Download audio-visual biofeedback for respiratory

Int. J. Radiation Oncology Biol. Phys., Vol. 65, No. 3, pp. 924 –933, 2006
Copyright © 2006 Elsevier Inc.
Printed in the USA. All rights reserved
0360-3016/06/$–see front matter
doi:10.1016/j.ijrobp.2006.02.035
PHYSICS CONTRIBUTION
AUDIO-VISUAL BIOFEEDBACK FOR RESPIRATORY-GATED
RADIOTHERAPY: IMPACT OF AUDIO INSTRUCTION AND AUDIO-VISUAL
BIOFEEDBACK ON RESPIRATORY-GATED RADIOTHERAPY
ROHINI GEORGE, PH.D.,*† THEODORE D. CHUNG, M.D., PH.D.,* SASTRY S. VEDAM, PH.D.,*
VISWANATHAN RAMAKRISHNAN, PH.D.,‡ RADHE MOHAN, PH.D.,§ ELISABETH WEISS, M.D.,*¶ AND
PAUL J. KEALL, PH.D.*
Departments of *Radiation Oncology, †Biomedical Engineering, and ‡Biostatistics, Virginia Commonwealth University, Richmond,
VA; §Department of Radiation Physics, The University of Texas M. D. Anderson Cancer Center, Houston, TX; and ¶Department of
Radiation Oncology, Georg-August-Universität, Göttingen, Germany
Purpose: Respiratory gating is a commercially available technology for reducing the deleterious effects of motion
during imaging and treatment. The efficacy of gating is dependent on the reproducibility within and between
respiratory cycles during imaging and treatment. The aim of this study was to determine whether audio-visual
biofeedback can improve respiratory reproducibility by decreasing residual motion and therefore increasing the
accuracy of gated radiotherapy.
Methods and Materials: A total of 331 respiratory traces were collected from 24 lung cancer patients. The protocol
consisted of five breathing training sessions spaced about a week apart. Within each session the patients initially
breathed without any instruction (free breathing), with audio instructions and with audio-visual biofeedback.
Residual motion was quantified by the standard deviation of the respiratory signal within the gating window.
Results: Audio-visual biofeedback significantly reduced residual motion compared with free breathing and audio
instruction. Displacement-based gating has lower residual motion than phase-based gating. Little reduction in
residual motion was found for duty cycles less than 30%; for duty cycles above 50% there was a sharp increase
in residual motion.
Conclusions: The efficiency and reproducibility of gating can be improved by: incorporating audio-visual
biofeedback, using a 30 –50% duty cycle, gating during exhalation, and using displacement-based gating.
© 2006 Elsevier Inc.
Audio-visual biofeedback, Respiratory-gated radiotherapy, Residual motion.
INTRODUCTION
Respiratory motion affects all tumor sites in the thorax and
abdomen, although the disease of most prevalence and
relevance for radiotherapy is lung cancer. Many studies
have been performed to study lung-tumor motion (1–14). It
can be seen from these studies that the magnitude of lung
motion is highly variable: for example, observed tumor
motion ranges from 0 to 5 cm for free breathing (9). Respiratory-gated radiotherapy (15–32) is a method to limit the
deleterious effects of respiratory motion during computed
tomography (CT) imaging (3, 12, 16, 33– 41) and radiation
delivery (42– 47).
Two important parameters that affect respiratory-gated
treatments are (1) the part of the breathing cycle during
which gating is performed and (2) duty cycle, the percentage of the beam on time to the total beam time (15, 21, 48).
To acquire maximal benefit from a gated treatment, gating
should preferably be performed at peak inhale or peak
exhale, as mobility of internal anatomy is at its minimum at
these positions. Vedam et al. (15), in a 5-patient study, have
shown that gating during exhale is more reproducible than
gating during inhale. As the duty cycle decreases, the radiation-treatment time increases because the beam will be
turned off for a longer period of time during the respiratory
cycle. This is speculated to result in an increase in patient
movement from the muscular skeletal system during delivery, which will negate the effect of the gating. Longer
radiation treatment time also negatively affects patient
throughput. Respiratory gating reduces but does not elimi-
Reprint requests to: Paul J. Keall, Ph.D., P.O. Box 980058,
Richmond, VA 23298-0058. Tel: (804) 628-0980; Fax: (804) 828
6042; E-mail: [email protected]
Acknowledgments—This research was supported by NCI grant
RO1 CA 93626. The authors thank Ms. Devon Murphy and Dr.
