Dosimetric Leaf Gap Research Articles

Technical Note: Investigating of dosimetric leaf gap and leaf transmission factor variations across gantry and collimator angles in volumetric modulation arc therapy.

This study investigates the influence of gantry and collimator angles on the dosimetric leaf gap (DLG) and leaf transmission factor (LTF) in a Varian LINAC equipped with rounded-end multi-leaf collimators (MLCs). While Varian guidelines recommend DLG measurements at zero degrees for both gantry and collimator, this research aims to address the knowledge gap by assessing DLG and LTF variations at different gantry and collimator angles. Measurements were conducted using a Varian TrueBeam LINAC with a Millennium 120-leaf MLC and Eclipse TPS version 16.1. The beams utilized in this study had energies of 6 MV, 10 MV, 6 FFF, and 10 FFF. LTF and DLG were determined using ionization chambers in solid water phantoms at various gantry angles (0°, 45°, 90°, 135°, 180°, 225°, 270°, and 315°). For each gantry angle, measurements were also taken at various collimator angles (0°, 45°, 90°, and 315°). Dosimetric impacts were evaluated through VMAT Picket Fence tests and patient-specific verification using portal dosimetry for 10 clinical VMAT plans. LTF values showed no significant variation across gantry and collimator angles. However, DLG values exhibited notable differences depending on the gantry angle and were independent of the collimator angle. The highest DLG value was observed at a gantry angle of 270 degrees, while the lowest was at 90 degrees. The AXB DLGAverage (averaging seven measurements of DLGs at different gantry angles) model demonstrated the best agreement between measured and calculated dose distributions, indicating the importance of considering averaged DLG values across multiple gantry angles for accurate dose calculations. Our study highlights the variability of DLG with gantry angle alterations, contrary to Varian guidelines recommending DLG measurements at zero gantry angle only. We advocate for utilizing an averaged DLG value from measurements across multiple gantry angles, as outlined in our methodology.

1646: Assessment of different methods of measuring the dosimetric leaf gap (DLG) for Varian TrueBeam HD.

1646: Assessment of different methods of measuring the dosimetric leaf gap (DLG) for Varian TrueBeam HD.

Investigating the Dosimetric Leaf Gap Correction Factor of Mobius3D Dose Calculation for Volumetric-modulated Arc Radiotherapy Plans.

The dosimetric leaf gap (DLG) is a parameter for correcting radiation transmission through the round leaf end of multileaf collimators. The purpose of this study was to determine and investigate the optimal DLG correction factor for 6 MV volumetric-modulated arc radiotherapy (VMAT) plan dose calculations in Mobius3D. Seventeen VMAT plans were selected for the DLG correction factor optimization process. The optimal DLG correction factor was defined as the minimum difference between the measured dose and the Mobius3D-calculated dose on the Mobius Verification Phantom™ with different DLG correction factors. Subsequently, the optimal DLG correction factor was applied for Mobius3D dose calculation, and accuracy was assessed by comparing the measured and calculated doses. For verification and validation, the 17 previous plans and 10 newly selected plans underwent Mobius3D calculations with the optimal DLG correction factor, and gamma analysis was performed to compare them to the treatment planning system (TPS). Gamma analysis was also performed between the electronic portal imaging device (EPID) and the TPS for cross-comparison between systems. The DLG correction factor was optimized to -1.252, which reduced the average percentage differences between measured and Mobius3D-calculated doses from 2.23% ±1.21% to 0.03% ±1.82%. The cross-comparison between Mobius3D/TPS and EPID/TPS revealed a similar trend in gamma passing rate (>95%) in both the verification and validation plans. The DLG correction factor strongly influences the accuracy of Mobius3D-calculated doses. Applying the optimal DLG correction factor can increase dose agreement and gamma passing rate between calculation and delivered doses of VMAT plans, which emphasizes the importance of optimizing this factor during the commissioning process.

Optimization of a commercial portal dose image prediction algorithm for pre-treatment verifications of plans using unflattened photon beams.

