This paper presents an alternative method to tune Monte Carlo electron beam parameters to match measured data using a minimal set of variables in order to reduce the model setup time prior to clinical implementation of the model. Monte Carlo calculations provide the possibility of a powerful treatment planning verification technique. The nonstandardized and nonautomated process of tuning the required accelerator model is one of the reasons for delays in the clinical implementation of Monte Carlo techniques. This work aims to establish and verify an alternative tuning method that can be carried out in a minimal amount of time, allowing it to be easily implemented in a clinical setting by personnel with minimal experience with Monte Carlo methods. This tuned model can then be incorporated into the MMCTP system to allow the system to be used as a second dose calculation check for IMRT plans. The technique proposed was used to establish the primary electron beam parameters for accelerator models for the Varian Clinac 2100 6 MV photon beam using the BEAMnrc Monte Carlo system. The method is intended to provide a clear, direct, and efficient process for tuning an accelerator model using readily available clinical quality assurance data. The tuning provides a refined model, which agrees with measured dose profile curves within 1.5% outside the penumbra or 3 mm in the penumbra, for square fields with sides of 3 cm up to 30 cm. These models can then be employed as the basis for Monte Carlo recalculations of dose distributions, using the MMCTP system, for clinical treatment plans, providing an invaluable assessment tool. This was tested on six IMRT plans and compared to the measurements performed for the pretreatment QA process. These Monte Carlo values for the average dose to the chamber volume agreed with measurements to within 0.6%.PACS number: 87.55.km
IMRT QA requires, among other tests, a time‐consuming process of measuring the absorbed dose, at least to a point, in a high‐dose, low‐dose‐gradient region. Some clinics use a technique of measuring this dose with all beams delivered at a single gantry angle (collapsed delivery), as opposed to the beams delivered at the planned gantry angle (rotated delivery). We examined, established, and optimized Monte Carlo simulations of the dosimetry for IMRT verification of treatment plans for these two different delivery modes (collapsed versus rotated). The results of the simulations were compared to the treatment planning system dose calculations for the two delivery modes, as well as to measurements taken. This was done in order to investigate the validity of the use of a collapsed delivery technique for IMRT QA. The BEAMnrc, DOSXYZnrc, and egs_chamber codes were utilized for the Monte Carlo simulations along with the MMCTP system. A number of different plan complexity metrics were also used in the analysis of the dose distributions in a bid to qualify why verification in a collapsed delivery may or may not be optimal for IMRT QA. Following the Alfonso et al. (1) formalism, the kQclin,Qfclin,fref correction factor was calculated to correct the deviation of small fields from the reference conditions used for beam calibration. We report on the results obtained for a cohort of 20 patients. The plan complexity was investigated for each plan using the complexity metrics of homogeneity index, conformity index, modulation complexity score, and the fraction of beams from a particular plan that intersect the chamber when performing the QA. Rotated QA gives more consistent results than the collapsed QA technique. The kQclin,Qfclin,fref factor deviates less from 1 for rotated QA than for collapsed QA. If the homogeneity index is less than 0.05 then the kQclin,Qfclin,fref factor does not deviate from unity by more than 1%. A value this low for the homogeneity index can only be obtained with the rotated QA technique.PACS number: 87.55.Qr
Purpose: To apply the new dosimetry formalism [Med. Phys. 35, 5179 (2008)] to clinical IMRT quality assurance (QA). Methods: 20 different linear accelerator (Varian Clinac 21 EX)‐based clinical IMRT fields were transferred to the CT images of a 30×30×17 cm3 Solid Water phantom to create IMRT QA fields. The phantom position was adjusted for each QA field to place the detector or chamber at the lowest dose gradient region in a virtual PTV. The reference doses in the IMRT QA and 10×10 cm2 fields were measured using a PTW micro liquid ion chamber (microLion). Based on the new dosimetry formalism, the clinical correction factor of each IMRT QA field was measured for a calibrated Exradin A12 Farmer‐type chamber in a fully‐rotated delivery and a delivery at a single gantry angle, a collapsed delivery. For each QA field, the measured dose with the correction factor was compared with a calculated dose using Analytical Anisotropic Algorithm (AAA) or Monte Carlo (MC) methods. Results: The clinical correction factor deviated from unity by up to 2.4% and 3.7% in the fully‐rotated and collapsed deliveries, respectively, depending on the dose homogeneity at the Exradin A12 collecting volume. In the fully‐rotated delivery, the measured dose with the correction factor is different from the calculated dose to within 5% and 3% for the AAA and MC, respectively. In the collapsed delivery, the discrepancy between the measured and AAA‐calculated doses was to within 8%, while it was improved to within 3.5% compared with the MC‐calculated dose. When applying the clinical correction factor, the decrease of the measured and calculated dose discrepancy is more significant for an IMRT QA field having higher dose heterogeneity. Conclusions: This work proves that the suggested dosimetry technique is effective to improve the dosimetric consistency of clinical IMRT QA.
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