Development and validation of a 1.5 T MR-Linac full accelerator head and cryostat model for Monte Carlo dose simulations

Validation of a Monte Carlo-based dose calculation engine including the 1.5 T magnetic field for independent dose-check in MRgRT

PURPOSE

Adaptive MRgRT by 1.5 T MR-linac requires independent verification of the plan-of-the-day by the primary TPS (MonacoTM) (M). Here we validated a Monte Carlo-based dose-check including the magnetostatic field, SciMoCaTM (S).

METHODS

M and S were validated first in water, by comparison with commissioning-dosimetry. PDD(2x2cm2) through a lung(air)-equivalent virtual-slab was then calculated. Clinical validation retrospectively included 161 SBRT plans, from five patients per-site: Pelvic-Nodes, Prostate, Liver, Pancreas, and Lungs. S-minus-M percentage differences (Δ%) were computed for target- and OARs-related dose-volume metrics. In-phantom dose verification per-patient was performed.

RESULTS

γ(2 %,1mm)-passing-rates (PR%) of in-water-computed PDD and transverse-dose-profiles vs. commissioning-dosimetry were (99.1 ± 2.0)% for M, and (99.3 ± 1.5)% for S. Calculated output-factors (OF) were typically within 1 % from measurements, except for OF(1x1cm2) which was misestimated by -4.4 % and + 2.2 %, by M and S respectively. Dose spikes (valleys) on the PDD(2x2cm2) by S across the lung-equivalent virtual-slab were slightly reduced with respect to M. In clinical plans, S computed higher V95% (p <0.05*, for pancreas and lung) and D2% (p <0.05*, for all sites) for the target, while D%>2% resulted for duodenal D(1cm3), in Pancreas-SBRT, and for mean-lung-dose, in Lung-SBRT. All mostly due to the underestimated OF(1x1cm2) by M. In-phantom dose verifications showed an average 1% increase in PR% by S vs. M.

CONCLUSIONS

Beam-model quality in S resulted equivalent to M, thus making S useful both for an independent validation of the same beam-model in M, and for a daily validation of the M-based online approval decisions, without significantly delaying the clinical workflow (2-3 min).

On the correction factors for small field dosimetry in 1.5T MR-linacs

Objective. Clinical dosimetry in the presence of a 1.5 T magnetic field is challenging, let alone in case small fields are involved. The scope of this study is to determine a set of relevant correction factors for a variety of MR-compatible detectors with emphasis on small fields. Two dosimetry formalisms adopted from the literature are considered.Approach. Six small-cavity ionization chambers (from three manufacturers), four active solid-state detectors and a thermoluminescence dosimeter microcube were modeled in the EGSnrc Monte Carlo code. Phase space files for field sizes down to 1 × 1 cm2of the Unity 1.5 T/7 MV MR-linac (Elekta, UK) were used as source models. Simulations were performed to calculate thekQB,QfB,f(also known askB,Q),kQmsrB,fmsrandkQclin,QmsrB,fclin,fmsrrelevant to two different dosimetry formalisms. Two detector orientations with respect to the magnetic field were considered. Moreover, the effect of the ionization chamber's stem length (a construction parameter) on the correction factor was investigated. Simulations were also carried out to determine whether correction factors obtained in water can be applied in dosimetry procedures involving water-equivalent solid phantoms.Main results. Under thekQB,QfB,f-based formalism, the required corrections to ionization chamber responses did not exceed 1.5% even for the smallest field size considered. A much wider range ofkQB,QfB,fvalues was obtained for the active solid-state detectors included in the simulations. This is the first study to reportkQclin,QmsrB,fclin,fmsrvalues for ionization chambers. The impact of the stem on correction factors is not significant for lengths ⩾0.75 cm. Correction factors determined in water are also valid in dosimetry protocols employing solid phantoms.Significance. This work substantially expands the range of available detectors that can be used in small field dosimetry, enabling more options for commissioning, beam modeling and quality assurance procedures in 1.5 T MR-Linacs. However, more studies are needed to establish a complete and reliable dataset.

Skin dose investigations on a 0.5 T parallel rotating biplanar linac-MR using Monte Carlo simulations and measurements

BACKGROUND

The Alberta rotating biplanar linac-MR has a 0.5 T magnetic field parallel to the beamline. When developing a new linac-MR system, interactions of charged particles with the magnetic field necessitate careful consideration of skin dose and tissue interface effects.