The aim was to improve the portal dosimetry-based quality assurance results of conventional treatment plans by adjusting the multileaf collimator (MLC) dosimetric leaf gap (DLG) and transmission (T) values of the anisotropic analytic algorithm (AAA) used for portal dose image prediction (PDIP). The AAA-based PDIP v. 16.1 algorithm (PDIP-AAA) of the Eclipse TPS was configured for 6 MV FFF energy. Optimal DLG and T values were achieved for this algorithm by comparing predicted versus measured portal images of the Chair pattern. Twenty clinical plans using 6 MV FFF beams were verified using the optimal PDIP-AAA algorithm and the standard PDIP v. 16 algorithm (PDIP-vE), configured using the van Esch package. The 3% global/2 mm gamma passing rates (GPRs) and average gamma indexes (AGIs) were computed for each acquired image. For each plan, the mean GPR (GPRmean) and mean GAI (GAImean) were compared for both algorithms. A 2-tailed Student t-test (α = 0.05) was used to evaluate whether there was a statistically significant difference. Optimal values of DLG = 0.1 mm and T = 0.01 were found for the PDIP-AAA algorithm, providing significantly better values of GPRmean and AGImean than PDIP-vE (p < 0.001). All plans verified with PIDP-AAA showed GPRmean ≥ 95%. In contrast, only 45% of the plans reported GPRmean ≥ 95% with the PDIP-vE algorithm. The MLC parameters available in the PDIP-AAA model must be tuned to improve the accuracy of the predicted dose image. This work-around is not possible using the standard PDIP algorithm. The adjusted PDIP-AAA resulted in significantly better results than PDIP-vE.

Multi-institutional investigation into the robustness of intra-cranial multi-target stereotactic radiosurgery plans to delivery errors.

The use of modulated techniques for intra-cranial stereotactic radiosurgery (SRS) results in highly modulated fields with small apertures, which may be susceptible to uncertainties in the delivery device. This study aimed to quantify the impact of simulated delivery errors on treatment plan dosimetry and how this is affected by treatment planning system (TPS), plan geometry, delivery technique, and plan complexity. A beam modelling error was also included as context to the dose uncertainties due to treatment delivery errors. Delivery errors were assessed for multiple-target brain SRS plans obtained through the Trans-Tasman Radiation Oncology Group (TROG) international treatment planning challenge (2018). The challenge dataset consisted of five intra-cranial targets, each with a prescription of 20Gy. Of the final dataset of 54 plans, 51 were created using the volumetric modulated arc therapy (VMAT) technique and three used intensity modulated arc therapy (IMRT). Thirty-five plans were from the Varian Eclipse TPS, 17 from Elekta Monaco TPS, and one plan each from RayStation and Philips Pinnacle TPS. The errors introduced included: monitor unit calibration errors, multi-leaf collimator (MLC) bank offset, single MLC leaf offset, couch rotations, and collimator rotations. Dosimetric leaf gap (DLG) error was also included as a beam modelling error. Dose to targets was assessed via dose covering 98% of planning target volume (PTV) (D98%), dose covering 2% of PTV (D2%), and dose covering 99% of gross tumor volume (GTV) (D99%). Dose to organs at risk (OARs) was assessed using the volume of normal brain receiving 12Gy (V12Gy), mean dose to normal brain, and maximum dose covering 0.03cc brainstem (D0.03cc). Plan complexity was also assessed via edge metric, modulation complexity score (MCS), mean MLC gap, mean MLC speed, and plan modulation (PM). PTV D98% showed high robustness on average to most errors with the exception of a bank shift of 1.0mm and large rotational errors ≥1.0° for either the couch or collimator. However, in some cases, errors close to or within generally accepted machine tolerances resulted in clinically relevant impacts. The greatest impact upon normal brain V12Gy, mean dose to normal brain, and D0.03cc brainstem was found for DLG error in alignment with other recent studies. All delivery errors had on average a minimal impact across these parameters. Comparing plans from the Monaco TPS and the Eclipse TPS, showed a lesser increase to V12Gy, mean dose to normal brain, and D0.03cc brainstem for Monaco plans (p<0.01) when DLG error was simulated. Monaco plans also correlated to lower plan complexity. Using Spearman's correlation coefficient (r) a strong negative correlation (r≤-0.8) was found between the mean MLC gap and dose to OARs for DLG errors. Reducing MLC complexity and using larger mean MLC gaps is recommended to improve plan robustness and reduce sensitivity to delivery and modelling errors. For cases in which the calculated dose distribution or dose indices are close to the clinically acceptable limits, this is especially important.

Deep learning-based detection and classification of multi-leaf collimator modeling errors in volumetric modulated radiation therapy.

