Automatic Generic Registration of Mass Spectrometry Imaging Data to Histology Using Nonlinear Stochastic Embedding

作者：Abdelmoula Walid M; Skraskova Karolina; Balluff Benjamin; Carreira Ricardo J; Tolner Else A; Lelieveldt Boudewijn P F; van der Maaten Laurens; Morreau Hans; van den Maagdenberg Arn M J M; Heeren Ron M A; McDonnell Liam A^*; Dijkstra Jouke

来源：Analytical Chemistry, 2014, 86(18): 9204-9211.

DOI：10.1021/ac502170f

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 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.

• 出版日期2014-9-16