PurposeData errors caught late in treatment planning require time to correct, resulting in delays up to 1 week. In this work, we identify causes of data errors in treatment planning and develop a software tool that detects them early in the planning workflow.MethodsTwo categories of errors were studied: data transfer errors and TPS errors. Using root cause analysis, the causes of these errors were determined. This information was incorporated into a software tool which uses ODBC‐SQL service to access TPS's Postgres and Mosaiq MSSQL databases for our clinic. The tool then uses a read‐only FTP service to scan the TPS unix file system for errors. Detected errors are reviewed by a physicist. Once confirmed, clinicians are notified to correct the error and educated to prevent errors in the future. Time‐cost analysis was performed to estimate the time savings of implementing this software clinically.ResultsThe main errors identified were incorrect patient entry, missing image slice, and incorrect DICOM tag for data transfer errors and incorrect CT‐density table application, incorrect image as reference CT, and secondary image imported to incorrect patient for TPS errors. The software has been running automatically since 2015. In 2016, 84 errors were detected with the most frequent errors being incorrect patient entry (35), incorrect CT‐density table (17), and missing image slice (16). After clinical interventions to our planning workflow, the number of errors in 2017 decreased to 44. Time savings in 2016 with the software is estimated to be 795 h. This is attributed to catching errors early and eliminating the need to replan cases.ConclusionsNew QA software detects errors during planning, improving the accuracy and efficiency of the planning process. This important QA tool focused our efforts on the data communication processes in our planning workflow that need the most improvement.

We investigate the relationship between the various parameters in the Monaco MLC model and dose calculation accuracy for an Elekta Agility MLC. The vendor‐provided MLC modeling procedure — completed first with external vendor participation and then exclusively in‐house — was used in combination with our own procedures to investigate several sets of MLC modeling parameters to determine their effect on dose distributions and point‐dose measurements. Simple plans provided in the vendor procedure were used to elucidate specific mechanical characteristics of the MLC, while ten complex treatment plans — five IMRT and five VMAT — created using TG‐119‐based structure sets were used to test clinical dosimetric effects of particular parameter choices. EDR2 film was used for the vendor fields to give high spatial resolution, while a combination of MapCHECK and ion chambers were used for the in‐house TG‐119‐based procedures. The vendor‐determined parameter set provided a reasonable starting point for the MLC model and largely delivered acceptable gamma pass rates for clinical plans — including a passing external evaluation using the IROC H&N phantom. However, the vendor model did not provide point‐dose accuracy consistent with that seen in other treatment systems at our center. Through further internal testing it was found that there existed many sets of MLC parameters, often at opposite ends of their allowable ranges, that provided similar dosimetric characteristics and good agreement with planar and point‐dose measurements. In particular, the leaf offset and tip leakage parameters compensated for one another if adjusted in opposite directions, which provided a level curve of acceptable parameter sets across all plans. Interestingly, gamma pass rates of the plans were less dependent upon parameter choices than point‐dose measurements, suggesting that MLC modeling using only gamma evaluation may be generally an insufficient approach. It was also found that exploring all parameters of the very robust MLC model to find the best match to the vendor‐provided QA fields can reduce the pass rates of the TG‐119‐based clinical distributions as compared to simpler models. A wide variety of parameter sets produced MLC models capable of meeting RPC passing criteria for their H&N IMRT phantom. The most accurate models were achievable using a combination of vendor‐provided and in‐house procedures. The potential existed for an over‐modeling of the Agility MLC in an effort to obtain the fine structure of certain quality assurance fields, which led to a reduction in agreement between calculation and measurement of more typical clinical dose distributions.PACS number(s): 87.56.nk, 87.53.Kn, 87.55.km, 87.55.Qr

Similar to what has been found in the Gamma Knife Perfexion, the PTW microDiamond over-responds in the smallest 4 mm field. The over-response can be corrected via the Alfonso formalism using the correction factors determined in this work. Using the MC calculated correction factors, the PTW microDiamond detector is an effective dosimeter in all available helmet sizes.

A comprehensive end‐to‐end test for head and neck IMRT treatments was developed using a custom phantom designed to utilize multiple dosimetry devices. Initial end‐to‐end test and custom H&N phantom were designed to yield maximum information in anatomical regions significant to H&N plans with respect to: (i) geometric accuracy, (ii) dosimetric accuracy, and (iii) treatment reproducibility. The phantom was designed in collaboration with Integrated Medical Technologies. The phantom was imaged on a CT simulator and the CT was reconstructed with 1 mm slice thickness and imported into Varian's Eclipse treatment planning system. OARs and the PTV were contoured with the aid of Smart Segmentation. A clinical template was used to create an eight‐field IMRT plan and dose was calculated with heterogeneity correction on. Plans were delivered with a TrueBeam equipped with a high definition MLC. Preliminary end‐to‐end results were measured using film, ion chambers, and optically stimulated luminescent dosimeters (OSLDs). Ion chamber dose measurements were compared to the treatment planning system. Films were analyzed with FilmQA Pro using composite gamma index. OSLDs were read with a MicroStar reader using a custom calibration curve. Final phantom design incorporated two axial and one coronal film planes with 18 OSLD locations adjacent to those planes as well as four locations for IMRT ionization chambers below inferior film plane. The end‐to‐end test was consistently reproducible, resulting in average gamma pass rate greater than 99% using 3normal%/3 mm analysis criteria, and average OSLD and ion chamber measurements within 1% of planned dose. After initial calibration of OSLD and film systems, the end‐to‐end test provides next‐day results, allowing for integration in routine clinical QA. Preliminary trials have demonstrated that our end‐to‐end is a reproducible QA tool that enables the ongoing evaluation of dosimetric and geometric accuracy of clinical head and neck treatments.PACS number(s): 87.55.Qr