Accuracy enhancement of L-band EPR tooth dosimetry by implementing multiple harmonic detection

• Published in: Radiation measurements 2024-08, Vol.176, p.107185, Article 107185
• Main Authors: Oh, Jeonghun, Koo, Chang Uk, Park, Jong In, Choi, Kwon, Lee, Junyoung, Hirata, Hiroshi, Ye, Sung-Joon
• Format: Article
• Language: English
• Subjects: Electron paramagnetic resonance; In vivo; Multiple harmonic detection; Retrospective dosimetry
• ISSN: 1350-4487; 1879-0925
• DOI: 10.1016/j.radmeas.2024.107185

In a large-scale radiation accident, the swift classification of individuals exposed to high levels of radiation is crucial to minimize casualties. In-vivo tooth dosimetry using L-band electron paramagnetic resonance (EPR) spectroscopy is a promising method for this purpose, as it can estimate individual exposure levels rapidly and non-invasively. However, the accuracy of dose estimation associated with this technique remains a great challenge. To enhance the accuracy, digital multiple harmonic detection (MHD) was incorporated into a home-built L-band EPR spectrometer. This approach enabled the utilization of information present in higher harmonics of EPR signals, which has been often discarded in traditional EPR spectroscopy. Acquired multiple harmonic spectra were reconstructed to the first derivative spectrum to merge information and mitigate the signal broadening. The modulation amplitude varied in a range of 0.3–0.7 mT to maximize the accuracy. In a 0.5-min measurement at 0.6 mT, the standard error of inverse prediction (SEIP) was reduced to 0.57 Gy from 0.71 Gy. The statistical significancy of the enhancement was validated. In conclusion, the accuracy enhanced by this MHD can contribute to improving the efficiency of triage systems in the aftermath of a mass radiation accident. •Digital multiple harmonic detection (MHD) was implemented for in-vivo L-band EPR tooth dosimetry.•The modulation amplitude was optimized within a range of 0.3–0.7 mT to maximize the accuracy.•The accuracy of dose estimation was enhanced by 20.1% in terms of the standard error of inverse prediction (SEIP).•This accuracy enhancement can improve the efficiency of the triage system in a large-scale radiological accident.