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Imaging mammalian lipids using desorption electrospray ionization mass spectrometry: A review

  • Reham Abu Ghoush
  • , Fakhri Geday
  • , Oz Alon
  • , Vijaya Lakshmi Kanchustambham
  • , Sarah E. Noll
  • , Katherine Margulis*
  • *Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

1 Scopus citations

Abstract

Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) has become an essential tool for spatial lipidomic profiling since its introduction in 2005. It provides key insights into the roles of lipids in cellular function, disease mechanisms, and therapeutic development, especially within heterogeneous tissues. Understanding lipid modifications and their spatiotemporal distribution in both healthy and diseased states is crucial, given the strong link between lipid metabolism dysregulation and numerous diseases. This review offers an overview of DESI-MS imaging of mammalian lipids, highlighting challenges and advancements in lipid quantification, identification, and sample preparation optimization. We further emphasized the integration of machine learning and statistical analyses with DESI-MSI to navigate the complexity of lipidomic data, enabling the discovery of diagnostic biomarkers and the development of personalized therapeutic strategies. Specific applications of DESI-MSI in studying lipids under physiological and pathological conditions are discussed, with an emphasis on disease diagnosis, precision medicine, and therapeutics. Additionally, we reviewed the use of lipid analysis in non-medical applications such as forensics, public safety, and cosmetics. In conclusion, this review highlights the role of DESI-MSI in lipidomics, emphasizing its current challenges and future directions. Ongoing technological progress in DESI-MSI is expanding its applications in clinical diagnostics, pharmaceutical research, and personalized medicine. With deeper integration of computational tools and multi-omics approaches, DESI-MSI is well-positioned to accelerate the discovery of novel lipid biomarkers and support the development of precise therapeutic strategies.

Original languageEnglish
Article number345143
JournalAnalytica Chimica Acta
Volume1392
DOIs
StatePublished - 22 Mar 2026

Bibliographical note

Publisher Copyright:
© 2026 Elsevier B.V.

Keywords

  • DESI-MSI
  • Electrospray ionization
  • Lipidomics
  • Lipids
  • Machine learning
  • Mass spectrometry imaging
  • OMICS

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