Mass spectrometry imaging combined with multivariate curve resolution as a reliable tool for quantification of chlordecone in mouse liver

In recent years, mass spectrometry imaging (MSI) has been proposed as a powerful analytical technique to directly study of a large number of compounds in different sample matrices [1]. A MSI image is a three-dimensional hyperspectral cube which is composed of vector pixels containing spectral information (of m/z values) as well as two-dimensional spatial information (of x rows and y columns). The high complexity and huge size of data obtained by this technique is where the interpretation and extraction of desired information from raw data runs into bottlenecks. Moreover, there are some major drawbacks inherent to quantitative analysis using MSI, due to the heterogeneity of matrix crystallization and also ion suppression effects. Therefore, chemometrics can play an important role in different steps of MSI data analysis [2]. The objective of this work was quantification of chlordecone (C10Cl10O) as a carcinogen pesticide in the mouse liver using matrix assisted laser desorption ionization MSI (MALDI-MSI) combined with multivariate chemometric techniques. On this matter, the images were captured from the livers of exposed mice to chlordecone in 1, 5 and 10 days of exposure (Data sets I-III). There were also seven spots related to the standard of chlordecone in quantity range of 0 to 450 g/g and four unknown ones. As a first step, MSI images were compressed using binning approach in 3 different bin sizes: 0.25, 0.5 and 1.0. Then, MSI images for calibration and exposed samples were column-wise augmented and analyzed by multivariate curve resolution-alternating least squares (MCR-ALS) under application of proper constraints of non-negativity, spectral normalization and component correspondence. The resolved spectral profiles were used for identification of chlordecone and other interferences. Also, the augmented spatial profiles were post-processed and 2D images for each component were obtained in calibration and unknown samples. The sum of these profiles was utilized to set the calibration curve and to obtain analytical figures of merit (AFOMs). Inspection of the results showed that the lower bin size (i.e., 0.25) provides more accurate results. Finally, the obtained results by MCR for three data sets were compared with those of gas chromatography (GC) and MALDI-MSI [3]. The results showed that MCR-assisted method gives chlordecone amount higher than MALDI-MSI and lower than GC. It is concluded that combination of chemometric methods with MSI can be considered as an alternative way for MSI quantification.