ESTRO 2020 Abstract Book

S792 ESTRO 2020

better dose conformity. AP plans are preferred for slightly superior dose falloff. PO-1475 Automated planning for pre-selection of head&neck patients for proton therapy J. Kouwenberg 1 , J. Penninkhof 1,2 , S. Habraken 1,2 , J. Zindler 1,2 , B. Heijmen 1 , M. Hoogeman 1,2 1 Erasmus Medical Center, Radiation Oncology, Rotterdam, The Netherlands ; 2 HollandPTC, Radiation Oncology, Delft, The Netherlands Purpose or Objective A comparative proton therapy (PT) treatment plan made at a PT center is often mandatory to justify the choice of PT for an individual patient. In practice, a clinician selects patients to be sent to a PT center for a comparative PT plan based on clinical factors, images, and treatment characteristics. However, this selection is subjective and dosimetric information is not included in the decision making process. Moreover, the PT treatment planning is labor-intensive and time-consuming. Therefore, it may withhold PT from patients that would have benefitted, or conversely could result in an unnecessary work and delay for patients for whom the comparison turns out to be negative. To overcome these undesired scenarios, we developed a novel automated procedure for selecting head & neck cancer patients for a comparative PT plan made at a PT center, using a non-clinical automated IMPT planning system (Erasmus-iCycle). Material and Methods Erasmus-iCycle was commissioned for a Varian ProBeam pencil beam scanning system used in the PT center. The wish-list, used to control the prioritization in the automated treatment planning process, and the robust optimization settings were configured to mimic the plans generated at the PT center. Subsequently, 18 H&N patients, who were referred to the PT center for a comparative PT plan, were selected. Differences in OAR doses and corresponding normal tissue complication probabilities (NTCP) between Erasmus-iCycle and the PT plans were determined. To this end, we evaluated NTCP models used in the Dutch model-based approach for PT patient selection, which are xerostomia, dysphagia, and tube feeding dependency. Results After commissioning the differences in range, spot size (70 – 244 MeV) and range-shifted spot size (100 – 244 MeV) were within 1, 0.2, and 0.7 mm, respectively. Comparing the Erasmus-iCycle and the PT center plans, the mean (± 1SD) differences in contralateral parotid gland, oral cavity, PCM superior, PCM inferior, and crycopharyngeus doses were 0.6 (± 2.4) Gy, -0.5 (± 3.6) Gy, 1.6 (± 3.7) Gy, -1.0 (± 4.3) Gy, and -2.37 (± 5.53) Gy, respectively. These OAR dose differences led to mean (± 1SD) differences in the NTCP for xerostomia, dysphagia, and feeding tube dependency -0.7 (± 2.7)%, -0.6 (± 2.3)%, and -0.6 (± 1.8)%, respectively. The outliers could be explained by a more conformal dose distribution that was achieved with Erasmus-iCycle, and the fact that the PT center sometimes allowed local underdosing of the robust target in order to spare OAR’s. Conclusion It was possible to approximate PT plans, which were manually generated at a PT center, with a non-clinical automated treatment planning system. This paves the way for an objective and efficient selection of patients who qualify for a comparative PT treatment plan, for example as part of the Dutch model-based approach.

Figure 1: Comparison of the PT plans made by the PT center (A) and Erasmus-iCycle (B). PO-1476 Monte Carlo based 3D treatment planning using intraoperative CBCT scanning for image guided IORT L. Probst 1 , L.D. Jiménez-Franco 1 , S. Clausen 1 , V. Steil 1 , F.A. Giordano 1 , F. Schneider 1 1 Universitätsmedizin Mannheim, Klinik für Strahlentherapie und Radioonkologie, Mannheim, Germany Purpose or Objective Intraoperative radiotherapy (IORT) allows delivering high doses of irradiation to the tumor bed with no to little involvement of healthy tissues. With the aim to more precisely calculate intraoperative dose distributions, we investigated if conventional intraoperative cone-beam CT (CBCT) imaging is suitable for IORT treatment planning. Material and Methods Seven different HU to electron density (ED) curves were acquired for corresponding CBCT (Artis ZeeGo TM , Siemens, Germany) protocols, using the RMI 467 ED phantom (Gammex, USA). The reference CT image data set was achieved from a conventional treatment planning CT (Brilliance Big Bore, Philips, Netherlands) (PCT). The acquired CT images provide 1 mm slice thickness and lead to a 400 mAs tube current-time product with 120 kV anode- cathode potential. Furthermore, PCT images with 150 mAs and 250 mAs were generated to confirm consistency of the analyzing method. All treatment plans were calculated on the CIRS model 057A triple modality 3D abdominal phantom (CIRS, USA) using Radiance (version 4.0.3, GMV, Spain), which employs the Intrabeam (Carl Zeiss Meditec GmbH, Germany) head model to simulate the dose with a Monte Carlo algorithm. To estimate the variance of the MC simulations, the dose distributions on the 400 mAs PCT were repeatedly calculated with several particle numbers on a 0.5 mm grid, using a 4 cm spherical applicator. All dose distributions simulated on CBCTs were then compared to the reference dose distribution calculated on PCTs. Plan evaluation was performed with Matlab, applying a 3D local gamma with 1%/ 1 mm passing criteria, after converting the grid to 0.25 mm via interpolation of the dose distribution. The region of interest was a shell of 2 cm thickness around the applicator. Results Five CBCT protocols reached more than 94% local 3D Gamma passing rates for 100 million photons (Table 1). The passing rate increased up to 3% for certain protocols using 4 million photons. The calculation times ranged between 1 and 200 minutes when simulating 500.000 up to 100 million photons (Figure 1). Consequently, the averaged standard deviations (obtained from ten individual plans on the same PCT) decrease in parallel from roughly 16% to less than 1%.