A stricter gamma-index (2%/2 mm) is necessary in order to detect positional errors of the MLC. Nevertheless, the quality assurance procedure of Rapidarc treatment plans must include a thorough examination of where dose discrepancies occur, and professional judgment is needed when interpreting the gamma-index analysis, since even a >90% passing rate using the 2%/2 mm gamma-index criterion does not guarantee the absence of clinically significance dose deviation.

Recently, a new type of radiochromic film, the EBT-XD film, has been introduced for high dose radiotherapy. The EBT-XD film contains the same structure as the EBT3 film but has a slightly different composition and a thinner active layer. This study benchmarks the EBT-XD against EBT3 film for 6 MV and 10 MV photon beams, as well as for 97.4 MeV and 148.2 MeV proton beams and 15-100 kV x-rays. Dosimetric and film reading characteristics, such as post irradiation darkening, film orientation effect, lateral response artifact (LRA), film sensitivity, energy and beam quality dependency were investigated. Furthermore, quenching effects in the Bragg peak were investigated for a single proton beam energy for both film types, in addition measurements were performed in a spread-out Bragg peak. EBT-XD films showed the same characteristic on film darkening as EBT3. The effects between portrait and landscape orientation were reduced by 3.1% (in pixel value) for EBT-XD compared to EBT3 at a dose of 2000 cGy. The LRA is reduced for EBT-XD films for all investigated dose ranges. The sensitivity of EBT-XD films is superior to EBT3 for doses higher than 500 cGy. In addition, EBT-XD showed a similar dosimetric response for photon and proton irradiation with low energy and beam quality dependency. A quenching effect of 10% was found for both film types. The slight decrease in the thickness of the active layer and different composition configuration of EBT-XD resulted in a reduced film orientation effect and LRA, as well as a sensitivity increase in high-dose regions for both photon and proton beams. Overall, the EBT-XD film improved regarding film reading characteristics and showed advantages in the high-dose region for photon and proton beams.

Introduction: This paper explores the potential of the StyleGAN model as an high-resolution image generator for synthetic medical images. The possibility to generate sample patient images of different modalities can be helpful for training deep learning algorithms as e.g. a data augmentation technique. Methods: The StyleGAN model was trained on Computed Tomography (CT) and T2-weighted Magnetic Resonance (MR) images from 100 patients with pelvic malignancies. The resulting model was investigated with regards to three features: Image Modality, Sex, and Longitudinal Slice Position. Further, the style transfer feature of the StyleGAN was used to move images between the modalities. The root-mean-squard error (RMSE) and the Mean Absolute Error (MAE) were used to quantify errors for MR and CT, respectively. Results: We demonstrate how these features can be transformed by manipulating the latent style vectors, and attempt to quantify how the errors change as we move through the latent style space. The best results were achieved by using the style transfer feature of the StyleGAN (58.7 HU MAE for MR to CT and 0.339 RMSE for CT to MR). Slices below and above an initial central slice can be predicted with an error below 75 HU MAE and 0.3 RMSE within 4 cm for CT and MR, respectively. Discussion: The StyleGAN is a promising model to use for generating synthetic medical images for MR and CT modalities as well as for 3D volumes.