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Technical Advance
Image Registration Accuracy
of a 3-Dimensional Transrectal
Ultrasound–Guided Prostate
Biopsy System
Yujun Guo, PhD, Priya N. Werahera, PhD,
Ramkrishnan Narayanan, PhD, Lu Li, MS, Dinesh
Kumar, MS, E. David Crawford, MD, Jasjit S. Suri, PhD
Objective. For a follow-up prostate biopsy procedure, it is useful to know the previous biopsy locations
in anatomic relation to the current transrectal ultrasound (TRUS) scan. The goal of this study was to
validate the performance of a 3-dimensional TRUS-guided prostate biopsy system that can accurately
relocate previous biopsy sites. Methods. To correlate biopsy locations from a sequence of visits by a
patient, the prostate surface data obtained from a previous visit needs to be registered to the followup visits. Two interpolation methods, thin-plate spline (TPS) and elastic warping (EW), were tested for
registration of the TRUS prostate image to follow-up scans. We validated our biopsy system using a
custom-built phantom. Beads were embedded inside the phantom and were located in each TRUS
scan. We recorded the locations of the beads before and after pressures were applied to the phantom
and then compared them with computer-estimated positions to measure performance. Results. In our
experiments, before system processing, the mean target registration error (TRE) ± SD was 6.4 ± 4.5
mm (range, 3–13 mm). After registration and TPS interpolation, the TRE was 5.0 ± 1.03 mm (range,
2–8 mm). After registration and EW interpolation, the TRE was 2.7 ± 0.99 mm (range, 1–4 mm). Elastic
warping was significantly better than the TPS in most cases (P < .0011). For clinical applications, EW
can be implemented on a graphics processing unit with an execution time of less than 2.5 seconds.
Conclusions. Elastic warping interpolation yields more accurate results than the TPS for registration of
TRUS prostate images. Experimental results indicate potential for clinical application of this method.
Key words: elastic warping interpolation; phantom validation; prostate cancer; surface-based registration; thin-plate spline interpolation; 3-dimensional transrectal ultrasound.
Abbreviations
EW, elastic warping; PCa, prostate cancer; PSA,
prostate-specific antigen; 3D, 3-dimensional; TPS, thinplate spline, TRE, target registration error; TRUS, transrectal ultrasound
Received February 2, 2009, from Eigen Inc, Grass
Valley, California USA (Y.G., R.N., L.L., D.K., J.S.S.);
University of Colorado, Denver, Colorado USA
(P.N.W.); and University of Colorado Health
Sciences Center, Aurora, Colorado USA (D.C.).
Revision requested March 23, 2009. Revised
manuscript accepted for publication May 5, 2009.
Yujun Guo, Ramakrishnan Narayanan, Lu Li,
Dinesh Kumar, and Jasjit S. Suri are employees of
Eigen Inc, manufacturer of the Artemis system.
Address correspondence to Jasjit S. Suri, PhD (CTO),
Eigen Inc, 13366 Grass Valley Ave, Grass Valley, CA
95945 USA.
E-mail: jas.suri@eigen.com
P
rostate cancer (PCa) is the most common noncutaneous human malignancy and the second
most lethal tumor among American men. In
2008, an estimated 186,320 men will have a diagnosis of PCa; 28,660 of them will die of this disease in
the United States.1 In general, a biopsy is recommended
when the patient shows elevated prostate-specific antigen (PSA) levels, a possible indicator of underlying malignancy. Transrectal ultrasound (TRUS)–guided biopsy is
used to remove tissue from the prostate gland for pathologic classification.2 One of the most perplexing aspects is
that patients with PCa who have similar PSA levels, clinical stages, and histopathologic features in their biopsy
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Image Registration Accuracy of 3D TRUS-Guided Prostate Biopsy
tissue can have markedly different clinical outcomes.3 Although localized PCa can become
lethal in some patients,4 most men die with PCa
rather than of it. Autopsy studies have confirmed
histologically apparent PCa in the prostate
glands of approximately 42% of men older than
50 years who died of other causes.5 Nevertheless,
the 5-year survival rate for American men with a
diagnosis of PCa was nearly 100% based on
patients with a diagnosis between 1996 and 2002
and followed through 2003.6 Therefore, early
detection and treatment play important roles in
the clinical management of this disease.
