International Journal of Engineering Trends and Technology (IJETT) – Volume23 Number 3- May 2015
Comparative Review of Ultrasound Based
Techniques used for Diagnosis of Prostate Cancer
Siddhi Bhandarkar[1], Antara Dandekar[1], Milparinka Desai[1], Purva Nanivadekar[2]
[1] U.G. Student, Biomedical Engineering Department, D.J. Sanghvi College of Engineering
[2] Assistant Professor, Biomedical Engineering Department, D.J. Sanghvi College of Engineering
Abstract-Prostate cancer is one of the leading causes for high mortality
rates in men worldwide. Hence, it becomes necessary to diagnose and
treat the disease in its rudimentary stage. In this paper, we review three
effective techniques used to diagnose and even, treat prostate cancer.
They are mostly used or are the derivative of the conventional Transrectal Ultrasound. We have compared three methods namelyAugmentation detection using TRUS with RF time series, Prostate
detection using Contrast Ultrasound and 3-D Ultrasound imaging. In this
paper, we aim at finding the most efficient method for the task.
Keywords: Prostate Cancer, Trans-rectal Ultrasound (TRUS), RF time
series, 3D Ultrasound, Contrast Ultrasound.
I.INTRODUCTION
Ultrasound Imaging is a non-invasive technique which
involves using ultrasound waves to determine the dimensions
or location of any organ inside the body. It is used to diagnose
the conditions of fetus inside the mother’s uterus, and can
even be used to detect and treat kidney stones and so on. In
this paper, we discuss the application of Ultrasound in
diagnosis of Prostate cancer.
Prostate cancer is the disease in which the cells of the prostate
gland, of the male reproductive system, metastasize
abnormally, leading to enlargement of the gland, which causes
discomfort and pain. If medical attention in not given, prostate
cancer may also prove fatal. Apart from being the most
diagnosed cancer disease among men, prostate cancer has
second highest mortality rate among men worldwide. It is
difficult to examine the organ, due to its location.The annual
incidence rate of prostate cancer in North America increased
since 1980[1].This was because of the introduction of the PSA
(Prostate specific antigen) blood test. The PSA and the digital
rectal examination are the most widely used screening
techniques. But, it was the use of ultrasound technique which
accounts for the minimal invasiveness of all the three methods
not enough to simply screen the disease but, there was a need
to bring various therapeutic methods to treat the disease as
well. With time, many new techniques were introduced. In this
review paper, we discuss three of the advanced methods used
in diagnosis and therapy of prostate cancer.
Percutaneous ultrasound-guided prostate therapy techniques
such as cryosurgery and brachytherapy, are currently under
intense investigation. Although these techniques are each
capable of destroying tumors while adjacent structures, the
inconsistency and wide variability of their outcomes in
different institutions suggest that current practice is highly
operator-dependent. The conventional method for imaging is
2D TRUS(Trans-rectal ultrasound), which includes image
guided cryosurgery and image guided brachysurgery. It is
generally agreed that the conventional 2-D TRUS examination
is an important, cost-effective and useful technique for imaging
the prostate. However, it is also agreed that conventional 2-D
ISSN: 2231-5381
TRUS has some serious limitations like time consumption,
low-accuracy, repeatability etc. The techniques evolved are 3D
Ultrasound imaging, Contrast ultrasound imaging and TRUS
using RF time series.
II. 3-D ULTRASOUND IMAGING SYSTEM
After acquiring a series of 2-D ultrasound images, a 3-D
image is reconstructed. The 3-D image is available to the
physician, permitting the prostate to be viewed interactively in
multiple simultaneous planes, allowing better visualization of
its internal architecture. This approach allows the physician to
record and view the whole prostate in successive
examinations, making 3-D TRUS well suited to performing
prospective or follow-up studies.[1] This procedure is
described in details in various steps.
