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.

Objective: To establish optimal robust optimization uncertainty settings for clinical head and neck cancer (HNC) patients undergoing 3D image-guided pencil beam scanning (PBS) proton therapy. Methods: We analyzed ten consecutive HNC patients treated with 70 and 54.25 Gy RBE to the primary and prophylactic clinical target volumes (CTV) respectively using intensity-modulated proton therapy (IMPT). Clinical plans were generated using robust optimization with 5 mm/3% setup/range uncertainties (RayStation v6.1). Additional plans were created for 4, 3, 2 and 1 mm setup and 3% range uncertainty and for 3 mm setup and 3%, 2% and 1% range uncertainty. Systematic and random error distributions were determined for setup and range uncertainties based on our quality assurance program. From these, 25 treatment scenarios were sampled for each plan, each consisting of a systematic setup and range error and daily random setup errors. Fraction doses were calculated on the weekly verification CT closest to the date of treatment as this was considered representative of the daily patient anatomy. Results: Plans with a 2 mm/3% setup/range uncertainty setting adequately covered the primary and prophylactic CTV (V 95 ! 99% in 98.8% and 90.8% of the treatment scenarios respectively). The average organat-risk dose decreased with 1.1 Gy RBE /mm setup uncertainty reduction and 0.5 Gy RBE /1% range uncertainty reduction. Normal tissue complication probabilities decreased by 2.0%/mm setup uncertainty reduction and by 0.9%/1% range uncertainty reduction. Conclusion: The results of this study indicate that margin reduction below 3 mm/3% is possible but requires a larger cohort to substantiate clinical introduction.

Patients with squamous cell carcinoma of the oropharynx are generally treated with (chemo) radiation. Patients with oropharyngeal cancer have better survival than patients with squamous cell carcinoma of other head and neck subsites, especially when related to human papillomavirus. However, radiotherapy results in a substantial percentage of survivors suffering from significant treatment-related side-effects. Late radiation-induced side-effects are mostly irreversible and may even be progressive, and particularly xerostomia and dysphagia affect health-related quality of life. As the risk of radiation-induced side-effects highly depends on dose to healthy normal tissues, prevention of radiation-induced xerostomia and dysphagia and subsequent improvement of health-relatedquality of life can be obtained by applying proton therapy, which offers the opportunity to reduce the dose to both the salivary glands and anatomic structures involved in swallowing. This review describes the results of the first cohort studies demonstrating that proton therapy results in lower dose levels in multiple organs at risk, which translates into reduced acute toxicity (i.e. up to 3 months after radiotherapy), while preserving tumour control. Next to reducing mucositis, tube feeding, xerostomia and distortion of the sense of taste, protons can improve general well-being by decreasing fatigue and nausea. Proton therapy results in decreased rates of tube feeding dependency and severe weight loss up to 1 year after radiotherapy, and may decrease the risk of radionecrosis of the mandible. Also, the model-based approach for selecting patients for proton therapy in the Netherlands is described in this review and future perspectives are discussed.

Patient selection for proton therapy is increasingly based on proton to photon plan comparisons. To improve efficient decision making, we developed a dose mimicking and reducing (DMR) algorithm to automatically generate a robust proton plan from a reference photon dose and target and organs at risk (OARs) delineations. The DMR algorithm was evaluated in 40 head and neck cancer patients. The first step of the DMR algorithm comprises DVH-based mimicking of the photon dose distribution in the clinical target volumes and OARs. Target robustness is included by mimicking the nominal photon dose in 21 perturbed scenarios. The second step of the optimization aims to reduce the OAR doses while retaining the robust target coverage as achieved in the first step. We evaluated each DMR plan against the 'manually' robustly optimized reference proton plan in terms of plan robustness (voxel-wise minimum dose). Furthermore, the DMR plans were evaluated against the reference photon plan using normal tissue complication probability (NTCP) models of xerostomia, dysphagia and tube feeding dependence. Consequently, ΔNTCPs were defined as the difference between the NTCPs of the photon and proton plans. The dose distributions of the DMR and reference proton plans were very similar in terms of target robustness and OAR dose values. Regardless of proton planning technique (i.e. DMR or reference proton plan), the same treatment modality was selected in 80% (32/40) of cases based on the ∑ΔNTCPs. In 15% (6/40) of cases a conflicting decision was made based on relatively small dose differences to the OARs (<2.0 Gy). The DMR algorithm automatically optimized robust proton plans from a photon reference dose comparable to the dosimetrist-optimized proton plans in head and neck cancer patients. This algorithm has been successfully embedded into a framework to automatically select patients for proton therapy based on normal tissue complication probabilities.

Elliptically birefringent fibre has been fabricated by spinning the preform of a highly linearly birefringent photonic crystal fibre (PCF) during the drawing process. The resulting Spun Highly Birefringent (SHi-Bi) PCF offers intrinsic sensitivity to magnetic fields through the Faraday effect without the high inherent temperature sensitivities suffered by conventional spun stress birefringence fibres. The ellipticity of the birefringence has been measured and temperature independence has been demonstrated.

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