Michael Fix for carefully reviewing and significantly improving
the clarity of this manuscript. We also thank the simulation,
therapy and administrative staff at the department of Radiation
Oncology, Virginia Commonwealth University, for their help in
the coordination of this study.
Received Sept 2, 2005, and in revised form Feb 15, 2006.
Accepted for publication Feb 16, 2006.
924
Audio-visual biofeedback for respiratory-gated radiotherapy
nate respiratory tumor motion during radiotherapy. Large
duty cycles may result in a large residual motion within the
gating window. Residual motion is the remaining respiratory motion that exists during respiratory-gated radiotherapy caused by motion within the gating window for a given
breathing cycle and the cycle-to-cycle variations. For this
work, the magnitude of residual motion was quantified by
the standard deviation. In general, residual motion will
● R. GEORGE et al.
925
increase with duty cycle as more motion within each cycle
is included.
Typical beam duty cycle values during gated treatments
vary between 30% and 50% (21, 22, 49, 50). For respiratory
gating, minimizing the variation of patient breathing within
a treatment fraction and from fraction to fraction, i.e., increasing the reproducibility of patient breathing, is important. However, the respiratory-gating amplitude and period
Fig. 1. Schematic diagram showing phase- and displacement-based gating and how a baseline shift affects these techniques.
Phase-based gating at (a) inhale and (b) exhale. In this case, the beam is turned on when the respiratory signal is within
a specified phase, even if the signal shifts trends. The beam on is shown as thicker lines in the respiratory trace.
Displacement-based gating at (c) inhale and (d) exhale. In this case, the beam is turned on when the respiratory signal
is within specified position limits. Because of baseline shift, after a while the beam may not be turned on at all (c) or
turned on in the wrong phase (d). In the cases shown above for displacement-based gating, the respiratory signal should
be retracked.
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vary with time and from patient to patient because of
various anatomic and physiologic factors (51–57).
Respiratory gating is also affected by the technique selected to trigger the radiation beam, namely, displacementbased gating or phase-based gating (15). For regular respiratory motion, displacement-based and phase-based gating
essentially give the same result for a given duty cycle. However, the differences between these two techniques are exhibited during irregular breathing and especially in the case
of a baseline shift. Figure 1 shows an example of one such
an irregular trace exhibiting a baseline shift. In this case, the
patient’s breathing trace shifts out of the gating window,
and therefore the beam is not triggered at all or is triggered
at the wrong phase of the breathing cycle. In such situations,
the treatment has to be stopped, and the patient’s breathing
has to be retracked. However, during phase-based gating,
baseline shifts do not cause the treatment or simulation to be
interrupted and thus, irrespective of the position of the
target, while the phase of the breathing cycle is within the
gating window the beam is triggered.
Biofeedback techniques are being increasingly embedded
in the behavioral treatment of patients with lung disease
such as chronic obstructive pulmonary disease, asthma, and
cystic fibrosis (58 – 65). For respiratory gating, several studies suggest that verbal prompts improve respiration reproducibility (21, 28, 44, 49, 50). Kini et al. (28) concluded
that audio prompts improves the stability of respiration
frequency of the patient but does not maintain the range of
respiratory motion, whereas visual prompts control only the
regularity of the displacement and the frequency is not
reproducible. Based on the results of Kini et al., combined
audio-visual biofeedback was devised to improve the reproducibility of audio-visual biofeedback. Recently Neicu et al.
(66) described results of audio and visual prompting and
demonstrated improvement in the efficacy of so-called synchronized moving aperture radiation therapy, using respiratory traces from single-patient and volunteer sessions.
The aim of this study was to determine the reproducibility
of patient breathing with (a) no feedback, called free breath-
Volume 65, Number 3, 2006
ing, (b) audio instruction, and (c) audio-visual biofeedback
as a function of two variables used in respiratory gating: the
duty cycle and the gating technique, i.e., displacementbased or phase-based gating.
