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      Novel methodologies for dosimetry audits: Adapting to advanced radiotherapy techniques


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          With new radiotherapy techniques, treatment delivery is becoming more complex and accordingly, these treatment techniques require dosimetry audits to test advanced aspects of the delivery to ensure best practice and safe patient treatment.

          This review of novel methodologies for dosimetry audits for advanced radiotherapy techniques includes recent developments and future techniques to be applied in dosimetry audits. Phantom-based methods (i.e. phantom-detector combinations) including independent audit equipment and local measurement equipment as well as phantom-less methods (i.e. portal dosimetry, transmission detectors and log files) are presented and discussed. Methodologies for both conventional linear accelerator (linacs) and new types of delivery units, i.e. Tomotherapy, stereotactic devices and MR-linacs, are reviewed.

          Novel dosimetry audit techniques such as portal dosimetry or log file evaluation have the potential to allow parallel auditing (i.e. performing an audit at multiple institutions at the same time), automation of data analysis and evaluation of multiple steps of the radiotherapy treatment chain. These methods could also significantly reduce the time needed for audit and increase the information gained. However, to maximise the potential, further development and harmonisation of dosimetry audit techniques are required before these novel methodologies can be applied.

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          Per-beam, planar IMRT QA passing rates do not predict clinically relevant patient dose errors.

          The purpose of this work is to determine the statistical correlation between per-beam, planar IMRT QA passing rates and several clinically relevant, anatomy-based dose errors for per-patient IMRT QA. The intent is to assess the predictive power of a common conventional IMRT QA performance metric, the Gamma passing rate per beam. Ninety-six unique data sets were created by inducing four types of dose errors in 24 clinical head and neck IMRT plans, each planned with 6 MV Varian 120-leaf MLC linear accelerators using a commercial treatment planning system and step-and-shoot delivery. The error-free beams/plans were used as "simulated measurements" (for generating the IMRT QA dose planes and the anatomy dose metrics) to compare to the corresponding data calculated by the error-induced plans. The degree of the induced errors was tuned to mimic IMRT QA passing rates that are commonly achieved using conventional methods. Analysis of clinical metrics (parotid mean doses, spinal cord max and D1cc, CTV D95, and larynx mean) vs. IMRT QA Gamma analysis (3%/3 mm, 2/2, 1/1) showed that in all cases, there were only weak to moderate correlations (range of Pearson's r-values: -0.295 to 0.653). Moreover, the moderate correlations actually had positive Pearson's r-values (i.e., clinically relevant metric differences increased with increasing IMRT QA passing rate), indicating that some of the largest anatomy-based dose differences occurred in the cases of high IMRT QA passing rates, which may be called "false negatives." The results also show numerous instances of false positives or cases where low IMRT QA passing rates do not imply large errors in anatomy dose metrics. In none of the cases was there correlation consistent with high predictive power of planar IMRT passing rates, i.e., in none of the cases did high IMRT QA Gamma passing rates predict low errors in anatomy dose metrics or vice versa. There is a lack of correlation between conventional IMRT QA performance metrics (Gamma passing rates) and dose errors in anatomic regions-of-interest. The most common acceptance criteria and published actions levels therefore have insufficient, or at least unproven, predictive power for per-patient IMRT QA.
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            Moving from gamma passing rates to patient DVH-based QA metrics in pretreatment dose QA.

            The purpose of this work is to explore the usefulness of the gamma passing rate metric for per-patient, pretreatment dose QA and to validate a novel patient-dose∕DVH-based method and its accuracy and correlation. Specifically, correlations between: (1) gamma passing rates for three 3D dosimeter detector geometries vs clinically relevant patient DVH-based metrics; (2) Gamma passing rates of whole patient dose grids vs DVH-based metrics, (3) gamma passing rates filtered by region of interest (ROI) vs DVH-based metrics, and (4) the capability of a novel software algorithm that estimates corrected patient Dose-DVH based on conventional phantom QA data are analyzed. Ninety six unique "imperfect" step-and-shoot IMRT plans were generated by applying four different types of errors on 24 clinical Head∕Neck patients. The 3D patient doses as well as the dose to a cylindrical QA phantom were then recalculated using an error-free beam model to serve as a simulated measurement for comparison. Resulting deviations to the planned vs simulated measured DVH-based metrics were generated, as were gamma passing rates for a variety of difference∕distance criteria covering: dose-in-phantom comparisons and dose-in-patient comparisons, with the in-patient results calculated both over the whole grid and per-ROI volume. Finally, patient dose and DVH were predicted using the conventional per-beam planar data as input into a commercial "planned dose perturbation" (PDP) algorithm, and the results of these predicted DVH-based metrics were compared to the known values. A range of weak to moderate correlations were found between clinically relevant patient DVH metrics (CTV-D95, parotid D(mean), spinal cord D1cc, and larynx D(mean)) and both 3D detector and 3D patient gamma passing rate (3%∕3 mm, 2%∕2 mm) for dose-in-phantom along with dose-in-patient for both whole patient volume and filtered per-ROI. There was considerable scatter in the gamma passing rate vs DVH-based metric curves. However, for the same input data, the PDP estimates were in agreement with actual patient DVH results. Gamma passing rate, even if calculated based on patient dose grids, has generally weak correlation to critical patient DVH errors. However, the PDP algorithm was shown to accurately predict the DVH impact using conventional planar QA results. Using patient-DVH-based metrics IMRT QA allows per-patient dose QA to be based on metrics that are both sensitive and specific. Further studies are now required to analyze new processes and action levels associated with DVH-based metrics to ensure effectiveness and practicality in the clinical setting.
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              Evaluating IMRT and VMAT dose accuracy: practical examples of failure to detect systematic errors when applying a commonly used metric and action levels.

              This study (1) examines a variety of real-world cases where systematic errors were not detected by widely accepted methods for IMRT/VMAT dosimetric accuracy evaluation, and (2) drills-down to identify failure modes and their corresponding means for detection, diagnosis, and mitigation. The primary goal of detailing these case studies is to explore different, more sensitive methods and metrics that could be used more effectively for evaluating accuracy of dose algorithms, delivery systems, and QA devices.

                Author and article information

                Phys Imaging Radiat Oncol
                Phys Imaging Radiat Oncol
                Physics and Imaging in Radiation Oncology
                19 March 2018
                January 2018
                19 March 2018
                : 5
                : 76-84
                [a ]Lake Constance Radiation Oncology Center Singen-Friedrichshafen, Germany
                [b ]Department of Medical Physics, Hospital Sant Joan de Reus, IISPV, Tarragona, Spain
                [c ]Servei de RadiofísicaiRadioprotecció, Hospital de la Santa CreuiSant Pau, Spain
                [d ]Department of Medical Physics, Royal Surrey County Hospital, Guildford, Surrey, UK
                [e ]Metrology for Medical Physics (MEMPHYS), National Physical Laboratory, Teddington, Middlesex, UK
                Author notes
                [* ]Corresponding author. pasler@ 123456strahlentherapie-fn.de
                © 2018 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                : 29 September 2017
                : 8 March 2018
                : 8 March 2018
                Review Article


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