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Title: MO-FG-202-03: Efficient Data Collection of Continuous 2D and Discrete Relative Dosimetric Data for Annual LINAC QA Using TrueBeam Developer Mode and a 1D Scanning Tank

Abstract

Purpose: To develop a method to exploit real-time dynamic machine and couch parameter control during linear accelerator (LINAC) beam delivery to facilitate efficient performance of TG-142 suggested, Annual LINAC QA tests. Methods: Varian’s TrueBeam Developer Mode (Varian Medical Systems, Palo Alto, CA) facilitates control of Varian’s TrueBeam LINAC via instructions provided in Extensible Markup Language (XML) files. This allows machine and couch parameters to be varied dynamically, in real-time, during beam delivery. Custom XML files were created to allow for the collection of (1) continuous Tissue Maximum Ratios (TMRs), (2) beam profiles, and (3) continuous output factors using a 1D-scanning tank. TMRs were acquired by orienting an ionization chamber (IC) at isocenter (depth=25cm) and synchronizing a depth scan towards the water surface while lowering the couch at 1mm/s. For beam profiles, the couch was driven laterally and longitudinally while logging IC electrometer readings. Output factors (OFs) where collected by continually varying field sizes (4×4 to 30×30-cm{sup 2}) at a constant speed of 6.66 mm/s. To validate measurements, comparisons were made to data collected using traditional methods (e.g. 1D or 3D tank). Results: All data collecting using the proposed methods agreed with traditionally collected data (TMRs within 1%, OFs within 0.5%more » and beam profile agreement within 1% / 1mm) while taking less time to collect (factor of approximately 1/10) and with a finer sample resolution. Conclusion: TrueBeam developer mode facilitates collection of continuous data with the same accuracy as traditionally collected data with a finer resolution in less time. Results demonstrate an order of magnitude increase in sampled resolution and an order of magnitude reduction in collection time compared to traditional acquisition methods (e.g. 3D scanning tank). We are currently extending this approach to perform other TG-142 tasks.« less

Authors:
;  [1];  [2];  [2];  [1];  [2];  [1];  [2];  [1];  [2];  [2]
  1. Rhode Island Hospital, Providence, RI (United States)
  2. (United States)
Publication Date:
OSTI Identifier:
22653874
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:
61 RADIATION PROTECTION AND DOSIMETRY; BEAM PROFILES; DEVELOPERS; IONIZATION CHAMBERS; LINEAR ACCELERATORS; QUALITY ASSURANCE; RESOLUTION

Citation Formats

Knutson, N, Schmidt, M, University of Rhode Island, Kingston, RI, University of Massachusetts Lowell, Lowell, MA, Nguyen, N, University of Massachusetts Lowell, Lowell, MA, Belley, M, University of Rhode Island, Kingston, RI, Price, M, University of Rhode Island, Kingston, RI, and Alpert Medical School of Brown University, Providence, RI. MO-FG-202-03: Efficient Data Collection of Continuous 2D and Discrete Relative Dosimetric Data for Annual LINAC QA Using TrueBeam Developer Mode and a 1D Scanning Tank. United States: N. p., 2016. Web. doi:10.1118/1.4957305.
Knutson, N, Schmidt, M, University of Rhode Island, Kingston, RI, University of Massachusetts Lowell, Lowell, MA, Nguyen, N, University of Massachusetts Lowell, Lowell, MA, Belley, M, University of Rhode Island, Kingston, RI, Price, M, University of Rhode Island, Kingston, RI, & Alpert Medical School of Brown University, Providence, RI. MO-FG-202-03: Efficient Data Collection of Continuous 2D and Discrete Relative Dosimetric Data for Annual LINAC QA Using TrueBeam Developer Mode and a 1D Scanning Tank. United States. doi:10.1118/1.4957305.
