Beam modeling and beam model commissioning for Monte Carlo dose calculation-based radiation therapy treatment planning: Report of AAPM Task Group 157

Multileaf collimator characterization and modeling for a 1.5 T MR-linac using static synchronous and asynchronous sweeping gaps

Objective.The Elekta unity MR-linac delivers step-and-shoot intensity modulated radiotherapy plans using a multileaf collimator (MLC) based on the Agility MLC used on conventional Elekta linacs. Currently, details of the physical Unity MLC and the computational model within its treatment planning system (TPS)Monacoare lacking in published literature. Recently, a novel approach to characterize the physical properties of MLCs was introduced using dynamic synchronous and asynchronous sweeping gap (aSG) tests. Our objective was to develop a step-and-shoot version of the dynamic aSG test to characterize the Unity MLC and the computational MLC models in theMonacoandRayStationTPSs.Approach.Dynamic aSG were discretized into a step-and-shoot aSG by investigating the number of segments/sweep and the minimal number of monitor units (MU) per segment. The step-and-shoot aSG tests were compared to the dynamic aSG tests on a conventional linac at a source-to-detector distance of 143.5 cm, mimicking the Unity configuration. the step-and-shoot aSG tests were used to characterize the Unity MLC through measurements and dose calculations in both TPSs.Main results.The step-and-shoot aSGs tests with 100 segments and 5 MU/segment gave results very similar to the dynamic aSG experiments. The effective tongue-and-groove width of the Unity gradually increased up to 1.4 cm from the leaf tip end. The MLC models inRayStationandMonacoagreed with experimental data within 2.0% and 10%, respectively. The largest discrepancies inMonacowere found for aSG tests with >10 mm leaf interdigitation, which are non-typical for clinical plans.Significance.The step-and-shoot aSG tests accurately characterize the MLC in step-and-shoot delivery mode. The MLC model inRayStation2023B accurately describes the tongue-and-groove and leaf tip effects whereasMonacooverestimates the tongue-and-groove shadowing further away from the leaf tip end.

Development of a LINAC head model for the CyberKnife VSI-System using EGSnrc Monte Carlo system

INTRODUCTION

In order to understand the interaction processes of photons and electrons of the CyberKnife VSI-System, a modeling of the LINAC head must take place. Here, a Monte Carlo simulation can help. By comparing the measured data with the simulation data, the agreement can be checked.

MATERIALS AND METHODS

For the Monte Carlo simulations, the toolkit EGSnrc with the user codes BEAMnrc and DOSXZYnrc was used. The CyberKnife VSI-System has two collimation systems to define the field size of the beam. On the one hand, it has 12 circular collimators and, on the other, an IRIS-aperture. The average energy, final source width, dose profiles, and output factors in a voxel-based water phantom were determined and compared to the measured data.

RESULTS

The average kinetic energy of the electron beam for the CyberKnife VSI LINAC head is 6.9 MeV, with a final source width of 0.25 cm in x-direction and 0.23 cm in y-direction. All simulated dose profiles for both collimation systems were able to achieve a global gamma criterion of 1%/1 mm to the measured data. For the output factors, the deviation from simulated to measured data is < 1% from a field size of 12.5 mm for the circular collimators and from a field size of 10 mm for the IRIS-aperture.

CONCLUSION

The beam characteristics of the CyberKnife VSI LINAC head could be exactly simulated with Monte Carlo simulation. Thus, in the future, this model can be used as a basis for electronic patient-specific QA or to determine scattering processes of the LINAC head.

Commissioning and validation of a Monte Carlo algorithm for spine stereotactic radiosurgery

PURPOSE

A 6FFF Monte Carlo (MC) dose calculation algorithm was commissioned for spine stereotactic radiosurgery (SRS). Model generation, validation, and ensuing model tuning are presented.

