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Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_5835_Библиотеки_им_академика_М_И_Перельмана.pdf
1.9.1 Early-Stage Prostate Cancer Management
The wide availability of the prostate-specific antigen (PSA) test and the increased
awareness of the public about prostate cancer have dramatically increased the num-
ber of men who have been diagnosed with early-stage prostate cancer [106]. For
men with early-stage prostate cancer, radical prostatectomy (the surgical removal of
the prostate) is often not a viable option due the morbidity (incontinence and impo-
tence) of the procedure. External beam radiotherapy can be effective; however, it
requires long treatment times and results in the irradiation of normal tissue [107].
Technological and pharmaceutical advances have led to the development of new
treatment options, such as brachytherapy, cryosurgery, hyperthermia, interstitial
laser photocoagulation (ILP), and photodynamic therapy (PDT). Of these new treat-
ments, brachytherapy is considered not only the most advanced but also the most
important treatment option for early-stage prostate cancer [108–110].
The following section describes a 3-D US-guided prostate brachytherapy appli-
cation that has been developed in our laboratory.
14 3-D Ultrasound Imaging
(c) (d)
(a) (b)
Figure 1.6 Two 3-D ultrasound images of the carotid arteries showing both the MPR and VR
approaches. (a) MPR view of a 3-D US image sliced parallel to the skin in the longitudinal direc-
tion. (b) The same image as in part (a) but volume rendered, showing the surface of the carotid
artery and the details of the plaque. (c, d) MPR and VR views of another 3-D US image of a carotid
artery.
1.9.2 US-Guided Prostate Brachytherapy
Low-dose-rate (LDR) brachytherapy is presently the most common form of pros-
tate brachytherapy. By placing approximately 80 radioactive seeds (e.g.,
125
I) into
the prostate, the organ can be subjected to high doses of radiation while sparing the
surrounding tissue [108–110]. The delivery of a high conformal dose to the prostate
requires that the radioactive sources be properly planned and accurately positioned
within the prostate [111]. Thus, efficient and accurate 3-D imaging of the prostrate
are required to plan and guide the procedure.
The first phase of the procedure involves preimplantation dose planning (pre-
planning). CT or US images are used to delineate the margins of the prostate and the
structures sensitive to radiation. Using the information obtained from CT or US
images, as well as the radiation distribution around the seeds, physicians can deter-
mined the distribution of the radioactive seeds in the prostate [112]. The preplan is
then used to implant the seeds while the patient is positioned in approximately the
same position as in the preplan. The implantation of the radioactive seeds is typi-
cally carried out using TRUS guidance. After implantation, CT or fluoroscopy is
used to determine the actual positions of the seeds, which may be different from the
planned positions due to implantation errors or seed migration. The actual seed
positions are then used to calculate a postimplantation dose plan. If significant devi-
ations of dose are detected, then additional seeds may be implanted.
Although CT and fluoroscopy are still used to determine the positions of the
seeds, 3-D US is beginning to establish itself as an effective modality for planning
and guiding brachytherapy procedures. Rapid scanning and viewing of the prostate
using 3-D US will allow a complete intraoperative procedure to be performed [38].
3-D US will permit preimplant dose planning and seed implantation during the
same session; therefore, problems of repositioning, prostate motion, prostate
size/contour changes, and image registration between imaging modalities can be
avoided. 3-D US images will also permit immediate postimplant verification to
detect and correct implantation errors immediately. We have been developing an
intraoperative 3-D US brachytherapy system that uses software to contour the pros-
tate, segment and track the needles, and detect the seeds for postplanning dosimetry
of the prostate.
We have reported on our development of a 3-D US imaging technique for the
diagnosis of prostate cancer [39, 113], prostate cryosurgery [4, 5], and prostate
brachytherapy [45, 46, 114, 115]. The following section briefly describes our 3-D
US-guided prostate brachytherapy approach.