PURPOSE

To investigate the effect of the magnetic field on skin dose using measurements and Monte Carlo (MC) simulations.

METHODS

We develop an MC model of our linac-MR, which we validate by comparison with ion chamber measurements in a water tank. Additionally, MC simulation results are compared with radiochromic film surface dose measurements on solid water. Variations in surface dose as a function of field size are measured using a parallel plate ion chamber in solid water. Using an anthropomorphic computational phantom with a 2 mm-thick skin layer, we investigate dose distributions resulting from three beam arrangements. Magnetic field on and off scenarios are considered for all measurements and simulations.

RESULTS

For a 20 × 20 cm2 field size,D 0.2 c c ${D_{0.2cc}}$ (the minimum dose to the hottest contiguous 0.2 cc volume) for the top 2 mm of a simple water phantom is 72% when the magnetic field is on, compared to 34% with magnetic field off (values are normalized to the central axis dose maximum). Parallel plate ion chamber measurements demonstrate that the relative increase in surface dose due to the magnetic field decreases with increasing field size. For the anthropomorphic phantom,D ∼ 0.2 c c ${D_{ \sim 0.2cc}}$ (minimum skin dose in the hottest 1 × 1 × 1 cm3 cube) shows relative increases of 20%-28% when the magnetic field is on compared to when it is off. With magnetic field off, skinD ∼ 0.2 c c ${D_{ \sim 0.2cc}}$ is 71%, 56%, and 21% for medial-lateral tangents, anterior-posterior beams, and a five-field arrangement, respectively. For magnetic field on, the corresponding skinD ∼ 0.2 c c ${D_{ \sim 0.2cc}}$ values are 91%, 67%, and 25%.

CONCLUSIONS

Using a validated MC model of our linac-MR, surface doses are calculated in various scenarios. MC-calculated skin dose varies depending on field sizes, obliquity, and the number of beams. In general, the parallel linac-MR arrangement results in skin dose enhancement due to charged particles spiraling along magnetic field lines, which impedes lateral motion away from the central axis. Nonetheless, considering the results presented herein, treatment plans can be designed to minimize skin dose by, for example, avoiding oblique beams and using a larger number of fields.

Relative profile measurements in 1.5T MR-linacs: investigation of central axis deviations

Objective. In 1.5 T MR-linacs, the absorbed dose central axis (CAX) deviates from the beam's CAX due to inherent profile asymmetry. In addition, a measured CAX deviation may be biased due to potential lateral (to the beam) effective point of measurement (EPOML) shifts of the detector employed. By investigating CAX deviations, the scope of this study is to determine a set ofEPOMLshifts for profile measurements in 1.5 T MR-linacs.Approach. The Semiflex 3D ion chamber and microDiamond detector (PTW, Germany) were considered in the experimental study while three more detectors were included in the Monte Carlo (MC) study. CAX deviations in the crossline and inline profiles were calculated based on inflection points of the 10×10 cm2field, at five centers. In MC simulations, the experimental setup was reproduced. A small water voxel was simulated to calculate CAX deviation without the impact of the detector-specificEPOMLshift.Main results. All measurements were consistent among the five centers. MC-based and experimental measurements were in agreement within uncertainties. Placing the microDiamond in the vertical orientation does not appear to affect the detector'sEPOML, which is on its central longitudinal axis. For the Semiflex 3D in the crossline direction, the CAX deviation was 2.3 mm, i.e. 1 mm larger than the ones measured using the microDiamond and simulated considering the ideal water detector. Thus, anEPOMLshift of 1 mm is recommended for crossline profile measurements under both Semiflex 3D orientations. For the inline profile, anEPOMLshift of -0.5 mm was determined only for the parallel configuration. In the MC study, CAX deviations were found detector- and orientation-dependent. The dead volume is responsible for theEPOMLshift only in the inline profile and under the parallel orientation.Significance. This work contributes to data availability on the correction or mitigation of the magnetic field-induced changes in the detectors' response.

Assessment of the deep learning-based gamma passing rate prediction system for 1.5 T magnetic resonance-guided linear accelerator

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.

