Application of a low‐cost Geiger–Müller monitoring system for clinical radiation environments
Jungsam Choi, Chaihong Rim, Hakyoung Kim, Wonho LeeAbstract
Background
Low‐cost Geiger–Müller detectors may support clinical radiation monitoring, but their response varies with radiation type and measurement conditions.
Purpose
To evaluate an Arduino‐based Geiger–Müller monitoring system in representative clinical radiation environments and determine whether condition‐specific calibration reduces disagreement with a reference survey meter.
Methods
The system was compared with a reference energy‐compensated Geiger–Müller survey meter (Ludlum Model 3005) under computed tomography scatter, Ir‐192 brachytherapy, and 6 MV linear accelerator maze conditions. Calibration coefficients, expressed as counts per minute (CPM) per µSv/h, were estimated using zero‐intercept regression, and method agreement was assessed using bias analysis and Bland–Altman plots. Portable deployment and user acceptability were also evaluated. The effective dead time of the counting chain was estimated using the first‐order two‐source approximation, and the intrinsic photon energy response was characterized using discrete‐energy gamma‐emitting sources (Co‐57, Cs‐137, and Co‐60). Calibration‐coefficient stability was also assessed at a fixed maze position across nominal dose rates of 100–600 MU/min to isolate count‐rate effects.
Results
Calibration coefficients ranged from 124 to 133 for computed tomography scatter, 99 to 179 for Ir‐192, and 145 to 233 for the 6 MV linear accelerator maze, demonstrating marked condition dependence. Applying condition‐specific calibration reduced systematic bias within the evaluated environments. The effective dead time was approximately 258 µs, and the detector showed greater response per unit dose at lower photon energies, consistent with the known energy dependence of uncompensated Geiger–Müller tubes and providing a plausible explanation for the condition‐dependent calibration coefficients. At a fixed maze position, the calibration coefficient varied little across nominal dose rates of 100–600 MU/min (coefficient of variation, 3.04%), with no evidence that count‐rate dependence dominated within this range. In the linear accelerator maze, mean bias approached zero after distance‐specific calibration, whereas the limits of agreement widened with increasing distance. Among 27 respondents, intention for continued use was more strongly associated with perceived stability and lower perceived risk than with numerical agreement alone.
Conclusions
With condition‐specific calibration, the low‐cost monitoring system showed low mean bias relative to the reference instrument in the evaluated low‐to‐moderate dose‐rate clinical environments. These findings support further evaluation of the system as a supplementary tool for routine radiation monitoring and safety checks under comparable clinical conditions.