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• W2022785682 abstract "Arguing against the Proposition is Andrea Molineu, M.S. Ms. Molineu obtained her M.S. in Medical Physics from the University of Kentucky, Lexington in 1999 and then moved to the Department of Radiation Oncology, St. Elizabeth's Medical Center, Boston, where she held a Medical Physicist appointment until 2001. She then moved to the Radiological Physics Center, Department of Radiation Physics, Division of Radiation Oncology, UT M. D. Anderson Cancer Center, Houston, TX, where she is currently a Senior Medical Physicist and Associate Director of the MD Anderson Phantom Laboratory. She is certified by the American Board of Radiology in Therapeutic Radiological Physics and her major research interests include anthropomorphic phantoms and radiotherapy QA, especially IMRT. She is a member of many AAPM committees and Task Groups and is the current Chair of the Working Group on Clinical Trials. “Patient-specific QA” is a misnomer. What we really need is “Quality Control (QC)”.1 Every service for each patient is tested to ensure that it meets our safety and quality specifications. There is general agreement that, in IMRT, the specification is that the actual delivered dose (or location) should be within 3% (or 3 mm) of that planned. But what is the actual dose? Film measurements are reliable only to within 5%. Diode arrays are typically only used on a beam-by- beam basis and provide no composite information, leading to a lack of predictive power for “clinically relevant patient dose errors.”2 When arrays are used in a composite setting, there are inaccuracies due to anisotropy of response with gantry angle. Also, arrays are low-resolution devices that could potentially miss errors in un-sampled areas. Apart from measurement inaccuracies, there is also the issue of troubleshooting combined system measurements. If something is wrong, how do you know which subsystem has the problem? Is it the linear accelerator? Or has the treatment planning system been pushed to the limits of beam modeling accuracy? Measured IMRT QA cannot parse the errors from the treatment database, planning system, and linear accelerator. An approach that solves these issues is to treat each subsystem separately. QA is performed on the delivery system at a high enough frequency to ensure that the system is operating as needed to achieve the accuracy required for IMRT.3 These tests should be done regardless of the number of patients receiving IMRT. QC is performed on the patient's planned dose distributions by using an independent, secondary, composite dose calculation system. Absolute dose is calculated using treatment planning system (TPS)-determined radiological depths to a single point. Treatment beam parameters used in the calculation are taken from the treatment delivery database. QC is also performed on the patient's treatment delivery parameters in the delivery system's database, to ensure that they match the values in the treatment plan. The patient-specific portion of “IMRT QA” can be done in software.4 This has the advantage of a quick turnaround on IMRT plan checks, reducing this from 2 h down to just 15 min. Every patient is checked, avoiding QA models that sample a few IMRT cases. We have used this method at the University of Iowa, where ROC tests, using 100 retrospective IMRT cases and 8 physicists, confirmed that our calculated “virtual film” allowed us to make better decisions than those made with film measurements.5 This is consistent with studies showing the potential for calculations to replace measurements via control charts.6 Furthermore, every time our calculation showed possible errors, subsequent film measurements confirmed our results. We have been successfully using this method and providing more consistent treatment planning quality control for all our IMRT patients for over five years. Why do we do patient-specific QA for IMRT? None of us wants to have the kind of errors reported by the New York Times or any smaller, yet dosimetrically significant, inaccuracies.7 We want to ensure that the treatment we deliver is close enough to the plan we created that the patient receives the desired clinical outcome. For static 3D conformal radiotherapy fields, this can easily be achieved using software methods, because the shaped fields are defined by the user to be something that the planning system was commissioned to accurately model. The complexity and inverse planning aspects of IMRT QA, however, require a more robust mechanism to verify that all of the small fields that are delivered have been modeled well enough so that they add together to achieve the expected dose. The dynamic aspect of the delivery along with the possibility of large dosimetric impacts due to small size differences in small fields means that we also want to verify that the planned delivery is physically achievable by the delivery system, i.e., that all of the moving parts are able to position themselves in ways that are fast enough and accurate enough to produce the planned delivery. For this type of verification we turn to hardware, specifically measurement. Reports that often-used verification techniques may not adequately predict clinically meaningful differences may make us eager to get rid of the measurements, because we all want to spend our limited time and resources in efficient, effective ways.2,8 However, in a report on over 13 000 plans, an