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Updated: Feb 14, 2026

Imaging of Biological Tissues by Desorption Electrospray Ionization Mass Spectrometry
Published on: July 12, 2013
Exploring Ion Suppression in Mass Spectrometry Imaging of a Heterogeneous Tissue
Adam J Taylor1, Alex Dexter1, Josephine Bunch1,2
1National Centre of Excellence in Mass Spectrometry Imaging (NiCE-MSI) , National Physical Laboratory , Hampton Road , Teddington , TW11 0LW , U.K.
Abstract:
In this study we have explored several aspects of regional analyte suppression in mass spectrometry imaging (MSI) of a heterogeneous sample, transverse cryosections of mouse brain. Olanzapine was homogeneously coated across the section prior to desorption electrospray ionization (DESI) and matrix-assisted laser desorption ionization (MALDI) mass spectrometry imaging. We employed the concept of a tissue extinction coefficient (TEC) to assess suppression of an analyte on tissue relative to its intensity in an off tissue region. We expanded the use of TEC, by first segmenting anatomical regions using graph-cuts clustering and calculating a TEC for each cluster. The single ion image of the olanzapine [M + H]+ ion was seen to vary considerably across the image, with anatomical features such as the white matter and hippocampus visible. While trends in regional ion suppression were conserved across MSI modalities, significant changes in the magnitude of relative regional suppression effects between techniques were seen. Notably the intensity of olanzapine was less suppressed in DESI than for MALDI. In MALDI MSI, significant differences in the concentration dependence of regional TECs were seen, with the TEC of white matter clusters exhibiting a notably stronger correlation with concentration than for clusters associated with gray matter regions. We further employed cluster-specific TECs as regional normalization factors. In comparison to published pixel-by-pixel normalization methods, regional TEC normalization exhibited superior reduction ion suppression artifacts. We also considered the usefulness of a segmentation-based approach to compare spectral information obtained from complementary modalities.
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