ESTRO 36 Abstract Book

S851 ESTRO 36 2017 _______________________________________________________________________________________________

presence of immunosuppressive cells in the tumor microenvironment and tumor infiltrating lymphocytes, the regulation of immunogenic cell surface receptors, and immunogenic cell death. However, the balance between pro-tumor and anti-tumor effects is delicate, and the application of immunotherapy in combination with radiotherapy has to be designed very carefully in order to tip the immunomodulatory effect of radiation in the right direction. There are many parameters that can be varied in this equation, including time, dose and fractionation. Therefore, in order to better understand the immunomodulatory effect of radiation, and to be able to optimize the combined treatment, there is a great need for mathematical models. Material and Methods In this work, a mathematical model based on the work by Serre et al. 1 was developed to describe the synergistic effect of immunotherapy and radiotherapy observed in a previous pre-clinical study in glioma carrying rats. 2 Animals with intracranial tumors were given indoleamine 2,3-dioxygenase (IDO) inhibitory treatments with intraperitoneal injections of 1-methyl tryptophan (1-MT), in combination with radiotherapy given as single fractions of 8 Gy. 1 Serre R, et al. Mathematical model of cancer immunotherapy and its synergy with radiotherapy. Cancer Res 76(17):4931–40, 2016. 2 Ahlstedt J, et al. Effect of Blockade of Indoleamine 2, 3- dioxygenase in Conjunction with Single Fraction Irradiation in Rat Glioma. J J Rad Oncol 2(3):022, 2015. Results Using the mathematical model tumor growth and survival curves were simulated, and the parameters of the model were fit to the experimental data. Good agreement for median survival time was achieved both for the two modalities given separately as monotherapies, as well as for the combined treatment, see Figure. Conclusion Conclusion: The simplified mathematical model presented in this work captures the general features of the synergistic combination of IDO-inhibitory immunotherapy and single fraction radiotherapy. The model can be used to explore possible alternative time, dose and fractionation, in order to gain improved insight into the effects of these parameters, and to generate plausible hypotheses for further pre-clinical studies. EP-1600 Delta radiomics of NSCLC using weekly cone- beam CT imaging: a feasibility study J. Van Timmeren 1 , R. Leijenaar 1 , W. Van Elmpt 1 , S. Walsh 1 , A. Jochems 1 , P. Lambin 1 1 Department of Radiation Oncology - MAASTRO, GROW School for Oncology and Developmental Biology - Maastricht University Medical Centre MUMC, Maastricht, The Netherlands Purpose or Objective Currently, prognostic information is commonly derived using radiomics features from medical images acquired prior to treatment. However, the potential of delta radiomics, i.e. the change of radiomic features over time, has not yet been extensively explored. Cone-beam CT (CBCT) imaging can be performed daily for lung cancer

patients and is therefore a potential candidate for delta radiomics, which may allow further treatment individualization. In this study we explored delta radiomics using CBCT imaging by investigating the number of features changing at a specific time point during treatment. Moreover, we investigated the differences between patients having an overall survival of less or more than 2 years. Material and Methods A total of 40 stage II-IV NSCLC patients, receiving curatively intended radiotherapy for a period of at least six weeks, were included in the study. The CBCT images used in this study were 1) CBCT prior to the first fraction of treatment (CBCTfx1), 2) CBCT prior the second fraction of treatment (CBCTfx2), 3) CBCT one week after the start of treatment (CBCTweek2), 4) CBCT three weeks after the start of treatment (CBCTweek4) and 5) CBCT five weeks after the start of treatment (CBCTweek6). For 38 patients CBCTfx1 and CBCTfx2 were available, whereas for 33 patients all weekly CBCTs were available. All patients had a minimal follow-up of 2 years. Per time point, a total of 1046 radiomic features were derived from the primary tumor volume. The images prior to the first and second fraction were used to calculate the variability in imaging features using the coefficient of repeatability (COR), defined as 1.96*SD. The weekly images were used to investigate the number of features changing more than the COR with respect to baseline (CBCTfx1). Results Figure 1 represents the total number of features that changed more than the COR, ranging from 0 to 999 features. The median number of features that changed for the group with overall survival <2 years was 279, whereas this was 500 for the group with overall survival >2 years (Mann-Whitney U test, p = 0.06). For 8 out of 10 patients that survived >2 years, more features (31.7%) changed one week after CBCTfx1 than for 13 out of 23 patients that did not survive two years.

Conclusion This study shows that a large proportion of the radiomic features derived from cone-beam CT images change significantly during the course of treatment, meaning that an interval of about two weeks is feasible for a radiomics study using CBCT imaging. The larger number of features that changed in the group with overall survival >2 years could reflect an early response of the tumor to the treatment. In future research, the prognostic value of changing radiomic features (delta radiomics) should be explored in a larger cohort. EP-1601 Do higher CT pixel values outside the GTV predict for poorer lung cancer survival? M. Van Herk 1 , J. Kennedy 2 , E. Vasquez Osorio 1 , C. Faivre- Finn 1 , A. McWilliam 1 1 University of Manchester, Division of Molecular and Clinical Cancer Sciences- Faculty of Biology- Medicine and Health, Manchester, United Kingdom 2 The Christie NHS Foundation Trust, Department of Infomatics, Mancehster, United Kingdom