Nuclear Engineering and Technology

Korean Nuclear Society (한국원자력학회)
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Monte Carlo-based identification of electron and proton edges for calibration of miniaturized tissue equivalent proportional counter

  • Mingi Eom (Program in Biomedical Radiation Sciences, Department of Transdisciplinary Studies, Graduate School of Convergence Science and Technology, Seoul National University) ;
  • Sukwon Youn (Department of Applied Bioengineering and Research Institute for Convergence Science, Graduate School of Convergence Science and Technology, Seoul National University) ;
  • Sung-Joon Ye (Program in Biomedical Radiation Sciences, Department of Transdisciplinary Studies, Graduate School of Convergence Science and Technology, Seoul National University)
  • Received : 2023.03.16
  • Accepted : 2023.07.27
  • Published : 2023.11.25
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Abstract

Miniaturized tissue equivalent proportional counters (mini-TEPCs) are proper for radiation dosimetry in medical application because the small size of the dosimeter could prevent pile-up effect under the high intensity of therapeutic beam. However, traditional methods of calibrating mini-TEPCs using internal alpha sources are not feasible due to their small size. In this study, we investigated the use of electron and proton edges on Monte Carlo-generated lineal energy spectra as markers for calibrating a 0.9 mm diameter and length mini-TEPC. Three possible markers for each spectrum were calculated and compared using different simulation tools. Our simulations showed that the electron edge markers were more consistent across different simulation tools than the proton edge markers, which showed greater variation due to differences in the microdosimetric spectra. In most cases, the second marker, yδδ, had the smallest uncertainty. Our findings suggest that the lineal energy spectra from mini-TEPCs can be calibrated using Monte Carlo simulations that closely resemble real-world detector and source geometries.

Keywords

Acknowledgement

This work was supported by the National Research Foundation of Korea (NRF) Grant funded by the Korea government (MSIP) (NRF-2017M1A3A4A01077173 and NRF-2017M1A3A4A01077220).

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