Mario Perez

Automating linear accelerator quality assurance.

PURPOSE The purpose of this study was 2-fold. One purpose was to develop an automated, streamlined quality assurance (QA) program for use by multiple centers. The second purpose was to evaluate machine performance over time for multiple centers using linear accelerator (Linac) log files and electronic portal images. The authors sought to evaluate variations in Linac performance to establish as a reference for other centers. METHODS The authors developed analytical software tools for a QA program using both log files and electronic portal imaging device (EPID) measurements. The first tool is a general analysis tool which can read and visually represent data in the log file. This tool, which can be used to automatically analyze patient treatment or QA log files, examines the files for Linac deviations which exceed thresholds. The second set of tools consists of a test suite of QA fields, a standard phantom, and software to collect information from the log files on deviations from the expected values. The test suite was designed to focus on the mechanical tests of the Linac to include jaw, MLC, and collimator positions during static, IMRT, and volumetric modulated arc therapy delivery. A consortium of eight institutions delivered the test suite at monthly or weekly intervals on each Linac using a standard phantom. The behavior of various components was analyzed for eight TrueBeam Linacs. RESULTS For the EPID and trajectory log file analysis, all observed deviations which exceeded established thresholds for Linac behavior resulted in a beam hold off. In the absence of an interlock-triggering event, the maximum observed log file deviations between the expected and actual component positions (such as MLC leaves) varied from less than 1% to 26% of published tolerance thresholds. The maximum and standard deviations of the variations due to gantry sag, collimator angle, jaw position, and MLC positions are presented. Gantry sag among Linacs was 0.336 ± 0.072 mm. The standard deviation in MLC position, as determined by EPID measurements, across the consortium was 0.33 mm for IMRT fields. With respect to the log files, the deviations between expected and actual positions for parameters were small (<0.12 mm) for all Linacs. Considering both log files and EPID measurements, all parameters were well within published tolerance values. Variations in collimator angle, MLC position, and gantry sag were also evaluated for all Linacs. CONCLUSIONS The performance of the TrueBeam Linac model was shown to be consistent based on automated analysis of trajectory log files and EPID images acquired during delivery of a standardized test suite. The results can be compared directly to tolerance thresholds. In addition, sharing of results from standard tests across institutions can facilitate the identification of QA process and Linac changes. These reference values are presented along with the standard deviation for common tests so that the test suite can be used by other centers to evaluate their Linac performance against those in this consortium.

ACPSEM ROSG Oncology-PACS and OIS working group recommendations for quality assurance

Abstract The Australasian College of Physical Scientists and Engineers in Medicine (ACPSEM) Radiation Oncology Specialty Group (ROSG) formed a series of working groups in 2011 to develop position papers for guidance of radiation oncology medical physics practice within the Australasian setting. These position papers are intended to provide guidance for safe work practices and a suitable level of quality control without detailed work instructions. It is the responsibility of the medical physicist to ensure that locally available equipment and procedures are sufficiently sensitive to establish compliance to these position papers. The recommendations are endorsed by the ROSG, have been subject to independent expert reviews. For the Australian audience, these recommendations should be read in conjunction with the Tripartite Radiation Oncology Practice Standards [1, 2]. This publication presents the recommendations of the ACPSEM OPACS and OIS Working Group (OISWG) and has been developed in alignment with other international associations. However, these recommendations should be read in conjunction with relevant national, state or territory legislation and local requirements, which take precedence over the ACPSEM position papers. It is hoped that the users of this and other ACPSEM position papers will contribute to the development of future versions through the Radiation Oncology Specialty Group of the ACPSEM.

