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.