A. 3-D Image acquisition
The 3-D ultrasound system for imaging the prostate consists
of three major components: 1) an ultrasound machine with a
trans-rectal ultrasound transducer; 2) a microcomputer with a
video frame-grabber; and iii) an motorized assembly to rotate
the transducer under computer control [1] .The microcomputer
is also used for image reconstruction, display, manipulation,
and analysis of the 3-D images. Fig. 1 shows the operating
principle of our approach. The TRUS transducer is mounted in
the assembly and is then covered with a water-filled condom
and inserted into the rectum in the same manner as for a
conventional TRUS examination. When the motor is
activated, it rotates the transducer around its long axis. As the
transducer is rotating at constant speed, conventional B-mode
images are digitized and stored in the micro-computer[1].
B. 3-D image reconstruction
The image reconstruction in this method is done by
designation transducer axis as the z-axis and reconstruction of
P(x, y) will give the image. The newly constructed image
would be mapped with cylindrical co-ordinates P(r, Ɵ, z)[1].
The value of r and Ɵ will be given as from (1) and (2)
r=
(1)
(2)
By using a pre-computed lookup table of interpolation
weights, which is applied repeatedly for each successive
value, the 3-D image can be rapidly reconstructed from the set
of 2-D images[1].
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International Journal of Engineering Trends and Technology (IJETT) – Volume23 Number 3- May 2015
III. THREE-DIMENSIONAL ULTRASOUND SYSTEM
PERFORMANCE
A. Distance Measurement
Fig.1. Schematic diagram showing a side-firing trans-rectal ultrasound
transducer being rotated for a 3-D imaging scan [1].
C. 3-D Image Viewing
Once reconstructed, the 3-D image can be viewed
interactively using any 3-D visualization software. We have
developed a multi-planar reformatting algorithm to view the 3D image as shown in Figs. 2 and 3. In our approach, the 3-D
image is displayed as a polyhedron representing the
boundaries of the reconstructed volume. Each face of the
polyhedron is rendered, using a texture-mapping technique
with the appropriate ultrasound image painted on that face.
The polyhedron can be rotated using simple mouse controls to
obtain the desired orientation of the 3-D image. Any of the
faces can be moved in or out (i.e.the 3-D image can be sliced),
parallel to the original, or reoriented obliquely, while the
appropriate ultrasound data is texture-mapped in real-time on
the new revealed face. In this way, the operator always has 3D image-based cues relating the plane being manipulated to
other planes and to the rest of the anatomy. Figs. 2 and 3 show
examples of the use of this approach in displaying 3-D images
of the prostate [1].
In reconstruction of the 3-D image from a set of acquired 2- D
images, any inconsistencies may result in image distortions
resulting in erroneous distance measurements. In this
method,the phantom was composed of four layers of 0.25 mm
diameter surgical wires, with eight parallel wires per layer.
Each layer was separated from its neighbor by 10.00 0.05 mm,
and each wire was also separated from its neighbors in the
layer by 10.00 mm. The wire phantom was immersed in a bath
composed of a 7% glycerolsolution (1540 m/s speed of sound)
and then imaged with the 3-D system[1].To obtain three
orthogonal separation measurements, the locations of the
centroid of each wire image were determined automatically by
a computer algorithm.
Fig. 3.Three-dimensional ultrasound image of a prostate with a tumor in the
left base (on the left of the image). The 3-D image has been “sliced” (a) in the
trans-axial plane to reveal the tumor (arrow), (b) in two planes (sagittal and
trans axial), and (c) in the coronal plane[1].
B. Volume Measurement in 3-D Images of Balloons
An important application of 3-D imaging of the prostate is for
normalizing the PSA value with the prostate volume. To
evaluate the accuracy of volume measurements using the 3-D
TRUS approach, five balloons filled with different known
volumes of 7% glycerol solution are imaged, and compared
the measured volumes obtained from the 3-D images, to the
true volumes[1].
Fig. 2.three-dimensional ultrasound images showing a prostate with a tumor.
The volume is “sliced” by planes that can be angulated and positioned
interactively by the user to obtain the desired view. (a) The prostate image has
been “cut” in the Trans axial plane to reveal the tumor as a hypo echoic
region, located just above the peri-prostatic fat region. (b) By “slicing” the
image parasagittal, the prostate can be viewed with two simultaneous planes.
(c) The 3-d prostate image has been “sliced” in a coronal plane to view the
prostate in a plane not available using conventional 2-d TRUS[1].