Big data readiness in Radiation Oncology: An efficient approach for re-labelling radiotherapy structures with their TG-263 standard name in real-world data sets

Purpose To prepare for big data analyses on radiation therapy data, we developed Stature, a tool-supported approach for standardization of structure names in existing radiation therapy plans. We applied the widely endorsed nomenclature standard TG-263 as the mapping target and quantified the structure name inconsistency in 2 real-world data sets. Methods and Materials The clinically relevant structures in the radiation therapy plans were identified by reference to randomized controlled trials. The Stature approach was used by clinicians to identify the synonyms for each relevant structure, which was then mapped to the corresponding TG-263 name. We applied Stature to standardize the structure names for 654 patients with prostate cancer (PCa) and 224 patients with head and neck squamous cell carcinoma (HNSCC) who received curative radiation therapy at our institution between 2007 and 2017. The accuracy of the Stature process was manually validated in a random sample from each cohort. For the HNSCC cohort we measured the resource requirements for Stature, and for the PCa cohort we demonstrated its impact on an example clinical analytics scenario. Results All but 1 synonym group (“Hydrogel”) was mapped to the corresponding TG-263 name, resulting in a TG-263 relabel rate of 99% (8837 of 8925 structures). For the PCa cohort, Stature matched a total of 5969 structures. Of these, 5682 structures were exact matches (ie, following local naming convention), 284 were matched via a synonym, and 3 required manual matching. This original radiation therapy structure names therefore had a naming inconsistency rate of 4.81%. For the HNSCC cohort, Stature mapped a total of 2956 structures (2638 exact, 304 synonym, 14 manual; 10.76% inconsistency rate) and required 7.5 clinician hours. The clinician hours required were one-fifth of those that would be required for manual relabeling. The accuracy of Stature was 99.97% (PCa) and 99.61% (HNSCC). Conclusions The Stature approach was highly accurate and had significant resource efficiencies compared with manual curation.

SU-G-TeP4-07: Automatic EPID-Based 2D Measurement of MLC Leaf Offset as a Quality Control Tool

PURPOSE The MLC dosimetric leaf gap (DLG) and transmission are measured parameters which impact the dosimetric accuracy of IMRT and VMAT plans. This investigation aims to develop an efficient and accurate routine constancy check of the physical DLG in two dimensions. METHODS The manufacturers recommended DLG measurement method was modified by using 5 fields instead of 11 and by utilizing the Electronic Portal Imaging Device (EPID). Validations were accomplished using an ion chamber (IC) in solid water and a 2D IC array. EPID data was collected for 6 months on multiple TrueBeam linacs using both Millennium and HD MLCs at 5 different clinics in an international consortium. Matlab code was written to automatically analyze the images and calculate the 2D results. Sensitivity was investigated by introducing deliberate leaf position errors. MLC calibration and initialization history was recorded to allow quantification of their impact. Results were analyzed using statistical process control (SPC). RESULTS The EPID method took approximately 5 minutes. Due to detector response, the EPID measured DLG and transmission differed from the IC values but were reproducible and consistent with changes measured using the ICs. For the Millennium MLC, the EPID measured DLG and transmission were both consistently lower than IC results. The EPID method was implemented as leaf offset and transmission constancy tests (LOC and TC). Based on 6 months of measurements, the initial leaf-specific action thresholds for changes from baseline were set to 0.1 mm. Upper and lower control limits for variation were developed for each machine. CONCLUSION Leaf offset and transmission constancy tests were implemented on Varian HD and Millennium MLCs using an EPID and found to be efficient and accurate. The test is effective for monitoring MLC performance using dynamic delivery and performing process control on the DLG in 2D, thus enhancing dosimetric accuracy. This work was supported by a grant from Varian Medical Systems.

SU-C-BRD-03: Analysis of Accelerator Generated Text Logs for Preemptive Maintenance

PURPOSE To develop a model to analyze medical accelerator generated parameter and performance data that will provide an early warning of performance degradation and impending component failure. METHODS A robust 6 MV VMAT quality assurance treatment delivery was used to test the constancy of accelerator performance. The generated text log files were decoded and analyzed using statistical process control (SPC) methodology. The text file data is a single snapshot of energy specific and overall systems parameters. A total of 36 system parameters were monitored which include RF generation, electron gun control, energy control, beam uniformity control, DC voltage generation, and cooling systems. The parameters were analyzed using Individual and Moving Range (I/MR) charts. The chart limits were calculated using a hybrid technique that included the use of the standard 3σ limits and the parameter/system specification. Synthetic errors/changes were introduced to determine the initial effectiveness of I/MR charts in detecting relevant changes in operating parameters. The magnitude of the synthetic errors/changes was based on: the value of 1 standard deviation from the mean operating parameter of 483 TB systems, a small fraction (≤ 5%) of the operating range, or a fraction of the minor fault deviation. RESULTS There were 34 parameters in which synthetic errors were introduced. There were 2 parameters (radial position steering coil, and positive 24V DC) in which the errors did not exceed the limit of the I/MR chart. The I chart limit was exceeded for all of the remaining parameters (94.2%). The MR chart limit was exceeded in 29 of the 32 parameters (85.3%) in which the I chart limit was exceeded. CONCLUSION Statistical process control I/MR evaluation of text log file parameters may be effective in providing an early warning of performance degradation or component failure for digital medical accelerator systems. Research is Supported by Varian Medical Systems, Inc.