METHODS

The model was generated using in-air and in-water commissioning measurements of field sizes between 10 and 400 mm2 . Commissioning measurements were compared to simulated water tank MC calculations to validate output factors, percent depth doses (PDDs), profile sizes and penumbras. Previously treated Spine SRS patients were re-optimized with the MC model to achieve clinically acceptable plans. Resulting plans were calculated on the StereoPHAN phantom and subsequently delivered to the microDiamond and SRSMapcheck to verify calculated dose accuracy. Model tuning was performed by adjusting the model's light field offset (LO) distance between physical and radiological positions of the MLCs, to improve field size and StereoPHAN calculation accuracy. Following tuning, plans were generated and delivered to an anthropomorphic 3D-printed spine phantom featuring realistic bone anatomy, to validate heterogeneity corrections. Finally, plans were validated using polymer gel (VIPAR based formulation) measurements.

RESULTS

Compared to open field measurements, MC calculated output factors and PDDs were within 2%, profile penumbra widths were within 1 mm, and field sizes were within 0.5 mm. Calculated point dose measurements in the StereoPHAN were within 0.26% ± 0.93% and -0.10% ± 1.37% for targets and spinal canals, respectively. Average SRSMapcheck per-plan pass rates using a 2%/2 mm/10% threshold relative gamma analysis was 99.1% ± 0.89%. Adjusting LOs improved open field and patient-specific dosimetric agreement. Anthropomorphic phantom measurements were within -1.29% ± 1.00% and 0.27% ± 1.36% of MC calculated for the vertebral body (target) and spinal canal, respectively. VIPAR gel measurements confirmed good dosimetric agreement near the target-spine junction.

CONCLUSION

Validation of a MC algorithm for simple fields and complex SRS spine deliveries in homogeneous and heterogeneous phantoms has been performed. The MC algorithm has been released for clinical use.

The NCS code of practice for the quality assurance of treatment planning systems (NCS-35)

A subcommittee of the Netherlands Commission on Radiation Dosimetry (NCS) was initiated in 2018 with the task to update and extend a previous publication (NCS-15) on the quality assurance of treatment planning systems (TPS) (Bruinviset al2005). The field of treatment planning has changed considerably since 2005. Whereas the focus of the previous report was more on the technical aspects of the TPS, the scope of this report is broader with a focus on a department wide implementation of the TPS. New sections about education, automated planning, information technology (IT) and updates are therefore added. Although the scope is photon therapy, large parts of this report will also apply to all other treatment modalities. This paper is a condensed version of these guidelines; the full version of the report in English is freely available from the NCS website (http://radiationdosimetry.org/ncs/publications). The paper starts with the scope of this report in relation to earlier reports on this subject. Next, general aspects of the commissioning process are addressed, like e.g. project management, education, and safety. It then focusses more on technical aspects such as beam commissioning and patient modeling, dose representation, dose calculation and (automated) plan optimisation. The final chapters deal with IT-related subjects and scripting, and the process of updating or upgrading the TPS.

Monitor unit verification for Varian TrueBeam VMAT plans using Monte Carlo calculations and phase space data

To use the open-source Monte Carlo (MC) software calculations for TPS monitor unit verification of VMAT plans, delivered with the Varian TrueBeam linear accelerator, and compare the results with a commercial software product, following the guidelines set in AAPM Task Group 219. The TrueBeam is modeled in EGSnrc using the Varian-provided phase-space files. Thirteen VMAT TrueBeam treatment plans representing various anatomical regions were evaluated, comprising 37 treatment arcs. VMAT plans simulations were performed on a computing cluster, using 107 -109 particle histories per arc. Point dose differences at five reference points per arc were compared between Eclipse, MC, and the commercial software, MUCheck. MC simulation with 5 × 107 histories per arc offered good agreement with Eclipse and a reasonable average calculation time of 9-18 min per full plan. The average absolute difference was 3.0%, with only 22% of all points exceeding the 5% action limit. In contrast, the MUCheck average absolute difference was 8.4%, with 60% of points exceeding the 5% dose difference. Lung plans were particularly problematic for MUCheck, with an average absolute difference of approximately 16%. Our EGSnrc-based MC framework can be used for the MU verification of VMAT plans calculated for the Varian TrueBeam; furthermore, our phase space approach can be adapted to other treatment devices by using appropriate phase space files. The use of 5 × 107 histories consistently satisfied the 5% action limit across all plan types for the majority of points, performing significantly better than a commercial MU verification system, MUCheck. As faster processors and cloud computing facilities become even more widely available, this approach can be readily implemented in clinical settings.