The purpose of this study was to create and evaluate deep learning-based models to detect and classify errors of multi-leaf collimator (MLC) modeling parameters in volumetric modulated radiation therapy (VMAT), namely the transmission factor (TF) and the dosimetric leaf gap (DLG). A total of 33 clinical VMAT plans for prostate and head-and-neck cancer were used, assuming a cylindrical and homogeneous phantom, and error plans were created by altering the original value of the TF and the DLG by±10, 20, and 30% in the treatment planning system (TPS). The Gaussian filters of and 1.0 were applied to the planar dose maps of the error-free plan to mimic the measurement dose map, and thus dose difference maps between the error-free and error plans were obtained. We evaluated 3 deep learning-based models, created to perform the following detections/classifications: (1) error-free versus TF error, (2) error-free versus DLG error, and (3) TF versus DLG error. Models to classify the sign of the errors were also created and evaluated. A gamma analysis was performed for comparison. The detection and classification of TF and DLG error were feasible for ; however, a considerable reduction of accuracy was observed for depending on the magnitude of error and treatment site. The sign of errors was detectable by the specifically trained models for and 1.0. The gamma analysis could not detect errors. We demonstrated that the deep learning-based models could feasibly detect and classify TF and DLG errors in VMAT dose distributions, depending on the magnitude of the error, treatment site, and the degree of mimicked measurement doses.

TUNING AND VALIDATION OF THE NEW RADCALC 3D MONTE CARLO BASED PRE-TREATMENT PLAN VERIFICATION TOOL

Verification procedures for patient-specific quality assurance (QA) in advanced radiotherapy are laborious and time-consuming. Moreover, it has been shown that these procedures cannot detect some inaccuracies for some particular complex cases due to tissue inhomogeneity and highly modulated plans. Secondary dose calculation verification of radiotherapy plans is an important aspect in patient-specific QA. A suitably optimized software, RadCalc equipped with 3D Monte Carlo Module (MC), was used to dosimetrically verify radiotherapy treatment plans where the measured dose distributions can be inaccurate due to the TPS dose calculation algorithm and/or treatment unit delivery uncertainties. MC Models were built using specific commissioning measurements and then the Additional Radiation to Light Field Offset parameter (Dosimetric Leaf Gap parameter) was tuned to achieve the best dose comparison agreement with phantom patient-specific QA measurements. The results showed a good agreement between the TPS and the simulations. RadCalc MC also allows to better estimate the plan doses in lung cancer patients and to detect the presence of possible inaccuracies due to tissue inhomogeneity, which is not estimable with a homogeneous phantoms.

Characterization of Ethos therapy systems for adaptive radiation therapy: A multi-machine comparison.

The recently released Ethos therapy system (Varian Medical Systems) allows for online CBCT-guided adaptive radiation therapy (RT). The clinical introduction of multiple systems requires machine characterization and machine variation quantification to allow patient interchangeability between systems. Despite several clinical introductions, limited vendor-independent information on machine performance is available. Our aim was to determine the relevant dosimetric and mechanical characteristics of individual machines and to quantify machine variations. Six Ethos treatment machines, equipped with a 6-MV FFF beam including dual-layer MLC and kV-CBCT system, were recently introduced clinically after extensive machine characterization and pre-configured beam model verification. Point doses and profiles were measured and compared to vendor-provided reference data and dose calculations. Also, dose calculations were verified based on point measurements for non-standard fields and dose distributions for optimized treatment plans. Agreements between dose profiles (dose distributions) were quantified using 1D (3D) γ-analysis. Additionally, we quantified leaf transmission, dosimetric leaf gap (DLG) and couch attenuation, determined isocenter accuracy and kV-MV isocenter coincidence and verified the kV-CBCT system. Machine variations were quantified for all dosimetric and mechanical characteristics. For all machines, distinct agreements were found between measurements and vendor-provided reference data as well as measurements and dose calculations. Mean γ1%/1mm values for all profiles were below 0.30. All profiles, point measurements and dose distributions matched well among the six machines. Minimal machine variations were found in terms of DLG (0.05mm), leaf transmission (0.001%), isocenter accuracy (0.08mm), kV-MV isocenter coincidence (0.15mm), couch attenuation (0.69%), and CBCT imaging dose (0.29mGy). This study demonstrates excellent agreement between individual Ethos therapy systems and vendor-provided reference data as well as a pre-configured beam model. Furthermore, our results show good consistency among all machines and provide valuable insights on relevant machine characteristics. The systematically obtained results provide benchmark data for future clinical introduction of Ethos therapy systems.

