On the sensitivity of TG-119 and IROC credentialing to TPS commissioning errors

Multi-institution single geometry plan complexity characteristics based on IROC phantoms

BACKGROUND

Clinical intensity modulated radiation therapy plans have been described using various complexity metrics to help identify problematic radiotherapy plans. Most previous studies related to the quantification of plan complexity and their utility have relied on institution-specific plans which can be highly variable depending on the machines, planning techniques, delivery modalities, and measurement devices used. In this work, 1723 plans treating one of only four standardized geometries were simultaneously analyzed to investigate how radiation plan complexity metrics vary across four different sets of common objectives.

PURPOSE

To assess the treatment plan complexity characteristics of plans developed for Imaging and Radiation Oncology Core (IROC) phantoms. Specifically, to understand the variability in plan complexity between institutions for a common plan objective, and to evaluate how various complexity metrics differentiate relevant groups of plans.

METHODS

1723 plans treating one of four standardized IROC phantom geometries representing four different anatomical sites of treatment were analyzed. For each plan, 22 MLC-descriptive plan complexity metrics were calculated, and principal component analysis (PCA) was applied to the 22 metrics in order to evaluate differences in plan complexity between groups. Across all metrics, pairwise comparisons of the IROC phantom data were made for the following classifications of the data: anatomical phantom treated, treatment planning system (TPS), and the combination of MLC model and treatment planning system. An objective k-means clustering algorithm was also applied to the data to determine if any meaningful distinctions could be made between different subgroups. The IROC phantom database was also compared to a clinical database from the University of Wisconsin-Madison (UW) which included plans treating the same four anatomical sites as the IROC phantoms using a TrueBeam™ STx and Pinnacle3 TPS.

RESULTS

The IROC head and neck and spine plans were distinct from the prostate and lung plans based on comparison of the 22 metrics. All IROC phantom plan group complexity metric distributions were highly variable despite all plans being designed for identical geometries and plan objectives. The clusters determined by the k-means algorithm further supported that the IROC head and neck and spine plans involved similar amounts of complexity and were largely distinct from the prostate and lung plans, but no further distinctions could be made. Plan complexity in the head and neck and spine IROC phantom plans were similar to the complexity encountered in the UW clinical plans.

CONCLUSIONS

There is substantial variability in plan complexity between institutions when planning for the same objective. For each IROC anatomical phantom treated, the magnitude of variability in plan complexity between institutions is similar to the variability in plan complexity encountered within a single institution database containing several hundred unique clinical plans treating corresponding anatomies in actual patients.

A radiotherapy community data-driven approach to determine which complexity metrics best predict the impact of atypical TPS beam modeling on clinical dose calculation accuracy

PURPOSE

To quantify the impact of treatment planning system beam model parameters, based on the actual spread in radiotherapy community data, on clinical treatment plans and determine which complexity metrics best describe the impact beam modeling errors have on dose accuracy.

METHODS

Ten beam modeling parameters for a Varian accelerator were modified in RayStation to match radiotherapy community data at the 2.5, 25, 50, 75, and 97.5 percentile levels. These modifications were evaluated on 25 patient cases, including prostate, non-small cell lung, H&N, brain, and mesothelioma, generating 1,000 plan perturbations. Differences in the mean planned dose to clinical target volumes (CTV) and organs at risk (OAR) were evaluated with respect to the planned dose using the reference (50th-percentile) parameter values. Correlation between CTV dose differences, and 18 different complexity metrics were evaluated using linear regression; R-squared values were used to determine the best metric.

RESULTS

Perturbations to MLC offset and transmission parameters demonstrated the greatest changes in dose: up to 5.7% in CTVs and 16.7% for OARs. More complex clinical plans showed greater dose perturbation with atypical beam model parameters. The mean MLC Gap and Tongue & Groove index (TGi) complexity metrics best described the impact of TPS beam modeling variations on clinical dose delivery across all anatomical sites; similar, though not identical, trends between complexity and dose perturbation were observed among all sites.