analysis showed that 2.3% of the patient-specific IMRT measurements did not meet the passing criteria, and the Radiologic Physics Center has reported a pass rate of only 82% for their independent head and neck phantom measurements, so we know that not all plans meet our standards and that not all treatments are delivered as planned.9,10 Measurement is still our best way to discover this before treating a patient with a plan that does not meet our delivery criteria, so we should work to improve our measurements, as well as our analysis, rather than rush to dismiss measurement. Measurement and analysis depend heavily on software, and we should take advantage of appropriate software advances. One such recent advance is the ability to use measurements to recalculate DVHs. This can detect clinically relevant dose errors better than the widely used gamma criteria.11,12 While we should be careful not to become overly dependent on computer technologies to the point that we are unable to detect mistakes or unintended outcomes of software that are certain to occur, we should continue to look for ways for software to improve how we spend our time.13 Though software developments are important, we are not ready to abandon all measurements for patient-specific IMRT QA. Measurement gives us the best method to confirm that the plan we created can be delivered accurately. Yes, incorporate meaningful software, analyze wisely, and improve types of measurements. But it is not yet the time to get rid of measurements. IMRT QA must be considered in two parts: the periodic QA for the system, and the QC for each patient. When commissioning the planning system, small field and MU limits for the desired accuracy are determined; dosimetrists must respect those limits. Verifying those limits requires measurement as part of the system QA. Checking that dosimetrists follow the constraints does not require measurement. The types of errors reported in the New York Times7 can be detected by software methods for verifying data transfers.14 As for small field models, most discrepancies occur in the penumbral toe and tails. If the independent calculation uses a different model in this region from the planning system, a large number of small fields will yield differences large enough to catch the problem. Also, these regions can be modeled accurately in a solid water phantom.5 With respect to the IMRT delivery capabilities of the Linac, these can be verified on a periodic basis as part of the system QA. Once the limitations of the Linac have been identified at commissioning, they can be incorporated as constraints in the planning system or in the physics plan check (QC). Separating TPS QA and QC from linac QA provides a more accurate view of the IMRT system's ability to deliver the desired quality, since the source of errors can be more readily identified and efficiently monitored. I am quite sure that most of the centers that failed the RPC credentialing tests used measurement-based methods (calculation methods are not widely implemented). While improving measurement based methods may solve these issues, developing robust 2D calculation QA could also provide a solution, while simultaneously making the process more efficient and cost-effective. (Our institution passed, by the way.) However, I do not advocate eagerly abandoning measurements. One must carefully verify through measurement that a calculation based QC process works as well as or better than hardware methods, as we did with our ROC testing. While it may not yet be time to eliminate measurements, it is always timely to improve our IMRT QA and QC processes. We agree that efficiencies in patient-specific QA should be found and employed when appropriate. However, I am not willing to automatically write off differences between secondary calculations and measurements as inaccuracies in measurements rather than inaccuracies in the dose calculations. We should have an understanding of why we sometimes get positive results with film and not with software calculations. Are those results truly false positives? Assuming measurement inaccuracies only for false positives, without addressing why we do not uniformly see inaccuracies, is an insufficient reason to choose software checks over measurements. We should investigate whether there is something unique or different about those cases that explains having measurement inaccuracy that would not also logically predict the same inaccuracy in the true negative cases. As the RPC's head and neck phantom data from 2012 indicates,10 we are still having problems accurately modeling and commissioning our primary treatment planning systems to accurately predict all of the complexities that are present in some patient treatments. There is no reason to think that a secondary system, which is not currently an option for many clinics, would not have many of the same differences. Certainly statistical process control can and should be implemented in software checks as well as measurements, which should improve both our accuracy and efficiency. Measurements have limitations that we should understand, but I am not convinced that we are ready to summarily throw out patient-specific measurements." @default.
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• W2022785682 title "Patient-specific QA for IMRT should be performed using software rather than hardware methods" @default.
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