Commissioning and Performance Evaluation of Varian TrueBeam Linear Accelerator

Aim: The aim of this study is to present a report on the commissioning results of the Varian TrueBeam machine with available photon energies so that it can benefit medical physicists during the entire commissioning process. Subjects and Methods: All tests were performed as per the recommendation of the Atomic Energy Regulatory Board. The beam profiles and percentage depth dose of both photon and electron beams were measured with Sun nuclear Radiation Field Analyzer and 0.125 cc ionization chamber. Output accuracy and consistency of photon and electron beams were measured using 0.6 cc cylindrical ionization chamber and 0.350 cc parallel plate ionization chamber, respectively. To measure the congruency of radiation and optical field and isocenter check with respect to gantry, collimator, and couch, self-developed films were used. Results: Isocenter shift due to gantry, collimator, and couch, rotation was found to be within ± 2-mm diameter circle. Congruency of optical and radiation fields was measured for symmetric fields 5 cm × 5 cm, 10 cm × 10 cm, 20 cm × 20 cm, and 30 cm × 30 cm for all available energy and was within ± 2 mm. Dosimetric leaf gap value for the multi-leaf collimator was measured with 0.125 cc ionization chamber and values are −0.853 mm, −1.106 mm, −1.097 mm, −0.765 mm, and −1.005 mm for energies 6 MV, 10 MV, 15 MV, 6 flattening filter free (FFF), and 10 FFF, respectively. Conclusions: All electrical, mechanical, dosimetric, and safety measurement were found to be within permissible limits. Before clinical use, the beam data are crosschecked with point dosimetry, portal dosimetry, and MapCHECK two-dimensional detector array and results are within tolerance.

Predicted Inferior Outcomes for Lung SBRT With Treatment Planning Systems That Fail Independent Phantom-Based Audits

More than 15% of radiotherapy clinics fail external audits with anthropomorphic phantoms conducted by Imaging and Radiation Oncology Core-Houston (IROC-H) while passing other industry-standard quality assurance (QA) tests. We seek to evaluate the predicted impact of such failed plans on outcomes for patients treated with stereotactic body radiation therapy (SBRT) for lung tumors. We conducted a retrospective study of 55 patients treated with SBRT for lung tumors with prescription BED10 ≥100Gy using a treatment planning system (TPS) that passed IROC-H phantom audits. Sample linac beam models with introduced errors were commissioned by varying the multi-leaf collimator leaf tip offset parameter (i.e., 'dosimetric leaf gap') over the range +/-1.0 mm relative to the validated model. These models mimic TPS that pass internal QA measures but fail IROC-H tests. Patient plans were recalculated on sample beam models. Predicted tumor control probability (TCP) and normal tissue complication probability (NTCP) were calculated based on published dose-response models. A leaf tip offset value of -1.0 mm decreased the fraction of plans receiving a PTV BED10 ≥100 Gy from 95% to 27%. This translated to a significant decrease in 2-yr TCP of 4.8% (95% CI: 2.0-5.5%) with a decrease in TCP up to 21%. Conversely, leaf tip offset of +1.0 mm resulted in 36% of patients exceeding previously met OAR constraints, including two instances of spinal cord and brachial plexus overdoses and a small increase in chest wall NTCP by 0.7%, (95% CI 0.5%-0.8%). Simulated treatment plans with modest MLC leaf offsets result in lung SBRT plans that significantly under-dose tumor or exceed OAR constraints. These dosimetric endpoints translate to significant detriments in TCP. These simulated plans mimic planning systems that pass internal QA measures but fail independent phantom-based tests, underscoring the need for enhanced quality assurance including external audits of TPS.

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

To investigate the use of statistical process control (SPC) for quality assurance of an integrated web-based autoplanning tool, Radiation Planning Assistant (RPA). 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. 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±0.019cm and MLC-TF value of 0.020±0.001 for Acuros and a DLG value of 0.135±0.031cm and MLC-TF value of 0.015±0.001 for AAA. 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.