Dose Calculation Accuracy of Beam Models in RadCalc for a 1.5 T MR-Linac

The purpose of this study is to evaluate RadCalc, an independent dose verification software, for patient-specific quality assurance (PSQA) in online adaptive planning with a magnetic resonance linear accelerator (MR-linac) of a 1.5 T. Version 7.1.4 of RadCalc to introduce the capability to establish a beam model that incorporates MR field characteristics. A total of six models were established, with one using manufacturer-provided data and the others differing in percentage depth dose (PDD) data sources. Overall, two models utilized PDD data from the treatment planning system (TPS), and three used commissioned PDD data from gantry angles of 0° and 270°. Simple tests on a virtual water phantom assessed dose-calculation accuracy, revealing percentage differences ranging from -0.5% to -20.6%. Excluding models with significant differences, clinical tests on 575 adaptive plans (prostate, liver, and breast) showed percentage differences of -0.51%, 1.12%, and 4.10%, respectively. The doses calculated using RadCalc demonstrated similar trends to those of the PSQA-based measurements. The newly released version of RadCalc enables beam modeling that considers the characteristics of the 1.5 T magnetic field. The accuracy of the software in calculating doses at 1.5 T magnetic fields has been verified, thereby making it a reliable and effective tool for PSQA in adaptive plans.

Development and clinical application of a GPU-based Monte Carlo dose verification module and software for 1.5 T MR-LINAC

BACKGROUND

Adaptive radiotherapy (ART) has made significant advances owing to magnetic resonance linear accelerator (MR-LINAC), which provides superior soft-tissue contrast, fast speed and rich functional magnetic resonance imaging (MRI) to guide radiotherapy. Independent dose verification plays a critical role in discovering errors, while several challenges remain in MR-LINAC.

PURPOSE

A Monte Carlo-based GPU-accelerated dose verification module for Unity is proposed and integrated into the commercial software ArcherQA to achieve fast and accurate quality assurance (QA) for online ART.

METHODS

Electron or positron motion in a magnetic field was implemented, and a material-dependent step-length limit method was used to trade off speed and accuracy. Transport was verified by dose comparison with EGSnrc in three A-B-A phantoms. Then, an accurate Monte Carlo-based Unity machine model was built in ArcherQA, including an MR-LINAC head, cryostat, coils, and treatment couch. In particular, a mixed model combining measured attenuation and homogeneous geometry was adopted for the cryostat. Several parameters in the LINAC model were tuned to commission it in the water tank. An alternating open-closed MLC plan on solid water measured with EBT-XD film was used to verify the LINAC model. Finally, the ArcherQA dose was compared with ArcCHECK measurements and GPUMCD in 30 clinical cases through the gamma test.

RESULTS

ArcherQA and EGSnrc were well matched in three A-B-A phantom tests, and the relative dose difference (RDD) was less than 1.6% in the homogenous region. A Unity model was commissioned in the water tank, and the RDD in the homogenous region was less than 2%. In the alternating open-closed MLC plan, the gamma result (3%/3 mm) between ArcherQA and Film was 96.55%, better than the gamma result between GPUMCD and Film (92.13%). In 30 clinical cases, the mean three-dimensional (3D) gamma result (3%/2 mm) was 99.36% ± 1.28% between ArcherQA and ArcCHECK for the QA plans and 99.27% ± 1.04% between ArcherQA and GPUMCD for the clinical patient plans. The average dose calculation time was 106 s in all clinical patient plans.

CONCLUSIONS

A GPU-accelerated Monte Carlo-based dose verification module was developed and built for the Unity MR-LINAC. The fast speed and high accuracy were proven by comparison with EGSnrc, commission data, the ArcCHECK measurement dose, and the GPUMCD dose. This module can achieve fast and accurate independent dose verification for Unity.

Dosimetry in 1.5 T MR-Linacs: Monte Carlo determination of magnetic field correction factors and investigation of the air gap effect

BACKGROUND

In Magnetic Resonance-Linac (MR-Linac) dosimetry formalisms, a new correction factor, k_B,Q , has been introduced to account for corresponding changes to detector readings under the beam quality, Q, and the presence of magnetic field, B.

PURPOSE

This study aims to develop and implement a Monte Carlo (MC)-based framework for the determination of k_B,Q correction factors for a series of ionization chambers utilized for dosimetry protocols and dosimetric quality assurance checks in clinical 1.5 T MR-Linacs. Their dependencies on irradiation setup conditions are also investigated. Moreover, to evaluate the suitability of solid phantoms for dosimetry checks and end-to-end tests, changes to the detector readings due to the presence of small asymmetrical air gaps around the detector's tip are quantified.