Validation of RayStation Monte Carlo dose calculation algorithm for multiple LINACs

PURPOSE

A photon Monte Carlo (MC) model was commissioned for flattened (FF) and flattening filter free (FFF) 6 MV beam energy. The accuracy of this model, as a single model to be used for three beam matched LINACs, was evaluated.

METHODS

Multiple models were created in RayStation v.10A for three linacs equipped with Elekta "Agility" collimator. A clinically commissioned collapsed cone (CC) algorithm (GoldCC), a MC model automatically created from the CC algorithm without further optimization (CCtoMC) and an optimized MC model (GoldMC) were compared with measurements. The validation of the model was performed by following the recommendations of IAEA TRS 430 and comprised of basic validation in a water tank, validation in a heterogeneous phantom and validation of complex IMRT/VMAT paradigms using gamma analysis of calculated and measured dose maps in a 2D-Array.

RESULTS

Dose calculation with the GoldMC model resulted in a confidence level of 3% for point measurements in water tank and heterogeneous phantom for measurements performed in all three linacs. The same confidence level resulted for GoldCC model. Dose maps presented an agreement for all models on par to each other with γ criteria 2%/2mm.

CONCLUSIONS

The GoldMC model showed a good agreement with measured data and is determined to be accurate for clinical use for all three linacs in this study.

Correction factors for commissioning and patient specific quality assurance of stereotactic fields in a Monte Carlo based treatment planning system : TPS correction factors

Validation of small field dosimetry is crucial for stereotactic radiosurgery (SRS) and stereotactic body radiotherapy (SBRT). Accurate and considered measurement of linear accelerator dose must be compared to precise and accurate calculation by the treatment planning system (TPS). Monte Carlo calculated distributions contain statistical noise, reducing the reliance that should be given to single voxel doses. The average dose to a small volume of interest (VOI) can minimise the influence of noise, but for small fields introduces significant volume averaging. Similar challenges present during measurement of composite dose from clinical plans when a small volume ionisation chamber is used. This study derived correction factors for VOI averaged TPS doses calculated for small fields, allowing correction to an isocentre dose following account for statistical noise. These factors were used to determine an optimal VOI to represent small volume ionisation chambers during patient specific quality assurance (PSQA). A retrospective comparison of 82 SRS and 28 SBRT PSQA measurements to TPS calculated doses from varying VOI was completed to evaluate the determined volumes. Small field commissioning correction factors of under 5% were obtained for field sizes of 8 mm and larger. Optimal spherical VOI with radius between 1.5 and 1.8 mm and 2.5 to 2.9 mm were determined for IBA CC01 and CC04 ionisation chambers respectively. Review of PSQA confirmed an optimal agreement between CC01 measured doses and a volume of 1.5 to 1.8 mm while CC04 measured doses showed no variation with VOI.

Effect of the Gaussian distribution parameters of the electron beam generated at the target on the simulated x-ray dose

The purpose of this work was to investigate by Monte Carlo method the adjustment of photon beams delivered by the medical LINear ACcelerator (LINAC) Elekta Synergy MLCi2. This study presents an optimization of the Gaussian distribution parameters of the accelerated electrons before the target simulated by two Monte Carlo codes and for three beams. The photon (x-ray) beam is produced by the interaction of accelerated electrons with the LINAC target. The electrons are accelerated by a potential difference created between the anode and the cathode of the gun and directed towards the target. In the Monte Carlo simulation, it is necessary to setup the spectrum parameters of the generated electrons to simulate the x-ray dose distribution. In this study, we modeled the LINAC geometry for photon beams 18MV and 6MV in cases Flattened (FF) and Flattening-Filter-Free (FFF). The Monte Carlo simulations are based on G4Linac_MT and GATE codes. The results of the optimized configurations determined after more than 20 tests for each beam energy show a very good agreement with the experimental measurements for different irradiation fields for the depth (PDD) and lateral (Profile) dose distribution. In all Monte Carlo calculations performed in this study, the statistical uncertainty is less than 2%. The results were also in very good agreement in terms ofγ-index analysis, for the 3%/3 mm and 2%/2 mm criteria.