Monte Carlo-based independent dose verification of radiosurgery HyperArc plans

PurposeTo investigate the feasibility of using the free PRIMO Monte Carlo software for independent dose check of cranial SRS plans designed with the Varian HyperArc (HA) technique. Materials and methodsIn this study, the PRIMO Monte Carlo software v. 0.3.64.1800 was used with the phase-space files (v. 2, Feb. 27, 2013) provided by Varian for 6 MV flattening-filter-free (FFF) photon beams from a Varian TrueBeam linear accelerator (linac), equipped with a Millennium 120 multileaf collimator (MLC). This configuration was validated by comparing the percentage depth doses (PDDs), lateral profiles and relative output factors (OFs) simulated in a water phantom against measurements for field sizes from 1 × 1 to 40 × 40 cm2. The agreement between simulated and experimental relative dose curves was evaluated using a global (G) gamma index analysis. In addition, the accuracy of PRIMO to model the MLC was investigated (dosimetric leaf gap, tongue and groove, leaf transmission and interleaf leakage).Thirty-five HA SRS plans computed in the Eclipse treatment planning system (TPS) were simulated in PRIMO. The Acuros XB algorithm v. 16.10 (dose to medium) was used in Eclipse. Sixty targets with diameters ranging from 6 to 33 mm were included. Agreement between the dose distributions given by Eclipse and PRIMO was evaluated in terms of 3D global gamma passing rates (GPRs) for the 2 %/2 mm criteria. ResultsAverage GPR greater than 95 % with the 2 %(G)/1 mm criteria were obtained over the PDD and profiles of each field size. Differences between PRIMO calculated and measured OFs were within 0.5 % in all fields, except for the 1 × 1 cm2 with a discrepancy of 1.5 %. Regarding the MLC modeling in PRIMO, an agreement within 3 % was achieved between calculated and experimental doses. Excellent agreement between PRIMO and Eclipse was found for the 35 HA plans. The 3D global GPRs (2 %/2 mm) for the targets and external patient contour were 99.6 % ± 1.1 % and 99.8 % ± 0.5 %, respectively. ConclusionsAccording to the results described in this study, the PRIMO Monte Carlo software, in conjunction with the 6X FFF Varian phase-space files, can be used as secondary dose calculation software to check stereotactic radiosurgery plans from Eclipse using the HyperArc technique.

Investigation on the impact of the leaf trailing effect using the Halcyon integrated platform system.

The double-stacked design of the Halcyon multileaf collimator (MLC) presents new challenges for treatment planning systems (TPSs). The leaf trailing effect has recently been described as the result of the interplay between the fluence transmitted through the leaf tip ends of each MLC layer. This effect makes the dosimetric leaf gap (DLG) dependent on the distance between the leaves of different layers (trailing distance) and is not adequately modeled by the Eclipse TPS. The purpose of our study was to investigate and report the dose discrepancies produced by these limitations in clinical plans and to explore how these discrepancies can be mitigated and avoided. The integrated platform with the Halcyon v2 system, Eclipse and Aria v15.6, was used. The dose discrepancies were obtained with electronic portal imaging device (EPID) images and the portal dosimetry software and validated using radiochromic film dosimetry. The results for the AIDA commissioning test and for nine selected clinical beams with the sliding window intensity modulated radiotherapy (dIMRT) technique were thoroughly analyzed and presented. First, the digital imaging and communications in medicine radiotherapy (DICOM RT) plans were exported and the fluences were computed using different leaf tip models, and then were compared. Second, the detailed characteristics of the corresponding leaf sequences were investigated. Finally, modified DICOM RT plans were created in which the noncollimating (backup) leaves were retracted 2mm to increase the leaf trailing distance, the modified plans were imported back into the TPS and the measurements were repeated. Dedicated in-house tools were developed in Python to carry out allanalyses. Dose discrepancies greater than 10% and regions of gamma failure were found in both the AIDA test and clinical beams using static-gantry dIMRT. Fluence analysis highlighted that the discrepancies were due to limitations in the MLC model implemented in the TPS. Analysis of leaf sequences indicated that regions of failure were associated with very low leaf speeds and virtually motionless leaves within the beam aperture. Some of these discrepancies were mitigated by increasing the trailing distance of the noncollimating leaves without affecting the beam aperture, but this strategy was not possible in regions where the leaves from both layers actively defined the beamaperture. Current limitations of the MLC model in Eclipse produced discrepancies between calculated and delivered doses in clinical beams that caused plan-specific quality assurance failures and interruptions in the clinical workflow. Careful evaluation of the clinical plans produced by Eclipse for the Halcyon is recommended, especially for static gantry dIMRT treatments. Some characteristics of leaf sequences are problematic and should be avoided in clinical plans and, in general, a better leaf tip model is needed. This is particularly important in adaptive radiotherapy treatments, where the accuracy and reliability of TPS dose calculations are of the utmostimportance.

