Program Information
SafetyNet: Automating Radiotherapy QA with An Event Driven Framework
S Hadley1*, M Kessler2 , D Litzenberg3 , C Lee4 , J Irrer5 , X Chen6 , E Acosta7 , G Weyburne8 , W Keranen9 , K Lam10 , E Covington11 , K Younge12 , M Matuszak13 , J Moran14 , (1) The University of Michigan, Ann Arbor, MI, (2) The University of Michigan, Ann Arbor, MI, (3) Univ Michigan, Ann Arbor, MI, (4) University of Michigan, Ann Arbor, MI, (5) University of Michigan, Ann Arbor, Mi, (6) University of Michigan, Ann Arbor, MI, (7) University of Michigan, Ann Arbor, MI, (8) University of Michigan, Ann Arbor, Michigan, (9) Varian Medical Systems, Palo Alto, California, (10) University of Michigan, Ann Arbor, MI, (11) University of Michigan Hospital and Health System, Ann Arbor, MI, (12) University of Michigan, Ann Arbor, MI, (13) University of Michigan, Ann Arbor, MI, (14) Univ Michigan Medical Center, Ann Arbor, MI
Presentations
WE-G-BRA-2 (Wednesday, July 15, 2015) 4:30 PM - 6:00 PM Room: Ballroom A
Purpose: Quality assurance is an essential task in radiotherapy that often requires many manual tasks. We investigate the use of an event driven framework in conjunction with software agents to automate QA and eliminate wait times.
Methods: An in house developed subscription-publication service, EventNet, was added to the Aria OIS to be a message broker for critical events occurring in the OIS and software agents. Software agents operate without user intervention and perform critical QA steps. The results of the QA are documented and the resulting event is generated and passed back to EventNet. Users can subscribe to those events and receive messages based on custom filters designed to send passing or failing results to physicists or dosimetrists. Agents were developed to expedite the following QA tasks: Plan Revision, Plan 2nd Check, SRS Winston-Lutz isocenter, Treatment History Audit, Treatment Machine Configuration.
Results: Plan approval in the Aria OIS was used as the event trigger for plan revision QA and Plan 2nd check agents. The agents pulled the plan data, executed the prescribed QA, stored the results and updated EventNet for publication. The Winston Lutz agent reduced QA time from 20 minutes to 4 minutes and provided a more accurate quantitative estimate of radiation isocenter. The Treatment Machine Configuration agent automatically reports any changes to the Treatment machine or HDR unit configuration. The agents are reliable, act immediately, and execute each task identically every time.
Conclusion: An event driven framework has inverted the data chase in our radiotherapy QA process. Rather than have dosimetrists and physicists push data to QA software and pull results back into the OIS, the software agents perform these steps immediately upon receiving the sentinel events from EventNet.
Funding Support, Disclosures, and Conflict of Interest: Mr Keranen is an employee of Varian Medical Systems Dr. Moran's institution receives research support for her effort for a linear accelerator QA project from Varian Medical Systems. Other quality projects involving her effort are funded by Blue Cross Blue Shield of Michigan, Breast Cancer Research Foundation, and the NIH.
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