Currently, there are 2 important clinical challenges: (1) diagnosis of clinically threatening cancer7 and (2) selection of a suitable treatment
regimen.8 Prostate biopsies are subjected to serious sampling errors. The success of prostate
biopsies largely depends on the size and location
of the tumor rather than the clinical importance
of the disease.9 There have been efforts to find
optimal locations for prostate biopsies, but the
selection does not guarantee that malignancy
will be detected in the first session. If the initial
biopsy results are negative, a second biopsy is
usually recommended when PSA levels remain
elevated. Studies have shown that up to 10% of
cases with initial negative biopsy results may
produce positive results during a subsequent
biopsy.10 For a subsequent biopsy, it is useful to
know the previous biopsy locations so that the
physician may plan the current procedure by
revisiting or avoiding some locations.
Because of the relatively long latency of PCa, a
considerable proportion of men with localized
PCa are subject to overdiagnosis and receive
unnecessary therapy10,11 with attendant morbidity, coupled with substantial cost escalations
from detection of minor tumors via aggressive
screening.12,13 Because most cases of PCa currently diagnosed by prostate biopsies have an
intermediate Gleason score, with either good or
poor clinical outcomes, some of these patients
may be treated with focal therapy as opposed to
more aggressive treatments, eg, surgery and radiation.14 Patients with disease localized to one
side of the prostate can be treated with focal therapy, thereby eliminating the usual side effects
associated with surgery and radiation. The success of focal therapy largely depends on the
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screening procedure (brachytherapy and template-guided saturation biopsy) and the ability to
focus treatment in relation to specific locations
within the prostate.15 Therefore, it is necessary to
accurately relocate initial biopsy locations (those
having malignancies) during focal treatment.
However, it is very difficult for a physician to
relocate the initial biopsy locations obtained
across the TRUS images during a subsequent
biopsy or therapy session. Although templateguided transperineal biopsy procedures may
provide some degree of relocation accuracy, currently there is no mechanism to accurately relocate biopsy locations performed transrectally.
This is partly due to use of a live 2-dimensional
TRUS image, whereas a 3-dimensional (3D) TRUS
image of the gland may provide anatomic features
that are more easily discerned. Furthermore, the
gland tends to move or deform because of external physical disturbances, discomfort introduced by the procedure, changes due to cancer
progression, therapy, or intrinsic peristalsis. The
quality of the image also depends on the type
and particular settings of the machine. It is,
therefore, necessary to find the correspondence
between TRUS images so that the previous biopsy sites can be identified on an ultrasound scan
during subsequent visits. Hence, there is a clinical need for a 3D TRUS-guided prostate biopsy
system in which initial biopsy locations can be
accurately relocated during follow-up visits.
A 3D TRUS-guided biopsy scheme was initially
demonstrated.16 It uses a mechanical tracker
having 4 degrees of freedom. An integral personal computer–based workstation can register
biopsy locations in 3D space and accurately relocate them in follow-up visits. In this study, we
evaluate the accuracy and utility of 2 image interpolation methods in this 3D TRUS-guided
prostate biopsy system using tissue phantoms.
Materials and Methods
System Overview
The 3D TRUS-guided biopsy system is partitioned into the following subsystems: image
acquisition, prostate segmentation, target planning, tracking, and reporting. Three-dimensional
image registration completed as a part of target
planning is a surface-based registration technique.
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This aligns the segmented surface of the current
3D prostate gland with that computed from the
previous visit so that previous biopsy sites can
be interpolated onto the current 3D TRUS volume. Only surface information is used in 3D
TRUS image segmentation because ultrasound
image quality is poor in certain regions within
the prostate and makes intensity-based registration methods impractical.
Both semiautomated and fully automated
image segmentation techniques are available in
this system.16 Figure 1 shows the process flow for
the selection of biopsy sites based on a previous
biopsy report. Figure 2 illustrates the essential
components of the surface-based registration
technique adapted into our system.17 Figure 3
shows a sample graphical user interface design
to load a previous biopsy plan onto the current
ultrasound scan. Once a patient’s previous visit
is selected, the corresponding previously segmented prostate surface is registered to the currently segmented surface. After this, the previous
biopsy sites are interpolated on the current volume based on the correspondence established
through registration.