Knutson, N, Schmidt, M, University of Rhode Island, Kingston, RI, University of Massachusetts Lowell, Lowell, MA, Nguyen, N, University of Massachusetts Lowell, Lowell, MA, Belley, M, University of Rhode Island, Kingston, RI, Price, M, University of Rhode Island, Kingston, RI, and Alpert Medical School of Brown University, Providence, RI. Wed . "MO-FG-202-03: Efficient Data Collection of Continuous 2D and Discrete Relative Dosimetric Data for Annual LINAC QA Using TrueBeam Developer Mode and a 1D Scanning Tank". United States. doi:10.1118/1.4957305.
@article{osti_22653874,
title = {MO-FG-202-03: Efficient Data Collection of Continuous 2D and Discrete Relative Dosimetric Data for Annual LINAC QA Using TrueBeam Developer Mode and a 1D Scanning Tank},
author = {Knutson, N and Schmidt, M and University of Rhode Island, Kingston, RI and University of Massachusetts Lowell, Lowell, MA and Nguyen, N and University of Massachusetts Lowell, Lowell, MA and Belley, M and University of Rhode Island, Kingston, RI and Price, M and University of Rhode Island, Kingston, RI and Alpert Medical School of Brown University, Providence, RI},
abstractNote = {Purpose: To develop a method to exploit real-time dynamic machine and couch parameter control during linear accelerator (LINAC) beam delivery to facilitate efficient performance of TG-142 suggested, Annual LINAC QA tests. Methods: Varian’s TrueBeam Developer Mode (Varian Medical Systems, Palo Alto, CA) facilitates control of Varian’s TrueBeam LINAC via instructions provided in Extensible Markup Language (XML) files. This allows machine and couch parameters to be varied dynamically, in real-time, during beam delivery. Custom XML files were created to allow for the collection of (1) continuous Tissue Maximum Ratios (TMRs), (2) beam profiles, and (3) continuous output factors using a 1D-scanning tank. TMRs were acquired by orienting an ionization chamber (IC) at isocenter (depth=25cm) and synchronizing a depth scan towards the water surface while lowering the couch at 1mm/s. For beam profiles, the couch was driven laterally and longitudinally while logging IC electrometer readings. Output factors (OFs) where collected by continually varying field sizes (4×4 to 30×30-cm{sup 2}) at a constant speed of 6.66 mm/s. To validate measurements, comparisons were made to data collected using traditional methods (e.g. 1D or 3D tank). Results: All data collecting using the proposed methods agreed with traditionally collected data (TMRs within 1%, OFs within 0.5% and beam profile agreement within 1% / 1mm) while taking less time to collect (factor of approximately 1/10) and with a finer sample resolution. Conclusion: TrueBeam developer mode facilitates collection of continuous data with the same accuracy as traditionally collected data with a finer resolution in less time. Results demonstrate an order of magnitude increase in sampled resolution and an order of magnitude reduction in collection time compared to traditional acquisition methods (e.g. 3D scanning tank). We are currently extending this approach to perform other TG-142 tasks.},
doi = {10.1118/1.4957305},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = {Wed Jun 15 00:00:00 EDT 2016},
month = {Wed Jun 15 00:00:00 EDT 2016}
}
  • Purpose: To automate gantry-resolved linear accelerator (linac) quality assurance (QA) for volumetric modulated arc therapy (VMAT) using an electronic portal imaging device (EPID). Methods: A QA system for VMAT was developed that uses an EPID, frame-grabber assembly and in-house developed image processing software. The system relies solely on the analysis of EPID image frames acquired without the presence of a phantom. Images were acquired at 8.41 frames per second using a frame grabber and ancillary acquisition computer. Each image frame was tagged with a gantry angle from the linac’s on-board gantry angle encoder. Arc-dynamic QA plans were designed to assessmore » the performance of each individual linac component during VMAT. By analysing each image frame acquired during the QA deliveries the following eight machine performance characteristics were measured as a function of gantry angle: MLC positional accuracy, MLC speed constancy, MLC acceleration constancy, MLC-gantry synchronisation, beam profile constancy, dose rate constancy, gantry speed constancy, dose-gantry angle synchronisation and mechanical sag. All tests were performed on a Varian iX linear accelerator equipped with a 120 leaf Millennium MLC and an aS1000 EPID (Varian Medical Systems, Palo Alto, CA, USA). Results: Machine performance parameters were measured as a function of gantry angle using EPID imaging and compared to machine log files and the treatment plan. Data acquisition is currently underway at 3 centres, incorporating 7 treatment units, at 2 weekly measurement intervals. Conclusion: The proposed system can be applied for streamlined linac QA and commissioning for VMAT. The set of test plans developed can be used to assess the performance of each individual components of the treatment machine during VMAT deliveries as a function of gantry angle. The methodology does not require the setup of any additional phantom or measurement equipment and the analysis is fully automated to allow for regular routine testing.« less
