a b s t r a c tBackground and purpose: A planning target volume (PTV) in photon treatments aims to ensure that the clinical target volume (CTV) receives adequate dose despite treatment uncertainties. The underlying static dose cloud approximation (the assumption that the dose distribution is invariant to errors) is problematic in intensity modulated proton treatments where range errors should be taken into account as well. The purpose of this work is to introduce a robustness evaluation method that is applicable to photon and proton treatments and is consistent with (historic) PTV-based treatment plan evaluations. Materials and methods: The limitation of the static dose cloud approximation was solved in a multiscenario simulation by explicitly calculating doses for various treatment scenarios that describe possible errors in the treatment course. Setup errors were the same as the CTV-PTV margin and the underlying theory of 3D probability density distributions was extended to 4D to include range errors, maintaining a 90% confidence level. Scenario dose distributions were reduced to voxel-wise minimum and maximum dose distributions; the first to evaluate CTV coverage and the second for hot spots. Acceptance criteria for CTV D98 and D2 were calibrated against PTV-based criteria from historic photon treatment plans. Results: CTV D98 in worst case scenario dose and voxel-wise minimum dose showed a very strong correlation with scenario average D98 (R 2 > 0.99). The voxel-wise minimum dose visualised CTV dose conformity and coverage in 3D in agreement with PTV-based evaluation in photon therapy. Criteria for CTV D98 and D2 of the voxel-wise minimum and maximum dose showed very strong correlations to PTV D98 and D2 (R 2 > 0.99) and on average needed corrections of À0.9% and +2.3%, respectively. Conclusions: A practical approach to robustness evaluation was provided and clinically implemented for PTV-less photon and proton treatment planning, consistent with PTV evaluations but without its static dose cloud approximation. Ó 2019 The Authors. Published by Elsevier B.V. Radiotherapy and Oncology 141 (2019) 267-274 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).The use of margins in photon radiotherapy is a long established and universally adopted method to provide adequate target coverage under the presence of uncertainties. The CTV-PTV margin provides a geometrical buffer zone around the target within which the desired dose is achieved for the majority of treatments; criteria of 95% of the prescription dose in 90% of the patient population has found general appeal [1,2]. The suitability of a geometricallyexpanded buffer zone arises from the (relative) insensitivity of megavoltage photon dose distributions to density changes in the beam path. By and large, the biggest risk to a photon dose distribution is a geometrical miss -a translation of the CTV relative to the beam. Therefore, the static dose cloud approximation (dose distribution is invariant to errors)...

In the Netherlands, head and neck cancer (HNC) patients qualify for intensity modulated proton therapy (IMPT) based on model-based selection (MBS). The aim of this study was to evaluate the first experience in MBS of HNC patients. Methods: Patients who were subjected to MBS (Jan 2018-Sep 2019) were evaluated. A VMAT plan was created for all patients with optimal sparing of organ at risks (OARs) in normal tissue complication probability (NTCP) models for a number of toxicities. An IMPT plan was created only for those with NTCP difference (DNTCP) between VMAT and best-case scenario for proton (assuming 0 Gy dose for all OARs in IMPT plan) that exceeded any DNTCP-thresholds defined in Dutch National Indication Protocol. These patients qualified for a robust IMPT-plan creation with similar target doses and subsequent plan comparison. Results: Of 227 patients, 141 (62%) qualified for plan comparison, of which 80 (35%) were eventually selected for proton therapy. Most patients were selected based on the DNTCP for dysphagia-related toxicities. The selection rate was higher among patients with advanced disease, pharyngeal tumors, and/or baseline complaints. A significant reduction in all OAR doses and NTCP values was obtained with IMPT compared with VMAT in both selected and non-selected patients, but more pronounced in patients selected for protons. Conclusion: Model-based selection of patients with HNC for proton therapy is clinically feasible. Approximately one third of HNC patients qualify for protons and these patients have the highest probability to benefit from protons in terms of toxicity prevention.

Pencil beam scanning (PBS) proton therapy requires the delivery of many thousand proton beams, each modulated for position, energy and monitor units, to provide a highly conformal patient treatment. The quality of the treatment is dependent on the delivery accuracy of each beam and at each fraction. In this work we describe the use of treatment log files, which are a record of the machine parameters for a given field delivery on a given fraction, to investigate the integrity of treatment delivery compared to the nominal planned dose. The dosimetry-relevant log file parameters are used to reconstruct the 3D dose distribution on the patient anatomy, using a TPS-independent dose calculation system. The analysis was performed for patients treated at Paul Scherrer Institute on Gantry 2, both for individual fields and per series (or plan), and delivery quality was assessed by determining the percentage of voxels in the log file dose distribution within  +/-  1% of the nominal dose. It was seen that, for all series delivered, the mean pass rate is 96.4%. Furthermore, this work establishes a correlation between the delivery quality of a field and the beam position accuracy. This correlation is evident for all delivered fields regardless of individual patient or plan characteristics. We have also detailed further usefulness of log file analysis within our clinical workflow. In summary, we have highlighted that the integrity of PBS treatment delivery is dependent on daily machine performance and is specifically highly correlated with the accuracy of beam position. We believe this information will be useful for driving machine performance improvements in the PBS field.