Automatic Generic Registration of Mass Spectrometry Imaging Data to Histology Using Nonlinear Stochastic Embedding
2014; American Chemical Society; Volume: 86; Issue: 18 Linguagem: Inglês
10.1021/ac502170f
ISSN1520-6882
AutoresWalid M. Abdelmoula, Karolina Škrášková, Benjamin Balluff, Ricardo J. Carreira, Else A. Tolner, Boudewijn P. F. Lelieveldt, Laurens van der Maaten, Hans Morreau, Arn M. J. M. van den Maagdenberg, Ron M. A. Heeren, Liam A. McDonnell, Jouke Dijkstra,
Tópico(s)Analytical Chemistry and Chromatography
ResumoThe 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 at present underexploited. Here we present a fully automated 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.
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