Seasonal variations in measurements of linear accelerator output

Abstract

Purpose Seasonal trends in linear accelerator output have been reported by at least one institution and data have suggested that they may be present at our center as well. The purpose of this work was to characterize these trends and determine whether local environmental conditions within the treatment rooms may be impacting the linear accelerators and/or the quality control (QC) dosimeter. Methods Runtime plots of daily output data, acquired using an in‐house ion chamber‐based device, over 3 yr and for 15 linear accelerators of different makes and models were reviewed and evaluated. Environmental conditions were monitored prospectively in a representative treatment room for approximately 9 months and evaluated for correlations with output trends. Independent measures of output using daily MV portal images were compared with output measurements using the ion chamber‐based device. A separate controlled experiment probing the response of the in‐house dosimeter to humidity changes over time was also carried out using a constant current source and a small enclosure. Results Runtime plots of output revealed sinusoidal, seasonal variations that were consistent across all treatment units, irrespective of manufacturer, model, or age of machine. The amplitude of the variation was on the order of 1% and maintained a yearly period. The independent measure of output using MV portal images did not corroborate the seasonal trends observed with the daily QC dosimeter. Based on the controlled experiment, the QC dosimeter was found to have a dependence on relative humidity changes, decreasing 1% in output per 30% increase in relative humidity. Conclusions Results confirm the presence of underlying seasonal variations in measured output from the linear accelerators. The findings identify humidity impact on the measurement device as the underlying cause of the cyclical changes and not the accelerators themselves. These results could help minimize unwarranted machine servicing.

A mathematical model to identify the output variations of TrueBeam linear accelerators using Machine Performance Check evaluations

“…Output increase per year Pearson et al (2020) [3] 8 Varian TrueBeams 3 years 3-4% Barnes and Greer (2017) [4] 1 Varian TrueBeam 5 months 3% Chan et al (2015) [6] 1 Varian Trilogy 5 years 3% Hossain (2014) [7] 1 Varian Trilogy and 2 iX Varian Linacs 3.5 years 2-4% Uddin (2012) [8] 3 Varian Linacs 4 years 2% Grattan and Hounsell (2011) [9] 4 Varian 2100 C/D 7 years 3% Luketina and Greig (2004) [10] 2 Varian 2100 C/D 5.5 years 2.5% Bartolac et al (2019) [11] 15 Linacs of different makes and models 3 years 2-3% Bolt et al (2018) [13] 27 Varian TrueBeams 6 months 2.1% [16] 8 Linacs of different makes and models 5 years 2% over time). It is known that increasing the output measurement frequency and decreasing the action level help to improve the quality of a radiotherapy treatment [17].…”

“…It is reported that the Linacs output does not remain constant over time but shows significant changes during the course of a year [3]- [9] and even seasonal variations [7,11], that must be corrected to keep output within the established tolerance limits. The recommended tolerances for daily and monthly output constancy checks are typically ±3% and ±2%, respectively [12], although a more restrictive limit is generally applied to daily tests executed with MPC [3,4].…”