METHODS

Phase space files for three irradiation fields of the ELEKTA Unity 1.5 T/7 MV flattening-filter-free MR-Linac were provided by the manufacturer and used as source models throughout this study. Twelve ionization chambers (three farmer-type and nine small-cavity detectors, from three manufacturers) were modeled (including their dead volume) using the EGSnrc MC code package. k_B,Q values were calculated for the 10 × 10 cm² irradiation field and for four cardinal orientations of the detectors' axes with respect to the 1.5 T magnetic field. Potential dependencies of k_B,Q values with respect to field size, depth, and phantom material were investigated by performing additional simulations. Changes to the detectors' readings due to the presence of small asymmetrical air gaps (0.1 up to 1 mm) around the chambers' sensitive volume in an RW3 solid phantom were quantified for three small-cavity chambers and two orientations.

RESULTS

For both parallel (to the magnetic field) orientations, k_B,Q values were found close to unity. The maximum correction needed was 1.1%. For each detector studied, the k_B,Q values calculated for the two parallel orientations agreed within uncertainties. Larger corrections (up to 5%) were calculated when the detectors were oriented perpendicularly to the magnetic field. Results were compared with corresponding ones found in the literature, wherever available. No considerable dependence of k_B,Q with respect to field size (down to 3 × 3 cm² ), depth, or phantom material was noticed, for the detectors investigated. As compared to the perpendicular one, in the parallel to the magnetic field orientation, the air gap effect is minimized but is still considerable even for the smallest air gap considered (0.1 mm).

CONCLUSION

For the 10 × 10 cm² field, magnetic field correction factors for 12 ionization chambers and four orientations were determined. For each detector, the k_B,Q value may be also applied for dosimetry procedures under different irradiation parameters provided that the orientation is taken into account. Moreover, if solid phantoms are used, even the smallest asymmetrical air gap may still bias small-cavity chamber response. This work substantially expands the availability and applicability of k_B,Q correction factors that are detector- and orientation-specific, enabling more options in MR-Linac dosimetry checks, end-to-end tests, and quality assurance protocols.

An independent Monte Carlo-based IMRT QA tool for a 0.35 T MRI-guided linear accelerator

PURPOSE

To develop an independent log file-based intensity-modulated radiation therapy (IMRT) quality assurance (QA) tool for the 0.35 T magnetic resonance-linac (MR-linac) and investigate the ability of various IMRT plan complexity metrics to predict the QA results. Complexity metrics related to tissue heterogeneity were also introduced.

METHODS

The tool for particle simulation (TOPAS) Monte Carlo code was utilized with a previously validated linac head model. A cohort of 29 treatment plans was selected for IMRT QA using the developed QA tool and the vendor-supplied adaptive QA (AQA) tool. For 27 independent patient cases, various IMRT plan complexity metrics were calculated to assess the deliverability of these plans. A correlation between the gamma pass rates (GPRs) from the AQA results and calculated IMRT complexity metrics was determined using the Pearson correlation coefficients. Tissue heterogeneity complexity metrics were calculated based on the gradient of the Hounsfield units.

RESULTS

The median and interquartile range for the TOPAS GPRs (3%/3 mm criteria) were 97.24% and 3.75%, respectively, and were 99.54% and 0.36% for the AQA tool, respectively. The computational time for TOPAS ranged from 4 to 8 h to achieve a statistical uncertainty of <1.5%, whereas the AQA tool had an average calculation time of a few minutes. Of the 23 calculated IMRT plan complexity metrics, the AQA GPRs had correlations with 7 out of 23 of the calculated metrics. Strong correlations (|r| > 0.7) were found between the GPRs and the heterogeneity complexity metrics introduced in this work.

CONCLUSIONS

An independent MC and log file-based IMRT QA tool was successfully developed and can be clinically deployed for offline QA. The complexity metrics will supplement QA reports and provide information regarding plan complexity.

