ESTRO 37 Abstract book

S1081

ESTRO 37

Results DIBH 3D technique provided a significant dose reduction in Heart Mean Dose (0.8 Gy DIBH 3D 2.6Gy 3D FB vs 4.5 VMAT FB), and LAD mean dose (3.8 Gy DIBH 3D 14.2Gy 3D FB vs 9.0 VMAT FB) . Better PTV coverage was found in DIBH 3D plans and no difference in Homolateral Lung parameters (V10, V20 and Dmedia) were achieved . Controlateral breast and lung and the normal tissue were significantly spared in DIBH 3D irradiation. Set-up verification with EPID and intra-fraction monitoring via the optical system provided an Intra-fraction variability <3.1 mm in translations and <3° in rotations. Conclusion Balancing target coverage and OAR sparing, DIBH 3D conformal can be considered the preferable of the investigated treatment options in left sided whole breast + lymph node supraclavicular region boost irradiation EP-1984 A radiobiological Markov simulation tool for aiding decision making in proton therapy referral A. Austin 1 , S. Penfold 2 , M. Douglass 2 , G. Nguyen 3 1 University of Adelaide, Physical Sciences, Adelaide, Australia 2 Royal Adelaide Hospital, Medical Physics, Adelaide, Australia 3 University of Adelaide, Mathematical Sciences, Adelaide, Australia Purpose or Objective The use of intensity modulated proton therapy (IMPT) for the treatment of cancer has become increasingly common in recent years. The main attraction of IMPT lies in the fact that a reduced integral dose can be deposited in the patient compared with intensity modulated radiation therapy with X-rays (IMRT) while maintaining an equivalent tumour dose. However, compared with IMRT it is more expensive with limited availability. This suggests that patients most in need should be given priority. Such clinical decisions are traditionally based on the results of clinical trials. The rapidly evolving nature of radiation oncology treatment technology, however, can make it difficult to base clinical decisions on data from clinical trials as the long follow-up times required can lead to results being outdated shortly after they are gathered. Alternatively, modelling studies can provide a prediction of the clinical outcome of a planned treatment, and hence can assist a clinician when deciding whether to refer a patient for proton therapy. Material and Methods A Monte Carlo-based Markov model has been developed to estimate the radiobiological effect of a given treatment plan and hence the clinical outcome of an individual patient. The Markov model approximates the time remaining of the patient’s life after treatment as a series of transitions between several discrete states that describe the health status of the patient. The radiobiological effect is quantified in terms of the tumour control probability (TCP), normal tissue complication probability (NTCP) and second primary cancer induction probability (SPCIP). These metrics are used as transition probabilities in the Markov chain, with the NTCP and SPCIP for each organ at risk (OAR) being time-variable. To demonstrate functionality, the model was applied to a paediatric patient presenting with base of skull chordoma. Results The model was successfully developed and verified to compare clinical outcomes for proton and X-ray treatment plans. This clinical outcome is quantified by Electronic Poster: Physics track: (Radio)biological modelling

Kaplan-Meier survival curves and the quality adjusted life expectancy (QALE) which accounts for the potential negative effects of a treatment, such as radiation- induced injuries or radiation-induced second cancers, on the quality of life of the patient. Conclusion The functionality of the model was demonstrated using the example patient. Other example patients will be considered in future applications of the model. In addition to base of skull chordoma, other treatment sites may be considered that are not typically associated with proton therapy, but where there is an elevated risk present with X-ray therapy. EP-1985 Analysis of HBV after CRT in patients with hepatocellular carcinoma using the Lyman NTCP model W. Huang 1 , Z. Li 2 , Y. Dong 3 1 Shandong Cancer Hospital, Radiation Oncology 6, Jinan, China 2 Shandong Cancer Hospital, Radiation Oncology, Jinan, China 3 University of Jinan-Shandong Academy of Medical Sciences, School of Medicine and Life Sciences, Jinan, China Purpose or Objective To analyze the correlation of hepatitis B virus (HBV) reactivation with patient-related and treatment-related dose-volume factors, and to describe the feasibility of HBV reactivation analyzed by a normal tissue complication probability (NTCP) model for patients with hepatocellular carcinoma (HCC) treated with conformal radiotherapy (CRT). Material and Methods 90 HBV-related HCC patients treated with CRT were enrolled in this retrospective study and were followed from June, 2009 to December, 2015. The parameters (TD 50 (1), n, and m) of the modified Lyman Kutcher Burman (LKB) NTCP model were derived using maximum likelihood estimation. Bootstrap and leave-one-out were employed to test the generalizability of the results for use in a general population. Results Radiation-induced liver diseases (RILD) were 17.8%, HBV reactivation was 22.2%, and HBV reactivation-induced hepatitis was 21.1%, respectively. In multivariate analysis, the V45, and V30 were associated with HBV reactivation. TD 50 (1), m and n were 32.3Gy, 0.55 and 0.71, respectively, for HBV reactivation. Bootstrap and leave-one-out results showed that the HBV parameter fits were extremely robust. Conclusion A modified Lyman NTCP model has been established to predict HBV reactivation for patients with HCC who received CRT. The finding derives parameters set to predict potential endpoints of HBV reactivation. EP-1986 Relative biological effectiveness and relative dose-rate effect on Lipiodol based on the MK model D. Kawahara 1 , N. Hisashi 2 , O. Shuichi 3 , S. Akito 3 , K. Tomoki 3 , S. Tatsuhiko 4 , T. Masato 4 , T. Sodai 5 , O. Yoshimi 6 , M. Yuji 3 , N. Yasushi 3 1 Hiroshima University, Graduate School of Biomedical & Health Sciences, Hiroshima, Japan 2 Hiroshima Heiwa Clinic- State of the Art Treatment Center, Radiation therapy, Hiroshima, Japan 3 Hiroshima University, Department of Radiation Oncology- Institute of Biomedical & Health Sciences, Hiroshima, Japan 4 Hiroshima University, Medical and Dental Sciences Course- Graduate School of Biomedical & Health Sciences, Hiroshima, Japan 5 University of Tokyo, Department of Nuclear Engineering and Management- School of Engineering, Tokyo, Japan 6 Hiroshima University Hospital, Radiation Therapy