ESTRO 2020 Abstract Book

S111 ESTRO 2020

from 6.7 MeV to 7.7 MeV with measured data for a 2×2 cm 2 field. The optimum radial intensity distribution was found by varying the radial full width at half maximum (FWHM) between 0.4 mm and 4.0 mm and comparing simulated to measured lateral profiles for a field size of 22×22 cm 2 . The influence of the energy distribution was investigated by comparing simulated lateral and depth dose profiles of 22×22 cm 2 fields with varying energy spreads (0% - 20%) to measured data. Additionally, PDDs and cross profiles were determined with the TPS Monaco (V4.40). Comparison of simulations and TPS with measurements was performed by calculating average and maximum local dose deviations with respect to the experimental data. In addition, output factors (OF) were compared for square fields from 2×2 to 22×22 cm 2 . Results The tuning of parameters for the EGSnrc accelerator and cryostat model of the 1.5 T Elekta Unity and comparison with experimental data showed that the optimum initial electron beam for MRL simulations was monoenergetic with an electron energy of (7.4 ± 0.2) MeV. The optimum Gaussian radial intensity distribution had a FWHM of (2.2 ± 0.3) mm. The average relative deviations of the simulations were below 1% for all simulated profiles with optimum electron parameters, whereas the largest maximum deviation of 2.07% was found for the 22×22 cm 2 cross-plane profile. For the TPS calculated profiles, mean and maximum deviations were <1% and 2.5%, respectively. Profiles were insensitive to energy spread variations. Figure 1 presents PDDs and profiles for exemplary fields. The mean relative difference (range) of simulation- or TPS- based OF with respect to measured data was 0.08% (-0.90% - 1.18%) and -0.19% (-0.88% – 0.44%), respectively (cf. Figure 2).

therefore shows the general possibility for investigation of more complex research questions and future secondary dose calculations.

Proffered Papers: Proffered papers 12: Artificial Intelligence and automation

OC-0220 Treatment planning without user interaction: Automatic plan approval of prostate Auto-Plans K. Kiers 1 , E. Van der Bijl 1 , J. Trinks 1 , A. Hogaarts 1 , R. Van der Bel 1 , G. Wortel 1 , E. Damen 1 , J. Tomas 1 1 The Netherlands Cancer Institute, Department of Radiation Oncology, Amsterdam, The Netherlands Purpose or Objective While automated treatment planning improves planning efficiency, in practice it is hard for dosimetrists to judge whether a plan can still be improved, resulting in unnecessary further optimizations. Using a combination of patient specific, delineation-based predictions, population statistics and strict clinical criteria, plans that potentially can be improved can be flagged and plan approval can be automated. The purpose of this work is to investigate the impact of fully automated treatment plan verification of prostate Auto-Plans on plan quality and efficiency. Material and Methods 100 treatment plans of prostate cancer patients with seminal vesicle invasion, without a hip prosthesis or bowel loop near the target, with a prescription of 20x3Gy were included and split in a train, test and validation set (42/10/48). The plans were generated using Pinnacle 3 Auto-Planning and automatically scaled to a sufficient coverage (Auto-Plans). In clinical practice Auto-Plans are evaluated manually and possibly adjusted (Clinical plans). The rectum- and anal sphincter Dmean and V95% were predicted using a linear regression model based on the PTV-OAR overlap volume histogram at 0 and 10 mm expansion. The conformity of the 80% isodose line was predicted based on the volume of the PTV, and thresholds on the PTV inhomogeneity were set based on population statistics such that the highest 5% would be captured. These thresholds and predictions, with a margin of 2 standard deviations to take in account inaccuracies of the models, were added to the existing general clinical criteria as personalized constraints to capture plans that can be improved even under the strict clinical criteria. The Auto-Plans in the validation set were evaluated on PTV coverage and - inhomogeneity, and the general and personalized OAR constraints. Plans that did not meet all criteria would be considered rejected and vice versa. This was retrospectively compared to which plans were adjusted in clinical practice. The magnitude of the adjustments was quantified and the relevance was discussed with an experienced dosimetrist. Results Only 4.2% of the automated plans in the validation set were rejected according to the automated plan approval for violation of one or more constraints (Table 1). All but one of the captured Auto-Plans could indeed be improved with manual adjustments. Of the automatically accepted plans, 13% had actually been adjusted in clinical practice. However, none of these adjustments were judged clinically relevant with no significant difference in rectum Dmean (0.55Gy ± 1.2Gy), anal sphincter Dmean (0.22Gy ± 0.8Gy) and target V95% (0.01% ± 0.5%).

Conclusion The developed EGSnrc MRL model for the 1.5 T Elekta Unity showed good agreement with measured data. It