Development of a GPU-superposition Monte Carlo code for fast dose calculation in magnetic fields

Objective. To develop and validate a graphics processing unit (GPU) based superposition Monte Carlo (SMC) code for efficient and accurate dose calculation in magnetic fields. Approach. A series of mono-energy photons ranging from 25 keV to 7.7 MeV were simulated with EGSnrc in a water phantom to generate particle tracks database. SMC physics was extended with charged particle transport in magnetic fields and subsequently programmed on GPU as gSMC. Optimized simulation scheme was designed by combining variance reduction techniques to relieve the thread divergence issue in general GPU-MC codes and improve the calculation efficiency. The gSMC code’s dose calculation accuracy and efficiency were assessed through both phantoms and patient cases. Main results. gSMC accurately calculated the dose in various phantoms for both B = 0 T and B = 1.5 T, and it matched EGSnrc well with a root mean square error of less than 1.0% for the entire depth dose region. Patient cases validation also showed a high dose agreement with EGSnrc with 3D gamma passing rate (2%/2 mm) large than 97% for all tested tumor sites. Combined with photon splitting and particle track repeating techniques, gSMC resolved the thread divergence issue and showed an efficiency gain of 186–304 relative to EGSnrc with 10 CPU threads. Significance. A GPU-superposition Monte Carlo code called gSMC was developed and validated for dose calculation in magnetic fields. The developed code’s high calculation accuracy and efficiency make it suitable for dose calculation tasks in online adaptive radiotherapy with MR-LINAC.

Evaluation of MU2net as an online secondary dose check for MR guided radiation therapy with the Elekta unity MR linac

During the adaptive workflow associated with MRgRT, a secondary dose calculation is required and MU2net (DOSIsoft, France) is one commercial option. The suitability of MU2net to be used in conjunction with the online Monaco treatment planning system of the Elekta Unity (Elekta AB, Stockholm, Sweden), is evaluated in this work. Monaco and MU2net point doses are compared for various fields on and off axis and at different SSDs. To investigate the comparative effects of attenuation due to the cryostat, couch and posterior coil, measured, MU2net and Monaco dose outputs at the isocentre, as a function of gantry angle, were compared. Point doses for the beams of nine step and shoot IMRT (SSIMRT) test plans (courtesy Elekta) were calculated with Monaco v5.4 and compared to corresponding doses computed with MU2net. In addition, Monaco v5.4 and MU2net point doses were compared for 1552 beams treated on the Unity at our facility. For the on-axis fields investigated the agreement between MU2net and measured data is acceptable. MU2net and Monaco point doses for the Elekta SSIMRT test plans were within ± 5.0% and ± 6.4% for beams delivered from gantry zero and at planned beam angles, respectively. For the 1552 beams delivered approximately 80.0% of MU2net and Monaco point doses agree within ± 5.0%, therefore it is recommended to correlate MU2net Dose Reference Points (DRPs) with pre and post treatment dosimetry verification. Computational accuracy of MU2net could be enhanced with improved modelling of attenuation due to the couch, cryostat and posterior MR imaging coil.

Convolution neural network toward Monte Carlo photon dose calculation in radiation therapy

PURPOSE

The Monte Carlo (MC) algorithm has been widely accepted as the most accurate algorithm for dosimetric calculations under various conditions in radiotherapy. However, the calculation time remains an important obstacle hindering the routine use of MC in clinical settings. In this study, full MC three-dimensional dose distributions were obtained with the inputs of the total energy release per unit mass (TERMA) distributions and the electron density (ED) distributions using a convolutional neural network (CNN). A new Dose-mixup data augmentation routine and training strategy are proposed and applied in the training process. Attempts were made to reduce the calculation time while ensuring that the calculation accuracy is comparable to that of the MC.

METHODS

Datasets were generated via the MC with random rectangular field sizes, random iso-centers, and random gantry angles for head and neck computed tomography (CT) images with Mohan 6-MV spectrum photon beams. 1500 samples were generated for the training set, and 150 samples were generated for the validation set. The T-MC Net model was obtained with the Dose-mixup data augmentation routine. The new CTs were used to test the performance of the model in the rectangular fields and the intensity-modulated radiation therapy (IMRT) fields. The mean ± 95% confidence interval of gamma pass rates were calculated.

