricalproperties of normal and malignant human tissues from50 to 900 MHz, Med. Phys., 21, 1994, 547.[Crossref]
• [4] M. Lazebnik, D. Popovic, L. McCartney, C.B. Watkins, M.J.Lindstrom, J. Harter and S. Sewall et al., A large-scale study ofthe ultrawideband microwave dielectric properties of normal,benign and malignant breast tissues obtained from cancersurgeries, Phys. Med. Biol, 52, 2007, 6093.[WoS][Crossref]
• [5] A.J. Surowiec, S.S. Stuchly, J. Robin Barr and A. Swarup, Dielectricproperties of breast carcinoma and the surroundingtissue, IEEE Trans Biomed Eng, 35, 1988, 257.[Crossref]
• [6] R.J. Halter, A. Hartov, J.A. Heaney, K.D. Paulsen and A.R.Schned, Electrical Impedance Spectroscopy of the HumanProstate, IEEE Trans. Biomed. Eng. 54, 2007, 1321.[Crossref]
• [7] W. Joines, R. Jirtle, M. Rafal, and D. Schaeffer, Microwavepower absorption differences between normal and malignanttissue, Int. J. Radiat. Oncol. Biol. Phys. 6, 1980, 681.[Crossref]
• [8] R.A. Kruger, K.D. Miller, H.E. Reynolds, W.L. Kiser, D.R. Reineckeand G.A. Kruger, Breast cancer in vivo: contrast enhancement with thermoacoustic CT at 434 MHz-feasibilitystudy, Radiology, 216, 2000, 279.[Crossref]
• [9] Y. Xu and L.V. Wang, Rhesus monkey brain imaging throughintact skull with thermoacoustic tomography, IEEE Trans.Ultrason. Ferroelectr. Freq. Control. 53, 2006, 542.[Crossref]
• [10] R. Siegel, D. Naishadham and A. Jemal, Cancer Statistics, CA:Cancer J. Clin. 63, 2013, 11.[Crossref]
• [11] T.J. Polascik, J.E. Oesterling, and A.W. Partin, Prostate specificantigen: a decade of discovery-what we have learned andwhere we are going, J. Urol. 162, 1999, 293.
• [12] G.D. Grossfeld and P.R. Carroll, Prostate cancer early detection:a clinical perspective, Epidemiol Rev. 23, 2001, 173.[Crossref]
• [13] C.R. Porter, Does the number of prostate biopsies performedaffect the nature of the cancer identified?, Nat. Clin. Pract.Urol. 4, 2007, 132.[WoS][Crossref]
• [14] V. Scattoni, A. Zlotta, R. Montironi, C. Schulman, P. Rigatti,and F. Montorsi, “Extended and saturation prostatic biopsyin the diagnosis and characterisation of prostate cancer: acritical analysis of the literature”, Eur. Urol. 52, 2007, 1309.[WoS][Crossref]
• [15] P.M. Meaney, K.D. Paulsen, and T.P. Ryan, Two-dimensionalhybrid element image reconstruction for TM illumination,IEEE Trans. Ant. Propag. 43, 1995, 239.[Crossref]
• [16] A.E. Souvorov, A.E. Bulyshev, S.Y. Semenov, R.H. Svenson,A.G.Nazarov, Y.E. Sizov, and G.P. Tatsis, Microwave tomography:A two-dimensional Newton iterative scheme, IEEE Trans.Microwave Th. & Tech. 46, 1998, 1654.
• [17] V.G. Andreev, A.A. Karabutov and A.A. Oraevsky, Detection ofultrawide-band ultrasound pulses in optoacoustic tomography,IEEE Trans. Ultrason. Ferroelectr. Freq. Control. 50, 2003,1383.[Crossref]
• [18] X. Wang, Y. Xu, M. Xu, S. Yokoo, E.S. Fry and L.V. Wang, Photoacoustictomography of biological tissues with high crosssectionresolution: reconstruction and experiment, Med.Phys. 29, 2002, 2799.[Crossref]
• [19] H. Jiang, Z. Yuan and X. Gu, Spatially varying optical andacoustic property reconstruction using finite-element-basedphotoacoustic tomography, J. Opt. Soc. Am. A. 23, 2006, 878.[Crossref]