CONCLUSION

Extreme values for MLC offset and MLC transmission beam modeling parameters were found to most substantially impact the dose distribution of clinical plans and careful attention should be given to these beam modeling parameters. The mean MLC Gap and TGi complexity metrics were best suited to identifying clinical plans most sensitive to beam modeling errors; this could help provide focus for clinical QA in identifying unacceptable plans.

Simulation of consequences of using nonideal detectors during beam data commissioning measurements

BACKGROUND

Beam data commissioning is a core task of radiotherapy physicists. Despite multiple detectors available, a feasible measurement program compromises between detector properties and time constraints. Therefore, it is important to understand how nonideal measurement data propagates into patient dose calculation.

PURPOSE

We simulated the effects of realistic errors, due to beam commissioning with presumably nonoptimal detectors, on the resulting patient dose distributions. Additionally, the detectability of such beam commissioning errors during patient plan quality assurance (QA) was evaluated.

METHODS

A clinically used beam model was re-commissioned introducing changes to depth dose curves, output factors, profiles or combinations of those. Seventeen altered beam models with incremental changes of the modelling parameters were created to analyze dose changes on simplified anatomical phantoms. Additionally, fourteen altered models incorporate changes in the order of signal differences reported for typically used detectors. Eighteen treatment plans of different types were recalculated on patient CT data sets using the altered beam models.

RESULTS

For the majority of clinical plans, dose distributions in the target volume recalculated on the patient computed tomography data were similar between the original and the modified beam models, yielding global 2%/2 mm gamma pass rates above 98.9%. Larger changes were observed for certain combinations of beam modelling errors and anatomical sites, most extreme for output factor changes in a small target volume plan with a pass rate of 80.6%. Modelling an enlarged penumbra as if measured with a 0.125 cm3 ion chamber had the largest effect on the dose distribution (average pass rate of 96.5%, lowest 85.4%). On different QA phantom geometries, dose distributions between calculations with modified and unmodified models typically changed too little to be detected in actual measurements.

CONCLUSION

While the simulated errors during beam modelling had little effect on most plans, in some cases changes were considerable. High-quality penumbra and small field output factor should be a main focus of commissioning measurements. Detecting modelling issues using standard patient QA phantoms is unlikely. Verification of a beam model should be performed especially for plans with high modulation and in different depths or geometries representing the variety of situations expected clinically.

Universal evaluation of MLC models in treatment planning systems based on a common set of dynamic tests

PURPOSE

To demonstrate the feasibility of characterising MLCs and MLC models implemented in TPSs using a common set of dynamic beams.

MATERIALS AND METHODS

A set of tests containing synchronous (SG) and asynchronous sweeping gaps (aSG) was distributed among twenty-five participating centres. Doses were measured with a Farmer-type ion chamber and computed in TPSs, which provided a dosimetric characterisation of the leaf tip, tongue-and-groove, and MLC transmission of each MLC, as well as an assessment of the MLC model in each TPS. Five MLC types and four TPSs were evaluated, covering the most frequent combinations used in radiotherapy departments.

RESULTS

Measured differences within each MLC type were minimal, while large differences were found between MLC models implemented in clinical TPSs. This resulted in some concerning discrepancies, especially for the HD120 and Agility MLCs, for which differences between measured and calculated doses for some MLC-TPS combinations exceeded 10%. These large differences were particularly evident for small gap sizes (5 and 10 mm), as well as for larger gaps in the presence of tongue-and-groove effects. A much better agreement was found for the Millennium120 and Halcyon MLCs, differences being within ± 5% and ± 2.5%, respectively.

CONCLUSIONS

The feasibility of using a common set of tests to assess MLC models in TPSs was demonstrated. Measurements within MLC types were very similar, but TPS dose calculations showed large variations. Standardisation of the MLC configuration in TPSs is necessary. The proposed procedure can be readily applied in radiotherapy departments and can be a valuable tool in IMRT and credentialing audits.

