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AuthorBalbekova A.
AuthorLohninger H.
Authorvan Tilborg G.A.F.
AuthorDijkhuizen R.M.
AuthorBonta M.
AuthorLimbeck A.
AuthorLendl B.
AuthorAl-Saad K.A.
AuthorAli M.
AuthorCelikic M.
AuthorOfner J.
Available date2020-02-05T08:53:35Z
Publication Date2018
Publication NameApplied Spectroscopy
ResourceScopus
ISSN37028
URIhttp://dx.doi.org/10.1177/0003702817734618
URIhttp://hdl.handle.net/10576/12737
AbstractMicrospectroscopic techniques are widely used to complement histological studies. Due to recent developments in the field of chemical imaging, combined chemical analysis has become attractive. This technique facilitates a deepened analysis compared to single techniques or side-by-side analysis. In this study, rat brains harvested one week after induction of photothrombotic stroke were investigated. Adjacent thin cuts from rats’ brains were imaged using Fourier transform infrared (FT-IR) microspectroscopy and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). The LA-ICP-MS data were normalized using an internal standard (a thin gold layer). The acquired hyperspectral data cubes were fused and subjected to multivariate analysis. Brain regions affected by stroke as well as unaffected gray and white matter were identified and classified using a model based on either partial least squares discriminant analysis (PLS-DA) or random decision forest (RDF) algorithms. The RDF algorithm demonstrated the best results for classification. Improved classification was observed in the case of fused data in comparison to individual data sets (either FT-IR or LA-ICP-MS). Variable importance analysis demonstrated that both molecular and elemental content contribute to the improved RDF classification. Univariate spectral analysis identified biochemical properties of the assigned tissue types. Classification of multisensor hyperspectral data sets using an RDF algorithm allows access to a novel and in-depth understanding of biochemical processes and solid chemical allocation of different brain regions.
SponsorThis work was supported by MEIBio doctoral project of TU Wien and by the funding from the Austrian FFG within project 84247. This work was co-funded by NPRP grant no. NPRP-5-381-3-101 from the Qatar National Research Fund (a member of The Qatar Foundation).
Languageen
PublisherSAGE Publications Inc.
Subjectbrain ischemia
Fourier transform infrared
FT-IR
LA-ICP-MS
laser ablation inductively coupled plasma mass spectrometry
Multisensor hyperspectral image analysis
partial least squares discriminant analysis
photothrombotic stroke
PLS-DA
random decision forest
RDF
TitleFourier Transform Infrared (FT-IR) and Laser Ablation Inductively Coupled Plasma–Mass Spectrometry (LA-ICP-MS) Imaging of Cerebral Ischemia: Combined Analysis of Rat Brain Thin Cuts Toward Improved Tissue Classification
TypeArticle
Pagination241-250
Issue Number2
Volume Number72
dc.accessType Abstract Only


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