RESULTS

For 150 rectangular field test samples, the 1%/2 mm, 2%/2 mm, and 3%/2 mm criteria gamma pass rates were 90.11% ± 0.65%, 97.65% ± 0.31%, and 99.16% ± 0.19%, respectively. For the 100 IMRT field test samples, the 1%/2 mm, 2%/2 mm, and 3%/2 mm criteria gamma pass rates were 96.48% ± 0.28%, 99.14% ± 0.10%, and 99.63% ± 0.06%, respectively. For the 7-fields IMRT plan, the 1%/2 mm, 2%/2 mm, and 3%/2 mm criteria gamma pass rates were 97.06%, 99.10%, and 99.52%, respectively. For the 9-fields IMRT plan, the 1%/2 mm, 2%/2 mm, and 3%/2 mm criteria gamma pass rates were 98.16%, 99.61%, and 99.89%, respectively.

CONCLUSIONS

The feasibility of calculating dose distribution using a CNN with the TERMA three-dimensional distribution and ED distribution was established. The dosimetric results were comparable to those of the full MC. The accuracy and speed of the proposed approach make it a potential solution for full MC in radiotherapy. This method may be used as an acceleration engine for the dose algorithm and shows great potential for cases where fast dose calculations are needed.

Extension and validation of a GPU-Monte Carlo dose engine gDPM for 1.5 T MR-LINAC online independent dose verification

PURPOSE

To extend and validate the accuracy and efficiency of a graphics processing unit (GPU)-Monte Carlo dose engine for Elekta Unity 1.5 T Magnetic Resonance-Linear Accelerator (MR-LINAC) online independent dose verification.

METHODS

Electron/positron propagation physics in a uniform magnetic field was implemented in a previously developed GPU-Monte Carlo dose engine-gDPM. The dose calculation accuracy in the magnetic field was first evaluated in heterogeneous phantom with EGSnrc. The dose engine was then commissioned to a Unity machine with a virtual two photon-source model and compared with the Monaco treatment planning system. Fifteen patient plans from five tumor sites were included for the quantification of online dose verification accuracy and efficiency.

RESULTS

The extended gDPM accurately calculated the dose in a 1.5 T external magnetic field and was well matched with EGSnrc. The relative dose difference along central beam axis was less than 0.5% for the homogeneous region in water-lung phantom. The maximum difference was found at the build-up regions and heterogeneous interfaces, reaching 1.9% and 2.4% for 2 and 6 MeV mono-energy photon beams, respectively. The root mean square errors for depth-dose fall-off region were less than 0.2% for all field sizes and presented a good match between gDPM and Monaco GPUMCD. For in-field profiles, the dose differences were within 1% for cross-plane and in-plane directions for all calculated depths except dmax. For penumbra regions, the distance-to-agreements between two dose profiles were less than 0.1 cm. For patient plan verification, the maximum relative average dose difference was 1.3%. The gamma passing rates with criteria 3% (2 mm) for dose regions above 20% were between 93% and 98%. gDPM can complete the dose calculation for less than 40 s with 5 × 10⁸ photons on a single NVIDIA GTX-1080Ti GPU and achieve a statistical uncertainty of 0.5%-1.1% for all evaluated cases.

CONCLUSIONS

A GPU-Monte Carlo package-gDPM was extended and validated for Elekta Unity online plan verification. Its calculation accuracy and efficiency make it suitable for online independent dose verification for MR-LINAC.

Automatic 3D Monte-Carlo-based secondary dose calculation for online verification of 1.5 T magnetic resonance imaging guided radiotherapy

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First implementation of an independent 3D-secondary dose calculation (3D-SDC).

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Validation of the 3D-SDC solution using patient plans and experimental plan QA.

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Online SDC of central targets is feasible with a median calculation time of 1:23 min.

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Peripheral targets with small beam numbers need alternative validation strategies.

Background and purpose

Hybrid magnetic resonance linear accelerator (MR-Linac) systems represent a novel technology for online adaptive radiotherapy. 3D secondary dose calculation (SDC) of online adapted plans is required to assure patient safety. Currently, no 3D-SDC solution is available for 1.5T MR-Linac systems. Therefore, the aim of this project was to develop and validate a method for online automatic 3D-SDC for adaptive MR-Linac treatments.

Materials and methods

An accelerator head model was designed for an 1.5T MR-Linac system, neglecting the magnetic field. The use of this model for online 3D-SDC of MR-Linac plans was validated in a three-step process: (1) comparison to measured beam data, (2) investigation of performance and limitations in a planning phantom and (3) clinical validation using n = 100 patient plans from different tumor entities, comparing the developed 3D-SDC with experimental plan QA.