1.9.3 3-D TRUS-Guided Brachytherapy System
The introduction of our3-D TRUS imaging system has overcome several limitations
of the 2-D TRUS guided brachytherapy system by providing: (1) an interactive view
of the prostate, (2) a more efficient segmentation of the prostate boundary, and (3) a
process to monitor the insertion of the needle during implantation [2, 5, 39,
115–118]. These developments, coupled with several efficient 3-D reconstruction
and visualization software tools, have allowed for the development of an
intraoperative system capable of dynamic reoptimization and intraoperative
postplanning verification.
1.9 3-D Ultrasound-Guided Prostate Therapy 15
The following sections describe the integration of robotic aids and implementa-
tion of 3-D TRUS in the development of an intraoperative system for prostate
brachytherapy.
Our approach uses a one-hole needle guide, which is attached to the arm of a
robot so that the trajectory of the needle can be changed in response to the move-
ments of the robot. Once the robot has positioned the needle, the physician inserts
the needle into the patient’s prostate. The position of the guidance hole can be
moved so that the needle can target any point identified in the 3-D TRUS image [45].
In addition, we have developed a near real-time method for not only automatically
segmenting the needle and prostate but also for tracking brachytherapy needles dur-
ing oblique insertion. Tracking allows us to follow the needle as it exits the 2-D
TRUS image plane.
A schematic diagram and a photograph of our robot and 3-D TRUS-guided sys-
tem are shown in Figures 1.7 and 1.8, respectively. The prototype system consists of
an A465 industrial robotic system (Thermo-CRS, Burlington, Ontario, Canada)
with six degrees of freedom and a 3-D TRUS imaging system developed in our labo-
ratory [45]. The one-hole needle guide is attached to the arm of the robot and a soft-
ware module transforms the coordinate system of the robot to the coordinate system
of the 3-D TRUS. This transformation allows the hole of the needle guide and,
hence, the trajectory of the needle to be displayed and tracked with the 3-D TRUS
images [45].
The following sections describe our 3-D TRUS acquisition system and its role in
prostate segmentation, dosimetry, calibrations, and evaluations of errors using cali-
bration, needle tracking, and seed implantation.
1.9.4 3-D TRUS Imaging System
Our results were obtained using a B-K Medical 2102 Hawk ultrasound machine
(B-K, Denmark) with a side-firing 7.5-MHz transducer; however, our 3-D TRUS
system can becoupled toany USmachine using a side-firing transducer. The side-fir-
ing linear array US transducer is mounted on a rotational mover [116]. To generate
a 3-D image volume in the shape of a fan, the motorized mover rotates the trans-
ducer approximately 100° around its long axis [39]. As the transducer is rotated, the
16 3-D Ultrasound Imaging
Needle
Needle guide
Ultrasound
machine
Patient prostate
TRUS transducer
Control and
display computer
Mover
controller
Video
frame-grabber
Robot
Figure 1.7 Schematic diagram of the robot-aided and 3-D US-guided prostate brachytherapy
system. The diagram shows that the TRUS transducer is attached to a rotational 3-D scanning
mechanism and is inserted into the rectum below the prostate. The 3-D US scanning mechanism is
mounted on a robotic device used to guide the brachytherapy needles into the prostate.
2-D US images acquired from the US machine are digitized by a frame grabber at
0.7° intervals at 30 Hz for approximately 9 seconds. The acquired 2-D US images
are reconstructed in real time to form a 3-D US image. 3-D visualization software is
used to view the 3-D US image [116]. Figure 1.3 earlier in this chapter shows an
example of several views of a 3-D TRUS image acquired in this manner.
1.9.5 Prostate Segmentation
Manually outlining prostate margins is a time-consuming and tedious process.
Thus, a semi- or fully automated prostate segmentation technique that is accurate,
reproducible, and fast is required. Because 3-D US images suffer from shadowing,
speckle, and poor contrast, procedures for fully automated segmentation can result
in unacceptable errors. Our approach has been to develop a semiautomated pros-
tate segmentation algorithm that allows users to correct errors [119–122]. Because
the details of our prostate segmentation technique have been described elsewhere
[119–122], this section merely summarizes the details of our technique.