Automated conversion of Millennium-120 VMAT plans to HDMLC geometry: Software development and treatment of first patients.

PurposeTo provide plan backup resiliency for patients treated on a solitary high definition multileaf collimator (HDMLC) linac by developing a fully integrated Eclipse script, which converts patient plans initially optimized on Millennium‐120 (M120) MLC to dosimetrically equivalent leaf motions for delivery on HDMLC. In the event of HDMLC machine downtime, affected patients can be transferred to Millennium‐120 units, and their backup plan delivered without delay.MethodsWrite‐enabled Eclipse scripting is leveraged to generate HDMLC treatment fields with control points parameterized to mimic apertures of an existing Millennium‐120 VMAT plan. Non‐parity between intermediate control point gantry angles of script generated arcs relative to VMAT is reconciled through an interpolation subroutine to correct for the apertures and monitor units that would have existed at intermediate angles. Differences in dosimetric leaf gap are corrected by displacing the subset of leaves undergoing dynamic motion. A nominal change to plan normalization corrects for remaining discrepancies between beam models.Results Over 220 non‐SABR VMAT patients were treated on a solitary HDMLC linac with plans converted using the developed script. All have undergone streamlined RO review and physics quality assurance (QA), where the converted plan replicates the original leaf patterns, representing a minor dosimetric perturbation. Analyzing a subset of converted plans delivered at four anatomical sites, on average 99.3% of points pass the 1%/1 mm gamma criterion. Dose‐volume histograms between the original and converted plans are in excellent agreement. ArcCheck measurements comparing delivery of the converted HDMLC plan to the calculated M120 dose distribution averaged a gamma pass rate of 99.4% (95.2%) at a 3%/3 mm (2%/2 mm) criterion. The conversion process takes 30 s to run, avoids errors in exporting/re‐importing, and generates leaf motions deliverable within machine limits.ConclusionThe methodology developed for automated plan conversion helped maximize the utilization of a solitary HDMLC linac, while preserving backup interoperability with minimal overhead.

Integration of an Independent Monitor Unit Check for High-Magnetic-Field MR-Guided Radiation Therapy System.

PurposeCommercial independent monitor unit (IMU) check systems for high-magnetic-field MR-guided radiation therapy (RT) systems are lacking. We investigated the feasibility of adopting an existing treatment planning system (TPS) as an IMU check for online adaptive radiotherapy using 1.5-Tesla MR-Linac.MethodsThe 7-MV flattening filter free (FFF) beam and multi-leaf collimator (MLC) models of a 1.5-T Elekta Unity MR-Linac within Monte Carlo-based Monaco TPS were used to generate an optimized beam model in Eclipse TPS. The MLC dosimetric leaf gap of the beam in Eclipse was determined by matching the dose distribution of Eclipse-generated intensity-modulated radiation therapy (IMRT) plans using the Analytical Anisotropic Algorithm (AAA) algorithm to Monaco plans. The plans were automatically adjusted for different source-to-axis distances (SADs) between the two systems. For IMU check, the treatment plans developed in Monaco were transferred to Eclipse to recalculate the dose using AAA. A plug-in within Eclipse was created to perform a 2D gamma analysis of the AAA and Monte Carlo dose distribution on a beam’s eye view parallel plane. Monaco dose distribution was shifted laterally by 2 mm during gamma analysis to account for the impact of magnetic field on electron trajectories. Eclipse doses for posterior beams were corrected for both the Unity couch and the posterior MR coil attenuation. Thirteen patients, each with 4–5 fractions for a variety of tumor sites (pancreas, rectum, and prostate), were tested.ResultsAfter thorough commissioning, the method was implemented as part of the standard clinical workflow. A total of 62 online plans, each with approximately 15 beams, were evaluated. The average per-beam gamma (3%/3 mm) pass rate for plans was 97.9% (range, 95.9% to 98.8%). The average pass rate per beam for all 932 beams used in these plans was 97.9% ± 1.9%, with the lowest per-beam gamma pass rate at 88.4%. The time for the process was within 3.2 ± 0.9 min.ConclusionThe use of a second planning system provides an efficient way to perform IMU checks with clinically acceptable accuracy for online adaptive plans on Unity MR-Linac. This is essential for meeting the safety requirements for second checks as outlined in American Association of Physicists in Medicine Task Group (AAPM TG) reports 114 and 219.

