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Vesicles (PSV), Prostate & Pelvic Nodes (PPN) and Head &
Neck (HN).
Material and Methods
A fully automated VMAT planning system has been
developed using the scripting functionality of RayStation
(RaySearch Laboratories, Stockholm, Sweden). For each
treatment site, a set of clinical priorities is determined as
a list of constraints and ‘tradeoffs’. The system is designed
to ensure constraints are met while optimization of the
prioritized tradeoffs is guided by an
a priori
calibration
process. This process involves optimizing for the first
priority trade-off with a range of objective weights. A GUI
allows the user to navigate through these plans using the
DVH and dose-distribution to determine the optimal
weight. This weight is then stored and the process is
repeated for the next priority. When all trade-offs have
been optimized, the whole process is repeated to refine
the set of objective weights.
As the underlying automated-planning algorithm tailors
the base plan to individual patient anatomy, a single set
of configuration data can be used for all patients of a given
site and plan can be generated with no user interaction.
Ten patients of each configured site were planned using
the automated system and compared against the clinically
approved manual plan. Quantitative comparisons were
made using relevant DVH metrics and qualitative
comparisons of dose distributions.
Results
A selection of the DVH metrics, averaged across all
patients in each site, is listed in Table 1. A set of
representative dose distributions is provided in Figure 1.
The tabulated data shows that the automated plans tend
towards improved OAR sparing. For PSV and PPN, this was
at the expense of target coverage. For HN plans, the
automated plans improved coverage while also reducing
OAR doses.
Visual comparisons of dose distributions showed that, for
all three sites, the automated plans were of equal or
better quality relative to manually optimized plans. All
plans met local clinical DVH constraints and were deemed
to be clinically acceptable.
Conclusion
A fully automated planning system has been developed
that allows configuration by expert treatment planners
and oncologists. The evaluative study presented shows
high quality plans can be produced with no user input,
following the initial site-specific configuration process.
This simple process allows high-quality automated plans to
be produced for new treatment sites in an efficient
manner.
OC-0447 CyberArc: a 4π-arc optimization algorithm
for CyberKnife
V. Kearney
1
, J. Cheung
1
, T. Solberg
1
, C. McGuinness
1
1
University of California UCSF, department of radiation
oncology, San Francisco CA, USA
Purpose or Objective
To demonstrate the feasibility of 4π-arc radiotherapy
using CyberKnife for decreased treatment delivery times.
Material and Methods
A novel 4π-arc optimization algorithm (CyberArc) was
developed and evaluated in 4 prostate and 2 brain cancer
patients previously treated with CyberKnife using Iris
collimation. CyberArc was designed for continuous
radiation delivery between beam and node positions using
4π treatment geometry. During beam delivery, the
isocenter and Iris collimator diameter are allowed to
freely move within machine tolerances. For comparison
purposes, new plans were generated using the same total
number of beams and range of Iris collimation. Dose
calculation was based on the MatRad pencil beam
algorithm, modified using the machine commissioning
data to fit the CyberKnife flattening filter free beam
profiles and percent depth doses. An initial 4π library of
beam coordinates is cast over the allowed delivery
space. A constrained subplex-based optimization
algorithm then selects from an initial library of 6 node
positions for each beam coordinate using a 5mm x 5mm
fluence map resolution to obtain the first set of
beam/node/collimator configurations. A preliminary
monitor unit calculation is performed, and
beam/node/collimator positions that fall under a
threshold are discarded. A 3D traveling salesman problem
is solved using a genetic algorithm to obtain the paths
between beams (
Figure 1)
. From the second set of
beam/node/collimator
positions,
intermediate
beam/node/collimator coordinates are calculated along
the path between neighboring coordinates using cubic
interpolation. A third set of continuous intermediate
beam/node/collimator doses are calculated every 2°
along the arc path with a 2mm x 2mm fluence map
resolution. MUs are calculated for each
beam/node/collimagor position using an L-BFGS-B
optimization engine. All plans were normalized to the 70%
dose volume of the PTV for comparison.
Figure 1. The set of final beam positions and their
corresponding paths for prostate patient 3.
Results
Among the six patients analyzed, the average difference
in PTV min dose, max dose, and V95 was 2.47% ± 2.13%,
4.11% ± 2.62%, and 1.63% ± 3.01% respectively. The
average conformity index (CI) was 1.09 ± 0.07 for the brain
patients and 1.12 ± 0.09 for the prostate patients.
Figure
2
shows the plan comparison DVHs for a prostate and brain