ESTRO 36 Abstract Book

S437 ESTRO 36 _______________________________________________________________________________________________

Conclusion In this study, we measured spectra for external neutrons and characterized neutron dose equivalents for a single gantry proton system, whose use in the United States and worldwide is increasing. Poster: Physics track: Treatment plan optimisation: algorithms PO-0816 LRPM for fast automated high quality treatment planning – towards a novel workflow for clinicians R. Van Haveren 1 , B.J.M. Heijmen 1 , W. Ogryczak 2 , S. Breedveld 1 1 Erasmus Medical Center Rotterdam Daniel den Hoed Cancer Center, Radiation Oncology, Rotterdam, The Netherlands 2 Warsaw University of Technology, Control and Computation Engineering, Warsaw, Poland Purpose or Objective The aim is to create a novel efficient workflow for clinicians, where high quality treatment plans are ready to be inspected minutes after the delineation is finished. In the current clinical workflow, plans are automatically generated using the in-house developed Erasmus-iCycle optimiser, but planning times can be in the order of hours. Therefore, we propose an extension of Erasmus-iCycle to substantially reduce computation times, but maintain plan quality.

minutes, a speed-up factor of 22. Plan quality was mostly similar on average. For individual cases however, the LRPM plans showed clinically more balanced trade-offs between OAR doses. In comparison with the plan resulting from the sequential method, relatively large dose reductions were possible for some OAR(s) at the cost of relatively small increases of dose for other OAR(s). Conclusion The LRPM features very fast automatic multi-criterial generation of high-quality treatment plans, reducing Erasmus-iCycle planning times to the order of minutes. Further research focuses on clinical implementation. PO-0817 Anatomical robust optimization to deal with variation in nasal cavity filling during IMPT S. Van de Water 1 , F. Albertini 2 , D.C. Weber 2 , B.J.M. Heijmen 1 , M.S. Hoogeman 1 , A.J. Lomax 2 1 Erasmus MC Cancer Institute, Radiation Oncology, Rotterdam, The Netherlands 2 Paul Scherrer Institute, Center for Proton Therapy, Villigen PSI, Switzerland Purpose or Objective Intensity-modulated proton therapy (IMPT) for tumors in the sinonasal and skull-base regions can be seriously affected by interfraction changes in nasal cavity filling, resulting in underdosage of the tumor and/or overdosage of organs-at-risk (OARs). The aim of this study was to develop an anatomical robust optimization method that accounts for variation in nasal cavity filling and to compare it with the conventional single-field uniform dose (SFUD) approach and with online plan adaptation. Material and Methods We included CT data of five patients with tumors in the sinonasal region, for which the clinical target volume (CTV) showed large overlap with the nasal cavity. Based on the planning CT, we generated for each patient 25 ‘artificial’ CTs with varying nasal cavity filling (Figure 1). The minimax robust optimization method available in our in-house developed treatment planning system was extended to account for anatomical uncertainties by including additional (artificial) CTs with varying patient anatomy as error scenarios in the inverse optimization. For each patient, we generated treatment plans using: 1) the SFUD approach (with varying planning target volume (PTV) margins of 0 mm, 3 mm or 5 mm), 2) anatomical robust optimization (including two, three or four artificial CTs, next to the planning CT), and 3) online plan adaptation (generating a new treatment plan for each artificial CT). We used the clinically applied 3- or 4-beam arrangements. Treatment plans were evaluated by recalculating and accumulating the dose for an entire fractionated 50-Gy treatment, assuming each artificial CT to correspond to a 2-Gy fraction. We assessed CTV and OAR dose parameters for the accumulated dose and individual fractions. A treatment planning strategy was considered adequate when V 95% ≥99% and V 107% ≤2% in each fraction.

Material and Methods We developed the Lexicographic Reference Point Method (LRPM), a fast algorithm to automatically generate multi- criterial treatment plans in a single optimisation run. In contrast, the currently implemented sequential method in Erasmus-iCycle requires multiple optimisations to generate a plan. We validate the LRPM by comparing automatically generated VMAT plans (mimicked by 23 static beams) with the LRPM and the sequential method for 30 prostate cancer patients and 15 head-and-neck cancer patients. For these treatment sites (and others), Erasmus-iCycle is in clinical use. Results For the 30 prostate cancer patients, plan differences between the LRPM and the sequential method were found neither clinically nor statistically significant. The LRPM reduced the average planning time from 12.4 to 1.2 minutes, a speed-up factor of 10. For head-and-neck, the LRPM reduced the planning times from 99.7 to 4.6