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Objective. To establish an open framework for developing plan optimization models for knowledge-based planning (KBP). Approach. Our framework includes radiotherapy treatment data (i.e. reference plans) for 100 patients with head-and-neck cancer who were treated with intensity-modulated radiotherapy. That data also includes high-quality dose predictions from 19 KBP models that were developed by different research groups using out-of-sample data during the OpenKBP Grand Challenge. The dose predictions were input to four fluence-based dose mimicking models to form 76 unique KBP pipelines that generated 7600 plans (76 pipelines × 100 patients). The predictions and KBP-generated plans were compared to the reference plans via: the dose score, which is the average mean absolute voxel-by-voxel difference in dose; the deviation in dose-volume histogram (DVH) points; and the frequency of clinical planning criteria satisfaction. We also performed a theoretical investigation to justify our dose mimicking models. Main results. The range in rank order correlation of the dose score between predictions and their KBP pipelines was 0.50-0.62, which indicates that the quality of the predictions was generally positively correlated with the quality of the plans. Additionally, compared to the input predictions, the KBP-generated plans performed significantly better ( P < 0.05; one-sided Wilcoxon test) on 18 of 23 DVH points. Similarly, each optimization model generated plans that satisfied a higher percentage of criteria than the reference plans, which satisfied 3.5% more criteria than the set of all dose predictions. Lastly, our theoretical investigation demonstrated that the dose mimicking models generated plans that are also optimal for an inverse planning model. Significance. This was the largest international effort to date for evaluating the combination of KBP prediction and optimization models. We found that the best performing models significantly outperformed the reference dose and dose predictions. In the interest of reproducibility, our data and code is freely available., (Creative Commons Attribution license.)

Linac based radiosurgery to multiple metastases is commonly planned with volumetric modulated arc therapy (VMAT) as it effectively achieves high conformality to complex target arrangements. However, as the number of targets increases, VMAT can struggle to block between targets, which can lead to highly modulated and/or nonconformal multi-leaf collimator (MLC) trajectories that unnecessarily irradiation of healthy tissue. In this study we introduce, describe, and evaluate a treatment planning technique called Conformal Arc Informed VMAT (CAVMAT), which aims to reduce the dose to healthy tissue while generating highly conformal treatment plans. CAVMAT is a hybrid technique which combines the conformal MLC trajectories of dynamic conformal arcs with the MLC modulation and versatility of inverse optimization. CAVMAT has 3 main steps. First, targets are assigned to subgroups to maximize MLC blocking between targets. Second, arc weights are optimized to achieve the desired target dose, while minimizing MU variation between arcs. Third, the optimized conformal arc plan serves as the starting point for limited inverse optimization to improve dose conformity to each target. Twenty multifocal VMAT cases were replanned with CAVMAT with 20Gy applied to each target. The total volume receiving 2.5 Gy [cm 3 ], 6 Gy [cm 3 ], 12 Gy [cm 3 ], and 16 Gy [cm 3 ], conformity index, treatment delivery time, and the total MU were used to compare the VMAT and CAVMAT plans. In addition, CAVMAT was compared to a broad range of planning strategies from various institutions (108 linear accelerator based plans, 14 plans using other modalities) for a 5-target case utilized in a recent plan challenge. For the linear accelerator-based plans, a plan complexity metric based on aperture opening area and perimeter, total monitor units (MU), and MU for a given aperture opening was utilized in the plan challenge scoring algorithm to compare the submitted plans to CAVMAT. After re-planning the 20 VMAT cases, CAVMAT reduced the average V 2.5Gy [cm 3 ] by 25.25 ± 19.23%, V 6Gy [cm 3 ] by 13.68 ± 18.97%, V 12Gy [cm 3 ] by 11.40 ± 19.44%, and V 16Gy [cm 3 ] by 6.38 ± 19.11%. CAVMAT improved conformity by 3.81 ± 7.57%, while maintaining comparable target dose. MU for the CAVMAT plans increased by 24.35 ± 24.66%, leading to an increased treatment time of 2 minutes. For the plan challenge case, CAVMAT was 1 of 12 linac based plans that met all plan challenge scoring criteria. Compared to the average submitted VMAT plan, CAVMAT increased the V 10% Gy[%] of healthy tissue (Brain-PTV) by roughly 3.42%, but in doing so was able to reduce the V 25% Gy[%] by roughly 3.73%, while also reducing V 50% Gy[%] , V 75% Gy[%], and V 100% Gy[%] . The CAVMAT technique successfully eliminated insufficient MLC blocking between targets prior to the inverse optimization, leading to less complex treatment plans and improved tissue sparing. Tissue sparing, improved conformity, and decreased plan complexity at the cost of slight increase in treatment delivery time indicates CAVMAT to be a promising method to treat brain metastases., (Copyright © 2020 American Association of Medical Dosimetrists. Published by Elsevier Inc. All rights reserved.)