Characterizing the interplay of treatment parameters and complexity and their impact on performance on an IROC IMRT phantom using machine learning

AIM OF THE STUDY

To elucidate the important factors and their interplay that drive performance on IMRT phantoms from the Imaging and Radiation Oncology Core (IROC).

METHODS

IROC's IMRT head and neck phantom contains two targets and an organ at risk. Point and 2D dose are measured by TLDs and film, respectively. 1,542 irradiations between 2012-2020 were retrospectively analyzed based on output parameters, complexity metrics, and treatment parameters. Univariate analysis compared parameters based on pass/fail, and random forest modeling was used to predict output parameters and determine the underlying importance of the variables.

RESULTS

The average phantom pass rate was 92% and has not significantly improved over time. The step-and-shoot irradiation technique had significantly lower pass rates that significantly affected other treatment parameters' pass rates. The complexity of plans has significantly increased with time, and all aperture-based complexity metrics (except MCS) were associated with the probability of failure. Random forest-based prediction of failure had an accuracy of 98% on held-out test data not used in model training. While complexity metrics were the most important contributors, the specific metric depended on the set of treatment parameters used during the irradiation.

CONCLUSION

With the prevalence of errors in radiotherapy, understanding which parameters affect treatment delivery is vital to improve patient treatment. Complexity metrics were strongly predictive of irradiation failure; however, they are dependent on the specific treatment parameters. In addition, the use of one complexity metric is insufficient to monitor all aspects of the treatment plan.

Dosimetric validation of Acuros® XB algorithm for RapidArc™ treatment technique: A post software upgrade analysis

Aim

To validate the Acuros^® XB (AXB) algorithm in Eclipse treatment planning system (TPS) for RapidArc™ (RA) technique following the software upgrades.

Materials and Methods

A Clinac-iX (2300CD) linear accelerator and Eclipse TPS (Varian Medical System, Inc., Palo Alto, USA) was used for commissioning of AXB algorithm using a 6 megavolts photon beam. Percentage depth dose (PDD) and profiles for field size 2 cm × 2 cm, 4 cm × 4 cm, 6 cm × 6 cm, 10 cm × 10 cm, 20 cm × 20 cm, 30 cm × 30 cm to 40 cm × 40 cm were taken. AXB calculated PDDs and profiles were evaluated against the measured and analytical anisotropic algorithm (AAA)-calculated PDDs and profiles. Test sites recommended by American Association of Physicists in Medicine task group (AAPM TG)-119 recommendation were used for RA planning and delivery verification using AXB algorithm.

Results

Dosimetric analysis of AXB calculated data showed that difference between calculated and measured data for PDD curves were maximum <1% beyond the depth of dose maximum and computed profiles in central region matches with maximum <1% for all considered field sizes. Ion-chamber measurements showed that the average confidence limit (CLs) was 0.034 and 0.020 in high-gradient and 0.047 and 0.042 in low-gradient regions, respectively, for AAA and AXB calculated RA plans. Portal measurements show the average CLs were 2.48 and 2.58 for AAA and AXB-calculated RA plans, with gamma passing criteria of 3%/3 mm.

Conclusions

AXB shows excellent agreement with measurements and AAA calculated data. The CLs were consistent with the baseline values published by TG-119. AXB algorithm has the potential to perform photon dose calculation with comparable fast calculation speed without negotiating the accuracy. AAPM TG-119 was successfully implemented to access the proper configuration of AXB algorithm following the TPS upgrade.

Photon beam modeling variations predict errors in IMRT dosimetry audits

Background & purpose:

To evaluate treatment planning system (TPS) beam modeling parameters as contributing factors to IMRT audit performance.

Materials & methods:

We retrospectively analyzed IROC Houston phantom audit performance and concurrent beam modeling survey responses from 337 irradiations performed between August 2017 and November 2019. Irradiation results were grouped based on the reporting of typical or atypical beam modeling parameter survey responses (<10th or >90th percentile values), and compared for passing versus failing (>7% error) or “poor” (>5% error) irradiation status. Additionally, we assessed the impact on the planned dose distribution from variations in modeling parameter value. Finally, we estimated the overall impact of beam modeling parameter variance on dose calculations, based on reported community variations.

