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Statistical quality control methods, like the Exponentially Weighted Moving Average (EWMA), can improve pencil beam scanning (PBS) delivery by reducing treatment time and enhancing safety. This EWMA algorithm detects delivery errors more effectively than traditional binary methods.

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Area of Science:

  • Medical Physics
  • Radiation Oncology
  • Quality Control

Background:

  • Pencil beam scanning (PBS) delivery relies on precise online measurement of beam parameters.
  • Current binary threshold algorithms can cause frequent pauses due to noise, increasing treatment time.
  • Statistical quality control (SQC) offers methods for early detection of process deviations.

Purpose of the Study:

  • To develop a more robust and intuitive algorithm for PBS delivery systems using SQC methods.
  • To reduce treatment time by minimizing unnecessary pauses.
  • To enhance the safety and reliability of PBS delivery.

Main Methods:

  • Implemented an Exponentially Weighted Moving Average (EWMA) control scheme to monitor beam property deviations.
  • Applied EWMA by averaging measurements with greater weight on recent data.
  • Simulated EWMA algorithm performance against delivery errors.

Main Results:

  • The EWMA algorithm safely detected both random and systematic delivery errors without false alarms.
  • EWMA demonstrated potential for decreased treatment times compared to binary threshold methods.
  • Combining EWMA with binary methods can improve reliability and patient safety.

Conclusions:

  • EWMA control schemes provide a robust method for monitoring PBS delivery, distinguishing between random and systematic uncertainties.
  • This approach allows for tailored interlock levels for different uncertainty types.
  • EWMA offers a promising strategy to optimize PBS delivery, reduce treatment time, and maintain safety.