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Purpose To validate a novel device developed at our institution for deep inspiration breath hold (DIBH) within a phase 2 clinical trial for left-sided breast cancer and to evaluate the dosimetric benefits of its use. Methods and Materials The device uses an external mechanical reference for guiding the patient to the desired breath level and gives acoustic and visual feedback to the patient and the radiation therapists, respectively. A phase 2 clinical trial was performed for its validation. The thoracic amplitude was used as a surrogate of the inspiration level. The stability, repeatability, reproducibility, and reliability of DIBH using the device were analyzed. The dosimetric parameters of the heart, the left anterior descending coronary artery, the ipsilateral lung, the contralateral breast, and the target coverage using free breathing and DIBH were compared. Results Thirty-eight patients were included in the analysis. The maximum population value of stability and repeatability were 1.7 mm and 3.3 mm, respectively. The reproducibility mean value was 1.7 mm, and population systematic and random errors were 0.3 mm and 0.9 mm, respectively. The reliability was 98.9%. Statistically significant dose reductions were found for the heart, the left anterior descending coronary artery, and the ipsilateral lung dosimetric parameters in DIBH, without losing dose coverage to the planning target volumes. Conclusions The validation of the device within the phase 2 clinical trial demonstrates that it offers reliable, stable, repeatable, and reproducible breast cancer treatments in DIBH with its dosimetric benefits.

PURPOSE Convolution/superposition algorithms used in MV photon radiotherapy model radiation transport in water, yielding dose to water-in-water (Dw,w ). Advanced algorithms constitute a step forward, but their dose distributions in terms of dose to medium-in-medium (Dm,m ) or dose to water-in-medium (Dw,m ) can be problematic when used in plan optimization due to their different dose responses to some atomic composition heterogeneities. Failure to take this into account can lead to undesired overcorrections and thus to unnoticed suboptimal and unrobust plans. Dose to reference-like medium (Dref,m ) was recently introduced to overcome these limitations while ensuring accurate transport. This work evaluates and compares the performance of these four dose quantities in PTV-based optimization. METHODS We considered three cases with heterogeneities inside the PTV: virtual phantom with water surrounded by bone; head and neck; and lung. These cases were planned with VMAT technique, optimizing with the same setup and objectives for each dose quantity. We used different algorithms of the Varian Eclipse treatment planning system (TPS): Acuros XB for Dm,m and Dw,m , and AAA for Dw,w . Dref,m was obtained from Dm,m distributions using an in-house software considering water as the reference medium (Dw,m ). The optimization process consisted of: (1) common first optimization, (2) dose distribution computed for each quantity, (3) re-optimization, (4) final calculation for each dose quantity. The dose distribution, robustness to patient setup errors, and complexity of the plans were analyzed and compared. RESULTS The quantities showed similar dose distributions after the optimization but differed in terms of plan robustness. The cases with soft tissue and high-density heterogeneities followed the same pattern. For AXB Dm,m , cold regions appeared in the heterogeneities after the first optimization. They were compensated in the second optimization through local fluence increases, but any positional mismatch impacted robustness, with CTV variations from the nominal scenario around +3% for bone and up to +7% for metal. For AXB Dw,m the pattern was inverse (hot regions compensated by fluence decreases) and more pronounced, with CTV dose variations around -7% for bone and up to -17% for metal. Neither AXB Dw,m nor AAA Dw,w presented these dose inhomogeneities, which resulted in more robust plans. However, Dw,w differed markedly from the other quantities in the lung case because of its lower radiation transport accuracy. AXB Dm,m was the most complex of the four dose quantities and AXB Dw,m the least complex, though we observed no major differences in this regard. CONCLUSIONS The dose quantity used in MV photon optimization can affect plan robustness. Dw,w distributions from convolution/superposition algorithms are robust but may not provide sufficient radiation transport accuracy in some cases. Dm,m and Dw,m from advanced algorithms can compromise robustness because their different responses to some composition heterogeneities introduce additional fluence compensations. Dref,m offers advantages in plan optimization and evaluation, producing accurate and robust plans without increasing complexity. Dref,m can be easily implemented as a built-in feature of the TPS and can facilitate and simplify the treatment planning process when using advanced algorithms. Final reporting can be kept in Dm,m or Dw,m for clinical correlations. This article is protected by copyright. All rights reserved.