Commissioning and validation of a novel commercial TPS for ocular proton therapy

BACKGROUND

Until today, the majority of ocular proton treatments worldwide were planned with the EYEPLAN treatment planning system (TPS). Recently, the commercial, computed tomography (CT)-based TPS for ocular proton therapy RayOcular was released, which follows the general concepts of model-based treatment planning approach in conjunction with a pencil-beam-type dose algorithm (PBA).

PURPOSE

To validate RayOcular with respect to two main features: accurate geometrical representation of the eye model and accuracy of its dose calculation algorithm in combination with an Ion Beam Applications (IBA) eye treatment delivery system.

METHODS

Different 3D-printed eye-ball-phantoms were fabricated to test the geometrical representation of the corresponding CT-based model, both in orthogonal 2D images for X-ray image overlay and in fundus view overlaid with a funduscopy. For the latter, the phantom was equipped with a lens matching refraction of the human eye. Funduscopy was acquired in a Zeiss Claus 500 camera. Tantalum clips and fiducials attached to the phantoms were localized in the TPS model, and residual deviations to the actual position in X-ray images for various orientations of the phantom were determined, after the nominal eye orientation was corrected in RayOcular to obtain a best overall fit. In the fundus view, deviations between known and displayed distances were measured. Dose calculation accuracy of the PBA on a 0.2 mm grid was investigated by comparing between measured lateral and depth-dose profiles in water for various combinations of range, modulation, and field-size. Ultimately, the modeling of dose distributions behind wedges was tested. A 1D gamma-test was applied, and the lateral and distal penumbra were further compared.

RESULTS

Average residuals between model clips and visible clips/fiducials in orthogonal X-ray images were within 0.3 mm, including different orientations of the phantom. The differences between measured distances on the registered funduscopy image in the RayOcular fundus view and the known ground-truth were within 1 mm up to 10.5 mm distance from the posterior pole. No clear benefit projection of either polar mode or camera mode could be identified, the latter mimicking camera properties. Measured dose distributions were reproduced with gamma-test pass-rates of >95% with 2%/0.3 mm for depth and lateral profiles in the middle of spread-out Bragg-peaks. Distal falloff and lateral penumbra were within 0.2 mm for fields without a wedge. For shallow depths, the agreement was worse, reaching pass-rates down to 80% with 5%/0.3 mm when comparing lateral profiles in air. This is caused by low-energy protons from a scatter source in the IBA system not modeled by RayOcular. Dose distributions modified by wedges were reproduced, matching the wedge-induced broadening of the lateral penumbra to within 0.4 mm for the investigated cases and showing the excess dose within the field due to wedge scatter.

CONCLUSION

RayOcular was validated for its use with an IBA single scattering delivery nozzle. Geometric modeling of the eye and representation of 2D projections fulfill clinical requirements. The PBA dose calculation reproduces measured distributions and allows explicit handling of wedges, overcoming approximations of simpler dose calculation algorithms used in other systems.

Statistical process control to monitor use of a web-based autoplanning tool

PURPOSE

To investigate the use of statistical process control (SPC) for quality assurance of an integrated web-based autoplanning tool, Radiation Planning Assistant (RPA).