A novel methodology for the optimization of transmission and dosimetric leaf gap parameters.

PurposeOptimization of dosimetric leaf gap (DLG) and transmission is commonly performed through a manual trial and error process, which can lead to sub‐optimal values. The purpose of this work is to create an alternative automated optimization process that provides the optimal DLG and transmission pair for use in a clinical setting.MethodsUtilizing the treatment planning system application programming interface, a phase space of clinically viable DLG and transmission pairs was generated. The phase space contained 51,051 dose planes for DLGs between 0.0 and 2.5 mm and transmission values between 0.01% and 2.5%. Thirteen plans were measured for multiple multileaf collimator types and nominal beam energies. The optimization minimized the mean γ‐index and maximized the γ‐index pass rate. The optimized values were validated using five plans excluded from the optimization.ResultsOf the nominal beam energies and multileaf collimator system (MLC)‐type combinations tested, 6/7 showed an increase in γ‐index pass rate and a decrease in mean γ‐index signifying better agreement between measurement and calculation. When comparing the optimized DLG and transmission values to the clinically implemented values identified via an iterative method, 5/7 energy, and MLC type combinations showed no statistically significant changes. In addition, the optimized values were benchmarked against three Task Group 119 plans with published γ‐index pass rates, which had been held out of the optimization. For those plans, the optimized DLG and transmission values provided the same or better γ‐index pass rates.ConclusionWe presented a novel and viable automated alternative to current approaches of selecting the DLG and transmission parameters. This method will reduce the time required to determine the clinically acceptable DLG and transmission parameters and ensure optimality for the plans included in the optimization.

Investigation of Halcyon multi-leaf collimator model in Eclipse treatment planning system: A focus on the VMAT dose calculation with the Acuros XB algorithm.

PurposeThe dual‐layer multi‐leaf collimator (MLC) in Halcyon involves further complexities in the dose calculation process, because the leaf‐tip transmission varies according to the leaf trailing pattern. For the volumetric modulated arc therapy (VMAT) treatment, the prescribed dose for the target volume can be sensitive to the leaf‐tip transmission change. This report evaluates the dosimetric consequence due to the uncertainty of the dual‐layer MLC model in Eclipse through the dose verifications for clinical VMAT. Additionally, the Halcyon leaf‐tip model is empirically adjusted for the VMAT dose calculation with the Acuros XB.Materials and methodsFor this evaluation, an in‐house program that analyzes the leaf position in each layer was developed. Thirty‐two clinical VMAT plans were edited into three leaf sequences: dual layer (original), proximal single layer, or distal single layer. All leaf sequences were verified using Delta4 according to the dose difference (DD) and the global gamma index (GI). To improve the VMAT dose calculation accuracy, the dosimetric leaf gap (DLG) was adjusted to minimize the DD in single‐layer leaf sequences.ResultsThe mean of DD were −1.35%, −1.20%, and −1.34% in the dual‐layer, proximal single‐layer, and distal single‐layer leaf sequences, respectively. The changes in the mean of DD between leaf sequences were within 0.2%. However, the calculated doses differed from the measured doses by approximately 1% in all leaf sequences. The tuned DLG was increased by 0.8 mm from the original DLG in Eclipse. When the tuned DLG was used in the dose calculation, the mean of DD neared 0% and GI with a criterion of 2%/2 mm yielded a pass rate of more than 98%.ConclusionNo significant change was confirmed in the dose calculation accuracy between the leaf sequences. Therefore, it is suggested that the dosimetric consequence due to the leaf trailing was negligibly small in clinical VMAT plans. The DLG tuning for Halcyon can be useful for reducing the dose calculation uncertainties in Eclipse VMAT and required in the commissioning for Acuros XB.

Evaluating Mobius3D Dose Calculation Accuracy for Small-Field Flattening- Filter-Free Photon Beams.