METHODS AND MATERIALS
Data collection
A total of 331 4-min breathing traces of patient-respiratory
motion using various types of feedback were collected for 24 lung
cancer patients enrolled in an Institutional Review Board–approved breathing feedback protocol. All lung cancer patients to be
treated with radiotherapy were approached for inclusion in this
study. No attempt was made to preselect patients for this study
other than by the inclusion criteria. These criteria were that the
patient: (1) was !18 years of age; (2) would undergo external
beam radiation at the Virginia Commonwealth University; (3) had
any form of lung cancer, with or without surgery, and with or
without chemotherapy; (4) was not oxygen dependent; (5) did not
experience pain while in the supine position; and (6) had given
signed informed consent. The patients’ respiratory traces were recorded using the Real Time Position Management (RPM) system
(Varian Medical Systems, Palo Alto, CA). A typical set-up is
shown in Fig. 2.
The protocol consisted of five respiratory training sessions
spaced about 1 week apart. Within each session, the patients
recruited for the protocol were initially asked to breathe normally
without any instruction or feedback (called a free-breathing session). Based on the breathing frequency recorded from the freebreathing session, the audio-instruction rate was determined.
Breathe-in/breathe-out instructions were given, and breathing was
recorded again for 4 min with audio instructions (referred to as an
audio-instruction session). Once the audio-instruction session was
completed, the patients were shown their respiratory trace on a
LCD monitor, which facilitates visual biofeedback. The visual
biofeedback showed the patients’ real-time respiratory motion
with the range of motion limits set as determined from the audioinstruction session. In addition to this visual biofeedback, the
patients were given audio instructions (referred to as an audiovisual biofeedback session). The breathing trace during this audiovisual biofeedback session was recorded for 4 min. If patients were
Fig. 2. Set-up for audio and audio-visual biofeedback showing a subject viewing the visual biofeedback on a liquid
crystal display screen. The respiratory signal obtained is the anterior–posterior motion of the marker block placed on the
abdomen of the subject between the umbilicus and the xyphoid. The television screen has a built-in speaker used during
the audio instructions and the audio-visual biofeedback.
Audio-visual biofeedback for respiratory-gated radiotherapy
uncomfortable with the set values for audio instruction or audiovisual biofeedback, the values were adjusted to comfort level on
the first day. These audio and audio-visual settings determined
during the first session were kept constant for the four subsequent
sessions.
The order of the respiratory data acquisition for each session
(free-breathing, audio, and audio-visual) was the same for all
sessions. This sequence of data acquisition could lead to potential
bias: an increase in reproducibility during each session as patients
relaxed and their breathing was less forced, and conversely a
decrease in respiratory reproducibility with time as a result of
fatigue. However, it was believed that the least biased way to
acquire free breathing was without the influence of breathing
training, i.e., before the breathing training. The training methods
(audio then audio-visual) were ordered such that the simple training came before the more complex training, again to reduce the
bias of the complex training on the simple training method.
The respiratory-motion data file obtained contains information
about the position of the patient’s breathing, the phase of the breathing cycle (0 –2") at that particular position and the time (0 –240 s)
for the particular feedback technique sampled at a rate of 30 Hz.
For an abdominal breather, anterior motion of the abdomen
corresponds to inhalation, and posterior motion of the abdomen
corresponds to exhalation. Patients positioned with their arms
extended above their head (typical for lung treatments) predominantly use their abdomen for breathing. Examples of breathing
traces 30 s in length and for all three breathing feedback types are
shown in Fig. 3.
Analysis of residual motion as a function of duty cycle
Although respiratory gating reduces the effects of patient
breathing variations within a treatment fraction and from fraction
to fraction, there is some amount of residual motion within the
gating window. For small duty cycles, however, the potential
advantage of small residual motion is mitigated by the increase in
treatment time leading to patient throughput issues and potential
errors resulting from musculoskeletally induced patient movement.
Large duty cycles may lead to errors caused by large residual
● R. GEORGE et al.
