ESTRO 2022 - Abstract Book

S548

Abstract book

ESTRO 2022

of an automatic interpretation of PGI data, which is highly desired for routine clinical application and required for including PGI in an automated feedback loop for online adaptive proton therapy.

OC-0621 Comparison of hypoxia adapting relative biological effectiveness models for proton therapy

G. Garrido Hernandez 1 , H. Henjum 2 , M. Høiskar 1 , T. Dahle 3 , K. Redalen 1 , K. Ytre-Hauge 2

1 Norwegian University of Science and Technology, Department of Physics, Trondheim, Norway; 2 University of Bergen, Department of Physics and Technology, Bergen, Norway; 3 Haukeland University Hospital, Department of Oncology and Medical Physics, Bergen, Norway Purpose or Objective In proton therapy, the biological dose ( D bio ) is calculated by means of the relative biological effectiveness (RBE). RBE has been proposed to vary with the linear energy transfer (LET), physical dose and other factors including the oxygen level in the tumor. Models to calculate D bio considering the effect of hypoxic cells typically estimate the oxygen enhancement ratio (OER) using the partial oxygen pressure (pO 2 ) and a parameter for the radiation quality such as the LET or the specific energy. Our aim was to implement and compare different OER models as input to RBE calculation and to use a Monte Carlo (MC) simulation tool to explore the impact of hypoxia on D bio . Hypoxia PET imaging was used to estimate the pO 2 in patients in order to investigate the effects of hypoxia adaptation on proton plans. Materials and Methods We implemented a calculation for hypoxia-adapted D bio , i.e., the RBE-OER-weighted dose (ROWD), based on four different approaches to estimate the OER (Wenzl and Wilkens 2011, Dahle et al. 2020, Tinganelli et al. 2015, Mein et al. 2021). The OER-calculations were combined with either a phenomenological RBE model for protons, or the microdosimetric kinetic model (MKM). First, the FLUKA MC tool was used to simulate a proton beam irradiating a virtual water phantom with different pO 2 levels. Secondly, a proton plan was made in Eclipse TPS (Varian) for a head and neck cancer case calculating the pO 2 from [ 18 F]-EF5 PET as input to the OER estimation. For both the phantom and the patient simulations, the physical dose ( D ), the hypoxia-adapted linear-quadratic parameters ( α h , β h ), the dose-averaged LET (LET d ), and the OER were estimated. Results Water phantom simulations using MC showed good agreement with theoretical OER models. OER estimates corresponded to clinically relevant pO 2 values and were similar between models except for the model from Tinganelli et al . 2015, which estimates approximately a 10% higher OER (Figure 1). At the same time, the models from Wenzl and Willkens 2011 and Dahle et al. 2020 are more susceptible to LET variations than the models from Mein et al. 2021 and Tinganelli et al. 2015 that particularly shows no change for the LET variations on proton LET scales. The corresponding depth-dose curves resulted in a ROWD for all implemented models that followed the same trend with a reduction of the ROWD in the hypoxic regions (Figure 2). Preliminary results from the patient case indicates an OER range of 1 to 1.6 in the planning target volume.