Results:

Use of atypical modeling parameters were more frequently seen with failing phantom audit results (p = 0.01). Most pronounced was for Eclipse AAA users, where phantom irradiations with atypical values of dosimetric leaf gap (DLG) showed a greater incidence of both poor-performing (p = 0.048) and failing phantom audits (p = 0.014); and in general, DLG value was correlated with dose calculation accuracy (r = 0.397, p < 0.001). Manipulating TPS parameters induced systematic changes in planned dose distributions which were consistent with prior observations of how failures manifest. Dose change estimations based on these dose calculations agreed well with true dosimetric errors identified.

Conclusion:

Atypical TPS beam modeling parameters are associated with failing phantom audits. This is identified as an important factor contributing to the observed failing phantom results, and highlights the need for accurate beam modeling.

Evaluation of differences and dosimetric influences of beam models using golden and multi-institutional measured beam datasets in radiation treatment planning systems

PURPOSE

The beam model in radiation treatment planning systems (RTPSs) plays a crucial role in determining the accuracy of calculated dose distributions. The purpose of this study was to ascertain differences in beam models and their dosimetric influences when a golden beam dataset (GBD) and multi-institution measured beam datasets (MBDs) are used for beam modeling in RTPSs.

METHODS

The MBDs collected from 15 institutions, and the MBDs' beam models, were compared with a GBD, and the GBD's beam model, for Varian TrueBeam linear accelerator. The calculated dose distributions of the MBDs' beam models were compared with those of the GBD's beam model for simple geometries in a water phantom. Calculated dose distributions were similarly evaluated in volumetric modulated arc therapy (VMAT) plans for TG-119 C-shape and TG-244 head and neck, at several dose constraints of the planning target volumes (PTVs), and organs at risk.

RESULTS

The agreements of the MBDs with the GBD were almost all within ±1%. The calculated dose distributions for simple geometries in a water phantom also closely corresponded between the beam models of GBD and MBDs. Nevertheless, there were considerable differences between the beam models. The maximum differences between the mean energy of the energy spectra of GBD and MBDs were -0.12 MeV (-10.5%) in AcurosXB (AXB, Eclipse) and 0.11 MeV (7.7%) in collapsed cone convolution (CCC, RayStation). The differences in the VMAT calculated dose distributions varied for each dose region, plan, X-ray energy, and dose calculation algorithm. The ranges of the differences in the dose constraints were -5.6% to 3.0% for AXB and -24.1% to 2.8% for CCC. In several VMAT plans, the calculated dose distributions of GBD's beam model tended to be lower in high-dose regions and higher in low-dose regions than those of the MBDs' beam models.

CONCLUSIONS

We found that small differences in beam data have large impacts on the beam models, and on calculated dose distributions in clinical VMAT plan, even if beam data correspond within ±1%. GBD's beam model was not a representative beam model. The beam models of GBD and MBDs and their calculated dose distributions under clinical conditions were significantly different. These differences are most likely due to the extensive variation in the beam models, reflecting the characteristics of beam data. The energy spectrum and radial energy in the beam model varied in a wide range, even if the differences in the beam data were <±1%. To minimize the uncertainty of the calculated dose distributions in clinical plans, it was best to use the institutional MBD for beam modeling, or the beam model that ensures the accuracy of calculated dose distributions.

Sensitivity of IROC phantom performance to radiotherapy treatment planning system beam modeling parameters based on community-driven data

PURPOSE

Treatment planning system (TPS) dose calculations have previously been shown to be sensitive to modeling errors, especially when treating with complex strategies like intensity-modulated radiation therapy (IMRT). This work investigates the dosimetric impact of several dosimetric and nondosimetric beam modeling parameters, based on their distribution in the radiotherapy community, in two commercial TPSs in order to understand the realistic potential for dose deviations and their clinical effects.

