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SU‐E‐T‐186: Cloud‐Based Quality Assurance Application for Linear Accelerator Commissioning
Author(s) -
Rogers J
Publication year - 2015
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4924547
Subject(s) - quality assurance , data collection , linear particle accelerator , computer science , outlier , cloud computing , beam (structure) , data mining , reliability engineering , mathematics , engineering , statistics , physics , optics , artificial intelligence , operating system , operations management , external quality assessment
Purpose: To identify anomalies and safety issues during data collection and modeling for treatment planning systems Methods: A cloud‐based quality assurance system (AQUIRE ‐ Automated QUalIty REassurance) has been developed to allow the uploading and analysis of beam data aquired during the treatment planning system commissioning process. In addition to comparing and aggregating measured data, tools have also been developed to extract dose from the treatment planning system for end‐to‐end testing. A gamma index is perfomed on the data to give a dose difference and distance‐to‐agreement for validation that a beam model is generating plans consistent with the beam data collection. Results: Over 20 linear accelerators have been commissioning using this platform, and a variety of errors and potential saftey issues have been caught through the validation process. For example, the gamma index of 2% dose, 2mm DTA is quite sufficient to see curves not corrected for effective point of measurement. Also, data imported into the database is analyzed against an aggregate of similar linear accelerators to show data points that are outliers. The resulting curves in the database exhibit a very small standard deviation and imply that a preconfigured beam model based on aggregated linear accelerators will be sufficient in most cases. Conclusion: With the use of this new platform for beam data commissioning, errors in beam data collection and treatment planning system modeling are greatly reduced. With the reduction in errors during acquisition, the resulting beam models are quite similar, suggesting that a common beam model may be possible in the future. Development is ongoing to create routine quality assurance tools to compare back to the beam data acquired during commissioning. I am a medical physicist for Alzyen Medical Physics, and perform commissioning services