Purpose: To quantify the error detection power of a new treatment delivery error detection method. The method validates monitor unit (MU) resolved beam apertures using real-time EPID images., Methods: The on-board EPID imager was used to measure cine-EPID (~10 Hz) images for 27 beams from 15 VMAT/SBRT clinical treatment plans and five nonclinical plans. For each frame acquisition, planned apertures were interpolated from the treatment plan multileaf collimator (MLC) positions expected during the frame acquisition interval. Inaccurate deliveries were identified by monitoring in-aperture missed fluence and out-of-aperture excess fluence beyond a specified buffer. Delivery errors were simulated by perturbing the planned MLC positions before comparison with nonperturbed measured apertures. Systematic 1-5 mm MLC leaf shifts were used to train a logistic regression model to determine the error detection threshold. Model accuracy was monitored using tenfold cross-validation. The model's error detection ability was tested with other error modes: plan control point (CP) weight perturbations, collimator rotations, random MLC leaf position errors, EPID imager shift, and stuck MLC leaf. The error detection accuracy was evaluated using the Matthews correlation coefficient (MCC) and the false positive rate (FPR). Per-beam error thresholds of >1, >5, and >10% errant frames were tested to label per-beam errors. The model also was tested for its ability to distinguish five cases with highly similar plans and compared with gamma analysis., Results: Delivery errors were detected by monitoring intended per-frame images with a 2 mm MLC buffer. Frame-by-frame aperture errors were identified with an optimal threshold of 0.3% of the expected aperture area. The per-frame FPR was 0.02%. The MCC was 1.00 (perfect classification) for detection based on 1% of frames for random CP weight shift, 3 mm random MLC shifts, 90° and 180° collimator rotations, and an MLC leaf stuck after 10% of the beam delivery. The MCC for 2°, 4°, and 8° collimator rotation were 0.53, 0.76, and 0.96, respectively, for the 1% of beam delivery threshold. The 3 mm EPID shift had poor detection, with a minimum MCC of 0.14. The highly similar plans were reliably detected by the aperture check but were not detectable with gamma analysis., Conclusion: The high error detection sensitivity and low FPR makes the aperture check error detection method well suited to pretreatment and during-treatment beam delivery quality assurance (QA). The aperture check detects subtle beam delivery errors, including those resulting from MLC leaf positioning deviations, CP MU shifts, and stuck MLC leaves. Furthermore, the method can distinguish between highly similar treatment plans. Since the aperture check method monitors for the aperture shapes over a given MU interval, it is also sensitive to errors in MU per CP, without requiring dosimetric calibration of the EPID. The aperture check is one part of a Swiss cheese error detection scheme, which provides redundant error testing of multiple error modes, including nonaperture related errors. The rapid error detection, at 1% of a beam's delivery, make the aperture check a potential candidate for QA of on-line adaptive radiotherapy, or other situations in which pretreatment delivery QA is impractical., (© 2020 American Association of Physicists in Medicine.)

Introduction: Within an International Atomic Energy Agency (IAEA) co-ordinated research project (CRP), a remote end-to-end dosimetric quality audit for intensity modulated radiation therapy (IMRT)/ volumetric arc therapy (VMAT) was developed to verify the radiotherapy chain including imaging, treatment planning and dose delivery. The methodology as well as the results obtained in a multicentre pilot study and national trial runs conducted in close cooperation with dosimetry audit networks (DANs) of IAEA Member States are presented. Material and methods: A solid polystyrene phantom containing a dosimetry insert with an irregular solid water planning target volume (PTV) and organ at risk (OAR) was designed for this audit. The insert can be preloaded with radiochromic film and four thermoluminescent dosimeters (TLDs). For the audit, radiotherapy centres were asked to scan the phantom, contour the structures, create an IMRT/VMAT treatment plan and irradiate the phantom. The dose prescription was to deliver 4 Gy to the PTV in two fractions and to limit the OAR dose to a maximum of 2.8 Gy. The TLD measured doses and film measured dose distributions were compared with the TPS calculations. Results: Sixteen hospitals from 13 countries and 64 hospitals from 6 countries participated in the multicenter pilot study and in the national runs, respectively. The TLD results for the PTV were all within ±5% acceptance limit for the multicentre pilot study, whereas for national runs, 17 participants failed to meet this criterion. All measured doses in the OAR were below the treatment planning constraint. The film analysis identified seven plans in national runs below the 90% passing rate gamma criteria. Conclusion: The results proved that the methodology of the IMRT/VMAT dosimetric end-to-end audit was feasible for its intended purpose, i.e., the phantom design and materials were suitable; the phantom was easy to use and it was robust enough for shipment. Most importantly the audit methodology was capable of identifying suboptimal IMRT/VMAT delivery.

Background and Purpose: An audit methodology for verifying the implementation of output factors (OFs) of small fields in treatment planning systems (TPSs) used in radiotherapy was developed and tested through a multinational research group and performed on a national level in five different countries., Materials and Methods: Centres participating in this study were asked to provide OFs calculated by their TPSs for 10 × 10 cm 2 , 6 × 6 cm 2 , 4 × 4 cm 2 , 3 × 3 cm 2 and 2 × 2 cm 2 field sizes using an SSD of 100 cm. The ratio of these calculated OFs to reference OFs was analysed. The action limit was ±3% for the 2 × 2 cm 2 field and ±2% for all other fields., Results: OFs for more than 200 different beams were collected in total. On average, the OFs for small fields calculated by TPSs were generally larger than measured reference data. These deviations increased with decreasing field size. On a national level, 30% and 31% of the calculated OFs of the 2 × 2 cm 2 field exceeded the action limit of 3% for nominal beam energies of 6 MV and for nominal beam energies higher than 6 MV, respectively., Conclusion: Modern TPS beam models generally overestimate the OFs for small fields. The verification of calculated small field OFs is a vital step and should be included when commissioning a TPS. The methodology outlined in this study can be used to identify potential discrepancies in clinical beam models., (© 2018 The Authors.)