1. Combined micro-XRF and TXRF methodology for quantitative elemental imaging of tissue samples.
- Author
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Wróbel PM, Bała S, Czyzycki M, Golasik M, Librowski T, Ostachowicz B, Piekoszewski W, Surówka A, and Lankosz M
- Subjects
- Algorithms, Animals, Kidney chemistry, Male, Organ Specificity, Rats, Wistar, Spleen chemistry, Fluorescence, Liver chemistry, Photoelectron Spectroscopy methods, Spectrometry, X-Ray Emission methods, Trace Elements analysis
- Abstract
Local differences in structural properties of biological specimens pose a major limitation to quantitative X-ray fluorescence imaging. This is because both the various tissue compartments of different density and variation in the sample thickness upon frequently used freeze-drying come up with the different values of the sample mass per unit area to be taken into account. Even though several solutions to tackle this problem based on the home-made standards for quantification in terms of thickness- and density-independent elemental mass fractions have been proposed, this issue is not addressed enough due to the samples' heterogeneity. In our recent study, we propose a calculation scheme based on combined external-standard micro X-ray fluorescence (micro-XRF) imaging and internal-standard total reflection X-ray fluorescence (TXRF) analysis to determine the corrected elemental mass fraction distributions in commonly analysed rat tissues: kidney, liver and spleen. The results of TXRF analysis of digested large tissue sections together with the mean values of elemental masses per unit area obtained with micro-XRF were employed to determine the average masses per unit area of the samples. The correction for variation of the tissue thickness and density was done through with the use of Compton intensities. Importantly, by its versatility, our novel approach can be used to produce elemental contrast in a variety of biological specimens where local variations in either the sample density or thickness are no longer the issue., (Copyright © 2016 Elsevier B.V. All rights reserved.)
- Published
- 2017
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