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S101
ESTRO 36 2017
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physiological environment than conventional 2D cell
cultures. Unfortunately, validation of their suitability to
do so and to fit to a particular scientific question is mostly
missing. In this teaching lecture I will discuss validation
strategies and data of comparative analyses between 2D,
3D and tumor xenografts of various processes such as
signal transduction, DNA repair and others. Based on our
long-standing experience, a large variety of endpoints can
be determined and many methods can be conducted in 3D
cell cultures. While this is sometimes not as easy as in 2D
and also requires a bit more financial invest, the
generated data reflect cell behavior in-vivo and thus have
a higher clinically relevance. Further, we are able to
address specific tumor features in detail. For example,
malignant tumors show great genetic/epigenetic and
morphological/cell biological heterogeneity. Another
important point is the sparing of animal experiments
based on our broad knowledge that human
(patho)physiology is significantly different from mice (or
other species). Many decades of in-vivo research have
demonstrated that only a negligible proportion of
therapeutic approaches could be translated from rodents
to humans. In conclusion, 3D cell culture models can
elegantly support our efforts to gain more knowledge for
precision cancer medicine as they present powerful tools
for generating more clinically relevant information. A
broader implementation of the 3D methodology is likely to
underscore our efforts to better understand tumor and
normal cell radiation responses and foster identification
of most critical cancer targets.
Teaching Lecture: Commissioning of dose calculations
in brachytherapy TPS
SP-0200 Commissioning of dose calculations in
brachytherapy TPS
J. Steenhuijsen
1
1
Catharina Ziekenhuis, Eindhoven, The Netherlands
When commissioning a Treatment Planning System for
brachytherapy, most attention is given to the accurate
calculation of the absolute dose and the dose distribution.
The goal of the TPS however is to devise a treatment with
an optimal dose distribution to both targets and organs at
risk with the use of an applicator or needles. Thus, when
commissioning the TPS, not only accurate calculation of
the dose distribution has to be established.
It is equally important to verify the correctness (size,
rotation, order, reconstruction) of the images (CT, MR,
US) used and to check the accuracy of (automatic)
contouring, the resulting Regions Of Interest, ROI-
mathematics and the Dose Volume Histograms based on
these ROIs. The user should also be aware of specific
behavior of the planning system (for instance with respect
to extremely small volumes or volumes defined on one
slice).
Also definitions of sources and applicators and accurate
reconstruction of applicators have to be verified. On the
other hand, the time available to spend on TPS-
commissioning is limited, so an intelligent choice of tests
to has to be made. A prospective risk analysis can help
with this choice.
The teaching lecture gives an overview on literature on
commissioning of TPS for brachytherapy and
provides practical methods to check the various parts of
the TPS.
Symposium: New developments in Personalised
Radiation Oncology (PRO)
SP-0201 E-health and Personalised Radiation
Oncology: cloud technologies and advanced sensing
S. Kyriazakos
1
1
Innovation Sprint, Brussels, Belgium
eHealth solutions have started in the past decade to
attract the attention of several markets, as they support
both healthy adults and patients of chronic diseases.
However, the level of maturity of eHealth solutions
targeting cancer patients is very low. Among the reasons
is the highly regulated environment, the cost of the
service and the technical challenges to offer accurate,
intelligent, personalized applications, respecting the
privacy of the patient.
In this talk, the best-of-breed of Internet technologies,
such as cloud infrastructures, Big Data analytics, advanced
sensing and smart applications will be presented and it will
be demonstrated how integrated approaches can break
the entry barriers, thus improving the daily life and the
treatment of cancer patients.
SP-0202 Integration and analysis of complex data for
Personalised Radiation Oncology
A. Dekker
1
1
Maastricht Radiation Oncology MAASTRO GROW - School
for Oncology and Developmental Biology- University
Maastricht, Maastricht, The Netherlands
Personalised radiation oncology requires a prediction of
the outcome of an individual cancer patient treated with
radiation oncology with or without additional treatment
modalities. This outcome prediction should include
prediction of tumour outcomes (e.g. survival, local
control, distant metastasis), toxicity outcomes affecting
quality of life (e.g. radiation induced and non-radiation
induced toxicities, overall quality of life) and ideally
should also predict expected cost, both for the treatment
itself and additional societal costs during the lifetime of a
patient.