Results

The developed model showed median gamma passing rates compared to MR-Linac base data of 84.7%, 100% and 99.1% for crossplane, inplane and depth-dose-profiles, respectively. Comparison of 3D-SDC and full dose calculation in a planning phantom revealed that with ⩾5 beams gamma passing rates >95% can be achieved for central target locations. With a median calculation time of 1:23 min, 3D-SDC of online adapted clinical MR-Linac plans demonstrated a median gamma passing rate of 98.9% compared to full dose calculation, whereas experimental plan QA reached 99.5%.

Conclusion

Here, we describe the first technical 3D-SDC solution for online adaptive MR-guided radiotherapy. For clinical situations with peripheral targets and a small number of beams additional verification appears necessary. Further improvement may include 3D-SDC with consideration of the magnetic field.

Technical Challenges of Real-Time Adaptive MR-Guided Radiotherapy

In the past few years, radiotherapy (RT) has experienced a major technological innovation with the development of hybrid machines combining magnetic resonance (MR) imaging and linear accelerators. This new technology for MR-guided cancer treatment has the potential to revolutionize the field of adaptive RT due to the opportunity to provide high-resolution, real-time MR imaging before and during treatment application. However, from a technical point of view, several challenges remain which need to be tackled to ensure safe and robust real-time adaptive MR-guided RT delivery. In this manuscript, several technical challenges to MR-guided RT are discussed. Starting with magnetic field strength tradeoffs, the potential and limitations for purely MR-based RT workflows are discussed. Furthermore, the current status of real-time 3D MR imaging and its potential for real-time RT are summarized. Finally, the potential of quantitative MR imaging for future biological RT adaptation is highlighted.

Development and evaluation of a GEANT4-based Monte Carlo Model of a 0.35 T MR-guided radiation therapy (MRgRT) linear accelerator

PURPOSE

The aim of this work was to develop and benchmark a magnetic resonance (MR)-guided linear accelerator head model using the GEANT4 Monte Carlo (MC) code. The validated model was compared to the treatment planning system (TPS) and was also used to quantify the electron return effect (ERE) at a lung-water interface.

METHODS

The average energy, including the spread in the energy distribution, and the radial intensity distribution of the incident electron beam were iteratively optimized in order to match the simulated beam profiles and percent depth dose (PDD) data to measured data. The GEANT4 MC model was then compared to the TPS model using several photon beam tests including oblique beams, an off-axis aperture, and heterogeneous phantoms. The benchmarked MC model was utilized to compute output factors (OFs) with the 0.35 T magnetic field turned on and off. The ERE was quantified at a lung-water interface by simulating PDD curves with and without the magnetic field for 6.6 × 6.6  cm 2 and 2.5 × 2.5  cm 2 field sizes. A 2%/2 mm gamma criterion was used to compare the MC model with the TPS data throughout this study.

RESULTS

The final incident electron beam parameters were 6.0 MeV average energy with a 1.5 MeV full width at half maximum (FWHM) Gaussian energy spread and a 1.0 mm FWHM Gaussian radial intensity distribution. The MC-simulated OFs were found to be in agreement with the TPS-calculated and measured OFs, and no statistical difference was observed between the 0.35 T and 0.0 T OFs. Good agreement was observed between the TPS-calculated and MC-simulated data for the photon beam tests with gamma pass rates ranging from 96% to 100%. An increase of 4.3% in the ERE was observed for the 6.6 × 6.6  cm 2 field size relative to the 2.5 × 2.5  cm 2 field size. The ratio of the 0.35 T PDD to the 0.0 T PDD was found to be up to 1.098 near lung-water interfaces for the 6.6 × 6.6  cm 2 field size using the MC model.

CONCLUSIONS

A vendor-independent Monte Carlo model has been developed and benchmarked for a 0.35 T/6 MV MR-linac. Good agreement was obtained between the GEANT4 and TPS models except near heterogeneity interfaces.

