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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.

The purpose of this study was to introduce a three‐field monoisocentric inverse treatment planning method without half‐beam blocks for breast cancer radiation treatments. Three‐field monoisocentric breast treatment planning with half‐beam blocks limits the tangential field length to 20 cm. A dual‐isocenter approach accommodates patients with larger breasts, but prolongs treatment time and may introduce dose uncertainty at the matching plane due to daily setup variations. We developed a novel monoisocentric, three‐field treatment planning method without half‐beam blocking. The new beam‐matching method utilizes the full field size with a single isocenter. Furthermore, an open/IMRT hybrid inverse optimization method was employed to improve dose uniformity and coverage. Geometric beam matching was achieved by rotating the couch, collimator, and gantry together. Formulae for three‐field geometric matching were derived and implemented in Pinnacle scripts. This monoisocentric technique can be used for patients with larger breast size. The new method has no constraints on the length of tangential fields. Compared with the dual‐isocenter method, it can significantly reduce patient setup time and uncertainties.PACS number: 87.55.D‐

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Purpose: A collaborative quality initiative (CQI) has been developed in the state of Michigan to assess physician and patient reported outcomes to compare conformal and IMRT techniques for a specific cohort of breast and lung cancer patients. Here, we present a web‐based database that was designed to collect planning and delivery information to facilitate analysis of outcomes for the CQI. Methods: A web‐based database was built to capture key physics information, including dose that may be related to acute toxicities. An annual institutional questionnaire captures the technology available for these patients. A patient‐specific survey collects simulation, planning, and delivery information. To overcome differences in DVH file formats, a simple interface was developed where the user selects from a structure list, submits numeric data, and reviews the data summary. To analyze the delivery type, DICOM‐RT plan files are uploaded via a web interface. The data are anonymized and displayed for the user to verify that no protected health information is submitted. Results: Initial partner institutions tested and provided feedback on all aspects of the physics data collection. Institutions have shared customized programs for extracting DVH and DICOM‐RT data and documents for electronic workflow. Data submission began via the web portal in April 2012. There are 4 planning systems represented among the 14 institutions. Delivery techniques include static, dynamic and segmental MLC, Tomotherapy, and VMAT. As of February, data have been submitted for approximately 80% of the 815 eligible cases. Centers will be audited for data quality once per year. Conclusion: A system has been designed to capture high integrity simulation, plan, and delivery data for a CQI focused on breast and lung cancer. This information will be used to quantitatively evaluate the use of IMRT techniques in the state of Michigan and to permit dose‐based correlations to physician and patient‐rated toxicities. This work was funded by Blue Cross Blue Shield of Michigan.