The anthropomorphic phantom program at the Houston branch of the Imaging and Radiation Oncology Core (IROC-Houston) is an end-to-end test that can be used to determine whether an institution can ...accurately model, calculate, and deliver an intensity modulated radiation therapy dose distribution. Currently, institutions that do not meet IROC-Houston's criteria have no specific information with which to identify and correct problems. In the present study, an independent recalculation system was developed to identify treatment planning system (TPS) calculation errors.
A recalculation system was commissioned and customized using IROC-Houston measurement reference dosimetry data for common linear accelerator classes. Using this system, 259 head and neck phantom irradiations were recalculated. Both the recalculation and the institution's TPS calculation were compared with the delivered dose that was measured. In cases in which the recalculation was statistically more accurate by 2% on average or 3% at a single measurement location than was the institution's TPS, the irradiation was flagged as having a "considerable" institutional calculation error. The error rates were also examined according to the linear accelerator vendor and delivery technique.
Surprisingly, on average, the reference recalculation system had better accuracy than the institution's TPS. Considerable TPS errors were found in 17% (n=45) of the head and neck irradiations. Also, 68% (n=13) of the irradiations that failed to meet the IROC-Houston criteria were found to have calculation errors.
Nearly 1 in 5 institutions were found to have TPS errors in their intensity modulated radiation therapy calculations, highlighting the need for careful beam modeling and calculation in the TPS. An independent recalculation system can help identify the presence of TPS errors and pass on the knowledge to the institution.
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GEOZS, IJS, NUK, OILJ, UL, UM, UPUK
To determine whether in-house patient-specific intensity modulated radiation therapy quality assurance (IMRT QA) results predict Imaging and Radiation Oncology Core (IROC)-Houston phantom results.
...IROC Houston's IMRT head and neck phantoms have been irradiated by numerous institutions as part of clinical trial credentialing. We retrospectively compared these phantom results with those of in-house IMRT QA (following the institution's clinical process) for 855 irradiations performed between 2003 and 2013. The sensitivity and specificity of IMRT QA to detect unacceptable or acceptable plans were determined relative to the IROC Houston phantom results. Additional analyses evaluated specific IMRT QA dosimeters and analysis methods.
IMRT QA universally showed poor sensitivity relative to the head and neck phantom, that is, poor ability to predict a failing IROC Houston phantom result. Depending on how the IMRT QA results were interpreted, overall sensitivity ranged from 2% to 18%. For different IMRT QA methods, sensitivity ranged from 3% to 54%. Although the observed sensitivity was particularly poor at clinical thresholds (eg 3% dose difference or 90% of pixels passing gamma), receiver operator characteristic analysis indicated that no threshold showed good sensitivity and specificity for the devices evaluated.
IMRT QA is not a reasonable replacement for a credentialing phantom. Moreover, the particularly poor agreement between IMRT QA and the IROC Houston phantoms highlights surprising inconsistency in the QA process.
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GEOZS, IJS, NUK, OILJ, UL, UM, UPUK
To compare radiation machine measurement data collected by the Imaging and Radiation Oncology Core at Houston (IROC-H) with institutional treatment planning system (TPS) values, to identify ...parameters with large differences in agreement; the findings will help institutions focus their efforts to improve the accuracy of their TPS models.
Between 2000 and 2014, IROC-H visited more than 250 institutions and conducted independent measurements of machine dosimetric data points, including percentage depth dose, output factors, off-axis factors, multileaf collimator small fields, and wedge data. We compared these data with the institutional TPS values for the same points by energy, class, and parameter to identify differences and similarities using criteria involving both the medians and standard deviations for Varian linear accelerators. Distributions of differences between machine measurements and institutional TPS values were generated for basic dosimetric parameters.
On average, intensity modulated radiation therapy-style and stereotactic body radiation therapy-style output factors and upper physical wedge output factors were the most problematic. Percentage depth dose, jaw output factors, and enhanced dynamic wedge output factors agreed best between the IROC-H measurements and the TPS values. Although small differences were shown between 2 common TPS systems, neither was superior to the other. Parameter agreement was constant over time from 2000 to 2014.
Differences in basic dosimetric parameters between machine measurements and TPS values vary widely depending on the parameter, although agreement does not seem to vary by TPS and has not changed over time. Intensity modulated radiation therapy-style output factors, stereotactic body radiation therapy-style output factors, and upper physical wedge output factors had the largest disagreement and should be carefully modeled to ensure accuracy.
