ESTRO 36 Abstract Book

S433 ESTRO 36 2017 _______________________________________________________________________________________________

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.

Results Anatomical robust optimization resulted in adequate CTV doses if at least three artificial CTs were included next to the planning CT. Online plan adaptation also resulted in adequate CTV irradiation, whereas this could not be achieved using the SFUD approach, even with a PTV margin of 5 mm (Figure 2). Anatomical robust optimization provided considerable OAR sparing compared with the SFUD approach (5 mm margin), with an average reduction in max-dose and mean-dose parameters of 6.0 Gy (17%) and 5.8 Gy (24%), respectively. The use of online plan adaptation resulted in further OAR sparing compared with anatomical robust optimization, reducing max-dose and mean-dose parameters on average by 3.8 Gy (13%) and 3.4 Gy (23%), respectively.

Conclusion We have developed an anatomical robust optimization method that effectively dealt with the variation in nasal cavity filling, providing substantially improved CTV coverage and OAR sparing compared with the conventional SFUD approach. Online plan adaptation allowed for further OAR dose reduction and we therefore recommend this planning strategy to be pursued for future application in these patients. PO-0818 Improving plan quality and efficiency by automated rectum VMAT treatment planning G. Wortel 1 , J. Trinks 1 , D. Eekhout 1 , P. De Ruiter 1 , R. De Graaf 1 , L. Dewit 1 , E. Damen 1 1 Netherlands Cancer Institute Antoni van Leeuwenhoek Hospital, Department of Radiation Oncology, Amsterdam, The Netherlands Purpose or Objective To develop, evaluate, and implement fully automated VMAT plan generation for rectum patients that receive either palliative 39 Gy (13×3 Gy), or curative 45 Gy (25×1.8 Gy, postoperative), 50 Gy (25×2 Gy, preoperative) treatment. Material and Methods The automatic rectum VMAT plan generation is performed by a combination of our in-house developed automation framework FAST and the Pinnacle 3 Auto-Planner. The automatic planning starts after the physician has delineated the rectum target volume(s). FAST starts our TPS Pinnacle 3 , creates a patient record, and imports the CT. The patient’s skin and bladder are auto-segmented by Pinnacle 3 ’s module SPICE. In addition, the small bowel is delineated using a custom-made FAST module. The