Two interpolation techniques are implemented. One is based on a thin-plate spline (TPS)
method, whereas the other is based on elastic
warping (EW). The TPS method uses the concept
of minimizing the “bending” energy of a thin
sheet of metal.18 In 3D cases, given 2-point sets
P and Q, each has n points. Each point (pi, i = 1
. . .n) in P corresponds to 1 point (qi, i = 1 . . .n) in
Q. Thin-plate spline interpolation is described
by 3(n + 4) parameters, which include 12 global
affine motion parameters and 3n coefficients
for correspondences of the n control points
(Equation 1):
Figure 1. Process flow diagram for the mapping
of biopsy sites from a previous patient visit onto the
current visit.
Figure 2. Surface-based registration flow chart.
(1)
The definition of Uij (i = 1 . . . n, j = 1 . . . n) is
(2)
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These parameters are computed by solving the
linear system.18 Elastic warping uses modeling of
elastic sheets, which are warped by an external
force applied to points (x, y, z) in data set D1, so
that they are deformed to the coordinates of their
corresponding points (f u (x, y, z), f v (x, y, z), f w (x,
y, z)) in data set D2.19 Given a set of n corresponding points, EW interpolation is used to find the
solution of function (U, V, W ) to the equations
describing the deformation of an elastic sheet:
(3)
Where U (X ) = [U V W ]T, X = (x, y, z), and q(X ) =
q(x, y, z) is unity when there is a correspondence
and 0 otherwise. Equation 3 is discretized, and the
resulting linear system is solved iteratively.
Evaluation Protocol
We used 5 custom-built tissue phantoms to evaluate the accuracy of the 3D TRUS-guided biopsy
scheme. A typical tissue phantom design is illustrated in Figure 4. Spherical beads comprising 2mm stainless steel balls are planted inside each
tissue phantom at random locations to emulate
several targeted biopsy sites and can be identified
on ultrasound scans. As shown in Figure 5, the
ultrasound signal was locally distorted by the presence of the beads; the beads, however, were identifiable, and the segmentation method was
unaffected. The evaluation procedure is as follows:
1. A 3D TRUS image scan of tissue phantom is
acquired.
2. The spherical beads in the ultrasound scan
are identified. The centers of spherical beads are
saved and designated as P. Then, either the semiautomated segmentation process or the fully
automated segmentation process is performed,
and the segmented prostate volume is obtained
and designated as a floating 3D image (labeled A).
3. Next, mechanical pressure is applied in an
arbitrary direction on the tissue phantom. This
mimics anatomic deformations (shape and size
variations) or movement of the prostate. The
aforementioned steps are repeated to obtain 3D
TRUS images, with the spherical beads centers
designated Q. The deformed tissue phantom surface is segmented and designated as a target 3D
image (labeled B).
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4. The floating 3D image, A, is registered to the
target 3D image, B, and then a nonrigid deformation between the 2 images is obtained.16
Now the 3D image, A, is aligned to the target 3D
image, B. Therefore, the set of points, P, inside
the floating 3D image, A, is accordingly
deformed and registered as points P′ inside the
target 3D image, B.
5. The target registration error (TRE) is defined
as the mean euclidean distance (D) between
corresponding locations of the ground truth
and the computer estimation. Before registration, the TRE is computed between P and Q.
After registration, the TRE is computed between
P′ and Q, as illustrated in Figure 6. The TRE is
used to assess the accuracy of the registration
technique.
6. The above protocol is repeated several
times, and the TRE is computed. The mean and
SD of the TRE are calculated to determine
whether the system meets the required performance standards for clinical applications.
7. The above steps are repeated the same number of times for the 2 interpolation techniques,
TPS and EW, respectively. The mean and SD of
the TREs are calculated and compared.
Target registration error metrics are calculated
from the measurements obtained using the following equations. For each set of experiments,
the euclidean distance between P and Q is computed using Equation 4, where N is the total
number of beads in the phantom. The mean ( D )
and SD (σ) from all of the experiments were computed using Equations 5 and 6, respectively, as
follows:
(4)
(5)
(6)
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Results
Five custom-built tissue phantoms having 3 to 5
beads randomly located within each phantom
were used to evaluate the accuracy of the system.
