ESTRO 2021 Abstract Book
Conclusion Including OER in dose optimization for simple SOBP scenarios led to a large increase in both physical dose and LET d in the hypoxic regions. The increase in LET d was reduced when combining the OER model with RBE models, thus the choice of model can affect both the LET d and physical dose distribution from ROWD optimization in proton therapy Comparing the SOBP results to the patient plan results shows that the change in LET d and physical dose from ROWD optimization most likely is strongly dependent on the location and size of the hypoxic region.
PO-1838 Dosimetric impact of the introduction of biological optimization objectives gEUD and RapidPlan
J. Perez-Alija 1 , P. Gallego 1 , M. Barceló 1 , C. Ansón 1 , J. Chimeno 1 , A. Latorre 1 , N. Jornet 1 , N. García 1 , H. Vivancos 1 , A. Ruíz 1 , M. Adrià 1 , P. Carrasco 1 1 Hospital de la Santa Creu i Sant Pau, Medical Physics, Barcelona, Spain Purpose or Objective The introduction of new strategies to optimize treatment plans requires an evaluation of its dosimetric impact. This study analyzes the impact on doses at OARs of two of the implemented improvements in the optimization process of the VMAT technique in prostate patients: the use of biological optimization objectives gEUD (Fogliata et al., 2018) and the use of RapidPlan (RP) automatic planning. Materials and Methods We introduced gEUD biological optimization into our clinical routine in January 2019. In January 2020, we implemented knowledge-based RP treatment planning. We selected a total of 60 prostate or prostate plus seminal vesicle cancer patients treated with VMAT radiotherapy in our department. The first 20 patients were our control group and were treated from July 2018 to December 2018. The following 20 patients received their treatment from July 2019 to December 2019, and the last 20 were planned from July 2020 to December 2020. Volume delineation, patient simulation, and patient preparation were consistent throughout the whole period. We normalized all plans to the highest dose prescription (76 Gy) to compare doses to OARs from different prescriptions. For Rectum and Bladder comparison, we used a metric directly related to our institutional dose-volume constraints: V30 Gy, V40 Gy, V50 Gy, V60 Gy, V70 Gy, V74 Gy, V76 Gy, and Dmean. All these parameters were extracted for each patient using an in-house developed script. We used a Student's t-test to established statistical significance between groups. Results Figure 1 shows that, for the rectum, the gEUD optimization achieved a statistically significant better dose-volume value for all metrics (p < 0.05). RapidPlan treatment planning did not significantly decrease the dose-volume parameters compared with the gEUD plans, but we observed a reduction of inter-patient variability. The rectum mean dose decreased significantly from its initial 2018 value Dmean (VMAT) = (42 ± 4) Gy to its 2019 Dmean (gEUD) = (30 ± 8) Gy (p <0.05) and 2020 Dmean (RapidPlan) = (27 ± 5) Gy (p <0.05). Figure 2 shows the results for the bladder. The dose-volume values of all the metrics and the variability decrease, both in gEUD as RapidPlan, although not all of them reached statistical significance (V70Gy, V74Gy, V76Gy). The bladder mean dose decreased significantly from its initial 2018 Dmean (VMAT) = (33 ± 9) Gy to 2019 Dmean (gEUD) = (24 ± 8) Gy (p <0.05) and 2020 Dmean (RapidPlan) = (26 ± 8) Gy (p <0.05).
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