Measurement-based verification is impossible for the patient-specific quality assurance (QA) of online adaptive magnetic resonance imaging-guided radiotherapy (oMRgRT) because the patient remains on the couch throughout the session. We assessed a deep learning (DL) system for oMRgRT to predict the gamma passing rate (GPR). This study collected 125 verification plans [reference plan (RP), 100; adapted plan (AP), 25] from patients with prostate cancer treated using Elekta Unity. Based on our previous study, we employed a convolutional neural network that predicted the GPRs of nine pairs of gamma criteria from 1%/1 mm to 3%/3 mm. First, we trained and tested the DL model using RPs (n = 75 and n = 25 for training and testing, respectively) for its optimization. Second, we tested the GPR prediction accuracy using APs to determine whether the DL model could be applied to APs. The mean absolute error (MAE) and correlation coefficient (r) of the RPs were 1.22 ± 0.27% and 0.29 ± 0.10 in 3%/2 mm, 1.35 ± 0.16% and 0.37 ± 0.15 in 2%/2 mm, and 3.62 ± 0.55% and 0.32 ± 0.14 in 1%/1 mm, respectively. The MAE and r of the APs were 1.13 ± 0.33% and 0.35 ± 0.22 in 3%/2 mm, 1.68 ± 0.47% and 0.30 ± 0.11 in 2%/2 mm, and 5.08 ± 0.29% and 0.15 ± 0.10 in 1%/1 mm, respectively. The time cost was within 3 s for the prediction. The results suggest the DL-based model has the potential for rapid GPR prediction in Elekta Unity.

OBJECTIVE: To evaluate patient-specific quality assurance (PSQA) of 3 targets in a single delivery using a novel film-based phantom.
METHODS: The phantom was designed to rotate freely as a sphere and could measure 3 targets with film in a single delivery. After identifying the coordinates of 3 targets in the skull, the rotation angles about the equator and meridian were computed for optimal phantom setup, ensuring the film plane intersected the 3 targets. The plans were delivered on the CyberKnife system using fiducial tracking. The irradiated films were scanned and processed. All films were analysed using 3 gamma criteria.
RESULTS: Fifteen CyberKnife test plans with 3 different modalities were delivered on the phantom. Both automatic and marker-based registration methods were applied when registering the irradiated film and dose plane. Gamma analysis was performed using a 3%/1 mm, 2%/1 mm, and 1%/1 mm criteria with a 10% threshold. For the automatic registration method, the passing rates were 98.2% ± 1.9%, 94.2% ± 3.7%, and 80.9% ± 6.3%, respectively. For the marker-based registration approach, the passing rates were 96.4% ± 2.7%, 91.7% ± 4.3%, and 78.4% ± 6.2%, respectively.
CONCLUSIONS: A novel spherical phantom was evaluated for the CyberKnife system and achieved acceptable PSQA passing rates using TG218 recommendations. The phantom can measure true-composite dose and offers high-resolution results for PSQA, making it a valuable device for robotic radiosurgery.
CONCLUSIONS: This is the first study on PSQA of 3 targets concurrently on the CyberKnife system.

Objective:The development of a stringent derivative-based gamma (DBG) index for patient-specific QA in stereotactic radiotherapy treatment planning (SRTP) to account for the spatial change in dose.Methods:Twenty-five patients of liver SBRT were selected retrospectively for this study. Deliberately, two different kinds of treatment planning approaches were used for each patient. Firstly, the treatment plans were generated using a conventional treatment planning (CTP) approach in which the target was covered with a homogeneous dose along with the nominal dose fall-off around the treatment field. Subsequently, the other treatment plans were generated using an SRTP approach with the intent of heterogeneous dose within the target region along with a steeper dose gradient outside the treatment field as much as possible. For both kinds of treatment plans, two dimensional (2D) conventional gamma (CG) and DBG analysis were performed using the 2D ion chamber array and radiochromic film.Results:Difference in the DBG index was statistically significant whereas, for CG analysis, the difference in CG index was insignificant for both types of treatment plans (CTP and SRTP). A significant positive correlation was observed between the difference in the DBG index and the difference in HI for high gamma criteria.Conclusion:The DBG evaluation is found to be more rigorous, and sensitive to the only SRTP. The proposed method could be opted-in the routine clinical practice in addition to CG.Advances in knowledge:DBG is more sensitive to detect the spatial change of dose, especially in high dose gradient regions.

OBJECTIVE: The study aims at a novel dosimetry methodology to reconstruct a 3D dose distribution as imparted to a virtual cylindrical phantom using an electronic portal imaging device (EPID).
METHODS: A deep learning-based signal processing strategy, referred to as 3DosiNet, is utilized to learn a mapping from an EPID image to planar dose distributions at given depths. The network was trained with the volumetric dose exported from the clinical treatment planning system (TPS). Given the latent inconsistency between measurements and corresponding TPS calculations, unsupervised learning is formulated in 3DosiNet to capture abstractive image features that are less sensitive to the potential variations.
RESULTS: Validation experiments were performed using five regular fields and three clinical intensity-modulated radiation therapy (IMRT) cases. The measured dose profiles and percentage depth dose (PDD) curves were compared with those measured using standard tools in terms of the 1D gamma index. The mean gamma pass rates (2%/2 mm) over the regular fields are 100% and 97.3% for the dose profile and PDD measurements, respectively. The measured volumetric dose was compared to the corresponding TPS calculation in terms of the 3D gamma index. The mean 2%/2 mm gamma pass rates are 97.9% for square fields and 94.9% for the IMRT fields.
CONCLUSIONS: The system promises to be a practical 3D dosimetric tool for pre-treatment patient-specific quality assurance and further developed for in-treatment patient dose monitoring.

