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Program Information

Analysis of Accelerator Generated Text Logs for Preemptive Maintenance

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A Baydush

CM Able1 , AH Baydush1*, C Nguyen1 , J Gersh2 , A Ndlovu3 , I Rebo3 , J Booth4 , M Perez4 , B Sintay5 ,MT Munley1 , (1) Wake Forest School of Medicine, Department of Radiation Oncology, Winston Salem, NC, (2) Gibbs Cancer Center and Research Institute, Spartenburg Regional Medical Ce, Spartenburg, SC, (3) John Theuer Cancer Center, Hackensack University Medical Center, Hackensack, NJ, (4) North Sydney Cancer Center, Royal North Shore Hospital, Sydney, St Leonards, (5) Cone Health Cancer Center, Greensboro, NC


SU-C-BRD-3 Sunday 1:00PM - 1:55PM Room: Ballroom D

To develop a model to analyze medical accelerator generated parameter and performance data that will provide an early warning of performance degradation and impending component failure.

A robust 6 MV VMAT quality assurance treatment delivery was used to test the constancy of accelerator performance. The generated text log files were decoded and analyzed using statistical process control (SPC) methodology. The text file data is a single snapshot of energy specific and overall systems parameters. A total of 36 system parameters were monitored which include RF generation, electron gun control, energy control, beam uniformity control, DC voltage generation, and cooling systems. The parameters were analyzed using Individual and Moving Range (I/MR) charts. The chart limits were calculated using a hybrid technique that included the use of the standard 3σ limits and the parameter/system specification. Synthetic errors/changes were introduced to determine the initial effectiveness of I/MR charts in detecting relevant changes in operating parameters. The magnitude of the synthetic errors/changes was based on: the value of 1 standard deviation from the mean operating parameter of 483 TB systems, a small fraction (≤ 5%) of the operating range, or a fraction of the minor fault deviation.

There were 34 parameters in which synthetic errors were introduced. There were 2 parameters (radial position steering coil, and positive 24V DC) in which the errors did not exceed the limit of the I/MR chart. The I chart limit was exceeded for all of the remaining parameters (94.2%). The MR chart limit was exceeded in 29 of the 32 parameters (85.3%) in which the I chart limit was exceeded.

Statistical process control I/MR evaluation of text log file parameters may be effective in providing an early warning of performance degradation or component failure for digital medical accelerator systems.

Funding Support, Disclosures, and Conflict of Interest: Research is Supported by Varian Medical Systems, Inc.

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