• [20] L. Yao, G. Guo and H. Jiang, Quantitative microwave-inducedthermoacoustic tomography, Med. Phys. 37, 2010, 3752.[Crossref]
• [21] S. Mukherjee, C. Bunting, and D. Piao, Finite-element-methodbased reconstruction of heterogeneous conductivity distributionunder point-illumination in trans-rectal imaginggeometry for thermo-acoustic tomography, OSA BiomedicalTopical Meeting (April 28-May 02, 2012, Miami, FL), Miami,2007, Bsu3A.44.
• [22] L. Huang, L. Yao, L. Liu, J. Rong and H. Jiang, Quantitativethermoacoustic tomography: Recovery of conductivity mapsof heterogeneous media, Applied Physics Letters, 101, 2012,244106.[WoS][Crossref]
• [23] C. Balanis, Advanced Engineering Electromagnetics, JohnWiley & Sons, Inc., New York, 1989.
• [24] J. Jin, The Finite Element Method in Electromagnetics, 2nd ed.,John Wiley & Sons, Inc., New York, 2002.
• [25] A. Peterson, S. Ray and R. Mittra, Computational Methods forElectromagnetics, IEEE press, New York, 1997.
• [26] J. Volakis, A. Chatterjee and L.C. Kempel, Finite ElementMethod for Electromagnetics IEEE press, New York, 1998.
• [27] A.F. Peterson and S.V. Castillo, A frequency-domain differentialequation formulation for electromagnetic scattering frominhomogeneous cylinders, IEEE Trans. Ant. Propag. 37, 1989,601.[Crossref]
• [28] A. Bayliss and E. Turkel, Radiation boundary conditions forwave-like equations, Commun. Pure Appl. Math. 33, 1980,707.[Crossref]
• [29] L. Wang and H. Wu, Biomedical Optics: Principles and Imaging,1st ed., John Wiley & Sons, Inc., New Jersey, 2007.
• [30] K. Levenberg, A Method for the Solution of Certain Non-LinearProblems in Least Squares, Quarterly J. of Applied Mathematics,II, 1944, 164.
• [31] D. Marquardt, An Algorithm for Least-Squares Estimation ofNonlinear Parameters, SIAM J. on Applied Mathematics, 11,1963, 431.
• [32] D. Andreuccetii, R. Fossi and C. Petrucci, Dielectric Propertiesof Body Tissues: Output Data, Italian National ResearchCouncil Institute for Applied Physics IFAC, http://niremf.ifac.cnr.it/tissprop/htmlclie/htmlclie.htm{#}atsftag.
• [33] L. Chin and M. Sherar, Changes in the dielectric properties ofrat prostate ex vivo at 915 MHz during heating, Int. J. Hyperthermia,20, 2004, 517.
• [34] X. Song, B.W. Pogue, S. Jiang, M.M. Doyley, H. Dehghani,T.D. Tosteson and K.D. Paulsen, Automated region detectionbased on the contrast-to-noise ratio in near-infrared tomography,Applied Optics, 43(5), 2004, 1053.[Crossref]
• [35] H. Dehghani, M.E. Eames, P.K. Yalavarthy, S.C. Davis, S. Srinivasan,C.M. Carpenter and B.W. Pogue et al., Near infraredoptical tomography using NIRFAST: Algorithm for numericalmodel and image reconstruction, Commun. Numer. Meth.Eng. 25, 2008, 711.[WoS]
• [36] K. Wang and T. C. Zhu, Reconstruction of in-vivo optical propertiesfor human prostate using interstitial diffuse opticaltomography, Opt. Exp. 17, 2009, 11665.[Crossref]
• [37] Q. Fang, Computational Methods for Microwave MedicalImaging, Ph.D. thesis, Dartmouth College, New Hampshire,USA, 2004.

Identifiers

DOI

10.2478/phto-2014-0001