ESTRO 36 Abstract Book

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S12 ESTRO 36 2017
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procedures. In mpUS different ultrasound modalities are
combined, including contrast-enhanced ultrasound
(CEUS), Doppler ultrasound, computerised transrectal
ultrasound and elastography.
Transrectal greyscale ultrasound is currently the standard
imaging tool for the prostate and is e.g. used for guiding
seed placement in brachytherapy. The performance
reported in the literature varies widely.
Several systems for computerised analysis of ultrasound
images have been developed. The far best results
published are from the artificial neural network/C-TRUS
(ANNA/C-TRUS) system. The initial results for a different
computerised analysis technique, histoscanning, were
favourable, however, recent studies state that
histoscanning is not recommended to reliably identify and
characterise prostate cancer.
Cancer requires angiogenesis to develop into clinically
significant disease. The increased perfusion in malignant
tissue can be visualised by Doppler ultrasound imaging.
Various authors reported additional value of the Doppler
techniques. However, the hypervascularity detected by
Doppler ultrasound is not based on true angiogenic
perfusion but on flow in larger feeding vessels.
In contrast-enhanced ultrasound, gas filled microbubbles
are administered intravenously during ultrasound imaging.
The microbubbles were first used as additional reflectors
in combination with Doppler techniques, increasing
sensitivity. In the past years, contrast-enhanced
ultrasound has emerged, and the technique now exploits
the microbubbles nonlinear oscillations to extract a
contrast specific image, sensitive enough to detect single
microbubbles. Recently, quantification techniques are
being developed that extract objective parameters from
CEUS data to further improve interpretation. The latest
developments focus on the assessment of the dispersion
kinetics of the contrast agent passing through the
microvasculature to image changes in the microvascular
architecture resulting from cancer neoangiogenesis.
Most prostate cancers are stiffer than normal prostatic
tissue. Two variants of ultrasound elastography exploit
this difference in stiffness: quasi-static or strain
elastography and the novel shear wave elastography. The
latter assesses stiffness by measuring the velocity at which
a shear wave travels through the tissues. Shear wave
elastography does not require manual cyclic compression
of the prostate and quantification is possible because
shear wave velocity is an absolute value.
Conclusion
The ultrasound modalities discussed above exploit
different physical characteristics of (malignant) tissue.
Combining the modalities has the potential to detect and
localise accurately tumours and dominant lesions. Until
now only limited data on the performance of combinations
of ultrasound modalities have been published. Therefore,
it is difficult to determine the exact value of mpUS in e.g.
brachytherapy. Due to the advantages of ultrasound over
MRI (i.e. more cost-effective, wider available, less time-
consuming, more practical, more suitable for
perioperative use and more easily combined with
therapeutic devices), the frequent use of US modalities in
therapy procedures, its enhanced performance in
multiparametric fashion, it is expected that mpUS will
become an increasingly interesting modality in also
brachytherapy.
Proffered Papers: Radiobiological modeling
OC-0035 Characterization and validation of a radiomics
signature for NSCLC and head and neck cancer patients
A. Jochems1, F. Hoebers1, D. De Ruysscher1, R.
Leijenaar1 , F. Walsh1, B. O´Sullivan2, J. Bussink3, R.
Monshouwer3, R. Leemans4, P. Lambin1
1 MAASTRO Clinic, Radiotherapy, Maastricht, The
Netherlands
2Princess Margaret Cancer Centre, Cancer Clinical
Research Unit, Toronto, Canada
3Radboud University Medical Center Nijmegen, Radiation
Oncology, Nijmegen, The Netherlands
4VU University Medical Center, Otolaryngology/Head and
Neck Surgery, Amsterdam, The Netherlands
Purpose or Objective
In order to facilitate a more personalized oncology,
research into non-invasive tumor related biomarkers is
essential. Radiomics, the comprehensive quantification of
tumour phenotypes by extracting large numbers of
quantitative image features, can capture intra-tumour
heterogeneity and gene-expression patterns [1]. It has
previously been shown that a radiomic signature may have
high value for survival prediction in lung and head and
neck cancer patients [1,2]. However, extensive analysis
on the quality of this signature has yet to be done. In this
project, we validate the existing radiomics signature in 5
validation sets. We hypothesize that the signature
performs above the chance level, in terms of
discrimination, on each validation set. Furthermore, we
expect that high, medium and low risk patients can be
identified using the radiomics signature.
Material and Methods
Five independent Lung and Head & Neck (H&N) cancer
cohorts (in total 1418 patients) treated with (chemo-
)radiation were used in this study. Radiomic features were
extracted from the pre-treatment computed tomography
(CT) images. The model was trained on the Institute 1 lung
cohort (N=422) and validated on the other datasets
(N=996). The outcome is two-year survival following
treatment. An exponential curve was fitted to the
radiomics signature predictions plotted against overall
survival. Risk group allocation for the Kaplan-Meier curves
was done by partitioning patients in 3 groups according to
radiomics score.
Results
As can be observed in figure 1, an upward trend of
radiomics signature response versus overall survival can be
observed for each validation set. Risk groups can be
identified using the radiomics signature in every dataset,
as is shown in figure 2.