Optimization of data analysis for the in vivo neutron activation analysis of aluminum in bone. (October 2016)

• Record Type: Journal Article
• Authors: Mohseni, H.K.; Matysiak, W.; Chettle, D.R.; Byun, S.H.; Priest, N.; Atanackovic, J.; Prestwich, W.V.
• Is Part Of: Applied radiation and isotopes. Volume 116(2016:Oct.)
• Page Start: 34
• Page End: 40
• Publication Date: 2016-10
• Subjects: IVNAA in vivo neutron activation analysis -- MDL minimum detection limit -- DSP digital signal processing -- RMSE root-mean-square error; In vivo neutron activation -- Aluminum -- Bone -- Data analysis -- Gamma spectroscopy -- Spectral decomposition -- Photopeak fit analysis; Radiology -- Periodicals; Radiation -- Industrial applications -- Periodicals; Nuclear chemistry -- Periodicals; Internet resource; Periodical; 660.298
• DOI: 10.1016/j.apradiso.2016.07.004
• Languages: English
• ISSNs: 0969-8043

Abstract

Abstract: An existing system at McMaster University has been used for the in vivo measurement of aluminum in human bone. Precise and detailed analysis approaches are necessary to determine the aluminum concentration because of the low levels of aluminum found in the bone and the challenges associated with its detection. Phantoms resembling the composition of the human hand with varying concentrations of aluminum were made for testing the system prior to the application to human studies. A spectral decomposition model and a photopeak fitting model involving the inverse-variance weighted mean and a time-dependent analysis were explored to analyze the results and determine the model with the best performance and lowest minimum detection limit. The results showed that the spectral decomposition and the photopeak fitting model with the inverse-variance weighted mean both provided better results compared to the other methods tested. The spectral decomposition method resulted in a marginally lower detection limit (5 μg Al/g Ca) compared to the inverse-variance weighted mean (5.2 μg Al/g Ca), rendering both equally applicable to human measurements. Highlights: Data analysis optimization for measuring aluminum in human subjects. Development and Comparison of multiple approaches to data analysis for NAA of Al. Improving the MDL of IVNAA method for Al measurement compared to previous studies. Exploring the advantage of sequential data acquisition for IVNAA data analysis.