Patient quality assurance (QA) is a required part of the treatment care path, and plan failure can lead to increased personnel hours or delay of treatment. The recommendation by the American Association of Physicists in Medicine is that gamma analysis be used to evaluate measured volumetric modulated arc therapy plans. Vendors have developed many different measurement geometries for patient QA devices which could yield varying pass rates when used with the recommended tolerances, normalization, and criterion. For this study, clinically treated stereotactic body radiation therapy plans were used to evaluate differences in gamma dose tolerances and sampled dose distribution complexity for centralized or peripheral measurement geometries on a cylindrical phantom. Random errors were then introduced into a subset of these plans, and the differences in pass rates between the geometries were correlated with differences in the observed mathematical differences. Finally, a single clinically relevant target coverage deviation was introduced to another subset of plans to evaluate whether a particular geometry is measurably better at identifying clinically relevant errors. It was found that centralized geometries resulted in more lenient dose tolerances and less complex sampled dose distributions compared to peripheral geometries. Pass rates were uniformly lower in the peripheral measurement geometry, and the difference in pass rates between the geometries correlated strongly with the difference in dose tolerance and weakly with the difference in the chosen complexity metrics. However, neither of the geometries were sufficiently sensitive enough to detect clinically relevant changes to target coverage when using recommended tolerances and criteria, and no statistically significant difference was found between their pass rates. Given these findings, the authors concluded that stereotactic body radiation therapy plans could fail patient QA when measured in the peripheral geometry but pass in the centralized geometry, with possibly neither having correlation to true clinical deviation.

The dosimetric effect of artefacts caused by metal hip prostheses in computed tomography imaging is most commonly encountered in the planning of prostate cancer treatment. In this study, a phantom, containing a metal with high atomic number, was prepared for intensity-modulated radiotherapy (IMRT) treatment plans to be used in quality assurance (QA) procedures. Two sets of image files, one without metal artefact correction (ORG) and another with MAR correction (MAR+), were sent to the treatment planning system. In this study, 12 IMRT treatment plans with different fields and segment numbers were calculated. The normal tissue complication probability (NTCP) values of imaginary organs at risk (OARs), such as the rectum and bladder, were investigated, as was the difference in dose maps for ORG and MAR+ derived by calculating gamma passing rates (GPRs). The MatriXX was used for the gamma evaluation of patient-specific IMRT QA measurements. The gamma evaluation was repeated, based on the measurements using an EBT3 gafchromic film, for the plan showing the lowest GPR. The mean relative difference in NTCP values between the two sets of image files was found to be 2.5, 2.1 and 1.4 for the rectum; and 5.33, 6.80 and 9.82 for the bladder, for the investigated 5-, 7- and 9-field beam arrangements, respectively. The relative differences and the standard deviations in GPRs for the standard and metal-containing phantoms were calculated for the MAR+ and ORG sets. The maximum difference found was 7.69% ± 0.88 for the 9-field beam arrangement calculated without metal artefact correction. In the IMRT QA procedures for prostate patients with hip prostheses, the application of a metal-containing phantom that is both easy and inexpensive to prepare, is considered to be a useful method for examining any dose changes involved in introducing a hip prosthesis. Therefore, it is recommended for use in clinics that do not have MAR correction algorithms.

Purpose To evaluate the intensity modulated radiotherapy (IMRT) quality assurance (QA) results of the multichannel film dosimetry analysis with single scan method by using Gafchromic™ EBT3 (Ashland Inc., Covington, KY, USA) film under 0.35 T magnetic field. Methods Between September 2018 and June 2019, 70 patients were treated with ViewRay MRIdian® (ViewRay Inc., Mountain View, CA) linear accelerator (Linac). Film dosimetry QA plans were generated for all IMRT treatments. Multichannel film dosimetry for red, green and blue (RGB) channels were compared with treatment planning system (TPS) dose maps by gamma evaluation analysis. Results The mean gamma passing rates of RGB channels are 97.3% ± 2.26%, 96.0% ± 3.27% and 96.2% ± 3.14% for gamma evaluation with 2% DD/2 mm distance to agreement (DTA), respectively. Moreover, the mean gamma passing rates of RGB channels are 99.7% ± 0.41%, 99.6% ± 0.59% and 99.5% ± 0.67% for gamma evaluation with 3% DD/3 mm DTA, respectively. Conclusion The patient specific QA using Gafchromic™ EBT3 film with multichannel film dosimetry seems to be a suitable tool to implement for MR-guided IMRT treatments under 0.35 T magnetic field. Multichannel film dosimetry with Gafchromic™ EBT3 is a consistent QA tool for gamma evaluation of the treatment plans even with 2% DD/2 mm DTA under 0.35 T magnetic field presence.