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IV. 2D TRUS USING RF TIME SERIES
In this type of imaging, the samples were needed to be
prepared for analysis.Tissue mimicking phantoms were built
in the form of gelatin agar based suspensions. Microscopic
glass beads with known distributions of particle sizes were
added to study the effects of cell size. Gelatin and agar were
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International Journal of Engineering Trends and Technology (IJETT) – Volume23 Number 3- May 2015
mixed in distilled water at room temperature and while being
performed using an iU22 ultrasound scanner equipped with a
constantly stirred, were heated to 90 ◦C. At this temperature,
C8-4v probe[3]. The effective pulse length of two cycles
point glass beads were added. Small quantities of bleach were
provided an axial resolution of 0.43 mm, while a low
added to avoid bacterial growth in the phantoms [2]
mechanical index (MI) of 0.06 minimized SF6 microbubble
disruption. The compression was set to C38 and the gain was
VI. EX-VIVO HUMAN STUDIES
adjustedto prevent truncation or saturation of the 8-bit grey
level. All acquired B-mode videos were stored in DICOM
Extracted prostate specimens were suspended in a water bath,
(Digital Imaging and Communication in Medicine) format.[3]
and were scanned along transverse planes that were 4 mm
apart. The location of the first cross section was marked with
B. Calibration
two parallel needles visible in an ultrasound image as two
lines. After ultrasound data acquisition, the prostate specimens
To reproduce the clinical conditions, the ultrasound probe was
were dissected along the scanned cross sections.
positioned about 1 cm away from the UCA dispersion. For
Histopathological analysis of whole mount slides was
each concentration, three measurements were performed, from
acquired and used as the gold standard. The contours of
three different SonoVue vials. The mean acoustic intensity
tumors were directly marked on the slides by a senior
was evaluated in a fixed region of interest (ROI) of the
pathologist. The process of histopathological characterization
recorded B-mode images [3].
of the prostate tissue is a routine clinical task [2].
C. Diffusion Modelling
VII. CLASSIFICATION
This two-stage method of feature selection (aimed at
optimizing both the dimension of the feature vector and the
choice of features) was not guaranteed to provide the highest
possible accuracy. An exhaustive search over all 22 features
combined could have resulted in a better performing subset.
However, it required examining 22 n=0 C22 n = 222 subsets
that was computationally infeasible[2].
Physical modelling of the intravascular UCA transport is
required to analysediffusion. The analysis is based on the local
density random walk (LDRW)model. This model can provide
a physical interpretation of the diffusion process, and it
accurately fits UCA indicator dilution curves (IDCs)[3].IDCs
measure the UCA concentration in a fixed sample volume as
function of time and can thus be obtained from TDC. After a
general introduction to the LDRW model, the local aspects of
the diffusion process by this model are discussed [3].
B.SVM Classifier
D.Parameter Estimation
SVM maps the input data to a higher dimension space where a
hyperplane can separate the data in different classes. The
process of training an SVM classifier is equivalent to finding
this optimal hyperplane in a way that minimizes the error on
the training dataset and maximizes the perpendicular distance
between the decision boundary and the closest data points in
classes.[2]
Local diffusion can be estimated from measured TDCs using
the modified LDRW IDC formalization and the relation
between UCA concentration and gray level. The accuracy of
the parameter estimation is determined by the temporal
characteristics of IDC noise, i.e., all signals that the model
function (1) cannot explain (3). The accuracy of the parameter
estimation is improved bylow-pass filtering the TDCs both in
space and time. The spatial filter design is based on the size of
the smallestmicro-vascular networks for which local diffusion
must be estimated.As angiogenesis is required for cancer to
grow beyond1 mm, a reliable analysis of image regions with a
radiusas small as 0.62 mm is necessary.[3]
A. Feature Selection
VIII. CONTRAST ULTRASOUND IMAGING
A. Data Acquisition [3]
The Data Acquisition for Contrast Ultrasound Diffusion
Imaging (CUDI) was performed after approval from the
patients A 2.4 mL Sono Vue UCA bolus was injected
intravenously in the patient’s arm. TRUS imaging was
ISSN: 2231-5381
This was a brief description about the various methods that we
intend to compare. In the next section, we list various
parameters that differentiate each method from one another.
