Three commercial metal artifact reduction methods were evaluated for use in computed tomography (CT) imaging in the presence of clinically realistic metal implants: Philips O-MAR, GE's monochromatic ...gemstone spectral imaging (GSI) using dual-energy CT, and GSI monochromatic imaging with metal artifact reduction software applied (MARs). Each method was evaluated according to CT number accuracy, metal size accuracy, and streak artifact severity reduction by using several phantoms, including three anthropomorphic phantoms containing metal implants (hip prosthesis, dental fillings and spinal fixation rods). All three methods showed varying degrees of success for the hip prosthesis and spinal fixation rod cases, while none were particularly beneficial for dental artifacts. Limitations of the methods were also observed. MARs underestimated the size of metal implants and introduced new artifacts in imaging planes beyond the metal implant when applied to dental artifacts, and both the O-MAR and MARs algorithms induced artifacts for spinal fixation rods in a thoracic phantom. Our findings suggest that all three artifact mitigation methods may benefit patients with metal implants, though they should be used with caution in certain scenarios.
Purpose
To evaluate the performance of an independent recalculation and compare it against current measurement‐based patient specific intensity‐modulated radiation therapy (IMRT) quality assurance ...(QA) in predicting unacceptable phantom results as measured by the Imaging and Radiation Oncology Core (IROC).
Methods
When institutions irradiate the IROC head and neck IMRT phantom, they are also asked to submit their internal IMRT QA results. Separately from this, IROC has previously created reference beam models on the Mobius3D platform to independently recalculate phantom results based on the institution's DICOM plan data. The ability of the institutions’ IMRT QA to predict the IROC phantom result was compared against the independent recalculation for 339 phantom results collected since 2012. This was done to determine the ability of these systems to detect failing phantom results (i.e., large errors) as well as poor phantom results (i.e., modest errors). Sensitivity and specificity were evaluated using common clinical thresholds, and receiver operator characteristic (ROC) curves were used to compare across different thresholds.
Results
Overall, based on common clinical criteria, the independent recalculation was 12 times more sensitive at detecting unacceptable (failing) IROC phantom results than clinical measurement‐based IMRT QA. The recalculation was superior, in head‐to‐head comparison, to the EPID, ArcCheck, and MapCheck devices. The superiority of the recalculation vs these array‐based measurements persisted under ROC analysis as the recalculation curve had a greater area under it and was always above that for these measurement devices. For detecting modest errors (poor phantom results rather than failing phantom results), neither the recalculation nor measurement‐based IMRT QA performed well.
Conclusions
A simple recalculation outperformed current measurement‐based IMRT QA methods at detecting unacceptable plans. These findings highlight the value of an independent recalculation, and raise further questions about the current standard of measurement‐based IMRT QA.
Full text
Available for:
BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
The purpose of this study was to summarize the findings of anthropomorphic proton phantom irradiations analyzed by the Imaging and Radiation Oncology Core Houston QA Center (IROC Houston).
A total of ...103 phantoms were irradiated by proton therapy centers participating in clinical trials. The anthropomorphic phantoms simulated heterogeneous anatomy of a head, liver, lung, prostate, and spine. Treatment plans included those for scattered, uniform scanning, and pencil beam scanning beam delivery modalities using 5 different treatment planning systems. For every phantom irradiation, point doses and planar doses were measured using thermoluminescent dosimeters (TLD) and film, respectively. Differences between measured and planned doses were studied as a function of phantom, beam delivery modality, motion, repeat attempt, treatment planning system, and date of irradiation.
The phantom pass rate (overall, 79%) was high for simple phantoms and lower for phantoms that introduced higher levels of difficulty, such as motion, multiple targets, or increased heterogeneity. All treatment planning systems overestimated dose to the target, compared to TLD measurements. Errors in range calculation resulted in several failed phantoms. There was no correlation between treatment planning system and pass rate. The pass rates for each individual phantom are not improving over time, but when individual institutions received feedback about failed phantom irradiations, pass rates did improve.
The proton phantom pass rates are not as high as desired and emphasize potential deficiencies in proton therapy planning and/or delivery. There are many areas for improvement with the proton phantom irradiations, such as treatment planning system dose agreement, range calculations, accounting for motion, and irradiation of multiple targets.