OBJECTIVE: The SRS MapCHECK® , a recently developed patient-specific quality assurance (PSQA) tool for end-to-end testing of stereotactic radiosurgery (SRS) and stereotactic body radiation therapy (SBRT), was evaluated in a multi-institution study and compared with radiochromic film.
METHODS: The SRS MapCHECK was used to collect data on 84 SBRT or SRS PSQA plans/fields at nine institutions on treatment delivery devices (TDD) manufactured by Varian and Elekta. PSQA plans from five different treatment planning software (TPS) were selected and executed on TDDs operating at beam energies of 6 and 10 MV with and without a flattening filter. The patient plans were all VMAT except for ten conformal arc therapy fields. The plans were selected to encompass a range of size and tumor sites including brain, lung, spine, abdomen, ear, pancreas, and liver. Corresponding radiochromic film data was acquired in 50 plans/fields. Results were evaluated using gamma analysis with absolute dose criterion of 3% global dose-difference (DD) and 1 mm distance-to-agreement (DTA).
RESULTS: The mean 3% DD/1 mm DTA Gamma pass rate of SRS MapCHECK in comparison to film was 95.9%, whereas comparison of SRS MapCHECK to the treatment planning software was 94.7%. 80% of SRS MapCHECK comparisons against film exceed 95% pass rate, and about 30% of SRS MapCHECK comparisons against film exceed 99% pass rate. To maintain good agreement between SRS MapCHECK and film or TPS, authors recommend avoiding plans with a modified modulation complexity score (MMCS) <0.1 arbitrary units (a.u.). In the examples presented, this coincides with avoiding plans with a mu/dose limit of >3 µ/cGy.
CONCLUSIONS: Stereotactic radiosurgery MapCHECK has been validated for PSQA for a variety of clinical SRS/SBRT plans in a wide range of treatment delivery conditions. The SRS MapCHECK comparison with film demonstrates near-equivalence for analysis of patient-specific QA deliveries comprised of small field measurements.

For radiation therapy, it is crucial to ensure that the delivered dose matches the planned dose. Errors in the dose calculations done in the treatment planning system (TPS), treatment delivery errors, other software bugs or data corruption during transfer might lead to significant differences between predicted and delivered doses. As such, patient specific quality assurance (QA) of dose distributions, through experimental validation of individual fields, is necessary. These measurement based approaches, however, are performed with 2D detectors, with limited resolution and in a water phantom. Moreover, they are work intensive and often impose a bottleneck to treatment efficiency. In this work, we investigated the potential to replace measurement-based approach with a simulation-based patient specific QA using a Monte Carlo (MC) code as independent dose calculation engine in combination with treatment log files. Our developed QA platform is composed of a web interface, servers and computation scripts, and is capable to autonomously launch simulations, identify and report dosimetric inconsistencies. To validate the beam model of independent MC engine, in-water simulations of mono-energetic layers and 30 SOBP-type dose distributions were performed. Average Gamma passing ratio 99 ± 0.5% for criteria 2%/2 mm was observed. To demonstrate feasibility of the proposed approach, 10 clinical cases such as head and neck, intracranial indications and craniospinal axis, were retrospectively evaluated via the QA platform. The results obtained via QA platform were compared to QA results obtained by measurement-based approach. This comparison demonstrated consistency between the methods, while the proposed approach significantly reduced in-room time required for QA procedures.

OBJECTIVE: Due to the increasing complexity of IMRT/IMPT treatments, quality assurance (QA) is essential to verify the quality of the dose distribution actually delivered. In this context, Monte Carlo (MC) simulations are more and more often used to verify the accuracy of the treatment planning system (TPS). The most common method of dose comparison is the γ-test, which combines dose difference and distance-to-agreement (DTA) criteria. However, this method is known to be dependent on the noise level in dose distributions. We propose here a method to correct the bias of the γ passing rate (GPR) induced by MC noise.
METHODS: The GPR amplitude was studied as a function of the MC noise level. A model of this noise effect was mathematically derived. This model was then used to predict the time-consuming low-noise GPR by fitting multiple fast MC dose calculations. MC dose maps with a noise level between 2% and 20% were computed, and the GPR was predicted at a noise level of 0.3%. Due to the asymmetry of the γ-test, two different cases were considered: the MC dose was first set as reference dose, then as evaluated dose in the γ-test. Our method was applied on six proton therapy plans including analytical doses from the TPS or patient-specific QA measurements.
RESULTS: An average absolute error of 4.31% was observed on the GPR computed for MC doses with 2% statistical noise. Our method was able to improve the accuracy of the gamma passing rate by up to 13%. The method was found especially efficient to correct the noise bias when the DTA criterion is low.
CONCLUSIONS: We propose a method to enhance the γ-evaluation of a treatment plan when there is noise in one of the compared distributions. The method allows, in a tractable time, to detect the cases for which a correction is necessary and can improve the accuracy of the resulting passing rates.