(Sunday, 7/12/2020) 3:30 PM - 4:30 PM [Eastern Time (GMT-4)]
Room: Track 3
Purpose:
TG-218 proposes a 3%/2mm threshold for ?-analysis of IMRT QA events and specifies a universal tolerance of 95% and action limit of 90% for ?-pass rate. The report also recommends tracking ?-pass rates for IMRT/VMAT patient-specific QA across patients, looking for systematic errors in the QA regime, and using a statistical control process to determine a local action limit. This work proposes the use of a free, open-source data mining tool to analyze IMRT reports and determine local action levels.
Methods:
The IMRT QA Data Mining (IQDM) tool uses Python code to parse IMRT QA reports, currently supporting ScandiDos Delta4 and SNC Patient. This software then generates an interactive dashboard including a time-plot with trending, a histogram, and a control chart per TG-218; the charting variable may be ? pass-rates or any other variable parsed from the reports.
Results:
Over 10,000 QA reports from six radiation oncology departments were imported and analyzed. TG-218 recommends determining control limits via a small amount (~20) of IMRT measurements while the process is in control. Clinics were able to determine action and control limits for IMRT QA processes. One clinic found for their QA scheme using both 2%/3 mm and 3%/3 mm tolerances as well as global normalization, the action limit was determined to be 90.1% and a lower control limit of 93.7%
Conclusion:
Through statistical process control charts, a local control limit can be established for individual clinics per TG-218 recommendations. The IQDM software assisted in identifying systemic biases in the TPS of one clinic as well as deviations in pass/fail criteria from IMRT QA policy.
Keywords
Quality Assurance, Software, Statistical Analysis
Taxonomy
TH- Dataset Analysis/Biomathematics: Informatics
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