바이오모니터링 프로그램을 위한 혈중 금속류 동시분석법 개발 및 확인 평가

Abstract

Objective: Biological monitoring of trace elements in human blood samples has become an important indicator of the health environment. The purpose of this study was to detect and evaluate multiple metal items in blood samples based on ICP-MS, to perform comparative evaluation with the existing analysis method, and to develop and verify a new method. Methods: 100 µL of whole blood from 80 healthy subjects was used to analyze ten metals (Sb, tAs, Cd, Pb, Mn, Hg, Mo, Ni, Se, Tl) using ICP-MS. Verification of the analysis method included calculation of linearity, accuracy, precision and detection limits. In addition, a comparative test with the conventional graphite furnace atomic absorption spectroscopy (GF-AAS) method was performed. In the case of Pb, Cd, and Hg in whole blood, cross-analysis between Pb, Cd, and Hg analysis methods was performed to confirm the difference between the existing method and the new method (ICP-MS). Results: The coefficient of determination (R2 ) was 0.999 or higher in seven items and 0.995 or higher in three items. The Pb result showed that Pearson’s correlation coefficient was very high at 0.983, and the intraclass correlation coefficient was 0.966. The Cd result showed that Pearson's correlation coefficient was 0.917 between the existing method and the new analysis concentration value. Its intraclass correlation coefficient was 0.960, and there was no significant difference between the two groups. Hg had a low correlation at 0.687, and the intraclass correlation coefficient was 0.761, which was lower than that of Pb and Cd. The intra-day and inter-day accuracy of Pd and Cd were satisfactory, but Hg did not meet the criteria for both accuracy and precision when compared with the conventional analysis method. Conclusion: This study can be meaningful in that it proposes a more efficient and feasible analysis method by verifying a blood heavy metal concentration experiment using multiple simultaneous analyses. All samples were processed and analyzed using the new ICP-MS. It was confirmed that the agreement between the two methods was very high, with the agreement between the current and new methods being 0.769 to 0.998. This study proposes an efficient simultaneous methodology capable of analyzing multiple elements with small samples. In the future, studies of various applications and the reliability of ICP-MS analysis methods are required, and research on the verification of accurate, precise, and continuous analysis methods is required.