METHODS

Automatically generated plans were downloaded and imported into two treatment planning systems (TPSs), RayStation and Eclipse, in which they were recalculated using fixed monitor units. The recalculated plans were then uploaded back to the RPA, and the mean dose differences for each contour between the original RPA and the TPSs plans were calculated. SPC was used to characterize the RPA plans in terms of two comparisons: RayStation TPS versus RPA and Eclipse TPS versus RPA for three anatomical sites, and variations in the machine parameters dosimetric leaf gap (DLG) and multileaf collimator transmission factor (MLC-TF) for two algorithms (Analytical Anisotropic Algorithm [AAA]) and Acuros in the Eclipse TPS. Overall, SPC was used to monitor the process of the RPA, while clinics would still perform their routine patient-specific QA.

RESULTS

For RayStation, the average mean percent dose differences across all contours were 0.65% ± 1.05%, -2.09% ± 0.56%, and 0.28% ± 0.98% and average control limit ranges were 1.89% ± 1.32%, 2.16% ± 1.31%, and 2.65% ± 1.89% for the head and neck, cervix, and chest wall, respectively. In contrast, Eclipse's average mean percent dose differences across all contours were -0.62% ± 0.34%, 0.32% ± 0.23%, and -0.91% ± 0.98%, while average control limit ranges were 1.09% ± 0.77%, 3.69% ± 2.67%, 2.73% ± 1.86%, respectively. Averaging all contours and removing outliers, a 0% dose difference corresponded with a DLG value of 0.202 ± 0.019 cm and MLC-TF value of 0.020 ± 0.001 for Acuros and a DLG value of 0.135 ± 0.031 cm and MLC-TF value of 0.015 ± 0.001 for AAA.

CONCLUSIONS

Differences in mean dose and control limits between RPA and two separately commissioned TPSs were determined. With varying control limits and means, SPC provides a flexible and useful process quality assurance tool for monitoring a complex automated system such as the RPA.

Determination and validation of the initial beam parameters of Elekta Agility collimator head by Monte Carlo simulations

The availability of geometrical, physical, and initial beam parameters for Monte Carlo (MC) simulations of the Elekta Agility collimator head has become very difficult due to the proprietary nature of this data. This study presents strategies to independently determine the geometrical and physical properties of the components and initial beam parameters of the Agility collimator head for full beam simulations and postulates a benchmarking process using the EGSnrc MC toolkit. Target material of W (90%) and Re (10%) of 0.09 cm thickness, flattening filter of 1.77 cm thick stainless steel placed on 0.5 cm Al disc, and primary and secondary collimators of Tungsten alloy have been found to best fit the Agility head. The initial beam energy of 6.0 MeV with a radial distribution given as full-width half maxima (FWHM) of 0.301 cm (crossline) × 0.201 cm (inline) for 6 MV beam with a mean angular spread of 1.34° has been found best fitting the model. Variations of 0.29% and 0.59% have been noted in the measured and calculated values of TPR_20,10 and D₁₀ respectively. More than 90% dose points for all simulations passed the 2D gamma criteria of 3% DD, 3 mm DTA. This MC model of the Agility head can be used for dose calculation and validation of advanced treatment techniques.

A multivariate approach to determine electron beam parameters for a Monte Carlo 6 MV Linac model: Statistical and machine learning methods

PURPOSE

This study aimed to determine the optimal initial electron beam parameters of a Linac for radiotherapy with a multivariate approach using statistical and machine-learning tools.

METHODS

For MC beam commissioning, a 6 MV Varian Clinac was simulated using the Geant4 toolkit. The authors investigated the relations between simulated dose distribution and initial electron beam parameters, namely, mean energy (E), energy spread (ES), and radial beam size (RS). The goodness of simulation was evaluated by the slope of differences between the simulated and the golden beam data. The best-fit combination of the electron beam parameters that minimized the slope of dose difference was searched through multivariate methods using conventional statistical methods and machine-learning tools of the scikit-learn library.

RESULTS

Simulation results with 87 combinations of the electron beam parameters were analyzed. Regardless of being univariate or multivariate, traditional statistical models did not recommend a single parameter set simultaneously minimizing slope of dose differences for percent depth dose (PDD) and lateral dose profile (LDP). Two machine learning classification modules, RandomForestClassifier and BaggingClassifier, agreed in recommending (E = 6.3 MeV, ES = ±5.0%, RS = 1.0 mm) for predicting simultaneous acceptance of PDD and LDP.