927
motion within the gating window. Thus, reducing treatment time
and increasing accuracy are competing goals.
The residual-motion data sets were tested for normality using
the Kolmogorov-Smirnov (67) test. After examining the D-values
from the Kolmogorov-Smirnov test and observing the probability
plots, D-values !0.08 were classified as approximately normal.
Although the 10% and 20% data sets had relatively high ("0.1)
D-values for the Kolmogorov-Smirnov test, the 30% to 100%
(with D-values ranging from "0.08 to 0.04 respectively) data sets
could be considered approximately normal, and thus the standard
deviation is appropriate to describe fully the distribution of the
residual motion.
For each breathing feedback type, the data of all patients for all
of the sessions were concatenated for analysis. To facilitate concatenating respiratory traces from different sessions and patients,
the respiratory traces were normalized such that the average of the
first three breathing cycles were set to 0. This normalization was
performed to be consistent with clinical gating treatments, as
tracking (learning the breathing cycle) is typically performed for
approximately 15 s (approximately three cycles) before the gated
treatment is initiated. Thus the assumption is that set-up accuracy
is maintained at gated position for each session at the start of the
session.
Gating techniques
The impact of breathing feedback on residual motion as a
function of duty cycle was investigated for phase- and displacement-based gating. For each training type (i.e., free breathing,
audio instruction, audio-visual biofeedback), each patient, and
each session, the respiratory trace was analyzed. For each respiratory trace, complete cycles were used to perform the phase- and
displacement-based analysis. If the respiratory signal was irregular
during simulation and treatment, the Real Time Position Management system did not initiate the CT simulator or the linear accelerator. Thus we excluded irregular respiratory motion by using the
phase values to determine complete cycles, which were included in
subsequent analyses. The two criteria for a complete cycle were
that (1) consecutive phase values were monotonically increasing,
and (2) the cycle started with phase values between the values 0
and 0.2 and ended with phase values between 6.1 and 6.28. The
rationale for the second criterion is that a regular breathing cycle
has approximately 120 points (4-s period at 30-Hz acquisition). As
the phase values were acquired discretely, the criteria of starting at
zero was approximated by ensuring that at least 1 data point had
phase !0.2. (For a 30-Hz signal acquisition, 3 or 4 points are
expected.) Similarly the end criterion of phase 6.1 assumes that at
least 1 point exists between 6.1 and 6.28.
Phase-based gating
In phase-based gating analysis, for both inhale and exhale for
each duty cycle interval, the standard deviations of the points
recorded in the gating thresholds were recorded. The percentage of
the duty cycle was increased from 10% to 100% in intervals of
10%, where 100% duty cycle indicated that no gating is performed. The breathing trace that was within this duty cycle range
was the residual motion and was grouped for all patients for all
sessions for each breathing type. The standard deviation is calculated from the data points within the phase-based gating window.
Fig. 3. Example of a respiratory trace for free breathing, audio
instruction, and audio-visual biofeedback. A constant y-offset
value has been added to the displacement values of each these
traces to improve the clarity of the figure.
Displacement-based gating
For displacement-based gating, the algorithm implemented to
calculate the duty cycle emulates the procedure followed in the
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clinic while treating a patient using displacement-based gating.
Unlike phase-based gating, during displacement-based gating the
beam is often turned off because of baseline shift, and the motion
is retracked to complete the treatment. Figure 1 shows a comparison of what happens in displacement-based gating as opposed to
phase-based gating in the presence of a baseline shift. At the point
at which the beam is not being triggered at all or is being triggered
at the wrong portion of the respiratory signal, the therapist turns off
the beam and the respiratory trace is retracked. For inhale and
exhale for each duty cycle the gating threshold was set depending
on the value for the initial 3 cycles. This value was kept constant
for each complete cycle, and the displacement within each duty
cycle was recorded. For each cycle, the number of points within
the duty cycle was checked, and if it exceeded #20% of the
initial duty cycle, the displacement parameter was acquired and set
again on the basis of the average of the next 3 cycles. The value
of #20% was chosen based on clinical experience in which the
gated treatment was stopped and retracked if the signal shifted by
approximately this amount. The standard deviation was calculated
from the data points recorded within the displacement-based gating window.