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GEOZS, IJS, NUK, OILJ, UL, UM, UPUK
Purpose: Optically stimulated luminescent detectors (OSLDs) are quickly gaining popularity as passive dosimeters, with applications in medicine for linac output calibration verification, ...brachytherapy source verification, treatment plan quality assurance, and clinical dose measurements. With such wide applications, these dosimeters must be characterized for numerous factors affecting their response. The most abundant commercial OSLD is the InLight/OSL system from Landauer, Inc. The purpose of this study was to examine the angular dependence of the nanoDot dosimeter, which is part of the InLight system.Methods: Relative dosimeter response data were taken at several angles in 6 and 18 MV photon beams, as well as a clinical proton beam. These measurements were done within a phantom at a depth beyond the build-up region. To verify the observed angular dependence, additional measurements were conducted as well as Monte Carlo simulations in MCNPX.Results: When irradiated with the incident photon beams parallel to the plane of the dosimeter, the nanoDot response was 4% lower at 6 MV and 3% lower at 18 MV than the response when irradiated with the incident beam normal to the plane of the dosimeter. Monte Carlo simulations at 6 MV showed similar results to the experimental values. Examination of the results in Monte Carlo suggests the cause as partial volume irradiation. In a clinical proton beam, no angular dependence was found.Conclusions: A nontrivial angular response of this OSLD was observed in photon beams. This factor may need to be accounted for when evaluating doses from photon beams incident from a variety of directions.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
The multileaf collimator (MLC) is a critical component to accurate intensity-modulated radiotherapy (IMRT) delivery. This study examined MLC positional accuracy via MLC logs from Varian machines from ...six institutions and three delivery techniques to evaluate typical positional accuracy and treatment and mechanical parameters that affect accuracy. Typical accuracy achieved was compared against TG-142 recommendations for MLC performance; more appropriate recommendations are suggested.
Over 85,000 Varian MLC treatment logs were collected from six institutions and analyzed with FractionCHECK. Data were binned according to institution and treatment type to determine overall root mean square (RMS) and 95th percentile error values, and then to look for correlations between those errors and with mechanical and treatment parameters including mean and maximum leaf speed, gantry angle, beam-on time, mean leaf error, and number of segments.
Results of treatment logs found that leaf RMS error and 95th percentile leaf error were consistent between institutions, but varied by treatment type. The step and shoot technique had very small errors: the mean RMS leaf error was 0.008 mm. For dynamic treatments the mean RMS leaf error was 0.32 mm, while volumetric-modulated arc treatment (VMAT) showed an RMS leaf error of 0.46 mm. Most MLC leaf errors were found to be well below TG-142 recommended tolerances. For the dynamic and VMAT techniques, the mean and maximum leaf speeds were significantly linked to the leaf RMS error. Additionally, for dynamic delivery, the mean leaf error was correlated with RMS error, whereas for VMAT the average gantry speed was correlated. For all treatments, the RMS error and the 95th percentile leaf error were correlated.
Restricting the maximum leaf speed can help improve MLC performance for dynamic and VMAT deliveries. Furthermore, the tolerances of leaf RMS and error counts for all treatment types should be tightened from the TG-142 values to make them more appropriate for clinical performance. Values of 1 mm for the 95th percentile of leaf RMS error and 1.5 mm for the 95th percentile leaf error are suggested as action levels for all treatment types.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Purpose
Reference dosimetry data can provide an independent second check of acquired values when commissioning or validating a treatment planning system (TPS). The Imaging and Radiation Oncology Core ...at Houston (IROC‐Houston) has measured numerous linear accelerators throughout its existence. The results of those measurements are given here, comparing accelerators and the agreement of measurement versus institutional TPS calculations.
Methods
Data from IROC‐Houston on‐site reviews from 2000 through 2014 were analyzed for all Elekta accelerators, approximately 50. For each, consistent point dose measurements were conducted for several basic parameters in a water phantom, including percentage depth dose, output factors, small‐field output factors, off‐axis factors, and wedge factors. The results were compared by accelerator type independently for 6, 10, 15, and 18 MV. Distributions of the measurements for each parameter are given, providing the mean and standard deviation. Each accelerator's measurements were also compared to its corresponding TPS calculation from the institution to determine the level of agreement, as well as determining which dosimetric parameters were most often in error.
Results
Accelerators were grouped by head type and reference dosimetric values were compiled. No class of linac had better overall agreement with its TPS, but percentage depth dose and output factors commonly agreed well, while small‐field output factors, off‐axis factors, and wedge factors often disagreed substantially from their TPS calculations.