Our approach is to automatically segment the boundary of the prostate into
sequential slices of 2-D images. These boundaries are then merged to form the com-
plete shape of the prostate. Our 2-D segmentation technique uses model-based ini-
tialization and a discrete dynamic contour (DDC) model to refine the initial
boundary of the prostate [123]. Once the prostate has been initially sliced and seg-
mented, the boundary is propagated automatically to the next slice and segmented
until the entire prostate has been completed. This process requires three phases: (1)
The DDC is initialized by an approximate outline of the object, (2) the initial outline
is deformed automatically to fit the desired organ boundary, and (3) the boundary
is propagated repeatedly and deformed until the complete prostate has been
segmented.
1.9 3-D Ultrasound-Guided Prostate Therapy 17
Robot
Needle guide
Phantom
TRUS probe
Needle
Figure 1.8 A photograph of the robot-aided and 3-D US-guided prostate brachytherapy system,
showing the TRUS transducer inserted into an agar phantom used to test the system. (From: [45].
© 2004 American Association of Physicists in Medicine. Reprinted with permission.)
1.9.5.1 Initialization
The initialization phase requires the operator to select four or more points on the
boundary of the prostate in a 2-D image slice of the 3-D image. Two points on the
midline of the prostate define an axis of symmetry; two points on both sides of the
base of the prostate define the width [Figure 1.9(a)]. Additional points may be used
if the prostate deviates significantly from an elliptical shape. Using the initialization
points, the size, approximate shape, and initial boundary of the prostate can be com-
puted using a precomputed model equation [119] or using a spline technique [see
Figure 1.9(a)].
18 3-D Ultrasound Imaging
(f)(e)
(d)(c)
(b)(a)
Figure 1.9 Steps showing the 3-D prostate segmentation procedure. (a) The user identifies four
points on the prostate boundary in a 2-D section. These points are used to calculate an initial
boundary for the segmentation. (b) The initial prostate boundary in the 2-D section is segmented
by refining the initial boundary using the DDC approach. (c) The 3-D segmentation is completed
by repeatedly propagating the refined boundary in one slice to the next and refining it. (d) View of
the prostate sliced perpendicular to the rotational slicing axis showing the boundaries after propa
-
gation and refining through about 45°. (e) View of the prostate sliced perpendicular to the rota
-
tional slicing axis showing the boundaries after the 3-D segmentation has been completed. (f) The
boundaries have been surfaced and displayed with the crossed-planes approach. (From: [45].
© 2004 American Association of Physicists in Medicine. Reprinted with permission.)
1.9.5.2 Refinement
In the boundary refinement phase, the initial contour is decomposed into vertices
that are separated by approximately 10 to 20 pixels. As seen in (1.1), which is based
on simple dynamics, this initial boundary is used in the operation of the DDC. A
weighted combination of the internal force (
`
int
f
i
), the image force (
`
f
i
img
), and the
damping force (
`
f
i
d
) is applied to each ith vertex of the DDC, resulting in the total
force (
`
f
i
tot
). This boundary will evolve until the total force acting on each vertex is
zero.
`` ``
int int
fwfwf f
i
tot
ii
i
img
i
img
i
d
=+ +
(1.1)
The relative weights for the image force and internal force are w
i
img
and w
i
int
,
respectively. These forces are vector quantities having both magnitude and direc-
tion [124].
The external force at each vertex is proportional to the local image gradient,
which causes the vertex to seek regions of high image gradient. These regions are
typically located at the boundary of the imaged prostate. The internal force mimics
an elastic force that is proportional to the edge length. This force determines the
rigidity of the boundary, minimizes the local curvature at each vertex, and keeps the
boundary smooth in the presence of image noise. Adjusting the weighting of the
internal and external forces can optimize the segmentation of the prostate. We have
typically used w
i
img
= 1.0 and w
i
int
= 0.3 for each vertex. Figure 1.9(b) shows the
results of a refined boundary superimposed onto a prostate image that demon-
strates good segmentation.
