ESTRO 36 Abstract Book

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 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. Purpose or Objective Gold nanoparticles have demonstrated a

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.