A Method for Portal Verification of 4D Lung Treatment
Geoffrey Hugo1, Di Yan1, Lindsay Watt2, Carlos Vargas1, Mark Oldham1, Daniel Létourneau1, John Wong1
1
Radiation Oncology Department, William Beaumont Hospital, Royal Oak, Michigan, USA
2
Elekta, Inc., Crawley, UK
Abstract
The implementation of respiratory-compensated treatment techniques requires new methods for verification. Specifically, a
technique which creates the planning target volume at the mean position of the tumor position as a function of time must be
associated with verification that this mean position is stable throughout the treatment. This study focuses on the development of a
"4D" portal verification technique formed from a respiratory correlated computed tomography scan. An onboard cone beam CT
was used to generate a respiratory correlated scan; a digitally reconstructed fluoroscopic movie (DRF) was then generated from
the volumetric data for each beam portal. For daily verification, fluoroscopic imaging using the same cone beam equipment is
acquired along each beam portal. The resulting fluoroscopic data and the DRF can be compared for conventional patient position
and orientation verification, as well as for verification of the extent and pattern of tumor motion to ensure stability of the mean
tumor position.
Keywords
4D, Respiratory correlated CT, Cone beam, lung cancer.
Introduction
Dose escalation in lung cancer has required the advent of new
methods to improve the accuracy and precision of targeting.
Techniques such as active breathing control [1] and voluntary
breath hold [2] aim to reduce tumor motion. Other methods
aim to compensate for respiratory motion by gating on a
respiratory signal [3, 4] or by adjusting the position and size of
the planning target volume (PTV) [5].
Regardless of the method utilized for respiratory compensation
during treatment, simulation and planning must also account
for "4D" changes in the patient volume due to respiration. The
development of prospectively [6] and retrospectively [7, 8, 9]
gated CT has allowed for the development of 4D planning
techniques to complement respiratory-compensated treatment
techniques.
Margins for the creation of the internal target volume (ITV) are
patient-specific, minimized based on the probability density
function of tumor position and on the planned dose distribution.
As reported [5], the margins are mainly dependent on the
standard deviation of the density function, while less effected
by the actual shape of the density distribution. The PTV is
created from the ITV using population-based interfraction
motion data initially, and the PTV margins are modified after 4
fractions based on patient specific setup information in an
adaptive approach. This adaptive method is similar to an
approach used clinically for the treatment of prostate cancer
[10].
However, the development of treatment verification methods
for 4D treatment has not been explored. The purpose of this
study is the development and validation of a "4D" portal
verification technique for 4D-planned lung treatment.
Material and methods
Effects of patient respiratory motion can be minimized by
designing the treatment plan with the target at the mean
respiratory position [5]. This mean position can be found using
the maximal positional excursion of the tumor (derived from a
retrospectively-gated CT scan) and the probability density
function of the tumor position (derived from a fluoroscopic
scan over multiple breathing cycles). The probability density
function is simply a histogram of tumor center of mass position
as a function of time, where the bins of the histogram are based
on the tumor position. An example histogram is shown in Fig.
1.
Figure 1: Probability density function of tumor position as a
function of time. Due to the near-sinusoidal nature of
respiratory-driven tumor motion, the histogram is weighted
higher near the end exhalation and inhalation positions.
The use of a mean position approach for respiratory
compensation relies on the assumptions that the mean position
of the tumor and the standard deviation of the motion are
reproducible over the course of one fraction or between
subsequent fractions.
This assumption holds when the
maximum excursion of the tumor (amplitude) and the
probability density function of the tumor position remain
constant both intra- and interfraction. The portal verification
technique for 4D lung cancer radiotherapy must allow
conventional parameters such as position and orientation to be
verified. In addition it should also provide information on the
amplitude and probability density of the tumor motion.
The method of 4D fluoroscopic portal verification consisted of
the creation of a digitally reconstructed fluoroscopic movie
loop (DRF) from a respiratory-correlated CT scan for each
beam portal. Before the treatment of each beam, the DRF
could then be compared to a fluoroscopic movie loop acquired
at the same angle as the beam portal. First, the position and
orientation of the bony anatomy could be verified, as with a
conventional DRF. Then, the amplitude and probability
distribution (frequency) of the tumor motion could be verified
in order to confirm that the mean position of the tumor was
stable.
subsequent production of a breathing trace based on the
superior/inferior position of this edge was based on a
previously published algorithm [11]. The advantage of such a
technique is that an external respiratory signal from external
markers or a spirometer is not necessary.
