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S436
ESTRO 36 2017
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A radiation oncologist found 96% of cervical cancer beam
apertures were clinically acceptable, with all failures
caused by a slight error in the position of the superior
border. The primary and secondary aperture calculations
agreed with average DICE and mean absolute distance of
0.93 and 5.5mm, respectively. An example is shown
below. Automated beam weighting reduced hotspots by
1.5% on average.
Conclusion
Normal tissue segmentation for head/neck cancer patients
and determination of the jaw/MLC for cervical cancer
patients are very successful. Both have been introduced
into use in our clinic. Next steps include full evaluation of
the resulting dose distributions, and assessing the use of
these techniques for a prototype linac with flattening-
filter-free beam and novel MLC design.
PO-0821 Automatic re-planning of VMAT plans in
prostate and HN patients using constrained optimization
L. Künzel
1
, O. Dohm
2
, M. Alber
3
, D. Thorwarth
1
1
University Hospital Tübingen Eberhard Karls University
Tübingen, Section for Biomedical Physics, Tübingen,
Germany
2
University Hospital Tübingen Eberhard Karls University
Tübingen, Radiation Oncology Division of Medical
Physics, Tübingen, Germany
3
University Hospital Heidelberg, Radiation Oncology,
Heidelberg, Germany
Purpose or Objective
To develop and evaluate a new concept for automatic re-
planning of VMAT plans as failure concept for solitary
treatment machines, e.g. MR-Linac. In contrast to
previously published automatic planning approaches
which replicate the planned dose distribution, we propose
an automatic re-planning concept which uses constrained
optimization to generate Pareto-optimal VMAT plans for
different treatment machines. The scheme interprets a
treatment plan as a point on the corresponding Pareto
front, and creates the re-planned one by projecting this
point onto the substitute´s Pareto front. Thereby,
comparable biological effect and hence clinical outcome
can be guaranteed.
Material and Methods
In this automatic re-planning study, n=16 prostate cancer
and n=19 head and neck cancer (HNC) cases were
included. All patients had previously planned clinical
VMAT plans created with in-house TPS Hyperion. Hyperion
uses constrained optimization where a Lagrange multiplier
λi is associated to each cost-function constraint Ci, rating
the effect of each organ-at-risk (OAR) constraint on the
target objective.
Automatic re-planning starts from the initially reached
optimal constraints Ci for PTVs and OARs and adapted
machine parameters. A full optimization was executed
automatically, in order to generate a comparable Pareto-
optimal plan. For prostate cases, Elekta BeamModulator
plans were re-planned for Elekta Agility, whereas for HNC,
Elekta Agility plans were re-planned for Elekta MLCi.
For prostate cases we identified rectum and bladder as
main OARs and for HNC contralateral parotid gland and
spinal cord. For PTV we evaluated variations in EUD, D
Mean
,
D
2%
and D
98%
and for OARs EUD and D
2%
.
Results
Automatic re-planning using constrained optimization was
successful in all cases. Auto-optimized plans never
corrupted OAR constraints, in some cases re-planning even
improved OAR sparing. The mean deviation (range) in
rectum EUD was 0,30% (-1,04 – -0,27%), bladder EUD 0,44%
(-1,08 – -0,13%), parotid EUD -0,34% (-14,79 – 8,23%) and
spinal cord EUD -0,02% (-0,49 – 0,31%). For the prostate
cases the mean EUD deviation in PTV was -0,15% (-0,57 –
0,56%) and for the HNC cases -0,60% for PTV_60 (-2,58
– -0,08%) and -0,79% (-3,44 – 0,20%) for PTV_54,
respectively. Except of 3 HNC cases, all evaluated
parameters for targets showed variations within ±1%. For
3 HN cases the target EUD is reduced by up to 3.44%,
indicated by λ > 10 * λ
avg
. Consequently, if all λ < 10* λ
avg
,
the original and the re-planned plan comply with the given
constraints and therefore represent the same optimal
point on the Pareto-front, which means they are equal in
terms of biological effect for targets and OAR.
Conclusion
This study showed that fully automatic re-planning by
taking a prescription list from previously optimized VMAT
plans is feasible and successful in terms of equal plan