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Title: SU-D-201-04: Evaluation of Elekta Agility MLC Performance Using Statistical Process Control

Abstract

Purpose: to evaluate the performance and stability of the Elekta Agility MLC model using an automated quality control (QC) test in combination with statistical process control tools. Methods: Leaf positions were collected daily for 11 Elekta units over 5–19 months using the automated QC test, which analyzes 23 MV images to determine the location of MLC leaves relative to the radiation isocenter. The leaf positions are measured at 5 nominal positions, and images are acquired at collimator 0° and 180° to capture all MLC leaves in the field-of-view. Leaf positioning accuracy was assessed using individual and moving range control charts. Control limits were recomputed following MLC recalibration (occurred 1–2 times for 4 units). Specification levels of ±0.5, ±1 and ±1.5mm were tested. The mean and range of duration between out-of-control and out-of-specification events were determined. Results: Leaf position varied little over time, as confirmed by very tight individual control limits (mean ±0.19mm, range 0.09–0.44). Mean leaf position error was −0.03mm (range −0.89–0.83). Due to sporadic out-of-control events, the mean in-control duration was 3.3 days (range 1–23). Data stayed within ±1mm specification for 205 days on average (range 3–372) and within ±1.5mm for the entire date range. Measurements stayed within ±0.5mmmore » for 1 day on average (range 0–17); however, our MLC leaves were not calibrated to this level of accuracy. Conclusion: The Elekta Agility MLC model was found to perform with high stability, as evidenced by the tight control limits. The in-specification durations support the current recommendation of monthly MLC QC tests with a ±1mm tolerance. Future work is on-going to determine if Agility performance can be optimized further using high-frequency QC test results to drive recalibration frequency. Factors that can affect leaf positioning accuracy, including beam spot motion, leaf gain calibration, drifting leaves, and image artifacts, are under investigation.« less

Authors:
; ;  [1]
  1. Princess Margaret Cancer Centre and University of Toronto, Toronto, ON (Canada)
Publication Date:
OSTI Identifier:
22624368
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 61 RADIATION PROTECTION AND DOSIMETRY; ACCURACY; BEAM OPTICS; CALIBRATION; COLLIMATORS; EVALUATION; IMAGES; PERFORMANCE; PROCESS CONTROL; QUALITY CONTROL

