Fourier 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

Anna Balbekova, Hans Lohninger, Geralda A.F. van Tilborg, Rick M. Dijkhuizen, Maximilian Bonta, Andreas Limbeck, Bernhard Lendl, Khalid A. Al-Saad, Mohamed Hosni M. Ali, Minja Celikic, Johannes Ofner

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Microspectroscopic 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.

Original languageEnglish
Pages (from-to)241-250
Number of pages10
JournalApplied Spectroscopy
Volume72
Issue number2
DOIs
Publication statusPublished - 1 Feb 2018

Fingerprint

ischemia
Laser ablation
Spectrometry
laser ablation
rats
brain
Rats
Brain
Fourier transforms
Tissue
Infrared radiation
Imaging techniques
strokes
spectroscopy
Inductively coupled plasma mass spectrometry
inductively coupled plasma mass spectrometry
Discriminant analysis
chemical analysis
Gold
complement

Keywords

  • brain 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

ASJC Scopus subject areas

  • Instrumentation
  • Spectroscopy

Cite this

Fourier 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. / Balbekova, Anna; Lohninger, Hans; van Tilborg, Geralda A.F.; Dijkhuizen, Rick M.; Bonta, Maximilian; Limbeck, Andreas; Lendl, Bernhard; Al-Saad, Khalid A.; Hosni M. Ali, Mohamed; Celikic, Minja; Ofner, Johannes.

In: Applied Spectroscopy, Vol. 72, No. 2, 01.02.2018, p. 241-250.

Research output: Contribution to journalArticle

Balbekova, Anna ; Lohninger, Hans ; van Tilborg, Geralda A.F. ; Dijkhuizen, Rick M. ; Bonta, Maximilian ; Limbeck, Andreas ; Lendl, Bernhard ; Al-Saad, Khalid A. ; Hosni M. Ali, Mohamed ; Celikic, Minja ; Ofner, Johannes. / Fourier 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. In: Applied Spectroscopy. 2018 ; Vol. 72, No. 2. pp. 241-250.
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abstract = "Microspectroscopic 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.",
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