To assess adherence to standard clinical practice for the diagnosis and treatment of patients undergoing prostate cancer (PCa) radiotherapy in four European countries using clinical audits as part of the international IROCA project. Multi-institutional, retrospective cohort study of 240 randomly-selected patients treated for PCa (n = 40/centre) in the year 2015 at six European hospitals. Clinical indicators applicable to general and PCa-specific radiotherapy processes were evaluated. All data were obtained directly from medical records. The audits were performed in the year 2017. Adherence to clinical protocols and practices was satisfactory, but with substantial inter-centre variability in numerous variables, as follows: staging MRI (range 27.5–87.5% of cases); presentation to multidisciplinary tumour board (2.5–100%); time elapsed between initial visit to the radiation oncology department and treatment initiation (42–102.5 days); number of treatment interruptions ≥ 1 day (7.5–97.5%). The most common deviation from standard clinical practice was inconsistent data registration, mainly failure to report data related to diagnosis, treatment, and/or adverse events. This clinical audit detected substantial inter-centre variability in adherence to standard clinical practice, most notably inconsistent record keeping. These findings confirm the value of performing clinical audits to detect deviations from standard clinical practices and procedures.

Advanced algorithms used in MV photon radiotherapy model radiation transport in any media. They represent a step forward but introduce new uncertainties and questions, including whether to report the doses to water (Dw,m) or medium (Dm,m) voxels, and the impact of fluence changes introduced by surrounding media. These aspects can compromise consistency between both reporting modes and with previous algorithms in which clinical experience is based. This study introduces a new dose quantity, the dose-to-reference-like medium, to overcome the aforementioned shortcomings. It is linked to a reference medium, water in this study (Dw,m*), and defined as the absorbed dose in a voxel of this reference medium surrounded by a reference-like medium with the same radiation transport characteristics as the original one. We propose to derive Dw,m* distributions by post-processing Dw,m or Dm,m applying a correction factor (CF) to each voxel which depends on its composition. We present and justify a simple and straightforward method to obtain CFs that only involves two phantoms with the same density: one with the considered composition and the other with that of the reference medium. A proof of concept was performed in a clinical environment for Acuros XB (AXB) advanced algorithm and 6 MV photon beams. The CFs were derived for the tissues characterised in Acuros. Dw,m* was compared to Dw,m, Dm,m, and Dw,w from AAA analytical algorithm for some virtual and clinical cases. All the previous quantities presented limitations that can be solved by Dw,m*. This new quantity allows the applicability of evaluation parameters, traceability to clinical experience, and isolation of heterogeneity effects to identify optimum plans, offering useful characteristics for plan evaluation and optimisation in clinical practice. Additionally, it also has potential applications in automated treatment planning and multi-centre activities such as clinical trials, audits, benchmarking, and shared models for automation.

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. (C) 2020 The Authors. Published by Elsevier B.V.

International audience; Purpose To assess the dosimetric impact of switching from the Analytical Anisotropic Algorithm (AAA) to Acuros XB (AXB) for both dose-to-medium (Dm) and dose-to-water (Dw) in VMAT for HandN patients. To study whether it should be linked to a change in the dose prescriptions to the PTVs and in the constraints to the OARs. Methods 110HandN patients treated with VMAT were included. Calculations were performed with AAA and AXB. PTV54, PTV60, PTV70, spinal cord, brainstem, brain, larynx, oral cavity, cochleas, parotid glands and mandible were delineated. Clinically-relevant dose-volume parameters were compared. Paired t-tests were used to analyze the differences in mean values. The Pitman-Morgan dispersion test was computed to evaluate inter-patient variability of these differences. Results AAA overestimated all dose-volume parameters compared to AXB Dm (0.2 Gy to 2.4 Gy). No systematic trend was observed in the differences between AAA and AXB Dw (-5.3 Gy to 0.6 Gy). Dose-volume parameters were significantly higher for AXB Dw compared to AXB Dm (0.1 Gy to 6.6 Gy). In all cases, the largest absolute differences (4%–14%) were found for maximum absorbed doses to the cochleas and the mandible. The number of parameters with significant inter-patient variability was greater when switching from AAA to AXB Dw than from AAA to AXB Dm. Conclusions There are important differences between AXB and AAA in VMAT planning for HandN cancer. The systematic differences and their inter-patient variability identified may help to facilitate decision-making about the dose prescriptions to the PTVs and the constraints to the OAR. © 2018 Associazione Italiana di Fisica Medica

