Description and verification of an algorithm for obtaining microdosimetric quantities for high-LET radiation using a...

Area of Science:

• Medical Physics
• Radiation Dosimetry
• Health Physics

Background:

• Microdosimetric spectra of single event distributions are crucial for estimating quality factors for high-Linear Energy Transfer (LET) radiation in radiation protection.
• High-dose rate environments pose challenges for measuring, recording, and storing energy deposition from individual events.

Purpose of the Study:

• To develop and validate an alternative algorithm for estimating radiation quality factors that bypasses the need to identify single events.
• To enable accurate measurements in high-dose rate scenarios by analyzing random energy deposition events within fixed time intervals.

Main Methods:

• Developed an algorithm based on expectation analysis of statistical estimators for moments of lineal energy (ȳf and ȳD).
• Utilized Monte Carlo simulations with single event distributions from spherical tissue equivalent proportional counters.
• Tested the algorithm with varying mean events per interval (dose rate) and numbers of intervals (duration).

Main Results:

• The algorithm effectively corrects for excess dispersion caused by random event counts per interval at constant dose rates.
• Demonstrated convergence to correct values even with linear trends in dose rate over the measurement duration.
• Achieved a coefficient of variation of 25% for ȳD estimates with 100 intervals and 10% with 400 intervals for various radiation sources.

Conclusions:

• The developed algorithm provides a robust method for estimating lineal energy moments (ȳf, ȳD) without single event identification, suitable for high-dose rate conditions.
• The approach is effective for constant and linearly varying dose rates but not applicable to pulsed radiation fields.
• Validated through Monte Carlo simulations and real-world measurements, showing good accuracy and precision.