Citation Formats

Meyers, SM, Balderson, MJ, and Letourneau, D. SU-D-201-04: Evaluation of Elekta Agility MLC Performance Using Statistical Process Control. United States: N. p., 2016. Web. doi:10.1118/1.4955616.
Meyers, SM, Balderson, MJ, & Letourneau, D. SU-D-201-04: Evaluation of Elekta Agility MLC Performance Using Statistical Process Control. United States. doi:10.1118/1.4955616.
Meyers, SM, Balderson, MJ, and Letourneau, D. 2016. "SU-D-201-04: Evaluation of Elekta Agility MLC Performance Using Statistical Process Control". United States. doi:10.1118/1.4955616.
@article{osti_22624368,
title = {SU-D-201-04: Evaluation of Elekta Agility MLC Performance Using Statistical Process Control},
author = {Meyers, SM and Balderson, MJ and Letourneau, D},
abstractNote = {Purpose: to evaluate the performance and stability of the Elekta Agility MLC model using an automated quality control (QC) test in combination with statistical process control tools. Methods: Leaf positions were collected daily for 11 Elekta units over 5–19 months using the automated QC test, which analyzes 23 MV images to determine the location of MLC leaves relative to the radiation isocenter. The leaf positions are measured at 5 nominal positions, and images are acquired at collimator 0° and 180° to capture all MLC leaves in the field-of-view. Leaf positioning accuracy was assessed using individual and moving range control charts. Control limits were recomputed following MLC recalibration (occurred 1–2 times for 4 units). Specification levels of ±0.5, ±1 and ±1.5mm were tested. The mean and range of duration between out-of-control and out-of-specification events were determined. Results: Leaf position varied little over time, as confirmed by very tight individual control limits (mean ±0.19mm, range 0.09–0.44). Mean leaf position error was −0.03mm (range −0.89–0.83). Due to sporadic out-of-control events, the mean in-control duration was 3.3 days (range 1–23). Data stayed within ±1mm specification for 205 days on average (range 3–372) and within ±1.5mm for the entire date range. Measurements stayed within ±0.5mm for 1 day on average (range 0–17); however, our MLC leaves were not calibrated to this level of accuracy. Conclusion: The Elekta Agility MLC model was found to perform with high stability, as evidenced by the tight control limits. The in-specification durations support the current recommendation of monthly MLC QC tests with a ±1mm tolerance. Future work is on-going to determine if Agility performance can be optimized further using high-frequency QC test results to drive recalibration frequency. Factors that can affect leaf positioning accuracy, including beam spot motion, leaf gain calibration, drifting leaves, and image artifacts, are under investigation.},
doi = {10.1118/1.4955616},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = 2016,
month = 6
}
  • Purpose: To evaluate the performance of the Elekta Agility multileaf collimator (MLC) for dynamic real-time tumor tracking. Methods: The authors have developed a new control software which interfaces to the Agility MLC to dynamically program the movement of individual leaves, the dynamic leaf guides (DLGs), and the Y collimators (“jaws”) based on the actual target trajectory. A motion platform was used to perform dynamic tracking experiments with sinusoidal trajectories. The actual target positions reported by the motion platform at 20, 30, or 40 Hz were used as shift vectors for the MLC in beams-eye-view. The system latency of the MLCmore » (i.e., the average latency comprising target device reporting latencies and MLC adjustment latency) and the geometric tracking accuracy were extracted from a sequence of MV portal images acquired during irradiation for the following treatment scenarios: leaf-only motion, jaw + leaf motion, and DLG + leaf motion. Results: The portal imager measurements indicated a clear dependence of the system latency on the target position reporting frequency. Deducting the effect of the target frequency, the leaf adjustment latency was measured to be 38 ± 3 ms for a maximum target speed v of 13 mm/s. The jaw + leaf adjustment latency was 53 ± 3 at a similar speed. The system latency at a target position frequency of 30 Hz was in the range of 56–61 ms for the leaves (v ≤ 31 mm/s), 71–78 ms for the jaw + leaf motion (v ≤ 25 mm/s), and 58–72 ms for the DLG + leaf motion (v ≤ 59 mm/s). The tracking accuracy showed a similar dependency on the target position frequency and the maximum target speed. For the leaves, the root-mean-squared error (RMSE) was between 0.6–1.5 mm depending on the maximum target speed. For the jaw + leaf (DLG + leaf) motion, the RMSE was between 0.7–1.5 mm (1.9–3.4 mm). Conclusions: The authors have measured the latency and geometric accuracy of the Agility MLC, facilitating its future use for clinical tracking applications.« less
  • Purpose: To report and investigate observed differences in electron beam profiles at various energies/applicators between Elekta MLCi2 and Agility treatment head on Elekta Infinity LINAC Methods: When we upgraded from MLCi2 to Agility on one of our Elekta Infinity LINAC's, electron beam PDDs and profiles were acquired for comparison purpose. All clinical electron energies (6/9/12/15/12/18 MeV) and electron applicators (6/10/14/20/25 square) were included in measurement. PDDs were acquired at 100 SSD in water (PTW MP3 water tank) with a plane-parallel ion chamber (PTW Roos). X and Y Profiles were acquired using IC Profiler (Sun Nuclear Corp.) at 1cm and maximummore » PDD depths (water equivalent). Results: All PDD curves match very well between MLCi2 and Agility treatment head. However, some significant differences on electron profiles were found. On Agility, even after increasing the default auto-tracking offset values for backup diaphragms in Y and MLC in X by 2.8 cm (the maximum allowed change is 3.0 cm), electron profiles still have rounder shoulders comparing to corresponding MLCi2 profiles. This difference is significantly more pronounced at larger applicators (20 and 25 square), for all electron energies. Conclusion: The significant design change between MLCi2 and Agility beam limiting device seems to affect exit electron beam profiles. In IEC1217 X direction, the main change on Agility is the removal of the original MLCi2 X backup diaphragms and replacing it with MLC leaves; In Y direction, the main change is the radius and materials on Y backup diaphragms.« less