Full text
Available for:
GEOZS, IJS, NUK, OILJ, UL, UM, UPUK
Purpose
Between July 2013 and August 2019, 22% of the imaging and radiation oncology core (IROC) spine, and 15% of the moving lung phantom irradiations have failed to meet established acceptability ...criteria. The spine phantom simulates a highly modulated stereotactic body radiation therapy (SBRT) case, whereas the lung phantom represents a low‐to‐none modulation moving target case. In this study, we assessed the contribution of dose calculation errors to these phantom results and evaluated their effects on failure rates.
Methods
We evaluated dose calculation errors by comparing the calculation accuracy of various institutions’ treatment planning systems (TPSs) vs IROC‐Houston’s previously established independent dose recalculation system (DRS). Each calculation was compared with the measured dose actually delivered to the phantom; cases in which the recalculation was more accurate were interpreted as a deficiency in the institution's TPS. A total of 258 phantom irradiation plans (172 lung and 86 spine) were recomputed.
Results
Overall, the DRS performed better than the TPSs in 47% of the spine phantom cases. However, the DRS was more accurate in 93% of failing spine phantom cases (with an average improvement of 2.35%), indicating a deficiency in the institution's treatment planning system. Deficiencies in dose calculation accounted for 60% of the overall discrepancy between measured and planned doses among spine phantoms. In contrast, lung phantom DRS calculations were more accurate in only 35% and 42% of all and failing lung phantom cases respectively, indicating that dose calculation errors were not substantially present. These errors accounted for only 30% of the overall discrepancy between measured and planned doses.
Conclusions
Dose calculation errors are common and substantial in IROC spine phantom irradiations, highlighting a major failure mode in this phantom and in clinical treatment management of these cases. In contrast, dose calculation accuracy had only a minimal contribution to failing lung phantom results, indicating that other failure modes drive problems with this phantom and similar clinical treatments.
Full text
Available for:
BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Purpose
To create a snapshot of common practices for 3D‐CRT and intensity‐modulated radiation therapy (IMRT) QA through a large‐scale survey and compare to TG‐218 recommendations.
Methods
A survey of ...3D‐CRT and IMRT QA was constructed at and distributed by the IROC‐Houston QA center to all institutions monitored by IROC (n = 2,861). The first part of the survey asked about methods to check dose delivery for 3D‐CRT. The bulk of the survey focused on IMRT QA, inquiring about treatment modalities, standard tools used to verify planned dose, how assessment of agreement is calculated and the comparison criteria used, and the strategies taken if QA fails.
Results
The most common tools for dose verification were a 2D diode array (52.8%), point(s) measurement (39.0%), EPID (27.4%), and 2D ion chamber array (23.9%). When IMRT QA failed, the highest average rank strategy utilized was to remeasure with the same setup, which had an average position ranking of 1.1 with 90.4% of facilities employing this strategy. The second highest average ranked strategy was to move to a new calculation point and remeasure (54.9%); this had an average ranking of 2.1.
Conclusion
The survey provided a snapshot of the current state of dose verification for IMRT radiotherapy. The results showed variability in approaches and that work is still needed to unify and tighten criteria in the medical physics community, especially in reference to TG‐218's recommendations.
Full text
Available for:
FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
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.
Full text
Available for:
GEOZS, IJS, NUK, OILJ, UL, UM, UPUK
Since the publication of AAPM Task Group (TG) 148 on quality assurance (QA) for helical tomotherapy, there have been many new developments on the tomotherapy platform involving treatment delivery, ...on‐board imaging options, motion management, and treatment planning systems (TPSs). In response to a need for guidance on quality control (QC) and QA for these technologies, the AAPM Therapy Physics Committee commissioned TG 306 to review these changes and make recommendations related to these technology updates. The specific objectives of this TG were (1) to update, as needed, recommendations on tolerance limits, frequencies and QC/QA testing methodology in TG 148, (2) address the commissioning and necessary QA checks, as a supplement to Medical Physics Practice Guidelines (MPPG) with respect to tomotherapy TPS and (3) to provide risk‐based recommendations on the new technology implemented clinically and treatment delivery workflow. Detailed recommendations on QA tests and their tolerance levels are provided for dynamic jaws, binary multileaf collimators, and Synchrony motion management. A subset of TPS commissioning and QA checks in MPPG 5.a. applicable to tomotherapy are recommended. In addition, failure mode and effects analysis has been conducted among TG members to obtain multi‐institutional analysis on tomotherapy‐related failure modes and their effect ranking.
Full text
Available for:
BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, 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.
Full text
Available for:
BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
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.
Full text
Available for:
BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
PDF
