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S100
ESTRO 36 2017
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management system itself can be introduced. Therefore,
registering and analysing errors is an efficient way to
improve safety.
Teaching Lecture: Automated planning, knowledge-
based planning and other novel developments in
treatment planning - how do they work and perform?
SP-0196 Automated planning, knowledge-based
planning and other novelties in treatment planning -
how do they work and perform?
B. Heijmen
1
, P. Voet
2
, L. Rossi
1
, A. Sharfo
1
, Y. Wang
1
, S.
Breedveld
1
1
Erasmus MC Cancer Institute, Radiation Oncology,
Rotterdam, The Netherlands
2
Elekta AB, Elekta AB, Stockholm, Sweden
This lecture will give an overview of latest developments
in treatment planning, both including principles of novel
approaches, and applications. More specifically, the
following topics will be discussed:
- Treatment plan generation as a formal multi-criterial
optimization problem - difference between Pareto-
optimal plan and clinically optimal plan
- Overview of algorithms for automated and knowledge-
based plan generation
- Validation of the quality of automatically generated
plans: how + results
- Automated planning for bias-free treatment technique
comparisons
- Automated planning for adaptive radiotherapy
- Future role of planners in the era of automated plan
generation
- Real-time planning
- Beam angle optimization for non-coplanar treatment
- Individualized automated plan QA: is the generated
plan optimal for the given patient anatomy?
- From PTV/PRV towards probabilistic or robust planning
Teaching Lecture: Building of NTCP models that contain
non-dosimetric parameters
SP-0197 Building of NTCP models that contain non-
dosimetric parameters
T. Rancati
1
1
Fondazione IRCCS Istituto Nazionale dei Tumori,
Prostate Cancer Program, Milan, Italy
It is well known that the risk of radio-induced toxicity
increases when higher doses and larger volumes are
involved in the irradiation and, in the last years, some
consistent results have been published on the possible
estimation of normal tissue complication probability
(NTCP) for a number of organs-at-risk.
The widespread method used for such calculations is
based on a sigmoid dose-response curve coupled to
reduction of the whole dose-volume histogram into one
parameter (such as the equivalent uniform dose).
NTCP models with their prediction based only on
dosimetric variables can be used in treatment planning
and can act as a baseline reference. On the other hand,
it is becoming clearer that radiation-related side effects
are also correlated to a number of patient-related factors.
With the advent of newer radiotherapy technologies,
which allow steep gradients and minimization of doses to
normal tissues, there is an increased interest in
understanding clinical/genetic risk factors that might
enhance patient radio-sensitivity and to develop NTCP
models which might include these variables in order to
achieve better normal tissue complication predictions.
A number of published studies have shown that current
NTCP models can be improved by incorporating clinical
risk factors into model formulation. Overview of published
results will be presented.
A further important step is the inclusion of
molecular/genetic predictors into NTCP models. This issue
is still at a very primitive stage and should be elucidated
because, given the same set of clinical/dosimetric factors,
patient-to patient variability in normal tissue response to
radiation has been widely recognized in clinical practice,
suggesting that this phenomenon might be, at least in
part, genetically driven.
In this presentation data on molecular/genetic markers
influencing radio-induced toxicity are presented, together
with the first findings supporting the hypothesis that a
genetically determined dose–response relationship is
possible and could be used to predict the probability of
side effects associated with radiotherapy and serve as a
rational basis for individualized radiation dose
prescriptions.
The future lies in these multi-factorial prediction models:
a great effort has to be done to collect reliable detailed
prospective data for the development of NTCP models
with the inclusion of predisposing clinical/genetic
features for normal tissues involved in radiotherapy.
Teaching Lecture: Particle therapy – how to start up and
carry out daily clinical practice
SP-0198 Particle therapy – how to start up and carry
out daily clinical practice
H. Hentschel
1
1
EBG MedAustron GmbH, Medical Department,
Wiener Neustadt, Austria
The MedAustron Center for ionbeam radiotherapy and
research started clinical operation, i.e. patient treatment
in December 2016.
MedAustron does not use any turn-key solutions for beam
acceleration, beam delivery, patient positioning and
positioning-verification but refined existing products and
teamed up with industrial and scientific partners to
develop novel solutions. The decision to use non off-the
shelf technology and to CE-certify the Synchrotron and
affiliated components as medical devices is an opportunity
to maximize the usability of the given technical conditions
as well as to optimize the efficiency of patient treatment.
The team of RTTs which was already integrated in the
project phase faced new challenges and demands off the
beaten path of existing and settled structures of hospital
based radiotherapy departments. The approach of
sequentially taking individual beam lines and particle
species in operation involves constant change and
demands a team of flexible and innovative
radiotherapists. MedAustron is an autonomous outpatient
clinic which is not affiliated with a hospital. As a
consequence RTTs are also involved in regulatory affairs,
quality management, risk management, purchase,
maintenance and documentation of inspections of medical
products and supplies.
Teaching Lecture: Three-dimensional cell culture
systems
SP-0199 Three-dimensional cell culture systems
N. Cordes
1
1
OncoRay - Center for Radiation Research in Oncology,
Dresden, Germany
3D cell cultures appear in many different self-made and
commercially available facets. A common denominator for
some of them is that they enable cell growth in a more