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Updated: Aug 3, 2025
Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System
Published on: April 11, 2018
Mitigation of Intensity Modulated Radiation Therapy and Stereotactic Body Radiation Therapy Treatment Planning Errors
Eric Simiele1, Bin Han2, Lawrie Skinner2
1Department of Radiation Oncology, Rutgers Cancer Institute of New Jersey, Robert Wood Johnson Medical School, New Brunswick, New Jersey.
Purpose:
The aim of this study was to apply the Six Sigma methodology and failure mode and effect analysis (FMEA) to mitigate errors in intensity modulated radiation therapy (IMRT) and stereotactic body radiation therapy (SBRT) treatment planning with the first clinical installation of RefleXion X1.
Methods And Materials:
The Six Sigma approach consisted of 5 phases: define, measure, analyze, improve, and control. The define, measure, and analyze phases consisted of process mapping and an FMEA of IMRT and SBRT treatment planning on the X1. The multidisciplinary team outlined the workflow process and identified and ranked the failure modes associated with the plan check items using the American Association of Physicists in Medicine Task Group 100 recommendations. Items with the highest average risk priority numbers (RPNs) and severity ≥7 were prioritized for automation using the Eclipse Scripting Application Programming Interface (ESAPI). The "improve" phase consisted of developing ESAPI scripts before the clinical launch of X1 to improve efficiency and safety. In the "control" phase, the FMEA ranking was re-evaluated 1 year after clinical launch.
Results:
Overall, 100 plan check items were identified in which the RPN values ranged from 10.2 to 429.0. Fifty of these items (50%) were suitable for automation within ESAPI. Of the 10 highest-risk items, 8 were suitable for automation. Based on the results of the FMEA, 2 scripts were developed: Planning Assistant, used by the planner during preparation for planning, and Automated Plan Check, used by the planner and the plan checker during plan preparation for treatment. After 12 months of clinical use of the X1 and developed scripts, only 3 errors were reported. The average prescript RPN was 138.0, compared with the average postscript RPN of 47.8 (P < .05), signifying a safer process.
Conclusions:
Implementing new technology in the clinic can be an error-prone process in which the likelihood of errors increases with increasing pressure to implement the technology quickly. To limit errors in clinical implementation of the novel RefleXion X1 system, the Six Sigma method was used to identify failure modes, establish quality control checks, and re-evaluate these checks 1 year after clinical implementation.
