Plan evaluation is a key step in the radiotherapy treatment workflow. Central to this step is the assessment of treatment plan quality. Hence, it is important to agree on what we mean by plan quality and to be fully aware of which parameters it depends on. We understand plan quality in radiotherapy as the clinical suitability of the delivered dose distribution that can be realistically expected from a treatment plan. Plan quality is commonly assessed by evaluating the dose distribution calculated by the treatment planning system (TPS). Evaluating the 3D dose distribution is not easy, however; it is hard to fully evaluate its spatial characteristics and we still lack the knowledge for personalising the prediction of the clinical outcome based on individual patient characteristics. This advocates for standardisation and systematic collection of clinical data and outcomes after radiotherapy. Additionally, the calculated dose distribution is not exactly the dose delivered to the patient due to uncertainties in the dose calculation and the treatment delivery, including variations in the patient set-up and anatomy. Consequently, plan quality also depends on the robustness and complexity of the treatment plan. We believe that future work and consensus on the best metrics for quality indices are required. Better tools are needed in TPSs for the evaluation of dose distributions, for the robust evaluation and optimisation of treatment plans, and for controlling and reporting plan complexity. Implementation of such tools and a better understanding of these concepts will facilitate the handling of these characteristics in clinical practice and be helpful to increase the overall quality of treatment plans in radiotherapy.

New treatment modalities in radiotherapy (RT) enable delivery of highly conformal dose distributions in patients. This creates a need for precise dose verification in three dimensions (3D). A radiochromic silicone-based 3D dosimetry system has recently been developed. Such a dosimeter can be used for dose verification in deformed geometries, which requires knowledge of the dosimeter's mechanical properties. In this study we have characterized the dosimeter's elastic behaviour under tensile and compressive stress. In addition, the dose response under strain was determined. It was found that the dosimeter behaved as an incompressible hyperelastic material with a non-linear stress/strain curve and with no observable hysteresis or plastic deformation even at high strains. The volume was found to be constant within a 2% margin at deformations up to 60%. Furthermore, it was observed that the dosimeter returned to its original geometry within a 2% margin when irradiated under stress, and that the change in optical density per centimeter was constant regardless of the strain during irradiation. In conclusion, we have shown that this radiochromic silicone-based dosimeter's mechanical properties make it a viable candidate for dose verification in deformable 3D geometries.

A B S T R A C TBackground and purpose: The limited image quality in Cone Beam CT (CBCT) stemming primarily from scattered radiation hinders accurate CBCT based dose calculation in radiotherapy. We investigated the use of a stoichiometric calibration for dose calculation on CBCT images of lung cancer patients. Materials and methods: CBCT calibrations were performed with thorax scan protocols, using a phantom with approximately the diameter of an average human thorax and a central cavity simulating the thoracic cavity. Thus scatter conditions resembling those in clinical thorax CBCT scans were simulated. A published stoichiometric parametrization was used. A treatment plan was simulated on CBCT and CT scans of an anthropomorphic phantom, the dose distributions were calculated, and clinically relevant DVH parameters were compared. Twelve lung cancer patients had surveillance CT scans (s-CT) taken twice during their treatment course in addition to daily setup CBCTs. Dose calculations were performed on the s-CTs and the corresponding CBCTs taken on the same day, and DVH parameters were compared. Results: Eighty percent of CBCT DVH parameters found for the phantom were within ± 1% of CT doses, and 98% were within ± 3%. For patients, the median CT/ CBCT dose difference was within ± 2%, and 98% of DVH parameters were within ± 4%. Minimum dose to the tumor was underestimated (median 1.9%) on CBCT, while maximum doses to most organs at risk were slightly overestimated. Conclusion: Direct dose calculations on CBCTs of lung cancer patients were feasible within ∼4% accuracy using a simple calibration method, which is easily implemented in a clinical setting.

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