Each volumetric CT set for each individual phase was imported
into a treatment planning system (Pinnacle, Philips Medical
Systems, Best, The Netherlands). The CT scans were fused
based on vertebral bodies only. A physician outlined the gross
tumor volume (GTV) for each phase. The mean tumor position
was determined using the center of mass of the CTV from the
two phases that corresponded to the maximal tumor excursion
(the end inhalation and end exhalation phases). Using these
two positions, the mean CTV position can be determined by
averaging the probability density function, which is generated
from the fluoroscopy study.
Digitally reconstructed fluoroscopy
In order to create a DRF, two separate studies are required.
Both a respiratory correlated CT and a fluoroscopic study
containing both the tumor and the diaphragm are used to create
the DRF. For this paper, an onboard cone beam CT (Elekta
Synergy, Elekta Oncology Systems, Crawley, UK) was used to
generate volumetric data for six independent respiratory
phases. Figure 2 shows an example scan, which consisted of
the acquisition of 1012 projections dispersed around 360
degrees of gantry rotation. Approximately 168 projections
were used to reconstruct a volume image for each respiratory
phase. Assuming a breathing period of 4s and a projection
acquisition rate of 2 projections per second, the angular spread
for the acquisition of one respiratory cycle was 2.4 degrees.
Each individual projection was sorted into one of six phases
based on the position of the diaphragm in the projection image.
The algorithm for the detection of the diaphragm edge and
The DRF for each beam portal is created by first producing a
DRR from each volume image. The probability density
function is then used to calculate the time length of each DRR
frame in the DRF as a fraction of the total length of the DRF
movie loop. The DRF is then assembled from each of the
individual DRRs.
Fluoroscopic portal verification
The onboard cone beam CT allows for fluoroscopic imaging at
a static gantry angle in addition to x-ray volumetric imaging
(XVI). The kV imaging plane is oriented 90 degrees to the
megavoltage treatment plane, so the gantry is rotated 90
degrees for each beam portal to allow the fluoroscopic beam
portal to correspond to the intended megavoltage beam portal.
A few seconds of fluoroscopic imaging data is acquired for
each beam portal.
Figure 2: Coronal sections from a respiratory correlated cone beam CT. Each image is corresponds to the same position spatially, each from a
different phase of respiration. The cycle proceeds clockwise from top left.
Figure 3: DRF for an AP beam. Each individual DRR corresponds to the same phase as in figure 1. The cycle proceeds clockwise from top
left.
Verification of the beam portal is comprised of two separate
procedures. First, the patient position and orientation are
verified using the visible bony anatomy. Second, the extent of
tumor motion and probability density of motion are verified.
The extent of tumor motion can be verified qualitatively by
assessing the position of the tumor at end inhalation and
exhalation on both the DRF and fluoroscopic movies. The
probability density can be assessed qualitatively by measuring
the period of motion in terms of number of frames between
successive end inhalation or exhalation positions. If the tumor
is not visible, then the diaphragm can be used as a surrogate for
verifying the stability of the respiratory cycle.
Currently, quantitative measures of the stability of the
respiratory cycle are being investigated. The extent of tumor
motion and the probability density function are already
measured from the respiratory-correlated CT and fluoroscopic
Figure 4: Fluoroscopic frames corresponding to the frames for the DRF in figure 3. The cycle proceeds clockwise from top left.
study during simulation. Work is under way to develop a
similar quantitative analysis of the diaphragm position on the
fluoroscopic movies.
Results and discussion
Figure 3 shows all the frames from a DRF movie loop. Figure
4 shows the frames from the corresponding fluoroscopic loop
for an AP beam portal. These two movie loops allow patient
position and orientation, as well as the extent and probability
distribution of motion, to be compared. From this comparison,
the stability of the mean position and standard deviation of
motion of the tumor can be assessed.
Conclusion
The implementation of respiratory-compensated radiotherapy
requires additional verification with respect to treatment with
conventional methods. The stability of the patient’s respiratory
cycle must be verified over the course of one treatment and for
subsequent treatments. A DRF with fluoroscopic portal images
is one possible method for implementing this additional
verification. This technique allows for the verification of
patient position and orientation as well as the extent and
probability distribution of respiratory motion. The extent and
probability distribution of respiratory motion must be stable in
order to ensure that the location and size of the PTV is correct.
Studies are underway to assess the intra- and interfraction
stability of the mean position-based PTV.
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