Hyperspectral Visualization of Mass Spectrometry Imaging Data

The acquisition of localized molecular spectra with mass
spectrometry
imaging (MSI) has a great, but as yet not fully realized, potential
for biomedical diagnostics and research. The methodology generates
a series of mass spectra from discrete sample locations, which is
often analyzed by visually interpreting specifically selected images
of individual masses. We developed an intuitive color-coding scheme
based on hyperspectral imaging methods to generate a single overview
image of this complex data set. The image color-coding is based on
spectral characteristics, such that pixels with similar molecular
profiles are displayed with similar colors. This visualization strategy
was applied to results of principal component analysis, self-organizing
maps and t-distributed stochastic neighbor embedding. Our approach
for MSI data analysis, combining automated data processing, modeling
and display, is user-friendly and allows both the spatial and molecular
information to be visualized intuitively and effectively.