The combination of mass spectrometry imaging and histology has proven a powerful approach for obtaining molecular signatures from specific cells/tissues of interest, whether to identify biomolecular changes associated with specific histopathological entities or to determine the amount of a drug in specific organs/compartments. Currently there is no software that is able to explicitly register mass spectrometry imaging data spanning different ionization techniques or mass analyzers. Accordingly the full capabilities of mass spectrometry imaging are under exploited. Here we present a fully automated and generic approach for registering mass spectrometry imaging data to histology, and demonstrate its capabilities for multiple mass analyzers, multiple ionization sources and multiple tissue types.

Additional Metadata
Publisher ACS
Persistent URL dx.doi.org/10.1021/ac502170f
Journal Anal. Chem.
Citation
Abdelmoula, W.M, Skraskova, K, Balluff, B, Carreira, R.J, Lelieveldt, B.F.P, van der Maaten, L, … McDonnell, L.A. (2014). Automatic generic registration of Mass Spectrometry Imaging Data to histology using nonlinear stochastic embedding. Anal. Chem., 86(18), 9204–9211. doi:10.1021/ac502170f