1.9.5.3 Propagation
The segmented 2-D boundary of the prostate is extended to form a 3-D image by
propagating a contour onto an adjacent image slice. The deformation process
is then repeated by radially slicing the prostate at a constant angle (e.g., 3°) that
intersects along an axis that is close to the center of the prostate [122] as shown in
Figures 1.9 and 1.10.
The accuracy of the segmentation algorithm was tested by comparing its results
with the results obtained using manual planimetry. Using the volume of the prostate
obtained by manual planimetry as a reference, the errors in the semiautomated
approach ranged from an underestimate of 3.5% to an overestimate of 4.1%. The
mean error was found to be −1.7% with a standard deviation of 3.1% [122].
Segmentations of the prostate require approximately 5 seconds when implemented
on a 1-GHz PC.
1.9.6 Dosimetry
We use AAPM TG-43 formalism, which uses predetermined dosimetry data in dose
rate evaluation [125]. After delineating the organs, users select the type of radioac-
tive source and enter its calibration data. The possible area of insertion is outlined,
and the preplan is produced using approximately 20 needles, which can be oriented
in oblique trajectories to avoid any interference with the pubic arch.
1.9 3-D Ultrasound-Guided Prostate Therapy 19
The isodose curves are displayed on the 3-D TRUS image in real time as well as
on a view that is surface rendered, which shows the needles and seeds. Because each
needle can be individually activated or deactivated, the modified isodose curves can
be observed instantly. Users can evaluate the plan using dose–volume histograms for
each organ and make the necessary modifications. Once the needle has been
retracted, the actual seed locations are determined or are assumed from the location
of the needle, and the new isodose curves are displayed. Once the needle has been
retracted, users have the option of modifying the plan according to the real seed
locations. Figure 1.11 shows an example of the use of the preplanning software for
planning an oblique trajectory of a needle.
1.9.7 Calibration of the Coordinate Systems
The goal of the calibration procedure is to determine the transformation between
the coordinate system of the 3-D TRUS image and the coordinate system of the
robot. This procedure involves the following two steps: (1) map the coordinate sys
-
20 3-D Ultrasound Imaging
(b)
(a)
Rotation
axis
180°
90°
0°
Figure 1.10 (a) A 3-D US prostate image showing the rotational slicing geometry used to seg-
ment the prostate in 3-D. (b) A 3-D US image showing the segmented 3-D boundary of the pros-
tate. (From: [122]. © 2003 American Association of Physicists in Medicine. Reprinted with
permission.)
tem of the transducer to the 3-D TRUS image (image calibration), and (2) map the
coordinate system of the robot to the transducer (robot calibration). The transfor-
mation between any two coordinate systems is found by solving the orthogonal Pro-
crustes problem as follows: Given two 3-D sets of points, K = [k
j
] and L = [l
j
] for j =
1, 2, …, N, and a rigid-body transformation, F: l
j
= F(k
j
) = Rk
j
+ T, where R is a 3 × 3
rotation matrix and T is a 3 × 1 translation vector, minimize the cost function as
shown:
(
)
C
N
lRkT
jj
j
N
=−+
=
∑
1
1
2
(1.2)
A unique solutionexists if, and only if, the sets of points K and L contain at least
four noncoplanar points [126].
1.9 3-D Ultrasound-Guided Prostate Therapy 21
(d)(c)
(b)(a)
Figure 1.11 The 3-D images from a typical prostate brachytherapy dose plan with oblique nee-
dle trajectories for use with 3-D TRUS guidance and robotic aids. Our 3-D visualization approach
allows display of a texture-mapped 3-D cube view of the prostate, extracted planes, and graphical
overlays of surfaces and contours. (a) Coronal view with delineated organs, needles, seeds and
isodose curves, (b) sagittal view, (c) transverse view, and (d) surface rendered view showing the
organs and needles with seeds.
