High resolution mass spectrometry imaging (MSI) is a technique used to visualize the spatial distribution of e.g. compounds, biomarker, metabolites, peptides or proteins by their molecular masses. Recently, we have researched methods that use Principle Component Analysis (PCA) to extract anatomical features from MS data cubes, and subsequently use these features for further analysis and visualization, [1, 2]. Until now, MSI has been used only on 2D surfaces; for example, to visualize biomolecule distributions on tissue sections. Recently, however, mass spectrometry has been used for the acquisition of 3D structural information of biomolecules present in tissues. This has been realized through a tedious and error-prone procedure of dissecting the tissue into stacks along the ’z-dimension’ and performing MSI on each tissue section of the stack. Goal The goal of this proposal is to extend and enhance our feature based extraction approach to develop robust and rigorous methods for the 3D reconstruction, analysis and visualization of stacks of MS data sets.

Project members

• Robert van Liere (project leader)
• Ferdi Smit

Partners

• AMOLF