METHODS AND MATERIALS

Beam models representing standard 120-leaf Varian Clinac-type machines were developed in Eclipse 13.5 (AAA algorithm) and RayStation 9A (v8.99, collapsed-cone algorithm) based upon median values of dosimetric measurements from Imaging and Radiation Oncology Core (IROC) Houston site visit data and community beam modeling parameter survey data in order to represent a baseline linear accelerator. Five clinically acceptable treatment plans (three IMRT, two VMAT) were developed for the IROC head and neck phantom. Dose distributions for each plan were recalculated after individually modifying parameters of interest (e.g., MLC transmission, percent depth doses [PDDs], and output factors) according to the 2.5th to 97.5th percentiles of community survey and machine performance data to encompass the realistic extent of variance in the radiotherapy community. The resultant dose distributions were evaluated by examining relative changes in average dose for thermoluminescent dosimeter (TLD) locations across the two target volumes and organ at risk (OAR). Interplay was also examined for parameters generating changes in target dose greater than 1%.

RESULTS

For Eclipse, dose calculations were sensitive to changes in the dosimetric leaf gap (DLG), which resulted in differences from -5% to +3% to the targets relative to the baseline beam model. Modifying the MLC transmission factor introduced differences up to ± 1%. For RayStation, parameters determining MLC behaviors likewise contributed substantially; the MLC offset introduced changes in dose from -4% to +7%, and the MLC transmission caused changes of -4% to +2%. Among the dosimetric qualities examined, changes in PDD implementation resulted in the most substantial changes, but these were only up to ±1%. Other dosimetric factors had <1% impact on dose accuracy. Interplay between impactful parameters was found to be minimal.

CONCLUSION

Factors related to the modeling of the MLC, particularly relating to the leaf offset, can cause clinically significant changes in the calculated dose for IMRT and VMAT plans. This should be of concern to the radiotherapy community because the clinical effects of poor TPS commissioning were based on reported data from clinically implemented beam models. These results further reinforce that dose errors caused by poor TPS calculations are often involved in IROC phantom failures.

Reference dataset of users' photon beam modeling parameters for the Eclipse, Pinnacle, and RayStation treatment planning systems

PURPOSE

The aim of this work was to provide a novel description of how the radiotherapy community configures treatment planning system (TPS) radiation beam models for clinically used treatment machines. Here we describe the results of a survey of self-reported TPS beam modeling parameter values across different C-arm linear accelerators, beam energies, and multileaf collimator (MLC) configurations.

ACQUISITION AND VALIDATION METHODS

Beam modeling data were acquired via electronic survey implemented through the Imaging and Radiation Oncology Core (IROC) Houston Quality Assurance Center's online facility questionnaire. The survey was open to participation from January 2018 through January 2019 for all institutions monitored by IROC. After quality control, 2818 beam models were collected from 642 institutions. This survey, designed for Eclipse, Pinnacle, and RayStation, instructed physicists to report parameter values used to model the radiation source and MLC for each treatment machine and beam energy used clinically for intensity-modulated radiation therapy. Parameters collected included the effective source/spot size, MLC transmission, dosimetric leaf gap, tongue and groove effect, and other nondosimetric parameters specific to each TPS. To facilitate survey participation, instructions were provided on how to identify requested beam modeling parameters within each TPS environment.

DATA FORMAT AND USAGE NOTES

Numeric values of the beam modeling parameters are compiled and tabulated according to TPS and calculation algorithm, linear accelerator model class, beam energy, and MLC configuration. Values are also presented as distributions, ranging from the 2.5th to the 97.5th percentile.

POTENTIAL APPLICATIONS

These data provide an independent guide describing how the radiotherapy community mathematically represents its clinical radiation beams. These distributions may be used by the community for comparison during the commissioning or verification of their TPS beam models. Ultimately, we hope that the current work will allow institutions to spot potentially suspicious parameter values and help ensure more accurate radiotherapy delivery.