Purpose: We aimed to investigate the dose calculation accuracy of Mobius3D for small-field flattening-filter-free x-rays, mainly utilized for stereotactic body radiation therapy (SBRT). The accuracy of beam modeling and multileaf collimator (MLC) modeling in Mobius3D, significantly affecting the dose calculation is investigated. Methods: The commissioning procedures of Mobius3D were performed for unflattened 6 MV and 10 MV x-ray beams of the linear accelerator, including beam model adjustment and dosimetric leaf gap (DLG) optimization. An experimental study with artificial plans was conducted to evaluate the accuracy of small-field modeling. The dose calculation accuracy of Mobius3D was also evaluated for retrospective SBRT plans with multiple targets. Results: Both studies evaluated the dose calculation accuracy through comparisons with the measured data. Relatively large differences were observed for off-axis distances over 5 cm and for small fields less than 1 cm field size. For the study with artificial plans, the maximum absolute error of 9.96% for unflattened 6 MV and 9.07% for unflattened 10 MV was observed when the field size was 1 cm. For the study with patient plans, the mean gamma passing rate with 3%/3 mm gamma criterion was 63.6% for unflattened 6 MV and 82.6% for unflattened 10 MV. The maximum of the average dose difference was -19.9% for unflattened 6MV and -10.1% for unflattened 10MV. Conclusions: The dose calculation accuracy uncertainties of Mobius3D for small-field flattening-filter-free photon beams were observed. The study results indicated that the beam and MLC modeling of Mobius3D must be improved for use in SBRT pretreatment QA in clinical practice.

A strategy to determine off-axis dosimetric leaf gap using OSLD and EPID.

BackgroundThe aim of the study was to investigate the dosimetric feasibility of using optically stimulated luminescence dosimeters (OSLD) and an electronic portal imaging device (EPID) for central axis (CA X) and off-axis (OAX) dosimetric leaf gap (DLG) measurement.Materials and methodsThe Clinac 2100C/D linear accelerator equipped with Millennium-120 multileaf collimator (MLC) and EPID was utilized for this study. The DLG values at CA X and ± 1 cm OAX (1 cm superior and inferior to the CA X position, respectively along the plane perpendicular to MLC motion) were measured using OSLD (DLGOSLD) and validated using ionization chamber dosimetry (DLGICD). The two-dimensional DLG map (2D DLGEPID) was derived from the portal images of the DLG plan using a custom-developed software application that incorporated sliding aperture-specific correction factors.ResultsDLGOSLD and DLGICD, though measured with diverse setup in different media, showed similar variation both at CA X and ± 1 cm OAX positions. The corresponding DLGEPID values derived using aperture specific corrections were found to be in agreement with DLGOSLD and DLGICD. The 2D DLGEPID map provides insight into the varying patterns of the DLG with respect to each leaf pair at any position across the exposed field.ConclusionsCommensurate results of DLGOSLD with DLGICD values have proven the efficacy of OSLD as an appropriate dosimeter for DLG measurement. The 2D DLGEP ID map opens a potential pathway to accurately model the rounded-leaf end transmission with discrete leaf-specific DLG values for commissioning of a modern treatment planning system.

Photon beam modeling variations predict errors in IMRT dosimetry audits

Background & purposeTo evaluate treatment planning system (TPS) beam modeling parameters as contributing factors to IMRT audit performance. Materials & methodsWe retrospectively analyzed IROC Houston phantom audit performance and concurrent beam modeling survey responses from 337 irradiations performed between August 2017 and November 2019. Irradiation results were grouped based on the reporting of typical or atypical beam modeling parameter survey responses (<10th or >90th percentile values), and compared for passing versus failing (>7% error) or “poor” (>5% error) irradiation status. Additionally, we assessed the impact on the planned dose distribution from variations in modeling parameter value. Finally, we estimated the overall impact of beam modeling parameter variance on dose calculations, based on reported community variations. ResultsUse of atypical modeling parameters were more frequently seen with failing phantom audit results (p = 0.01). Most pronounced was for Eclipse AAA users, where phantom irradiations with atypical values of dosimetric leaf gap (DLG) showed a greater incidence of both poor-performing (p = 0.048) and failing phantom audits (p = 0.014); and in general, DLG value was correlated with dose calculation accuracy (r = 0.397, p < 0.001). Manipulating TPS parameters induced systematic changes in planned dose distributions which were consistent with prior observations of how failures manifest. Dose change estimations based on these dose calculations agreed well with true dosimetric errors identified. ConclusionAtypical TPS beam modeling parameters are associated with failing phantom audits. This is identified as an important factor contributing to the observed failing phantom results, and highlights the need for accurate beam modeling.