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Purpose: To assess the implementation, accuracy, and validity of the dosimetric leaf gap correction (DLGC) in Mobius3D VMAT plan calculations. Methods: The optimal Mobius3D DLGC was determined for both a TrueBeam with a Millennium multi-leaf collimator and a TrueBeamSTx with a high-definition multileaf collimator. By analyzing a broad series of seven VMAT plans and comparing the calculated to the measured dose delivered to a cylindrical phantom, optimal DLGC values were determined by minimizing the dose difference for both the collection of all plans, as well as for each plan individually. The effects of plan removal from the optimization of the collective DLGC value, as well as plan-specific DLGC values, were explored to determine the impact of plan suite design on the final DLGC determination. Results: Optimal collective DLGC values across all energies were between −0.71 and 0.89 mm for the TrueBeam, and between 0.35 and 1.85 mm for the True-BeamSTx. The dose differences ranged between −6.1% and 2.6% across all plans when the optimal collective DLGC values were used. On a per-plan basis, the planspecific optimal DLGC values ranged from −4.36 to 2.35 mm for the TrueBeam, and between −1.83 and 2.62 mm for the TrueBeamSTx. Comparing the plan-specific optimal DLGC to the average absolute leaf position from the central axis for each plan, a negative correlation was observed. Conclusions: The optimal DLGC determination depends on the plans investigated, making it essential for users to utilize a suite of test plans that encompasses the full range of expected clinical plans when determining the optimal DLGC value. Validation of the secondary dose calculation should always be based on measurements, and not a comparison with the primary TPS. Varying disagreement with measurements across plans for a single DLGC value indicates potential limitations in the Mobius3D MLC model.
Purpose: To assess the implementation, accuracy, and validity of the dosimetric leaf gap correction (DLGC) in Mobius3D VMAT plan calculations. Methods: The optimal Mobius3D DLGC was determined for both a TrueBeam with a Millennium multi-leaf collimator and a TrueBeamSTx with a high-definition multileaf collimator. By analyzing a broad series of seven VMAT plans and comparing the calculated to the measured dose delivered to a cylindrical phantom, optimal DLGC values were determined by minimizing the dose difference for both the collection of all plans, as well as for each plan individually. The effects of plan removal from the optimization of the collective DLGC value, as well as plan-specific DLGC values, were explored to determine the impact of plan suite design on the final DLGC determination. Results: Optimal collective DLGC values across all energies were between −0.71 and 0.89 mm for the TrueBeam, and between 0.35 and 1.85 mm for the True-BeamSTx. The dose differences ranged between −6.1% and 2.6% across all plans when the optimal collective DLGC values were used. On a per-plan basis, the planspecific optimal DLGC values ranged from −4.36 to 2.35 mm for the TrueBeam, and between −1.83 and 2.62 mm for the TrueBeamSTx. Comparing the plan-specific optimal DLGC to the average absolute leaf position from the central axis for each plan, a negative correlation was observed. Conclusions: The optimal DLGC determination depends on the plans investigated, making it essential for users to utilize a suite of test plans that encompasses the full range of expected clinical plans when determining the optimal DLGC value. Validation of the secondary dose calculation should always be based on measurements, and not a comparison with the primary TPS. Varying disagreement with measurements across plans for a single DLGC value indicates potential limitations in the Mobius3D MLC model.
Purpose:The purpose of this study was to investigate the matching error that occurs when the Mobius3D fingerprinting system is applied in conjunction with an Elekta linear accelerator (LINAC) and to offer an acceptable and alternative method for circumventing this problem. Material and methods: To avoid the multileaf collimator (MLC) conflicting error in the Mobius3D fingerprinting system, we developed an in-house program to move the MLC in the Digital Imaging and Communications in Medicine (DICOM) radiotherapy (RT)-Plan to pertinent positions, considering the relationship between log data and planned data. The re-delivered log files were calculated in the Mobius3D system, and the results were compared with those of corrected data (i.e., we analyzed a pair of re-collected log data and the previous DICOM RT-Plan data). The results were then evaluated by comparing several items, such as point dose errors, gamma index (GI) passing rates, and MLC root-mean-square (RMS) values. Results: For the point dose error, the maximum difference found was below 2.0%. In the case of GI analysis of all plans, the maximum difference in the passing rates was below 1.4%. The statistical results obtained using a paired Student's t-test showed that there were no significant differences within the uncertainty. In the case of the RMS test, the maximum difference found was approximately 0.08 mm. Conclusions: Our results showed that all the mismatched log files were sufficiently acceptable within the uncertainty. We conclude that the matching error obtained when applying Mobius3D to an Elekta LINAC may be addressed using a simple modification of the fingerprinting system, and we expect that our study findings will help vendors resolve this issue in the near future.
Purpose Well‐designed routine multileaf collimator (MLC) quality assurance (QA) is important to assure external‐beam radiation treatment delivery accuracy. This study evaluates the clinical necessity of a comprehensive weekly (C‐Weekly) MLC QA program compared to the American Association of Physics in Medicinerecommended weekly picket fence test (PF‐Weekly), based on our seven‐year experience with weekly MLC QA. Methods The C‐Weekly MLC QA program used in this study includes 5 tests to analyze: (1) absolute MLC leaf position; (2) interdigitation MLC leaf position; (3) picket fence MLC leaf positions at static gantry angle; (4) minimum leaf‐gap setting; and (5) volumetric‐modulated arc therapy delivery. A total of 20,226 QA images from 16,855 tests (3,371 tests × 5) for 11 linacs at 5 photon clinical sites from May 2014 to June 2021 were analyzed. Failure mode and effects analysis was performed with 5 failure modes related to the 5 tests. For each failure mode, a risk probability number (RPN) was calculated for a C‐Weekly and a PF‐Weekly MLC QA program. The probability of occurrence was evaluated from statistical analyses of the C‐Weekly MLC QA. Results The total number of failures for these 16,855 tests was 143 (0.9%): 39 (27.3%) for absolute MLC leaf position, 13 (9.1%) for interdigitation position, 9 (6.3%) for static gantry picket fence, 2 (1.4%) for minimum leaf‐gap setting, and 80 (55.9%) for VMAT delivery. RPN scores for PF‐Weekly MLC QA ranged from 60 to 192 and from 48 to 96 for C‐Weekly MLC QA. Conclusion RPNs for the 5 failure modes of MLC QA tests were quantitatively determined and analyzed. A comprehensive weekly MLC QA is imperative to lower the RPNs of the 5 failure modes to the desired level (<125); those from the PF‐Weekly MLC QA program were found to be higher (>125). This supports the clinical necessity for comprehensive weekly MLC QA.
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