Journal
JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY
Volume 23, Issue 6, Pages 1147-1156Publisher
SPRINGER
DOI: 10.1007/s13361-012-0361-7
Keywords
3D Mass Spectrometry Imaging; Tissue imaging; Statistical Analysis
Funding
- National Science Foundation [CHE-0847205, DBI-0852740]
- National Institute of Health [5R21RR031246]
- National Natural Science Foundation of China [20728505]
- Walther Cancer Institute [205017]
- Direct For Biological Sciences
- Div Of Biological Infrastructure [0852740] Funding Source: National Science Foundation
- Direct For Mathematical & Physical Scien
- Division Of Chemistry [847205] Funding Source: National Science Foundation
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Data processing for three dimensional mass spectrometry (3D-MS) imaging was investigated, starting with a consideration of the challenges in its practical implementation using a series of sections of a tissue volume. The technical issues related to data reduction, 2D imaging data alignment, 3D visualization, and statistical data analysis were identified. Software solutions for these tasks were developed using functions in MATLAB. Peak detection and peak alignment were applied to reduce the data size, while retaining the mass accuracy. The main morphologic features of tissue sections were extracted using a classification method for data alignment. Data insertion was performed to construct a 3D data set with spectral information that can be used for generating 3D views and for data analysis. The imaging data previously obtained for a mouse brain using desorption electrospray ionization mass spectrometry (DESI-MS) imaging have been used to test and demonstrate the new methodology.
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