Validation of the RapidArc Delivery System Using a Volumetric Phantom as Per Task Group Report 119 of the American Association of Physicists in Medicine

Aim

This study validated the RapidArc (RA) delivery using a volumetric ArcCHECK phantom as per the guidelines proposed in Task Group Report 119 from the American Association of Physicists in Medicine Task group 119 (AAPM TG 119). This study also investigated the impact of the Acuros XB (AXB) algorithm in comparison to analytical anisotropic algorithm (AAA) on the RA dose calculations in the homogeneous medium of the ArcCHECK phantom.

Materials and Methods

A volumetric ArcCHECK phantom along with AAPM TG 119 tests was used to evaluate the RA plans and verify the dose delivery for photon beam of 6 MV energy.

Results

The RA planning results were comparable and satisfied the planning criteria stated in the TG 119 report for all test cases. The average percentage gamma passing rates for the AAA-calculated plans were 98.5 (standard deviation [SD]: 0.6), 98.5 (SD: 1.3), and 98.1 (SD: 2.0) and for the AXB-calculated plans were 95.1 (SD: 1.8), 96.1 (SD: 1.3), and 94.0 (SD: 0.9) for the Clinac-iX (6 MV) and TrueBeam (TB)-STx (6 MV_filtered beam [FB] and 6 MV_flattening filter-free beam [FFFB]), respectively. For ion chamber measurements, the average percentage dose differences for the AAA-calculated plans were 1.5 (SD: 2.5), 2.7 (SD: 1.4), and 1.4(SD: 2.7) and for AXB-calculated plans were 2.3 (SD: 1.6), 3.2 (SD: 1.5), and 2.3 (SD: 2.0) for Clinac-iX (6 MV) and TB-STx (6 MV_FB and 6 MV_FFFB), respectively.

Conclusion

Thus, the ArcCHECK can successfully be utilized for the validation of the RA delivery. The AXB has potential to perform dose calculations comparable to those of the AAA for RA plans in the homogeneous medium of the ArcCHECK phantom.

Evaluation of Targeted Image-Guided Radiation Therapy Treatment Planning System by Use of American Association of Physicists in Medicine Task Group-119 Test Cases

BACKGROUND

This study aimed to evaluate the overall accuracy of the beam commissioning criteria of targeted image-guided radiation therapy (TiGRT) treatment planning system (TPS) based on the American Association of Physicists in Medicine (AAPM) Task Group Report 119 (TG-119).

METHODS

The work was performed using 6 MV energy LINAC with a variable dose rate of 200 MU/min which equipped with the high-quality external TiGRT dynamic multileaf collimator model H. The AAPM TG-119 intensity-modulated radiation therapy (IMRT) commissioning tests are composed of two preliminary tests and four clinical test cases. The clinical tests consisted of mock prostate, mock head and neck, C-shaped target, and multitarget. EDR2 film was used for evaluating the IMRT plans and point dose measured by a Pinpoint chamber positioned in slab phantom. The film analysis was done with the Sun Nuclear Corporation patient software. The dose prescription for each fraction was 200 cGy in mock prostate, mock head and neck, C-shaped target, and multitarget. Dose distributions were analyzed using gamma criteria of 3% and 2% dose difference (DD) and 3 and 2 mm distance to agreement.

RESULTS

In all test cases, the gamma criteria for 2%/2 and 3%/3 were found to be 94% and 98%, respectively. Results showed that the average gamma criteria result was in the range of 99.1% to 93% (3%/3, 2%/2) overall test cases.

CONCLUSIONS

Findings were favorable and in some tests were comparable with the other studies. The dose point values were within the mean values of the range reported by TG-119. Overall, the TiGRT TPS is needed to apply IMRT technique in radiation therapy centers.

Radiation Therapy Deficiencies Identified During On-Site Dosimetry Visits by the Imaging and Radiation Oncology Core Houston Quality Assurance Center

PURPOSE

To review the dosimetric, mechanical, and programmatic deficiencies most frequently observed during on-site visits of radiation therapy facilities by the Imaging and Radiation Oncology Core Quality Assurance Center in Houston (IROC Houston).