CONCLUSIONS

The machine learning with random-forest and bagging classifier modules recommended a consistent result. It was possible to draw an optimal electron beam parameter set using multivariate methods for MC simulation of a radiotherapy 6 MV Linac.

Comparative study of the collapsed cone convolution and Monte Carlo algorithms for radiation therapy planning of canine sinonasal tumors reveals significant dosimetric differences

Computer-based radiation therapy requires high targeting and dosimetric precision. Analytical dosimetric algorithms typically are fast and clinically viable but can have increasing errors near air-bone interfaces. These are commonly found within dogs undergoing radiation planning for sinonasal cancer. This retrospective methods comparison study is designed to compare the dosimetry of both tumor volumes and organs at risk and quantify the differences between collapsed cone convolution (CCC) and Monte Carlo (MC) algorithms. Canine sinonasal tumor plans were optimized with CCC and then recalculated by MC with identical control points and monitor units. Planning target volume (PTV)_air , PTV_{soft tissue} , and PTV_bone were created to analyze the dose discrepancy within the PTV. Thirty imaging sets of dogs were included. Monte Carlo served as the gold standard calculation for the dosimetric comparison. Collapsed cone convolution overestimated the mean dose (D_mean ) to PTV and PTV_{soft tissue} by 0.9% and 0.5%, respectively (both P < 0.001). Collapsed cone convolution overestimated D_mean to PTV_bone by 3% (P < 0.001). Collapsed cone convolution underestimated the near-maximum dose (D₂ ) to PTV_air by 1.1% (P < 0.001), and underestimated conformity index and homogeneity index in PTV (both P < 0.001). Mean doses of contralateral and ipsilateral eyes were overestimated by CCC by 1.6% and 1.7%, respectively (both P < 0.001). Near-maximum doses of skin and brain were overestimated by CCC by 2.2% and 0.7%, respectively (both P < 0.001). As clinical accessibility of Monte Carlo becomes more widespread, dose constraints may need to be re-evaluated with appropriate plan evaluation and follow-up.

Validation of spline modeling for calculation of electron insert factors for varian linear accelerators

There are several methods available in the literature for predicting the insert factor for clinical electron beams. The purpose of this work was to build on a previously published technique that uses a bivariate spline model generated from elliptically parameterized empirical measurements. The technique has been previously validated for Elekta linear accelerators for limited clinical electron setups. The same model is applied to Varian machines to test its efficacy for use with these linear accelerators. Insert factors for specifically designed elliptical cutouts were measured to create spline models for 6, 9, 12, 16, and 20 MeV electron energies for four different cone sizes at source-to-surface distances (SSD) of 100, 105, and 110 cm. Insert factor validation measurements of patient cutouts and clinical standard cutouts were acquired to compare to model predictions. Agreement between predicted insert factors and validation measurements averaged 0.8% over all energies, cones, and clinical SSDs, with an uncertainty of 0.6% (1SD), and maximum deviation of 2.1%. The model demonstrated accurate predictions of insert factors using the minimum required amount of input data for small cones, with more input measurements required for larger cones. The results of this study provide expanded validation of this technique to predict insert factors for all energies, cones, and SSDs that would be used in most clinical situations. This level of accuracy and the ease of creating the model necessary for the insert factor predictions demonstrate its acceptability to use clinically for Varian machines.

Technical note: Extraction of proton pencil beam energy spectrum from measured integral depth dose in a cyclotron proton beam system

PURPOSE

Proton pencil beam energy spectrum is an essential parameter for calculations of dose and linear energy transfer. We extract the energy spectrum from measured integral depth dose (IDD).