To calibrate the image, we used a phantom that contained three sets of nylon
strings with diameters of 1 mm orthogonally positioned in a Plexiglas box. Each set
of strings was immersed in an agar gel and placed 1 cm apart. The coordinates of the
intersections of the strings were determined in the coordinate system of the US trans-
ducer from the design of the phantom. The coordinates of the points in the 3-D
TRUS image coordinate system were determined by imaging the intersections of the
strings in 3-D. Using the coordinates of the intersections created by the orthogonally
positioned strings, we determined the transformation that mapped the coordinate
system of the transducer to the 3-D TRUS image by solving (1.2) [45].
To calibrate the robot, we used two orthogonal plates mounted on a device to
hold the transducer and drilled five hemispherical divots on each plate to produce
homologous points in the coordinate system of the transducer and in the coordinate
system of the robot. The coordinates of the divot centers in the coordinate system of
the transducer were known from the design of the plate, and the coordinates of the
divot centers in the coordinate system of the robot were determined by moving the
robot so that it sequentially touched the divots with a stylus tip, which was attached
to the arm of the robot. Using the coordinates of the divots in the two coordinate
systems, we determined the transformation that mapped the coordinate system of
the transducer to the coordinate system of the robot by solving (1.2).
1.9.8 Needle Segmentation
Our approach to robot-assisted brachytherapy allows for the implantation of the
needle to be nonparallel, meaning the conventional template does not require a set
of rectilinear holes. The needle may, therefore, be inserted in an oblique trajectory,
which will result in the image of the needle exiting the real-time 2-D US image. Thus,
it is necessary to track the tip of the needle as it is being inserted into the prostate in
order to ensure proper placement of the needle and to avoid implanting the seeds at
incorrect locations.
Our approach to tracking uses near real-time 3-D US imaging to segment the
needle in three dimensions; display the oblique sagittal, coronal, and transverse
views; and highlight the trajectory of the needle [46, 117, 118, 127]. Because the
needle may be angled approximately 20° from the orientation of the 2-D US plane,
and a series of 2-D images may be acquired at 30 images per second, a new 3-D
image may be formed in less than 1 second. From these 3-D images, a needle may be
automatically segmented [46, 117, 118], and the three planes needed to visualize the
insertion of the needle may be displayed immediately. Figure 1.12 shows the results
of tracking the insertion of a needle into a prostate.
1.10 Evaluation of 3-D TRUS-Guided Brachytherapy System
Using test phantoms, we evaluated the performance of our robot-aided system and
3-D TRUS-guided brachytherapy system. The following sections discuss the meth-
ods and results of calibration as well as the accuracy of needle placement, needle
angulation, targeting, tracking, and seed implantation for the 3-D TRUS-guided
brachytherapy system.
22 3-D Ultrasound Imaging
1.10.1 Methods of Calibration
Evaluations of the calibrations of the image and robot were performed by analyzing
the accuracy of the point-based, rigid-body registration and calculating the fiducial
localization error (FLE), fiducial registration error (FRE), and target registration
error (TRE) [128].
1.10.1.1 Fiducial Localization Error
The FLE isa statistical measure of the error in locating the fiducial points used in the
registration process [129]. We have assumed that the mean value of the error in
locating the fiducial points is zero and have calculated the root-mean-square (rms)
distance between the exact and calculated fiducial positions using [130]:
FLE
2 222
=++σσσ
xyz
(1.3)
The variances of the errors in locating the fiducial points along the three
orthogonal axes are given by
σ
x
2
,
σ
y
2
, and
σ
z
2
. Each of the variances is calculated
using (1.4):
(
)
σ
ij ijk ij
k
n
n
xx
2
2
1
1
1
=
−
−
=
∑
(1.4a)
1.10 Evaluation of 3-D TRUS-Guided Brachytherapy System 23
Transverse view with needle projected
(a)
(b)
(c)
Coronal view
Sagittal view
Figure 1.12 Example of the views displayed during oblique needle tracking in a patient’s pros-
tate. (a) Oblique sagittal view showing the oblique plane with the needle, and (b) oblique coronal
view showing the plane with the needle (this view cannot be obtained with conventional US sys-
tem). (c) The 3-D TRUS image was sliced in a transverse direction showing the segmented needle
trajectory.