The evolution of DESI-MSI: A comprehensive look at preprocessing and quantification strategies for metabolomics

Authors

• Cheng-Hung Yang, Metabolomics Core Laboratory, Healthy Aging Research Center, Chang Gung University, Taoyuan City, Taiwan
• Hung-Yao Ho, Metabolomics Core Laboratory, Healthy Aging Research Center, Chang Gung University, Taoyuan City, Taiwan
• Chen-Yu Chang, Metabolomics Core Laboratory, Healthy Aging Research Center, Chang Gung University, Taoyuan City, Taiwan
• Mei-Ling Cheng, Metabolomics Core Laboratory, Healthy Aging Research Center, Chang Gung University, Taoyuan City, TaiwanFollow

Keywords

DESI-MSI, Mass spectrometry imaging, Sample preprocessing

Abstract

Mass spectrometry imaging (MSI) has become an indispensable tool in metabolomics for visualizing the spatial distribution of biomolecules within tissues. Due to its direct, ambient analysis capability, desorption electrospray ionization (DESI-MSI) has evolved from a rapid screening tool into a precise and reliable quantitative platform. We delve into its technical principles and particularly review the criticality of sample preprocessing, highlighting the paradigm shift from a "no-preprocessing" approach to one of "optimized preprocessing." The paper details how factors like sample preservation, choice of embedding agents, washing, drying, and on-tissue chemical derivatization all impact data quality. We also discuss how the addition of standards and internal standards can mitigate matrix effects and signal variability, enabling accurate quantitative analysis. Finally, this article looks ahead to the future of DESI-MSI, including its combination with emerging technologies such as tissue expansion mass spectrometry imaging to achieve single-cell-level spatial resolution and open up new possibilities for metabolomics research.

Abstract Image

Recommended Citation

Yang, Cheng-Hung; Ho, Hung-Yao; Chang, Chen-Yu; and Cheng, Mei-Ling (2026) "The evolution of DESI-MSI: A comprehensive look at preprocessing and quantification strategies for metabolomics," Journal of Food and Drug Analysis: Vol. 34 : Iss. 1 , Article 6.
Available at: https://doi.org/10.38212/2224-6614.3583

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