METHODS

A measured IDD (measIDD) in water is decomposed into many IDDs of mono-energetic pencil beams (monoIDDs) in water. A simultaneous iterative technique is used to do the decomposition that extracts the energy spectrum of protons from the measIDD. The monoIDDs are generated by our analytic random walk model-based proton dose calculation algorithm. The linear independence of the monoIDDs is considered and high spatial resolution monoIDDs are used to improve their linear independence. To validate the extraction, first we use synthesized IDDs (synIDD) with Gaussian energy spectrum and compare the extracted energy spectrum with the Gaussian; second, for the energy spectrum extracted from measIDDs, the accuracy of the extraction is validated by comparing the calculated IDD from the energy spectrum with the measIDD. The measIDDs are derived from commissioning of a cyclotron proton pencil beam system with a Bragg peak ionization chamber. The nominal energy of the pencil beams is from 70 to 245 MeV. The monoIDDs are generated for energies from 0.05 to 275 MeV in steps of 0.05 MeV with a spatial resolution of 1 mm.

RESULTS

The difference of the extracted and original Gaussian energy spectrum peaked at 75 and 80 MeV was <1%. As the energy decreased, the difference increased but was reduced by using 0.1-mm monoIDDs. The difference was not sensitive to the energy interval of monoIDDs when the interval increased from 0.05 to 1 MeV. For the energy spectrum extraction from measIDDs, there was a main peak near the nominal energy but the spectrum was not in Gaussian distribution. In three example cases (70, 160, and 245 MeV), the relative differences of the measIDDs and calculated IDDs were within 3.4%, 2.9%, and 4.7% of the Bragg peak value, respectively. Fitting the spectrum by Gaussian distribution, we had σ = 0.87, 1.51, and 0.86 MeV, respectively, for these three examples, and the relative differences of the resultant calculated IDDs from the measIDDs were within 4.7%, 7.4%, and 4.5%, respectively.

CONCLUSIONS

Our algorithm accurately extracted the energy spectrum from the synIDDs and measIDDs. High-resolution monoIDDs are necessary to extract low-energy spectrum. Energy spectrum extraction from measIDD reveals important information for beam modeling.

Report of AAPM Task Group 219 on independent calculation-based dose/MU verification for IMRT

Independent verification of the dose per monitor unit (MU) to deliver the prescribed dose to a patient has been a mainstay of radiation oncology quality assurance (QA). We discuss the role of secondary dose/MU calculation programs as part of a comprehensive QA program. This report provides guidelines on calculation-based dose/MU verification for intensity modulated radiation therapy (IMRT) or volumetric modulated arc therapy (VMAT) provided by various modalities. We provide a review of various algorithms for "independent/second check" of monitor unit calculations for IMRT/VMAT. The report makes recommendations on the clinical implementation of secondary dose/MU calculation programs; on commissioning and acceptance of various commercially available secondary dose/MU calculation programs; on benchmark QA and periodic QA; and on clinically reasonable action levels for agreement of secondary dose/MU calculation programs.

Commissioning of and preliminary experience with a new fully integrated computed tomography linac

Purpose

A new medical linear accelerator (linac) platform integrated with helical computed tomography (CT), the uRT‐linac 506c, was introduced into clinical application in 2019 by United Imaging Healthcare (UIH) Co., Ltd. (Shanghai, China). It combines a Carm linac with a diagnostic‐quality 16‐slice CT imager, providing seamless workflow from simulation to treatment. The aim of this report is to assess the technical characteristics, commissioning results and preliminary experiences stemming from clinical usage.

Methods

The mechanical and imaging test procedures, commissioning data collection and TPS validation were summarized. CTIGRT accuracy was investigated with different loads and couch extensions. A series of end‐to‐end cases for different treatment sites and delivery techniques were tested preclinically to estimate the overall accuracy for the entire treatment scheme. The results of patient‐specific QA and machine stability during a one‐year operation are also reported.