  • Purpose: Historically, beam matching of similar Linear Accelerators has been accomplished by sending beam data to the manufacturer to match at their factory. The purpose of this work is to demonstrate that fine beam matching can be carried out on-site as part of the acceptance test, with similar or better results. Methods: Initial scans of a 10 × 10 Percent depth dose (PDD) and a 40 × 40 beam profile at the depth of Dmax, for 6MV and 10 MV were taken to compare with the standard beam data from the Versa. The energy was then adjusted and the beammore » steered to achieve agreement between the depth dose and the horns of the beam profile. This process was repeated until the best agreement between PDD and profiles was achieved. Upon completion, all other clinical data were measured to verify match. This included PDD, beam profiles, output factors and Wedge factors. For electron beams PDD’s were matched and the beam profiles verified for the final beam energy. Confirmatory PDD and beam profiles for clinical field sizes, as well as Output Factors were measured. Results: The average difference in PDD’s for 6MV and 10MV were within 0.4% for both wedged and open fields. Beam profile comparisons over the central 80% of the field, at multiple depths, show agreement of 0.8% or less for both wedged and open fields. Average output factor agreement over all field sizes was 0.4% for 6MV and 0.2 % for 10MV. Wedge factors agreement was less than 0.6% for both photon energies over all field sizes. Electron PDD agreed to 0.5mm. Cone ratios agreed to 1% or less. Conclusion: This work indicates that beam matching can be carried out on-site simply and quickly. The results of this beam matching can achieve similar or better results than factory matching.« less
  • Purpose: High-quality radiation therapy using highly conformal dose distributions and image-guided techniques requires optimum machine delivery performance. In this work, a monitoring system for multileaf collimator (MLC) performance, integrating semiautomated MLC quality control (QC) tests and statistical process control tools, was developed. The MLC performance monitoring system was used for almost a year on two commercially available MLC models. Control charts were used to establish MLC performance and assess test frequency required to achieve a given level of performance. MLC-related interlocks and servicing events were recorded during the monitoring period and were investigated as indicators of MLC performance variations. Methods:more » The QC test developed as part of the MLC performance monitoring system uses 2D megavoltage images (acquired using an electronic portal imaging device) of 23 fields to determine the location of the leaves with respect to the radiation isocenter. The precision of the MLC performance monitoring QC test and the MLC itself was assessed by detecting the MLC leaf positions on 127 megavoltage images of a static field. After initial calibration, the MLC performance monitoring QC test was performed 3–4 times/week over a period of 10–11 months to monitor positional accuracy of individual leaves for two different MLC models. Analysis of test results was performed using individuals control charts per leaf with control limits computed based on the measurements as well as two sets of specifications of ±0.5 and ±1 mm. Out-of-specification and out-of-control leaves were automatically flagged by the monitoring system and reviewed monthly by physicists. MLC-related interlocks reported by the linear accelerator and servicing events were recorded to help identify potential causes of nonrandom MLC leaf positioning variations. Results: The precision of the MLC performance monitoring QC test and the MLC itself was within ±0.22 mm for most MLC leaves and the majority of the apparent leaf motion was attributed to beam spot displacements between irradiations. The MLC QC test was performed 193 and 162 times over the monitoring period for the studied units and recalibration had to be repeated up to three times on one of these units. For both units, rate of MLC interlocks was moderately associated with MLC servicing events. The strongest association with the MLC performance was observed between the MLC servicing events and the total number of out-of-control leaves. The average elapsed time for which the number of out-of-specification or out-of-control leaves was within a given performance threshold was computed and used to assess adequacy of MLC test frequency. Conclusions: A MLC performance monitoring system has been developed and implemented to acquire high-quality QC data at high frequency. This is enabled by the relatively short acquisition time for the images and automatic image analysis. The monitoring system was also used to record and track the rate of MLC-related interlocks and servicing events. MLC performances for two commercially available MLC models have been assessed and the results support monthly test frequency for widely accepted ±1 mm specifications. Higher QC test frequency is however required to maintain tighter specification and in-control behavior.« less
  • Tissue-phantom ratios (TPRs) are a common dosimetric quantity used to describe the change in dose with depth in tissue. These can be challenging and time consuming to measure. The conversion of percentage depth dose (PDD) data using standard formulae is widely employed as an alternative method in generating TPR. However, the applicability of these formulae for small fields has been questioned in the literature. Functional representation has also been proposed for small-field TPR production. This article compares measured TPR data for small 6 MV photon fields against that generated by conversion of PDD using standard formulae to assess the efficacymore » of the conversion data. By functionally fitting the measured TPR data for square fields greater than 4 cm in length, the TPR curves for smaller fields are generated and compared with measurements. TPRs and PDDs were measured in a water tank for a range of square field sizes. The PDDs were converted to TPRs using standard formulae. TPRs for fields of 4 × 4 cm{sup 2} and larger were used to create functional fits. The parameterization coefficients were used to construct extrapolated TPR curves for 1 × 1 cm{sup 2}, 2 × 2-cm{sup 2}, and 3 × 3-cm{sup 2} fields. The TPR data generated using standard formulae were in excellent agreement with direct TPR measurements. The TPR data for 1 × 1-cm{sup 2}, 2 × 2-cm{sup 2}, and 3 × 3-cm{sup 2} fields created by extrapolation of the larger field functional fits gave inaccurate initial results. The corresponding mean differences for the 3 fields were 4.0%, 2.0%, and 0.9%. Generation of TPR data using a standard PDD-conversion methodology has been shown to give good agreement with our directly measured data for small fields. However, extrapolation of TPR data using the functional fit to fields of 4 × 4 cm{sup 2} or larger resulted in generation of TPR curves that did not compare well with the measured data.« less