Types of comparisons
In accordance with the aims of this paper, two types of comparisons were made. First, free breathing, audio instruction and
audio-visual biofeedback were compared for each technique, i.e.,
separately for phase- and displacement-based gating. Second, a
comparison of the two techniques was made for free breathing,
audio instruction and audio-visual biofeedback; that is, the standard deviation of the residual motion for free breathing of phasebased gating was compared with the standard deviation of the
residual motion for free breathing of displacement-based gating.
For comparison, the percentage of the duty cycle was the same for
phase- and displacement-gated radiotherapy. An F test was used to
calculate the statistical significance of the comparisons.
RESULTS
Typical observations about patient breathing caused by
various types of training
The characteristics of the patients enrolled in this study
are given in Table 1 and Table 2. These tables show the
diverse nature of the patient population. Patients were not
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Table 2. Distribution of the discrete variables recorded
Variable
Distribution
Sex
Ethnicity
Disease stage
Surgery status
Chemotherapy status
Inhaler use
Female, 11; male, 13
White, 17; African American, 6; Asian, 1
NSCLC, 18; other, 6
With, 2; without, 22
With, 14; without, 10
Yes, 5; no, 19
preselected based on potentially favorable characteristics
such as young age, high Karnofsky performance status
(KPS), or high forced expiratory volume in 1 s (FEV1). In
general, patient tolerance of audio instructions and audiovisual biofeedback was good. Of the patients who enrolled in the study only 1 patient withdrew before completing a session. Furthermore, of the 24 patients who
completed at least one session, only 3 patients did not
complete the five sessions. One of the patients died half
way through the treatment, and the other two patients did
not continue because of pre-existing back pain when
supine.
The audio instructions tended to cause the amplitude to
increase as compared with the effects of the other two
training types. With the discrete audio instructions it was
observed, in some cases, that the transition of patient
respiratory motion from inhale to exhale was abrupt
rather than smooth. With the audio-visual biofeedback
the breathing cycles obtained for some patients tended to
be saw-toothed, as the patients did not have feedback of
their breathing phase between the upper (inhale) and
lower (exhale) limits set in the visual program. Limits did
not need to be changed once patients were comfortable.
Although this training was conducted on the day of
treatment, it was not performed on a linac, and so psy-
Table 1. Characteristics of the patients enrolled in the breathing
training study
Variable
Mean
Range
Age (y)
Height (cm)
Weight (kg)
Gross tumor volume (cm3)
Total dose (Gy)
Number of fractions
Smoking status (packs/year)
Fractional lung volume V20 (%)
FEV1 value (L)
Karnofsky performance status (%)
62
164
70
175
53
27
91
22
1.6
80
36–83
139–188
44–98
0.5–1920
20–70
5–37
25–700
2–38
0.5–3.3
40–90
FEV1 $ forced expiratory volume in 1 s.
Variables are continuous.
Fig. 4. Residual motion standard deviation for each duty cycle
value for phase-based gating comparing all three breathing types.
A $ audio instruction; AV $ audio-visual biofeedback; FB $ free
breathing.
Audio-visual biofeedback for respiratory-gated radiotherapy
Fig. 5. Residual motion standard deviation for each duty cycle
value for displacement-based gating comparing all three breathing
types. A $ audio instruction; AV $ audio-visual biofeedback;
FB $ free breathing.
chological factors such as patient anxiety could affect the
training during treatment.
Comparison of the three breathing types by
phase-based gating
The results of duty cycle versus the standard deviation of
residual motion are shown in Fig. 4. All comparisons made
below are statistically significant based on the F test. The
standard deviation values of the residual motion for gating
at exhale for all three breathing types are lower than the
corresponding values for gating at inhale.
For phase-based gating at inhale it is evident that audio
instruction has, on average, no reduction in motion compared with free breathing. Audio-visual biofeedback has an
average of 15% lower standard deviation of residual motion
● R. GEORGE et al.
929
compared with free breathing up to 90% duty cycle and
20% lower standard deviation of residual motion compared
with audio instruction for all duty cycles.