METHODS AND MATERIALS

The findings of IROC Houston between 2000 and 2014, including 409 institutions and 1020 linear accelerators (linacs), were compiled. On-site evaluations by IROC Houston include verification of absolute calibration (tolerance of ±3%), relative dosimetric review (tolerances of ±2% between treatment planning system [TPS] calculation and measurement), mechanical evaluation (including multileaf collimator and kilovoltage-megavoltage isocenter evaluation against Task Group [TG]-142 tolerances), and general programmatic review (including institutional quality assurance program vs TG-40 and TG-142).

RESULTS

An average of 3.1 deficiencies was identified at each institution visited, a number that has decreased slightly with time. The most common errors are tabulated and include TG-40/TG-142 compliance (82% of institutions were deficient), small field size output factors (59% of institutions had errors ≥3%), and wedge factors (33% of institutions had errors ≥3%). Dosimetric errors of ≥10%, including in beam calibration, were seen at many institutions.

CONCLUSIONS

There is substantial room for improvement of both dosimetric and programmatic issues in radiation therapy, which should be a high priority for the medical physics community. Particularly relevant was suboptimal beam modeling in the TPS and a corresponding failure to detect these errors by not including TPS data in the linac quality assurance process.

Examining credentialing criteria and poor performance indicators for IROC Houston's anthropomorphic head and neck phantom

PURPOSE

To analyze the most recent results of the Imaging and Radiation Oncology Core Houston Quality Assurance Center's (IROC-H) anthropomorphic head and neck (H&N) phantom to determine the nature of failing irradiations and the feasibility of altering credentialing criteria.

METHODS

IROC-H's H&N phantom, used for intensity-modulated radiation therapy credentialing for National Cancer Institute-sponsored clinical trials, requires that an institution's treatment plan agrees within ±7% of measured thermoluminescent dosimeter (TLD) doses; it also requires that ≥85% of pixels pass ±4 mm distance to agreement (7%/4 mm gamma analysis for film). The authors re-evaluated 156 phantom irradiations (November 1, 2014-October 31, 2015) according to the following tighter criteria: (1) 5% TLD and 5%/4 mm, (2) 5% TLD and 5%/3 mm, (3) 4% TLD and 4%/4 mm, and (4) 3% TLD and 3%/3 mm. Failure rates were evaluated with respect to individual film and TLD performance by location in the phantom. Overall poor phantom results were characterized qualitatively as systematic errors (correct shape and position but wrong magnitude of dose), setup errors/positional shifts, global but nonsystematic errors, and errors affecting only a local region.

RESULTS

The pass rate for these phantoms using current criteria was 90%. Substituting criteria 1-4 reduced the overall pass rate to 77%, 70%, 63%, and 37%, respectively. Statistical analyses indicated that the probability of noise-induced TLD failure, even at the 5% criterion, was <0.5%. Phantom failures were generally identified by TLD (≥66% failed TLD, whereas ≥55% failed film), with most failures occurring in the primary planning target volume (≥77% of cases). Results failing current criteria or criteria 1 were primarily diagnosed as systematic >58% of the time (11/16 and 21/36 cases, respectively), with a greater extent due to underdosing. Setup/positioning errors were seen in 11%-13% of all failing cases (2/16 and 4/36 cases, respectively). Local errors (8/36 cases) could only be demonstrated at criteria 1. Only three cases of global errors were identified in these analyses. For current criteria and criteria 1, irradiations that failed from film only were overwhelmingly associated with phantom shifts/setup errors (≥80% of cases).

CONCLUSIONS

This study highlighted that the majority of phantom failures are the result of systematic dosimetric discrepancies between the treatment planning system and the delivered dose. Further work is necessary to diagnose and resolve such dosimetric inaccuracy. In addition, the authors found that 5% TLD and 5%/4 mm gamma criteria may be both practically and theoretically achievable as an alternative to current criteria.