  • Purpose: To validate a machine learning approach to Virtual IMRT QA for accurately predicting gamma passing rates using different QA devices at different institutions. Methods: A Virtual IMRT QA was constructed using a machine learning algorithm based on 416 IMRT plans, in which QA measurements were performed using diode-array detectors and a 3%local/3mm with 10% threshold. An independent set of 139 IMRT measurements from a different institution, with QA data based on portal dosimetry using the same gamma index and 10% threshold, was used to further test the algorithm. Plans were characterized by 90 different complexity metrics. A weighted poisonmore » regression with Lasso regularization was trained to predict passing rates using the complexity metrics as input. Results: In addition to predicting passing rates with 3% accuracy for all composite plans using diode-array detectors, passing rates for portal dosimetry on per-beam basis were predicted with an error <3.5% for 120 IMRT measurements. The remaining measurements (19) had large areas of low CU, where portal dosimetry has larger disagreement with the calculated dose and, as such, large errors were expected. These beams need to be further modeled to correct the under-response in low dose regions. Important features selected by Lasso to predict gamma passing rates were: complete irradiated area outline (CIAO) area, jaw position, fraction of MLC leafs with gaps smaller than 20 mm or 5mm, fraction of area receiving less than 50% of the total CU, fraction of the area receiving dose from penumbra, weighted Average Irregularity Factor, duty cycle among others. Conclusion: We have demonstrated that the Virtual IMRT QA can predict passing rates using different QA devices and across multiple institutions. Prediction of QA passing rates could have profound implications on the current IMRT process.« less
  • Purpose: EPID-based patient-specific quality assurance provides verification of the planning setup and delivery process that phantomless QA and log-file based virtual dosimetry methods cannot achieve. We present a method for EPID-based QA utilizing spatially-variant EPID response kernels that allows for direct calculation of the entrance fluence and 3D phantom dose. Methods: An EPID dosimetry system was utilized for 3D dose reconstruction in a cylindrical phantom for the purposes of end-to-end QA. Monte Carlo (MC) methods were used to generate pixel-specific point-spread functions (PSFs) characterizing the spatially non-uniform EPID portal response in the presence of phantom scatter. The spatially-variant PSFs weremore » decomposed into spatially-invariant basis PSFs with the symmetric central-axis kernel as the primary basis kernel and off-axis representing orthogonal perturbations in pixel-space. This compact and accurate characterization enables the use of a modified Richardson-Lucy deconvolution algorithm to directly reconstruct entrance fluence from EPID images without iterative scatter subtraction. High-resolution phantom dose kernels were cogenerated in MC with the PSFs enabling direct recalculation of the resulting phantom dose by rapid forward convolution once the entrance fluence was calculated. A Delta4 QA phantom was used to validate the dose reconstructed in this approach. Results: The spatially-invariant representation of the EPID response accurately reproduced the entrance fluence with >99.5% fidelity with a simultaneous reduction of >60% in computational overhead. 3D dose for 10{sub 6} voxels was reconstructed for the entire phantom geometry. A 3D global gamma analysis demonstrated a >95% pass rate at 3%/3mm. Conclusion: Our approach demonstrates the capabilities of an EPID-based end-to-end QA methodology that is more efficient than traditional EPID dosimetry methods. Displacing the point of measurement external to the QA phantom reduces the necessary complexity of the phantom itself while offering a method that is highly scalable and inherently generalizable to rotational and trajectory based deliveries. This research was partially supported by Varian.« less