At exhale, audio-visual biofeedback has an average of a
15% lower standard deviation of residual motion compared
with free breathing up to an 80% duty cycle and an average
of a 10% lower standard deviation of residual motion compared with audio instruction. Audio instruction has an average of 5% lower standard deviation of residual motion
compared with free breathing up to a 60% duty cycle.
However, with a duty cycle %60%, the audio instruction has
a greater standard deviation of residual motion compared
with that of free breathing.
For all curves in Fig. 4, with the possible exception of the
inhale audio-visual biofeedback curve (also in Fig. 5, described below), there is very little reduction in residual
motion with a duty cycle !30%, indicating that of these low
duty cycles the residual motion is dominated by cycle– cycle
variations rather than intracycle motion.
Table 3 contains values of 1 standard deviation of the
residual motion for the duty cycles of 30% to 50%, which is
the typical gating duty cycle used the clinical setting (21,
22, 49, 50). For this range, audio-visual biofeedback has on
average a 25% lower standard deviation of residual motion
compared with free breathing and on average a 25% lower
standard deviation of residual motion compared with audio
instruction at inhale. In this range for inhale, audio instruction shows no improvement over free breathing in terms of
lower residual motion. At exhale, in the 30% to 50% range,
audio-visual biofeedback has an average of a 15% lower
standard deviation of residual motion compared with free
breathing and an average of a 10% lower standard deviation
of residual motion compared with audio instruction. Audio
instruction has a lower standard deviation of residual motion of 5% compared with free breathing at exhale for this
range.
Table 3. Population average residual motion standard deviation (1 #) and minimal and maximal individual patient values for
phase-based gating and displacement based gating from the 30% to 50% duty cycle range typically used clinically for
respiratory-gated treatments
Average residual motion (range)
Gating type
Phase-based gating
Inhale/exhale
Training type
30% duty cycle (cm)
40% duty cycle (cm)
50% duty cycle (cm)
Inhale
FB
A
AV
FB
A
AV
FB
A
AV
FB
A
AV
0.45 (0.14–0.73)
0.45 (0.20–0.65)
0.32 (0.12–0.66)
0.31 (0.11–0.57)
0.29 (0.12–0.51)
0.25 (0.12–0.46)
0.39 (0.13–0.62)
0.42 (0.16–0.61)
0.26 (0.10–0.45)
0.25 (0.07–0.50)
0.25 (0.06–0.46)
0.18 (0.09–0.32)
0.47 (0.15–0.76)
0.47 (0.21–0.66)
0.36 (0.13–0.68)
0.32 (0.12–0.58)
0.31 (0.14–0.51)
0.27 (0.13–0.48)
0.42 (0.15–0.64)
0.44 (0.19–0.62)
0.31 (0.10–0.49)
0.27 (0.11–0.51)
0.27 (0.10–0.50)
0.21 (0.08–0.34)
0.49 (0.18–0.80)
0.50 (0.21–0.68)
0.41 (0.15–0.69)
0.35 (0.13–0.59)
0.33 (0.16–0.50)
0.30 (0.14–0.49)
0.45 (0.17–0.67)
0.48 (0.19–0.67)
0.36 (0.11–0.60)
0.30 (0.13–0.54)
0.30 (0.10–0.49)
0.26 (0.09–0.37)
Exhale
Displacement-based gating
Inhale
Exhale
Abbreviations: A $ audio instruction; AV $ audio-visual biofeedback; FB $ free breathing.
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Comparison of the three breathing types by
displacement-based gating
The results of duty cycle versus the standard deviation of
residual motion are shown in Fig. 5. It can be seen that the
trends for displacement-based gating are the same as those
for phase-based gating. The number of baseline shifts observed was lowest for audio-visual biofeedback and ranged
on average between one and four occurrences per 4-min
session for duty cycles from 30% to 50%.
