Purpose With the advent of volumetric modulated arc therapy (VMAT) and intensity‐modulated radiation therapy (IMRT) treatment techniques, the requirement for more elaborate approaches in reviewing linac components’ integrity has become even more stringent. A possible solution to this challenge is to employ the usage of log files generated during treatment. The log files generated by the new generation of Elekta linacs record events at a higher frequency (25 Hz) than their predecessors, which allows for retrospective analysis and identification of subtle changes and provides another means of quality assurance. The ability to track machine components based on log files for each treatment can allow for constant monitoring of fraction consistency in addition to machine reliability. Using Elekta Agility log files, a set of tests were developed to evaluate the reliability and robustness of the multileaf collimators (MLCs). Methods To evaluate Elekta log file utilization for linac MLC QA effectiveness, five MLC test patterns were constructed to review the effects of leaf velocity and acceleration on positional accuracy, including gravitational effects for the Elekta MLC system. Each test was run five times in a particular setting to obtain reproducibility data and statistical averages. This study was performed on two identical Versa HD machines, each delivering a full set of test plans with all possible variations. Plans were delivered using Elekta's iCOMcat software and recorded log files were extracted. Log files were reformatted for readability and automatically analyzed in Matlab®. Results The Elekta Agility MLC system was shown to be capable of obtaining speeds within the range of 5–35 mm/s. MLC step and shoot tests have demonstrated the MLC system's capability of having positional repeatability, averaging 0.03‐ and 0.08‐mm offsets with and without gravitational effects, respectively. The IMRT‐specific tests have shown that gravitational effects are negligible with all positional tests averaging 0.5‐mm offsets. The largest speed root‐mean‐square error (RMSE) for the MLC system was found at the maximum speed of 35 mm/s with an average error of 0.8 mm. For slower speeds, the value was found to be much lower. Conclusion Utilizing log files has demonstrated the feasibility for higher precision of MLC motions to be reviewed, based on the performance tests that were instituted. Log files provide insight on the effects of friction, acceleration, and gravity, with MU's delivered that previously could not be reviewed in such detail. Based on our results, log file‐based QA has enhanced our ability to review performance, functionality, and perform QA on Elekta's MLC system.
Introduction: Numerous studies have proven the Monte Carlo method to be an accurate means of dose calculation. Although there are several commercial Monte Carlo treatment planning systems (TPSs), some clinics may not have access to these resources.We present a method for routine,independent patient dose calculations from treatment plans generated in a commercial TPS with our own Monte Carlo model using free, open-source software. Materials and methods: A model of the Elekta Versa HD linear accelerator was developed using the EGSnrc codes. A MATLAB script was created to take clinical patient plans and convert the DICOM RTP files into a format usable by EGSnrc. Ten patients' treatment plans were exported from the Monaco TPS to be recalculated using EGSnrc. Treatment simulations were done in BEAMnrc, and doses were calculated using Source 21 in DOSXYZnrc. Results were compared to patient plans calculated in the Monaco TPS and evaluated in Verisoft with a gamma criterion of 3%/2 mm. Results: Our Monte Carlo model was validated within 1%/1-mm accuracy of measured percent depth doses and profiles. Gamma passing rates ranged from 82.1% to 99.8%, with 7 out of 10 plans having a gamma pass rate over 95%. Lung and prostate patients showed the best agreement with doses calculated in Monaco. All statistical uncertainties in DOSXYZnrc were less than 3.0%. Conclusion: A Monte Carlo model for routine patient dose calculation was successfully developed and tested. This model allows users to directly recalculate DICOM RP files containing patients' plans that have been exported from a commercial TPS.
Objective: The aim of this work is an AI based approach to reduce the volume effect of ionization chambers used to measure high energy photon beams in radiotherapy. In particular for profile measurements, the air-filled volume leads to an inaccurate measurement of the penumbra. Approach: The AI-based approach presented in this study was trained with synthetic data intended to cover a wide range of realistic linear accelerator data. The synthetic data was created by randomly generating profiles and convolving them with the lateral response function of a Semiflex 3D ionization chamber. The neuronal network was implemented using the open source tensorflow.keras machine learning framework and a U-Net architecture. The approach was validated on three accelerator types (Varian TrueBeam, Elekta VersaHD, Siemens Artiste) at FF and FFF energies between 6 MV and 18 MV at three measurement depths. For each validation, a Semiflex 3D measurement was compared against a microDiamond measurement, and the AI processed Semiflex 3D measurement was compared against the microDiamond measurement. Main results: The AI approach was validated with dataset containing 306 profiles measured with Semiflex 3D ionization chamber and microDiamond. In 90 % of the cases, the AI processed Semiflex 3D dataset agrees with the microDiamond dataset within 0.5 mm / 2% gamma criterion. 77 % of the AI processed Semiflex 3D measurements show a penumbra difference to the microDiamond of less than 0.5 mm, 99 % of less than 1 mm. Significance: This AI approach is the first in the field of dosimetry which uses synthetic training data. Thus, the approach is able to cover a wide range of accelerators and the whole specified field size range of the ionization chamber. The application of the AI approach offers an quality improvement and time saving for measurements in the water phantom, in particular for large field sizes.
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