ESTRO 36 Abstract Book

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S246 ESTRO 36
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observer registration variation was minimal in the right-
left (R-L) direction (mean, 2.8mm, sd 2.4 mm). Overall,
on Anova analysis, there were no statistically significant
differences in inter-observer registration (p = 0.8214,
0.3136, and 0.3270, in the R-L, A-P and C-C directions
respectively). To determine intra-observer variability,
each observer performed repeat image registrations on 5
patients at 3 separate time-points. The observers mean
reproducibility of ≤ 4mm, 2.5 mm and 5 mm in all
directions, respectively (Figure 1).
Conclusion
Despite the limitations in geometric fidelity of DW MRI, it
is a potentially useful tool for the generation of BTV and
image registration for adaptive bladder radiotherapy. In
this study we quantified the inter-observer variation to
<5mm +/- 5mm, in image registration of BTV generated
using DW-MRI to planning CT. Current application to
clinical practice may necessitate revision of PTV margins
but further quantification of geometric distortions and
validation is on going.
We acknowledge NHS funding to the NIHR Biomedical
Research Centre for Cancer and to Cancer Research UK
(CRUK).
PV-0462 E-learning in the Radiotherapy Department-
Ortello
J.P. De Jong1, P. De Boer1, D. Ages2, F. Telgenhof3, D.
Hasken3
1 Netherlands Cancer Institute Antoni van Leeuwenhoek
Hospital, Radiotherapy, Amsterdam, The Netherlands
2 Leiden University Medical Center, Radiotherapy,
Leiden, The Netherlands
3 University Medical Center Utrecht, Radiotherapy,
Utrecht, The Netherlands
Purpose or Objective
In 2006 four Radiation therapy technologist (RTT) heads of
Radiation Oncology departments agreed to create an E-
learning environment. Their goal was to introduce a
learning method for RTTs involved in new radiation
techniques for whom the learning environment would be
easily accessible, relatively cheap and offer new teaching
and learning techniques.
Material and Methods
From 2006 till 2008 a dedicated group of four RTTs created
a web-based environment called “Ortello”. By December
2015 Ortello had been fully revised and updated to current
website standards. In 2008 Ortello started with 8
Radiotherapy case studies (CS), 3 games and a multiple-
choice test. Radiotherapy was highlighted in these CS, but
other treatment modalities, such as surgery and
chemotherapy, were also represented. Each CS consists of
a patient’s pathway during their cancer treatment. Ortello
now contains 21 different E-learning CS, which are
categorized in Radiotherapy, Techniques, Imaging, and
Radiobiology, coupled to 21 multiple-choice tests to
examine the gained knowledge. The e-learning
environment is linked to the Dutch Register for Paramedics
to automatically register credit points obtained after
completing a CS and the corresponding test. Every 2 years,
reapplication for accreditation is required to guarantee
the quality and relevance of each CS.
Results
Since it’s introduction, Ortello has gained more than 1100
users in 21 departments; 19 in The Netherlands and 2 in
Suriname and Curacao. Each year new CS are launched on
the website. Up to now, Ortello contains 11 CS in the
category Radiotherapy: prostate-, oropharyngeal-, larynx
carcinoma, 2 in the category Technique: ”Photons vs
electrons” and ”Teaching & Brachytherapy”, 2 in the
category Imaging: MRI and MRI & bone tumors and 3 in the
category Radiobiology: Radiobiology, Linac &
Radioactivity and Radiotherapy side effects. Currently,
Ortello is no longer exclusive for RTTs, but can also be
used by Diagnostic radiographers.
Conclusion
The E-learning environment Ortello is fully operational. On
the Ortello website, RTTs can train their skills, maintain
their knowledge, learn newly introduced technologies,
and have the opportunity to learn techniques used in other
departments. Furthermore, Ortello provides CS with the
accreditation points to ensure RTTs continuous
competence.
Award Lecture: Donal Hollywood Award
OC-0463 In vitro prediction of DNA repair defects
reveals association with poor clinical outcome in
HNSCC
P. Essers1, C. Verhagen1, M. Van der Heijden 1, M. Van den
Brekel2, H. Bartelink3, M. Verheij3, C. Vens1
1Netherlands Cancer Institute Antoni van Leeuwenhoek
Hospital, Division of Biological Stress Response,
Amsterdam, The Netherlands
2Netherlands Cancer Institute Antoni van Leeuwenhoek
Hospital, Department of Head and Neck Surgery /
Department of Maxillofacial Surgery, Amsterdam, The
Netherlands
3Netherlands Cancer Institute Antoni van Leeuwenhoek
Hospital, Department of Radiation Oncology,
Amsterdam, The Netherlands
Purpose or Objective
Recent studies highlight the relevance of DNA repair
defects in genome instability and tumour development.
Little is known about the impact of DNA repair aberrations
on patient prognosis or treatment outcome. However, new
targeted treatment options, such as PARP inhibitors, can
exploit these repair defects if present. Here we tested
whether gene expression analysis could identify DNA
repair defects, with the ultimate aim to determine an
association with clinical outcome and identify patients for
targeted treatments.
Material and Methods
Mitomycin C (MMC) or PARP inhibitor olaparib
hypersensitivity is a hallmark of functional homologous
recombination (HR) or Fanconi anaemia (FA) pathway DNA
repair defects. We determined whole transcriptome
expression and sensitivity to MMC and olaparib in a panel
of 28 patient derived head and neck squamous cell
carcinoma (HNSCC) cell lines. Based on their sensitivity
(IC50 values), cell lines were classified as Normal (N),
hypersensitive to both drugs (MOS) or hypersensitive to
mitomycin C but not olaparib (MS). To esta blish a “DNA
repair defect” signature, relevant genes were extracted
by differential expression analysis and used as input to
various machine learning algorithms. Performance was
evaluated using 20 repetitions of 5-fold int ernal cross
validation.
Probabilities of defects calculated by these m odels were
used in a multivariate cox proportional hazard model to
determine their prognostic capacity in a cohort of 84
HNSCC tumours, treated with chemo-radiation, and the
TCGA HNSCC cohort.
Results
Expression analysis of the three groups yielded genes
enriched for targets of transcription factors involved in
DNA damage response, including p53, demonstrating its
relevance to the system under study. The random forest
model performed best, achieving a high sensitivity of 0.91
and specificity of 0.86.
We validated our model in the Cancer Genome Project
dataset of drug sensitivities in cell lines. The predicted
repair defected groups had significantly lower IC50 values
for DNA damage inducing agents, including cisplatin (MS:
p=5.9e-05; MOS: p=0.042).
Encouraged by this data, we used our model in the patient
data sets. Increased probabilities of DNA repair defects