These parameters include the various advantages and
disadvantages of the methods.
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International Journal of Engineering Trends and Technology (IJETT) – Volume23 Number 3- May 2015
IX.COMPARISON
Parameters
CUDI (Contrast Ultrasound)
Phantom used for
study
Not used
Apparatus,
equipment,
software
1.
2.
Parameter which is
detected
Time required
Results
2.4 ml SonoVue UCA bolus.
iU22
ultrasound
scanner
equipped with C8-4v probe.
3. Matlab software.
4. Windows based workstation
running on Intel Core2 Duo
processor.
Diffusion-related parameter (k)
5 minutes
Sensitivity: 81.2%
Specificity: 84.6%
Advantages
It overcomes the problem of the
selection of proper TRUS plane.
Disadvantages
1.
2.
3.
UCA has to be injected.
Validation is restricted to only
peripheral zones.
Validation restricted to patients
whose histology did not show
significant
variation
across
subsequent slices.
TRUS using SVM and RF time
series
Microscopic glass beads of various
sizes with known distributions are
added to gelatin based agar
suspension.
1. Sonix RP ultrasound machine.
2. Sun microsystems
3D
ultrasound
imaging
system
Four layers of 0.25mm
diameter surgical wires, with 8
parallel wires per layer.
Various parameters are used.
Various parameters are used.
7 seconds
Acquisition rate: 22 fps
Accuracy: 80.5%
Sensitivity: 79.8%
Specificity: 81.1%
Color maps with accurately
highlighted areas of tissue with
high risk of cancer are created on
the ultrasound image.
8 seconds
Error: less than 3%
Volume
measurement:
accuracy:2.6%
Precision:2.5%
1. Minimally invasive.
2. Overcomes all drawbacks
of TRUS.
3. Can be interfaced with
any
conventional
ultrasound machine.
1)
Surgeon should keep his/her
hand steady for 7 seconds.
2)
Detection is done in only
peripheral zones but for 80% of
cases cancer occur in this region.
3)
In vivo studies are not
conducted.
4)
Selection of proper plane is
difficult
Not mentioned.
1.
ALT
Ultramark
9
ultrasound
imaging
system.
REFERENCES
CONCLUSION
[1]A. Fenster, S. Tong, H. N. Cardinal, C. Blake, and D. B. Downey,
Ultrasound is a novel tool for detecting prostate cancer. The
three methods discussed above are reliable and under early
stages of research. Principle of CUDI is an increase in
angiogenesis whereas TRUS based on size of cancerous cells.
3D ultrasound imaging is a modification of TRUS. CUDI is an
alternative to TRUS as it overcomes the main drawback.
Moreover specificity and sensitivity is better but requirement
for injection of contrast agent is its demerit and time required
is also more. The technique with most benefits is 3D
ultrasound since, it gives 3D image which makes it potential
tool for diagnosis, therapy and follow-up of prostate disease. It
can be interfaced with any conventional ultrasound machine.
Cost is high and that has to be considered.
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“Three-Dimensional Ultrasound Imaging System for Prostate Cancer
Diagnosis and Treatment”,IEEE transactions on instrumentation and
measurement, vol. 47, no. 6, December 1998.
[2]Mehdi Moradi, Student Member, IEEE, Purang Abolmaesumi,
Member, IEEE, D. Robert Siemens, Eric E. Sauerbrei,Alexander H.
Boag, and Parvin Mousavi, Senior Member, IEEE, “ Augmenting
Detection of Prostate Cancerin Transrectal Ultrasound Images
Using SVMand RF Time Series”,IEEE transactions on biomedical
engineering, vol. 56, no. 9, September 2009.
[3] Maarten P. J. Kuenen, Massimo Mischi, and Hessel Wijkstra,”
Contrast-Ultrasound Diffusion Imaging for Localization of Prostate
Cancer”, IEEE transactions on medical imaging, vol. 30, no. 8,
August 2011.
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