888 / 1096
S872
ESTRO 36
_______________________________________________________________________________________________
Conclusion
The estimation of α/β ratio for prostate cancer presented
here included two unknown parameters in the model, as
such, no definitive conclusion was reached. However,
including Tk in the model consistently reduced the
squared difference and increased the α/β ratio.
References
1. Vogelius, I.R., et al., Int J Radiat Oncol Biol Phys, 2013.
85(1): p. 89-94.
2. Dearnaley, D., et al., Lancet Oncol, 2016. 17(8): p.
1047-60.
3. Incrocci, L., et al., Lancet Oncol, 2016. 17(8): p. 1061-
9.
4. Catton, C., J Clin Oncol, 2016. 34(suppl).
5. Lee, W.R., et al., J Clin Oncol, 2016. 34(20): p. 2325-
32.
EP-1613 Modelling DNA damage on gold nanoparticle
enhanced proton therapy
M. Sotiropoulos
1
, N.T. Henthorn
1
, J.W. Warmenhoven
1
,
R.I. Mackay
2
, K.J. Kirkby
1,3
, M.J. Merchant
1,3
1
University of Manchester, Faculty of Biology Medicine
and Health Division of Molecular & Clinical Cancer
Sciences, Manchester, United Kingdom
2
The Christie NHS Foundation Trust, Christie Medical
Physics and Engineering, Manchester, United Kingdom
3
The Christie NHS Foundation Trust, Manchester, United
Kingdom
Purpose or Objective
Gold nanoparticles have demonstrated a
radiosensitization potential under photon and proton
irradiation. Most existing studies have attributed the
effect to the increased local dose delivered by electrons
generated from interactions of the beam protons with the
gold nanoparticles. However, the mechanism leading to an
increase in the cell killing is yet not clear.
Material and Methods
To further understand the underlying mechanisms of the
radiosensitization at the cellular level, a cell model with
detailed nuclear DNA structure was implemented in the
Geant4 Monte Carlo simulation toolkit. A realistic gold
nanoparticle distribution was incorporated, allowing for
the formation of clusters of vesicles filled with the gold
nanoparticles. A clinically relevant gold concentration was
simulated for the gold nanoparticle size of 6, 15, and 30
nm. Protons with linear energy transfer values found in a
spread out Bragg peak (1.3-4.8 keV/µm) were simulated.
The event-by-event models available through the Geant4-
DNA were used for accurate calculations of DNA damage.
Damage to the DNA inducing either single (SSB) or double
strand breaks (DSB) was used for the quantification of the
radiosensitization effect, for a dose fraction of 2 Gy. Each
case was repeated 100 times to get an average number of
SSB or DSB numbers.
Results
For the combinations of gold nanoparticle size and proton
energies studied in the present work, no statistically
significant increase in the single or double strand break
formation was observed. The DSBs induced for the 4.8
kev/µm protons were 14.93 ± 0.38 for the control while
ranged from 15.09 ± 0.39 to 15.76 ± 0.41 when the gold
nanoparticles were present, depending on the gold
nanoparticle size. Similarly, for the 1.3 keV/µm protons
the control value was 12.21 ± 0.34 DSBs and in the
presence of gold nanoparticle was 11.94 ± 0.36 to 12.48 ±
0.33 DSBs depending on the gold nanoparticle size.
Conclusion
As gold nanoparticles enhanced proton therapy have been
proven experimentally, our results allow hypothesizing
contribution from alternative mechanisms
of
radiosensitization.
EP-1614 Uncertainty of dose-volume constraints
obtained from radiation pneumonitis dose-response
analysis
C.M. Lutz
1
, D.S. Møller
2
, L. Hoffmann
2
, A.A. Khalil
1
, M.M.
Knap
1
, M. Alber
1,3
1
Aarhus University Hospital, Department of Oncology,
Aarhus C, Denmark
2
Aarhus University Hospital, Department of Medical
Physics, Aarhus C, Denmark
3
Heidelberg University Hospital, Department of
Radiooncology, Heidelberg, Germany
Purpose or Objective
Dose planning constraints, such as the volume receiving
xGy (V
x
), are often extracted from clinical outcome data.
These data are tainted by uncertainties in dose- and
output recording, large patient heterogeneity, small
sample size and -variability. Our study is dedicated to the
investigation of the fundamental uncertainty with which
dose planning constraints can be extracted from clinical
radiation pneumonitis data and how this relates to patient
number and complication incidence rate.
Material and Methods
In order to measure the reliability of a V
x
logistic
regression model, the dose-response mechanism
generating the complication events needs to be known.
For this reason, we generated cohorts of patients using
real-life dose distributions of patients treated for
advanced lung cancer, combined with a postulated V
x
logistic dose-response model. In each of the 1000 cohorts,
the patients were randomly assigned complication/no-
complication based on the individual risks given by the
postulated model. Thus, “alternative reality” cohorts
comprised of the same patients, but with different
outcomes from the same dose distributions were created.
Each cohort thus represented a possible result of a clinical
study. They were analyzed with a number of logistic V
x
models, and the best fitting model was selected. This was
matched to the postulated model to determine its
recognition rate. The postulated model was varied to
produce low, intermediate and high incidence rates.
Results
For a patient cohort of 100 individuals, a postulated model
with an incidence rate of 15/100 was recognized in 31% of
the cohorts. For a cohort size of 500, the correct-
recognition rates increased to 75%. For a lower incidence
model (7/100), these recognition frequencies dropped to
20% and 56%,
respectively.
To ensure a recognition rate >90%, large cohorts of
between 500 and 2000 patients were required, see Figure
1(a). Figure 1(b) shows that the distribution width for the
15/100 incidence rate model decreased from a standard
deviation of 10Gy for 100 patients to 1Gy for 2000
patients.