Conclusion
Reference data has been collected and analyzed for numerous Elekta linacs, which provide an independent way for a physicist to double‐check their own measurements to prevent gross treatment errors. In addition, treatment planning parameters more often in error have been highlighted, providing practical caution for physicists commissioning treatment planning systems for Elekta linacs.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Purpose:
Accurate data regarding linear accelerator (Linac) radiation characteristics are important for treatment planning system modeling as well as regular quality assurance of the machine. The ...Imaging and Radiation Oncology Core-Houston (IROC-H) has measured the dosimetric characteristics of numerous machines through their on-site dosimetry review protocols. Photon data are presented and can be used as a secondary check of acquired values, as a means to verify commissioning a new machine, or in preparation for an IROC-H site visit.
Methods:
Photon data from IROC-H on-site reviews from 2000 to 2014 were compiled and analyzed. Specifically, data from approximately 500 Varian machines were analyzed. Each dataset consisted of point measurements of several dosimetric parameters at various locations in a water phantom to assess the percentage depth dose, jaw output factors, multileaf collimator small field output factors, off-axis factors, and wedge factors. The data were analyzed by energy and parameter, with similarly performing machine models being assimilated into classes. Common statistical metrics are presented for each machine class. Measurement data were compared against other reference data where applicable.
Results:
Distributions of the parameter data were shown to be robust and derive from a student’s t distribution. Based on statistical and clinical criteria, all machine models were able to be classified into two or three classes for each energy, except for 6 MV for which there were eight classes. Quantitative analysis of the measurements for 6, 10, 15, and 18 MV photon beams is presented for each parameter; supplementary material has also been made available which contains further statistical information.
Conclusions:
IROC-H has collected numerous data on Varian Linacs and the results of photon measurements from the past 15 years are presented. The data can be used as a comparison check of a physicist’s acquired values. Acquired values that are well outside the expected distribution should be verified by the physicist to identify whether the measurements are valid. Comparison of values to this reference data provides a redundant check to help prevent gross dosimetric treatment errors.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Purpose:
Photo-stimulable phosphor computed radiography (CR) has characteristics that allow the output to be manipulated by both radiation and optical light. The authors have developed a method that ...uses these characteristics to carry out radiation field and light field coincidence quality assurance on linear accelerators.
Methods:
CR detectors from Kodak were used outside their cassettes to measure both radiation and light field edges from a Varian linear accelerator. The CR detector was first exposed to a radiation field and then to a slightly smaller light field. The light impinged on the detector's latent image, removing to an extent the portion exposed to the light field. The detector was then digitally scanned. AMATLAB-based algorithm was developed to automatically analyze the images and determine the edges of the light and radiation fields, the vector between the field centers, and the crosshair center. Radiographic film was also used as a control to confirm the radiation field size.
Results:
Analysis showed a high degree of repeatability with the proposed method. Results between the proposed method and radiographic film showed excellent agreement of the radiation field. The effect of varying monitor units and light exposure time was tested and found to be very small. Radiation and light field sizes were determined with an uncertainty of less than 1 mm, and light and crosshair centers were determined within 0.1 mm.
Conclusions:
A new method was developed to digitally determine the radiation and light field size using CR photo-stimulable phosphor plates. The method is quick and reproducible, allowing for the streamlined and robust assessment of light and radiation field coincidence, with no observer interpretation needed.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Optically stimulated luminescent dosimeters (OSLDs) are becoming increasingly popular for measuring an absorbed dose in clinical radiotherapy. OSLDs have known energy dependence, and this is ...accounted for by either calibrating the OSLD with a specific nominal energy, or using a standard energy correction factor to account for differences between the experimental beam photon energy and the photon energy used to establish the OSLD's sensitivity (e.g., 60Co). This work is typically done under reference conditions (e.g., at dmax). The impact of variations in photon spectra on the OSLD response is typically ignored for measurement positions that are different than the reference position. We determined that it is generally necessary to apply an additional non-reference energy correction factor to OSLD measurements made at locations that do not correspond to the reference position, particularly for OSLD measurements made out-of-field, where the photon spectra are softer. We determined this energy correction factor for a range of 6 MV photon spectra using two independent methods: Burlin cavity theory and measurements. The non-reference energy correction factor was found to range from 0.97 to 1.00 for in-field measurement locations and from 0.69 to 0.95 for out-of-field measurement locations. The use of a non-reference energy correction factor can improve the accuracy of OSLDs, especially when used out-of-field.
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