Results

Gantry/couch/collimator isocentricity was measured as 0.63 mm in radius. The TPS models were in agreement with the beam commissioning data within a deviation of 2%. An overall submillimeter accuracy was demonstrated for the CT‐IGRT process under all conditions. The absolute point dose difference for all the preclinical end‐to‐end tests was within 3%, and the gamma passing rate of the 2D dose distribution measured by EBT3 film was better than 90% (3% DD, 3 mm DTA and 10% threshold). Pretreatment QA of clinical cases resulted with better than 3% point dose difference and more than 99% gamma passing rate (3% DD/2 mm DTA/10% threshold) tested with Delta4. The output of the linac was mostly within 1% of variation in a one‐year operation.

Conclusion

The commissioning results and clinical QA results show that the uRT‐linac 506c platform exhibits good and stable performance in mechanical and dosimetric accuracy. The integrated CT system provides an efficient workflow for image guidance with submillimeter localization precision, and will be a good starting point to proceed advanced adaptive radiotherapy.

Monte Carlo as quality control tool of stereotactic body radiation therapy treatment plans

PURPOSE/OBJECTIVE

The objective of this study was to verify the accuracy of treatment plans of stereotactic body radiation therapy (SBRT) and to verify the feasibility of the use of Monte Carlo (MC) as quality control (QC) on a daily basis.

MATERIAL/METHODS

Using EGSnrc, a MC model of Agility™ linear accelerator was created. Various measurements (Percentage depth dose (PDD), Profiles and Output factors) were done for different fields sizes from 1x1 up to 40x40 (cm²). An iterative model optimization was performed to achieve adequate parameters of MC simulation. 40 SBRT patient's dosimetry plans were calculated by Monaco™ 3.1.1. CT images, RT-STRUCT and RT-PLAN files from Monaco™ being used as input for Moderato MC code. Finally, dose volume histogram (DVH) and paired t-tests for each contour were used for dosimetry comparison of the Monaco™ and MC.

RESULTS

Validation of MC model was successful, as <2% difference comparing to measurements for all field's sizes. The main energy of electron source incident on the target was 5.8 MeV, and the full width at half maximum (FWHM) of Gaussian electron source were 0.09 and 0.2 (cm) in X and Y directions, respectively. For 40 treatment plan comparisons, the minimum absolute difference of mean dose of planning treatment planning (PTV) was 0.1% while the maximum was 6.3%. The minimum absolute difference of Max dose of PTV was 0.2% while the maximum was 8.1%.

CONCLUSION

SBRT treatment plans of Monaco agreed with MC results. It possible to use MC for treatment plans verifications as independent QC tool.

Recommended procedures and responsibilities for radiosurgery (SRS) and extracranial stereotactic body radiotherapy (SBRT): report of the SEOR in collaboration with the SEFM

Today, patient management generally requires a multidisciplinary approach. However, due to the growing knowledge base and increasing complexity of Medicine, clinical practice has become even more specialised. Radiation oncology is not immune to this trend towards subspecialisation, which is particularly evident in ablative radiotherapy techniques that require high dose fractions, such as stereotactic radiosurgery (SRS), and stereotactic body radiotherapy (SBRT). The aim of the present report is to establish the position of the Spanish Society of Radiation Oncology (SEOR), in collaboration with the Spanish Society of Medical Physics (SEFM), with regard to the roles and responsibilities of healthcare professionals involved in performing SRS and SBRT. The need for this white paper is motivated due to the recent changes in Spanish Legislation (Royal Decree [RD] 601/2019, October 18, 2019) governing the use and optimization of radiotherapy and radiological protection for medical exposure to ionizing radiation (article 11, points 4 and 5) [1 ], which states: "In radiotherapy treatment units, the specialist in Radiation Oncology will be responsible for determining the correct treatment indication, selecting target volumes, determining the clinical radiation parameters for each volume, directing and supervising treatment, preparing the final clinical report, reporting treatment outcomes, and monitoring the patient's clinical course." Consequently, the SEOR and SEFM have jointly prepared the present document to establish the roles and responsibilities for the specialists-radiation oncologists (RO), medical physicists (MP), and related staff -involved in treatments with ionizing radiation. We believe that it is important to clearly establish the responsibilities of each professional group and to clearly establish the professional competencies at each stage of the radiotherapy process.