Objective: The aim of this work was to investigate the main dosimetric characteristics and the performance of an A26 Exradin ionization microchamber (A26 IC) and a W1 Exradin plastic scintillation detector (W1 PSD) in small photon beam dosimetry for treatment planning system commissioning and quality assurance programme. Methods: Detector characterization measurements (short-term stability, dose linearity, angular dependence and energy dependence) were performed in water for field sizes up to 10 3 10 cm 2 . Polarity effect (P pol ) was examined for the A26 IC. The behaviour of the detectors in small field relative dosimetry [percentage depth dose, dose profiles often called the off-axis ratio and output factors (OFs)] was investigated for field sizes ranging from 1 3 1 to 3 3 3 cm 2 . Results: Results were compared with those obtained with other detectors we already use for small photon beam dosimetry. A26 IC and W1 PSD showed a linear dose response. While the A26 IC showed no energy dependence, the W1 PSD showed energy dependence within 2%; no angular dependence was registered. P pol values for A26 IC were below 0.9% (0.5% for field size .2 3 2 cm 2 ). A26 IC and W1 PSD depth-dose curves and lateral profiles agreed with those obtained with an EDGE diode. No differences were observed among the detectors in OF measurement for field sizes larger than 1 3 1 cm 2 , with average differences ,1%. For field sizes ,1 3 1 cm 2 , the effective volume of ionization chamber and non-water equivalence of EDGE diode become significant. A26 IC OF values were significantly lower than EDGE diode and W1 PSD values, with percentage differences of about 223 and 213% for the smallest field, respectively. W1 PSD OF values lay between ion chambers and diode values, with a maximum percentage difference of about 210% with respect to the EDGE diode, for a 6 3 6-mm 2 field size. Conclusion: The results of our investigation confirm that A26 IC and W1 PSD could play an important role in small field relative dosimetry. Advances in knowledge: Dosimetric characteristics of Exradin A26 ionization microchamber and W1 plastic scintillation detector for small field dosimetry.

Proper delineation of both target volumes and organs at risk is a crucial step in the radiation therapy workflow. This process is normally carried out manually by medical doctors, hence demanding timewise. To improve efficiency, auto-contouring methods have been proposed. We assessed a specific commercial software to investigate its impact on the radiotherapy workflow on four specific disease sites: head and neck, prostate, breast, and rectum. For the present study, we used a commercial deep learning-based auto-segmentation software, namely Limbus Contour (LC), Version 1.5.0 (Limbus AI Inc., Regina, SK, Canada). The software uses deep convolutional neural network models based on a U-net architecture, specific for each structure. Manual and automatic segmentation were compared on disease-specific organs at risk. Contouring time, geometrical performance (volume variation, Dice Similarity Coefficient—DSC, and center of mass shift), and dosimetric impact (DVH differences) were evaluated. With respect to time savings, the maximum advantage was seen in the setting of head and neck cancer with a 65%-time reduction. The average DSC was 0.72. The best agreement was found for lungs. Good results were highlighted for bladder, heart, and femoral heads. The most relevant dosimetric difference was in the rectal cancer case, where the mean volume covered by the 45 Gy isodose was 10.4 cm3 for manual contouring and 289.4 cm3 for automatic segmentation. Automatic contouring was able to significantly reduce the time required in the procedure, simplifying the workflow, and reducing interobserver variability. Its implementation was able to improve the radiation therapy workflow in our department.

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