<div class="csl-bib-body">
<div class="csl-entry">Balbekova, A., Bonta, M., Török, S., Ofner, J., Döme, B., Limbeck, A., & Lendl, B. (2017). FTIR-spectroscopic and LA-ICP-MS imaging for combined hyperspectral image analysis of tumor models. <i>Analytical Methods</i>, <i>9</i>, 5464–5471. https://doi.org/10.1039/c7ay01369h</div>
</div>
-
dc.identifier.issn
1759-9660
-
dc.identifier.uri
http://hdl.handle.net/20.500.12708/20235
-
dc.description.abstract
Modern chemical imaging techniques provide spatially resolved information on the molecular and elemental composition of samples with both high spatial and spectral resolution. Over the past few decades these techniques, in particular, Fourier transform infrared (FTIR) spectroscopy and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) have been successfully applied in histopathological research. This work demonstrates that the multivariate analysis of combined FTIR and LA-ICP-MS microscopy hyperspectral images can bring additional knowledge to biomedical research. The concept of such analysis was demonstrated while investigating two different tumor samples subjected to anticancer therapy. Combined analysis has revealed a correlation between the lateral distribution of analytes and sample properties within the different techniques. Correlations between alterations in the average protein secondary structure and platinum distribution were found, as well as between changes in the cell nuclear morphology and a reduction of physiologically relevant trace elements. The results of combined analysis suggested different degrees of tumor viability. Univariate analysis and k-means clustering successfully discriminated dead tumor regions and supported the results of combined analysis.
en
dc.language.iso
en
-
dc.publisher
ROYAL SOC CHEMISTRY
-
dc.relation.ispartof
Analytical Methods
-
dc.rights.uri
http://creativecommons.org/licenses/by/3.0/
-
dc.subject
FTIR spectroscopy
en
dc.subject
LA-ICP-MS
en
dc.title
FTIR-spectroscopic and LA-ICP-MS imaging for combined hyperspectral image analysis of tumor models