Metodiev, M; Dexter, A; Zhou, W; Gonzalez-Fernández, A; Nikula, C; Johns, L M; Karali, E; Kazanc, E; Tsalikis, A; Tripp, A; Takats, Z; Poulogiannis, G; Bunch, J (2026) Evaluating Batch Correction Methods for Large-Scale Mass Spectrometry Imaging of Heterogeneous Tissues. Analytical Chemistry, 98 (5). pp. 3531-3543. ISSN 0003-2700

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Abstract

In MSI, the fluctuation in detected ion intensities which is associated with ‘technical factors’ and not the variability of molecular composition of the sample itself, may be referred to as ‘batch effects’. These batch effects are a major barrier to more widespread uptake and use of MSI for larger clinical and preclinical studies. In other fields, such as metabolomics and transcriptomics, batch correction methods have been introduced and commonly adopted. These methods aim to mitigate systematic biases introduced by differences in experimental conditions, instruments, or processing batches in high-dimensional data, such as omics or imaging datasets. Mass spectrometry imaging poses additional challenges compared to these fields such as the need to ensure that expected intensity fluctuations throughout a sample, associated with expected spatial variability are maintained, and inability to randomly introduce quality control spectra. To date, there is no widely adopted approach to batch correction of mass spectrometry imaging data. In this work we evaluate a variety of batch correction methods which are suitable for pixel-to-pixel data correction in MSI.

Item Type:	Article
Subjects:	Mathematics and Scientific Computing > Signal Processing
Divisions:	Chemical & Biological Sciences
Identification number/DOI:	10.1021/acs.analchem.5c04371
Last Modified:	11 Sep 2026 14:15
URI:	https://eprintspublications.npl.co.uk/id/eprint/10513