For each tissue phantom, 10 to 15 TRUS scans
were obtained using the Falcon 2101 ultrasound
machine with a type 8667 transducer (5–10 MHz;
BK Medical, Herlev, Denmark). The first scan was
performed without any pressure. Remaining
scans were performed with varying mechanical
pressure applied in an arbitrary direction on the
tissue phantom. All scans were segmented, and
then the segmented surfaces from the same
phantom were registered with a corresponding
deformed phantom in pairs. Figure 7 shows an
example of overlapped surfaces before and after
registration as well as the locations of the beads
(both computer estimated and ground truth).
Altogether, the evaluation procedure was
repeated 100 times for each phantom, and then
the TREs for each trial were recorded both before
and after registration. The same procedure was
performed for both the TPS interpolation and
EW methods. Table 1 lists the TRE (both mean
and SD) for all phantom trials. The results for the
TPS and EW are shown side by side for comparison. Before system processing, the TRE was 6.4 ±
4.5 mm (range, 3–13 mm). After registration and
TPS interpolation, the TRE was 5.0 ± 1.03 mm
(range, 2–8 mm). After registration and EW interpolation, the TRE was 2.7 ± 0.99 mm (range, 1–4
mm). Figure 8 illustrates the TREs for trials on
phantom 4. In most cases, EW outperformed the
TPS method (2-tailed t test, P < .0011).
ods were implemented, and the results were
compared. Elastic warping outperformed the
TPS method in most cases. Both the TPS and EW
are approximations of prostate tissue property.
However, the TPS is used to solve a given finite
number of equations, more suitable to a collection of scattered points marking distinct surface
features, whereas EW tends to preserve the
shape and relative position of given point sets
because of its smoothness.19 Because the structure of the segmented surface is fairly consistent
on a case-by-case basis, EW is more appropriate
for our system. The EW approach is also more
robust compared with the TPS because the soluFigure 3. Biopsy planning graphical user interface. A, The previous visit to load
can be selected from the bottom right display quadrant. B, After the selected visit
is loaded, corresponding biopsy sites (white spheres) and surfaces (blue-green) are
displayed.
A
B
Discussion
We have presented a 3D prostate biopsy system
that can be used to map previous biopsy sites
onto a current ultrasound scan. This is very
important during a prostate biopsy procedure
because the urologist may want to either avoid
or rebiopsy previous sites.
A custom-built phantom was used to simulate
the prostate deformation between 2 scans.
Because the identification from the second scan
can serve as the ground truth, it can be used to
measure the performance of the registration system. In our experiments, 2 interpolation methJ Ultrasound Med 2009; 28:1561–1568
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A
Clinical application of either method will
depend on computing time. For a 15-minute
biopsy session, for example, it is desirable to have
a registration procedure done in 20 seconds. The
current central processing unit time for the registration procedure on an Intel Core 2 processor
(Intel Corporation, Santa Clara, CA) with a 2.66GHz clock speed is 150 seconds; this is unacceptable in clinical practice. When the registration
algorithm was implemented on a graphics processing unit (an 8800 GT video board running at
640 MHz and accessing 512 MB of onboard RAM;
NVIDIA Corporation, Santa Clara, CA), the running time was reduced to 12 seconds. For the
interpolation procedure, the TPS method can be
performed onboard the central processing unit
in 0.3 second, whereas the EW method requires
15 seconds. However, after EW migrated to a
graphics processing unit implementation, its
total time was reduced to 2.5 seconds. This meets
the clinical requirement.
B
Figure 4. Customized phantom design. A, Four views of the
design. B, beads distributed in the customized phantom.
Figure 6. Measurement of the registration error. Top, Overlaid
scans before registration. Bottom, Overlaid scans after registration.
tion of the former is solved iteratively, whereas
the TPS approach may construct a singular
matrix and may lead to a singular matrix error.
This error may result in a less accurate TRE for
the TPS approach.
Figure 5. Ultrasound scan with the identified bead (red).
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In addition to the errors introduced by the
interpolation methods, there are other sources of
error contributing to the overall TRE. A bead
identification error is introduced by the operator
while locating the beads in the phantom scan;
this is due to poor ultrasound scan image quality
and the software tool used. Table 2 lists the
experimental results for the bead identification
error. Three operators were requested to identify
the beads inside 6 phantom scans, respectively.