Experimental determination of magnetic field correction factors for ionization chambers in parallel and perpendicular orientations

Magnetic field correction factors are needed for absolute dosimetry in magnetic resonance (MR)-linacs. Currently experimental data for magnetic field correction factors, especially for small volume ionization chambers, are largely lacking. The purpose of this work is to establish, independent methods for the experimental determination of magnetic field correction factors [Formula: see text] in an orientation in which the ionization chamber is parallel to the magnetic field. The aim is to confirm previous experiments on the determination of Farmer type ionization chamber correction factors and to gather information about the usability of small-volume ionization chambers for absolute dosimetry in MR-linacs. The first approach to determine [Formula: see text] is based on a cross-calibration of measurements using a conventional linac with an electromagnet and an MR-linac. The absolute influence of the magnetic field in perpendicular orientation is quantified with the help of the conventional linac and the electromagnet. The correction factors for the parallel orientation are then derived by combining these measurements with relative measurements in the MR-linac. The second technique utilizes alanine electron paramagnetic resonance dosimetry. The alanine system as well as several ionization chambers were directly calibrated with the German primary standard for absorbed dose to water. Magnetic field correction factors for the ionization chambers were determined by a cross-calibration with the alanine in an MR-linac. Important quantities like [Formula: see text] for Farmer type ionization chambers in parallel orientation and the change of the dose to water due the magnetic field [Formula: see text] have been confirmed. In addition, magnetic field correction factors have been determined for small volume ionization chambers in parallel orientation. The electromagnet-based measurements of [Formula: see text] for [Formula: see text] MR-linacs and parallel ionization chamber orientations resulted in 0.9926(22), 0.9935(31) and 0.9841(27) for the PTW 30013, the PTW 31010 and the PTW 31021, respectively. The measurements based on the second technique resulted in values for [Formula: see text] of 0.9901(72), 0.9955(72), and 0.9885(71). Both methods show excellent accuracy and reproducibility and are therefore suitable for the determination of magnetic field correction factors. Small-volume ionization chambers showed a variation in the resulting values for [Formula: see text] and should be cross-calibrated instead of using tabulated values for correction factors.

Feasibility of using a commercial collapsed cone dose engine for 1.5T MR-LINAC online independent dose verification

PURPOSE

To validate the feasibility and accuracy of commonly used collapsed cone (CC) dose engine for Elekta Unity 1.5T MR-LINAC online independent dose verification.

MATERIALS AND METHODS

The Unity beam model was built and commissioned in RayStation treatment planning system with CC dose engine. Four AAPM TG-119 test plans were created and measured with ArcCHECK phantom for comparison, another thirty patient plans from six tumor sites were also included. The dosimetric criteria for various ROIs and 3D gamma passing rates were quantitatively evaluated, and the effects of magnetic field and dose deposition type on the dose difference between two systems were further analyzed.

RESULTS

ArcCHECK based measurement showed a clear magnetic field induced profile shift between CC with both measurement and GPUMCD. For clinical plans, gamma passing rates with criteria (3%, 3 mm) between GPUMCD and CC large than 90% can be achieved for most tumor sites except esophagus and lung cases, the mean dose difference of 3% can be satisfied for most ROIs from all tumor sites. The magnetic field caused a large dose impact on low density areas, the average gamma passing rates were improved from 85.54% to 96.43% and 87.40% to 99.54% for esophagus and lung cases when the magnetic field effect was excluded.

CONCLUSIONS

It is feasible to use CC dose engine as a secondary dose calculation tool for Elekta Unity system for most tumor sites, while the accuracy is limited and should be used carefully for low density areas, such as esophagus and lung cases.

Influence of beam quality on reference dosimetry correction factors in magnetic resonance guided radiation therapy

Correction factors for reference dosimetry in magnetic resonance (MR) imaging-guided radiation therapy (k B → , M , Q ) are often determined in setups that combine a conventional 6 MV linac with an electromagnet. This study investigated whether results based on these measurements were applicable for a 7 MV MR-linac using Monte Carlo simulations. For a Farmer-type ionization chamber,k B → , M , Q was assessed for different tissue-phantom ratios (TPR 20 , 10 ).k B → , M , Q differed by 0.0029 ( 43 ) betweenTPR 20 , 10 = 0.6790 ( 23 ) (6 MV linac) andTPR 20 , 10 = 0.7028 ( 14 ) (7 MV MR-linac) at 1.5 T . The agreement was best in an orientation in which the secondary electrons were deflected to the stem of the ionization chamber.