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correlation of visual acuity loss with the mean (r = 0.49,
p = 0.001) and maximum (r = 0.47, p = 0.001) retina dose
and tumor basal diameter (r = 0.50, p < 0.001). The dose
to the macula showed no correlation with visual outcome
(r = 0.24, p = 0.12). In the subgroup of patients with
anterior tumor locations the maximum retina dose
remained the only predictive factor (r = 0.46, p = 0.043).
Evaluating the Cox proportional hazards model yielded a
significantly higher risk for visual acuity loss (of more than
0.3 Snellen) for patients receiving a maximum dose of
500 Gy or higher (p = 0.009). A Cox multivariate analysis
including the macula dose (p = 0.11) and basal diameter
(p = 0.78) showed that a high maximum retinal dose is the
highest risk factor (p = 0.017). The evaluation of the BED
metrics showed no better correlation with the
investigated endpoints and in some cases BED was even
inferior.
Conclusion
The study showed that retina dose (D
2
and D
mean
) is a
suitable predictor for visual acuity loss, especially in case
of anterior tumors where other risk factors (i.e. basal
diameter) fail.
References
[1] R.G. Dale and B. Jones. The clinical radiobiology of
brachytherapy. Br. J. Radiol.
71
, 465-483 (1998)
PV-0186 MaxiCalc: a tool to calculate dose distributions
from measured source positions in HDR brachytherapy
M. Hanlon
1
, R.L. Smith
2
, R.D. Franich
1
1
RMIT University, School of Science, Melbourne, Australia
2
The Alfred Hospital, Alfred Health Radiation Oncology,
Melbourne, Australia
Purpose or Objective
Dosimetric treatment verification via source tracking in
HDR brachytherapy requires evaluation of the delivered
dose as source dwell positions are detected. Current TPSs
are not configured to perform this function, hence a fast
dose calculation engine (DCE) that can accept the input of
arbitrary dwell positions from the source tracking system
is required. Here we present a TG-43 based DCE that
computes 3D dose grids for measured dwell positions and
performs a comparison with the treatment plan.
Material and Methods
The DCE, dubbed MaxiCalc, takes the input of measured
dwell positions and times and calculates a dose grid of
nominated dimensions and grid spacing for direct
comparison to the treatment plan. MaxiCalc was validated
against Oncentra Brachy (OCB v4.3) at 27 single dose
points, as per OCB commissioning, as well as a 3D dose grid
of 13 dwells.
Dwell positions and times delivered in a phantom were
measured by our source tracking system, as previously
published.
1
The measured dwell positions were then used
as input to MaxiCalc and the resultant dose grid compared
to that from OCB. Observed dose differences due to
source position measurement uncertainties were
investigated.
Results
For the 27 dose points, MaxiCalc differed from OCB by a
mean of 0.08% (σ=0.07%, max 0.41%) demonstrating
differences that are similar to those between published
values
2
and OCB. In a multi-source plan for doses between
50-200% of the prescription dose, MaxiCalc yields a
maximum difference of <1%, which arises due to minor
calculation differences in the steep dose gradients near
the source. There was a gamma pass rate of >99% at
1mm/1%.
A dose grid was calculated for a plan of 25 dwell positions
acquired using our source tracking system, there was
maximum difference of 12.2% (mean = 0.7%). The
maximum difference arises from a small shift in the
apparent dwell positions causing large differences due to
the high dose gradients near the source, which is only
significant within 10 mm of the source. For this volume of
interest, only 0.2% of voxels differ by >5%, showing good
agreement throughout. Results from measured delivery
errors, such as those in figure 1, will also be presented.
Figure 1: Dosimetric comparison between planned and
delivered doses for a HDR brachytherapy treatment in a
phantom with an introduced error.
Conclusion
Real-time dosimetric treatment verification is possible
with our source tracking system combined with MaxiCalc.
Fast dose calculation based on measured source dwell
positions is achieved and overcomes the limitation of
current TPSs.
References
1.
Smith, R L., et al. Medical physics 43.5 (2016):
2435-2442.
2.
Daskalov, G M., et al. Medical physics 25.11
(1998): 2200-2208.
PV-0187 Source dwell time and transit time
measurement for a HDR afterloading unit
T.L. Chiu
1
, B. Yang
1
, H. Geng
1
, W.W. Lam
1
, C.W. Kong
1
,
K.Y. Cheung
1
, S.K. Yu
1
1
Hong Kong Sanatorium & Hospital, Medical Physics &
Research Department, Happy Valley, Hong Kong SAR
China
Purpose or Objective
To evaluate dwell time and transit time of HDR
brachytherapy treatment by an in-house fluorescent
screen based QA system. Since dosimetric effect would be
directly affected by source dwell time, an accurate QA
method on temporal accuracy is essential.
Material and Methods
The system included a fluorescent screen (Kodak, Lanex
regular screen) which converts the radiation signal to
optical signal and a high-speed camera with frame rate up
to 500 fps and pixel resolution of 1280X720. The temporal
resolution was 2 ms. A catheter in which an Ir-192 source
would be loaded was fixed on the fluorescent screen and
the camera was placed 30 cm away from the screen. The
whole system was light-shielded. When the source
travelled inside the catheter, the camera would capture
images on the fluorescent screen sequentially. Source
position was traced out by locating the centroid of the
captured image. The accuracy of dwell time was assessed
by measuring 3 different dwell times, namely, 1 s, 0.5 s &
0.1 s. According to a white paper from vendor, transit time
for separations below 35 mm would occupied part of the
next dwell time and those for separations above 35 mm
would have 0.1 s compensation. Thus, the influence of
transit time on dwell time was studied by measuring 0.5 s
dwell time under 3 different dwell separations, namely, 6
cm, 4 cm & 0.5 cm. Dwell time was assessed by counting
the number of images in which source positions were
unchanged to the subsequent image. Transit time was the
time between two dwell positions.
Results