The locations were recorded and compared. The
overall bead identification error was 0.8682 ±
0.2377 mm.
Segmentation error is also important because
the segmented prostate volume is always different from the actual phantom volume. For example, in our experiments, the customized phantom
has a designed volume of 44 cm3, whereas the
average segmented volume is 36.77 cm3: a segmentation error of 8.07%. Also, the error due to
surface registration adds to the TRE. Image calibration and acquisition errors can also contribute to errors in the TRE.
Figure 7. Phantom validation. A, Prostate model surface
(white) and simulated biopsy sites (red). B, Deformed model surface (green) overlapped onto the original surface (white). Biopsy
sites from different sources are illustrated in different colors,
such as original biopsy sites (red), deformed sites (yellow), and
registered sites (blue).
A
Figure 8. Comparison of TREs before and after processing
using different interpolation methods.
Table 1. Comparison of TREs Before and After System Processing
(Registration and Interpolation)
TRE, mm
D
Dmax
B
Dmin
Postprocessing
TPS
EW
Preprocessing
µ
σ
µ
σ
µ
σ
6.396
4.500
6.915
4.626
5.880
4.390
5.060
1.630
6.220
1.840
3.787
1.960
2.727
0.995
3.784
1.288
1.995
0.857
Target registration errors from 2 interpolation methods (TPS and EW) are
also listed; EW gave better results.
Table 2. Bead Identification Error for 6 Phantom Trials
Trial
1
2
3
4
5
6
Maximal, mm
Minimal, mm
Average, mm
1.3265
1.6247
1.2384
2.5616
2.1363
0.9619
0.2500
0.7586
0.4223
0.2162
0.3063
0.2268
0.7112
1.007
0.7457
1.1802
0.8758
0.6886
Each trial had a different number of beads; the maximal, minimal, and
average identification errors for each trial are listed.
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There are other variabilities that may also introduce errors due to (1) probe or transducer settings,
(2) the scanning method during the ultrasound
scan or navigation, and (3) the changes in the
morphologic shape due to medications and
other factors. Issue 1 can be compensated by our
hardware interfaces,20 whereas the other 2 issues
related to the pressure of the probe or transducer
on the prostate gland and the shape deformation
can be mitigated by physician training and
motion compensation procedures.21
In conclusion, we have presented a 3D image
registration system in which previous patient
biopsy sites can be mapped onto a current
ultrasound scan. Our system is based on a
robust, surface-based registration algorithm.
The transformation method to project biopsy
sites after registration is fast and accurate. Two
interpolation methods were implemented and
compared, and has been shown that EW performs better than the TPS method. The registration system reported here is currently being
integrated in our Artemis system, a US Food and
Drug Administration 510(k)–approved 3D
TRUS-guided prostate biopsy system developed
by Eigen Inc (Grass Valley, CA). The phantombased validation results have been published,20
and the product is now at hospital sites for clinical validation.
7.
Kawata N, Miller GJ, Crawford ED, et al. Laterally directed
biopsies detect more clinically threatening prostate cancer:
computer simulated results. Prostate 2003; 57:118–128.
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Damber JE, Aus G. Prostate cancer. Lancet 2008; 371:
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Crawford ED, Hirano D, Werahera PN, et al. Computer
modeling of prostate biopsy: tumor size and location—not
clinical significance—determine cancer detection. J Urol
1998; 159:1260–1264.
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Lubeck DP, Grossfeld GD, Carroll PR. A review of measurement of patient preferences for treatment outcomes after
prostate cancer. Urology 2002; 60:72–77.
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Meng MV, Elkin EP, Harlan SR, Mehta SS, Lubeck DP, Carroll
PR. Predictors of treatment after initial surveillance in men
with prostate cancer: results from CaPSURE. J Urol 2003;
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Wilson SS, Crawford ED. Screening for prostate cancer:
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Cooperberg MR, Moul JW, Carroll PR. The changing face
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Crawford ED, Wilson SS, Torkko KC, et al. Clinical staging
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Shen F, Shinohara K, Kumar D, et al. Three-dimensional
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