SU-E-T-144: Effective Analysis of VMAT QA Generated Trajectory Log Files for Medical Accelerator Predictive Maintenance

PURPOSE To determine the effectiveness of SPC analysis for a model predictive maintenance process that uses accelerator generated parameter and performance data contained in trajectory log files. METHODS Each trajectory file is decoded and a total of 131 axes positions are recorded (collimator jaw position, gantry angle, each MLC, etc.). This raw data is processed and either axis positions are extracted at critical points during the delivery or positional change over time is used to determine axis velocity. The focus of our analysis is the accuracy, reproducibility and fidelity of each axis. A reference positional trace of the gantry and each MLC is used as a motion baseline for cross correlation (CC) analysis. A total of 494 parameters (482 MLC related) were analyzed using Individual and Moving Range (I/MR) charts. The chart limits were calculated using a hybrid technique that included the use of the standard 3σ limits and parameter/system specifications. Synthetic errors/changes were introduced to determine the initial effectiveness of I/MR charts in detecting relevant changes in operating parameters. The magnitude of the synthetic errors/changes was based on: TG-142 and published analysis of VMAT delivery accuracy. RESULTS All errors introduced were detected. Synthetic positional errors of 2mm for collimator jaw and MLC carriage exceeded the chart limits. Gantry speed and each MLC speed are analyzed at two different points in the delivery. Simulated Gantry speed error (0.2 deg/sec) and MLC speed error (0.1 cm/sec) exceeded the speed chart limits. Gantry position error of 0.2 deg was detected by the CC maximum value charts. The MLC position error of 0.1 cm was detected by the CC maximum value location charts for every MLC. CONCLUSION SPC I/MR evaluation of trajectory log file parameters may be effective in providing an early warning of performance degradation or component failure for medical accelerator systems.

WE‐E‐141‐07: Automating Linac QA for Delivery and Analysis

PURPOSE To assess the quantitative performance and reproducibility of a new generation linear accelerator using images and trajectory log files across institutions. METHODS A test suite was created to include tests recommended by TG142 (e.g, picket fence at cardinal static gantry angles and during VMAT) and TG179 (e.g. image quality). The test suite, distributed to a consortium of 7 institutions, consisted of DICOM-RT files and a phantom with BBs at known locations. During each delivery, EPID images were acquired along with trajectory log files. Baseline for each irradiation was set with a flood field without the table or phantom. The phantom was then placed in position and the remaining tests were performed. An analysis program, created in Matlab, assessed the accuracy of leaf, jaw, and collimator positions utilizing the EPID images. Trajectory log files were analyzed as well to assess dynamic parameters such as the reproducibility of gantry motion during arc delivery. RESULTS Fifteen irradiations were performed on 5 accelerators. Leaf position reproducibility was 0.095 mm for a standard MLC and 0.110 mm for an HDMLC, with maximum standard deviations of 0.019, 0.053, and 0.002 mm for static, IMRT, and arc fields over all linacs. Trajectory logs were consistent with measurements. The maximum gantry deviation was 0.247 ± 0.0160 degrees. Using two different materials, the contrast-to-noise ratio was 1.43 ±0.740 and 7.41 ±0.24 for kV and MV images with kV CNR varying by more than a factor of 2 between different machines. CONCLUSION EPID and trajectory logs demonstrated thresholds for detection of leaf position errors that were an order of magnitude less than TG142 requirements for different delivery types across institutions. Trajectory log files provided more detailed information regarding stability of gantry position. When tracked over time, these data can be used to reassess the frequency of different test types. This work is supported by Varian Medical Systems.