Highlights • Several complexity metrics were highly correlated and can be considered equivalent. • Other metrics produced different results, especially for plans from different TPSs. • Different TPSs prioritise modulation of different plan parameters. • The ranking of plan complexity can greatly depend on the metric used. • This must be carefully considered in multi-institutional plan comparisons., Background and purpose It is known that intensity-modulated radiotherapy plans that are highly complex might be less accurate in dose calculation and treatment delivery. Multiple complexity metrics have been proposed, but the relationships between them have not been thoroughly investigated. This study investigated these relationships in multi-institutional comparisons of treatment plans, where plans from multiple treatment planning systems (TPSs) are typically evaluated. Materials and methods A program was developed to compute several complexity indices and provide analysis of dynamic plan parameters. This in-house software was used to analyse plans from a recent multi-institutional audit. Additionally, 100 clinical volumetric modulated arc therapy (VMAT) plans from two institutions using different TPSs were analysed. Results All plans produced satisfactory pre-treatment verification results and, hence, complexity metrics could not be used to predict plans failing QA. Regarding the relationship among complexity indices, some very strong correlations were found (r > 0.9 with p

Purpose Our purpose was to assess the dosimetric effect of switching from the analytical anisotropic algorithm (AAA) to Acuros XB (AXB), with dose-to-medium (Dm) and dose-to-water (Dw) reporting modes, in lung stereotactic body radiation therapy patients and determine whether planning-target-volume (PTV) dose prescriptions and organ-at-risk constraints should be modified under these circumstances. Methods and Materials We included 54 lung stereotactic body radiation therapy patients. We delineated the PTV, the ipsilateral lung, the contralateral lung, the heart, the spinal cord, the esophagus, the trachea, proximal bronchi, the ribs, and the great vessels. We performed dose calculations with AAA and AXB, then compared clinically relevant dose-volume parameters. Paired t tests were used to analyze differences of means. We propose a method, based on the composition of the involved structures, for predicting differences between AXB Dw and Dm calculations. Results The largest difference between the algorithms was 4%. Mean dose differences between AXB Dm and AXB Dw depended on the average composition of the volumes. Compared with AXB, AAA underestimated all PTV dose-volume parameters (-0.7 Gy to -0.1 Gy) except for gradient index, which was significantly higher (4%). It also underestimated V5 of the contralateral lung (-0.3%). Significant differences in near-maximum doses (D2) to the ribs were observed between AXB Dm and AAA (1.7%) and between AXB Dw and AAA (-1.6%). AAA-calculated D2 was slightly higher in the remaining organs at risk. Conclusions Differences between AXB and AAA are below the threshold of clinical detectability (5%) for most patients. For a small subgroup, the difference in maximum doses to the ribs between AXB Dw and AXB Dm may be clinically significant. The differences in dose volume parameters between AXB Dw and AXB Dm can be predicted with reference to structure composition

Background and purpose: We performed a multi-centre intercomparison of VMAT dose planning and pretreatment verification. The aims were to analyse the dose plans in terms of dosimetric quality and deliverability, and to validate whether in-house pre-treatment verification results agreed with those of an external audit. Materials and methods: The nine participating centres encompassed different machines, equipment, and methodologies. Two mock cases (prostate and head and neck) were planned using one and two arcs. A plan quality index was defined to compare the plans and different complexity indices were calculated to check their deliverability. We compared gamma index pass rates using the centre's equipment and methodology to those of an external audit (global 3D gamma, absolute dose differences, 10% of maximum dose threshold). Log-file analysis was performed to look for delivery errors. Results: All centres fulfilled the dosimetric goals but plan quality and delivery complexity were heterogeneous and uncorrelated, depending on the manufacturer and the planner's methodology. Pretreatment verifications results were within tolerance in all cases for gamma 3%-3 mm evaluation. Nevertheless, differences between the external audit and in-house measurements arose due to different equipment or methodology, especially for 2%-2 mm criteria with differences up to 20%. No correlation was found between complexity indices and verification results amongst centres. Conclusions: All plans fulfilled dosimetric constraints, but plan quality and complexity did not correlate and were strongly dependent on the planner and the vendor. In-house measurements cannot completely replace external audits for credentialing. (C) 2017 Elsevier B.V. All rights reserved.