  • Purpose: The Varian EDGE machine is a new stereotactic platform, combining Calypso and VisionRT localization systems with a stereotactic linac. The system includes TrueBeam DeveloperMode, making possible the use of XML-scripting for automation of linac-related tasks. This study details the use of DeveloperMode to automate commissioning tasks for Varian EDGE, thereby improving efficiency and measurement consistency. Methods: XML-scripting was used for various commissioning tasks,including couch model verification,beam-scanning,and isocenter verification. For couch measurements, point measurements were acquired for several field sizes (2×2,4×4,10×10cm{sup 2}) at 42 gantry angles for two couch-models. Measurements were acquired with variations in couch position(rails in/out,couch shifted inmore » each of motion axes) compared to treatment planning system(TPS)-calculated values,which were logged automatically through advanced planning interface(API) scripting functionality. For beam scanning, XML-scripts were used to create custom MLC-apertures. For isocenter verification, XML-scripts were used to automate various Winston-Lutz-type tests. Results: For couch measurements, the time required for each set of angles was approximately 9 minutes. Without scripting, each set required approximately 12 minutes. Automated measurements required only one physicist, while manual measurements required at least two physicists to handle linac positions/beams and data recording. MLC apertures were generated outside of the TPS,and with the .xml file format, double-checking without use of TPS/operator console was possible. Similar time efficiency gains were found for isocenter verification measurements Conclusion: The use of XML scripting in TrueBeam DeveloperMode allows for efficient and accurate data acquisition during commissioning. The efficiency improvement is most pronounced for iterative measurements, exemplified by the time savings for couch modeling measurements(approximately 10 hours). The scripting also allowed for creation of the files in advance without requiring access to TPS. The API scripting functionality enabled efficient creation/mining of TPS data. Finally, automation reduces the potential for human error in entering linac values at the machine console,and the script provides a log of measurements acquired for each session. This research was supported in part by a grant from Varian Medical Systems, Palo Alto, CA.« less
  • Purpose: The use of gamma analysis for IMRT quality assurance has well-known limitations. Traditionally, a simple thresholding technique is used to evaluated passing criteria. However, like any image the gamma distribution is rich in information which thresholding mostly discards. We therefore propose a novel method of analyzing gamma images that uses quantitative image features borrowed from radiomics, with the goal of improving error detection. Methods: 368 gamma images were generated from 184 clinical IMRT beams. For each beam the dose to a phantom was measured with EPID dosimetry and compared to the TPS dose calculated with and without normally distributedmore » (2mm sigma) errors in MLC positions. The magnitude of 17 intensity histogram and size-zone radiomic features were derived from each image. The features that differed most significantly between image sets were determined with ROC analysis. A linear machine-learning model was trained on these features to classify images as with or without errors on 180 gamma images.The model was then applied to an independent validation set of 188 additional gamma distributions, half with and half without errors. Results: The most significant features for detecting errors were histogram kurtosis (p=0.007) and three size-zone metrics (p<1e-6 for each). The sizezone metrics detected clusters of high gamma-value pixels under mispositioned MLCs. The model applied to the validation set had an AUC of 0.8, compared to 0.56 for traditional gamma analysis with the decision threshold restricted to 98% or less. Conclusion: A radiomics-based image analysis method was developed that is more effective in detecting error than traditional gamma analysis. Though the pilot study here considers only MLC position errors, radiomics-based methods for other error types are being developed, which may provide better error detection and useful information on the source of detected errors. This work was partially supported by a grant from the Agency for Healthcare Research and Quality, grant number R18 HS022244-01.« less