Our study shows that displacement-based gating has a
significantly lower standard deviation compared with phasebased gating. For free breathing, displacement-based gating
has an average of a 20% lower standard deviation of residual motion compared with phase-based gating for both
inhale and exhale. For inhale and exhale curves with audio
instruction, displacement-based gating has an average of
20% and 30% lower standard deviation of residual motion,
respectively, as compared with phase-based gating. Audiovisual biofeedback for displacement-based gating has very
little advantage over phase-based gating for inhale curves.
However, for exhale curves with audio-visual biofeedback,
displacement-based gating has an average of 40% lower
standard deviation of residual motion compared with phasebased gating.
An analysis of the variables in Table 1 and Table 2 that
had a significant correlation with residual motion were
disease type (SCLC vs. NSCLC) and dose per fraction for
both inhale- and exhale-based gating. Variables found to be
significant at inhale only were training type (both audio and
audio-visual), visual training displacement, and KPS.
DISCUSSION
Respiratory signal amplitude and period vary with time
and from patient to patient because of various factors (51–
57). This study acquired 331 4-min respiratory traces from
24 lung cancer patients to investigate the improvement in
the efficacy of respiratory gating using audio instruction and
audio-visual biofeedback. Although audio instructions have
been used previously for respiratory-gated radiotherapy,
this is the first investigation of the benefits of audio-visual
biofeedback for respiratory gating. Previous studies on comparison between the phase- and displacement-based respiratory gating techniques consisted of small patient sets
compared with the 24-patient data set used in this study.
Audio instruction and audio-visual biofeedback
From the results, it is clear that audio-visual biofeedback
reduces the residual motion standard deviation and thereby
increases the advantages of using respiratory gating for
radiotherapy imaging and treatment. Audio instruction, compared with free breathing, can benefit respiratory gating at
exhale up to a certain duty cycle. However, it is observed
that audio instruction increases overall respiratory magnitude. Increasing the magnitude of the respiration or, in this
case, the amplitude of respiratory motion clinically means
hyperventilation, which can potentially lead to fainting.
Volume 65, Number 3, 2006
A question arising from our investigations was whether
breathing training would increase the accuracy of treatments
without respiratory gating, corresponding to the 100% duty
cycle results shown in Fig. 5. The audio instructions alone
increased the magnitude of the respiratory motion and thus
would decrease the treatment accuracy. Audio-visual biofeedback had a similar magnitude to that of free breathing at the
100% duty cycle value, so no benefit would be obtained
using the method described here. However, our study was
not designed to minimize overall respiratory motion but
rather to improve respiratory reproducibility. Therefore audio-visual biofeedback designed to reduce respiratory motion may be effective and useful for treatments in centers
that do not have access to technology for the explicit sake of
managing respiratory motion.
Phase- and displacement-based gating
Our results show that displacement-based gating has a
lower residual motion standard deviation compared with
phase-based gating, a finding contradictory to that observed
in a smaller patient study by Vedam et al. (15). However,
displacement-based gating can be sensitive to sudden movement of the marker block, such as abrupt couch motion for
prospective gated CT scanning. Thus displacement-based
gating should be used with careful monitoring to ensure
accuracy of CT imaging. During CT imaging and treatment
delivery the respiratory trace needs to be monitored for
baseline shift if displacement-based gating is used.
For both phase- and displacement-based gating used with
free breathing, audio instruction, and audio-visual biofeedback, it is seen that the residual motion standard deviations
are lower for exhale compared with the respective inhale
values. This supports the common notion that the exhale
position is more reproducible and that the patient spends
more time at exhale than at inhale (13, 15, 68).
Clinically, the premise of respiratory gating relies on
correlation between the respiratory signal (in this case an
external respiratory signal) and the tumor motion. If a good
correlation exists, then it follows that reduction in respiratory marker motion variation will result in a reduction in
apparent tumor motion during respiratory-gated radiation
therapy.
Because respiration motion contributes to both systematic
errors (during imaging) and random errors (during treatment), a reduction in the effective respiration motion will
affect both of these contributors.
Range of duty cycle
We observed little reduction of residual motion for duty
cycles !30%, independent of the breathing type or inhale/
exhale. For phase-based exhale gating, residual motion starts
to increase at values %50%, and for inhale-based gating
residual motion starts to increase at values %30%. For displacement-based gating, for both exhale- and inhale-based
gating, residual motion starts to increase at values %30%.
Audio-visual biofeedback for respiratory-gated radiotherapy
● R. GEORGE et al.
931
Exhale- versus inhale-based gating
The advantage of treating at inhale as opposed to exhale
is that the lung volume is larger than at exhale, and therefore
the mass of lung receiving radiation is less at inhale as
compared with exhale. Recently, however, a gated intensity-modulated radiation therapy (IMRT) lung cancer study
showed limited benefit for treatment at regular, as opposed
to deep, inspiration levels (69).
Given that a good correlation is observed and remains
constant during treatment, the reduction of internal motion
with audio-visual biofeedback will be proportional to the
ratio of the magnitude of the external motion reduction.
Although this study uses external motion data to analyze
audio-visual biofeedback, the benefits of using this biofeedback will also be observed if used while tracking internal
motion, for example using the signal from radiopaque markers (8, 76) or electromagnetic transponders (77).
External versus internal respiratory signal
In this study, the external respiratory signal was analyzed.
There are several studies that correlate external respiration
signal to internal organ motion (70 –74, 48, 75). Vedam
et al. (71) reported a good correlation between diaphragmatic motion and abdominal motion (mean correlation coefficient, 0.94). Hoisak et al. (72) showed a correlation with
coefficients ranging from 0.51 to 0.98 between abdominal
motion and lung-tumor motion. Ahn et al. (73) found an
average correlation of 0.77 between skin and tumor movements with a range between 0.41 and 0.97. Schweikard
et al. (70) have also confirmed the hypothesis that external
motion is related to internal motion. Tsunashima et al. (74)
have also found an evident correlation between 3D tumor
motion and external respiratory motion obtained from laser
displacement sensors. Mageras et al. (75; personal communication, Mageras et al., 2004) investigated the lung-tumor
motion with respiratory correlated CT and found a correlation range of 0.73 to 0.96 with phase shifts !1 s. Berbeco
et al. (48) examined internal marker motion and the external
respiratory signal correlation in the respiratory gating context for 8 patients, observing beam-to-beam and day-to-day
variations; however an overall positive correlation was
found (inferred from the general reduction in residual motion with duty cycle). Thus, the external signal may potentially be used as a surrogate for lung-cancer motion, although these studies indicate that day-to-day variations in
tumor position can be significant and will not be detected by
the use of an external respiratory signal alone. From our
results and the previous works described, we can hypothesize that a reproducible respiratory signal is a necessary (if
insufficient) condition for reproducible tumor motion. From
this hypothesis the increase in respiratory reproducibility
observed will lead to improved tumor motion reproducibility. This hypothesis is the subject of an ongoing study.
Improved audio-visual biofeedback
The current audio-visual biofeedback system does not
yield information to guide the position of the patient’s
breathing at each instant in time but, rather, only at the
inhale and exhale points. This can limit the cycle-to-cycle
reproducibility. An improved audio-visual biofeedback system providing the patient with information to guide the
respiratory position throughout the breathing cycle may
further reduce the variability of the residual motion.
CONCLUSION
Respiratory gating effectively reduces motion during CT
imaging and radiation treatments. However, as the residual
motion increases, the gating accuracy decreases. Based on
the 24-patient, multisession study described in this article,
the following statistically significant conclusions can be made
regarding respiratory motion: (1) Audio-visual biofeedback
can significantly reduce residual motion variability for a
given duty cycle, thus potentially improving the accuracy
of respiratory-gating. (2) Displacement-based gating has a
lower residual motion variability compared with phasebased gating. (3) Duty cycles !30% provide little benefit
for respiratory gating, as there is only a slight reduction in
residual motion below this value at the cost of increased
treatment time. Duty cycles %50% show a sharp increase in
residual motion. (4) Exhale-based gating has a lower residual motion variability compared with inhale-based gating.
However, the potential of increased lung sparing at deep
inspiration levels of inhale may outweigh this increase in
residual motion.
In light of these findings, audio-visual biofeedback with
displacement-based gating using duty cycles of 30% to 50%
should be implemented when possible to improve the efficacy of respiratory gating.
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