Label‐free analysis of inflammatory tissue remodeling in murine lung tissue based on multiphoton microscopy, Raman spectroscopy and machine learning

Language
en
Document Type
Article
Issue Date
2022-10-25
First published
2022-09-05
Issue Year
2022
Authors
Kreiss, Lucas
Ganzleben, Ingo
Mühlberg, Alexander
Ritter, Paul
Schneidereit, Dominik
Becker, Christoph
Neurath, Markus F.
Friedrich, Oliver
Schürmann, Sebastian
Waldner, Maximilian
Editor
Publisher
WILEY‐VCH Verlag GmbH & Co. KGaA
Abstract

Abstract Inflammatory fibrotic tissue remodeling can lead to severe morbidity. Histopathology grading requires extraction of biopsies and elaborate tissue processing. Label‐free optical technologies can provide diagnostic readout without preparation and artificial stainings and show potential for in vivo applications. Here, we present an integration of Raman spectroscopy (RS) and multiphoton microscopy for joint investigation of the bio‐chemical composition and morphological features related to cellular components and connective tissue. Both modalities show that collagen signatures were significantly increased in a murine fibrosis model. Furthermore, autofluorescence signatures assigned to immune cells show high correlation with disease severity. RS indicates increased levels of elastin and lipids. Further, we investigated the effect of joint data sets on prediction performance in machine learning models. Although binary classification did not benefit from adding more features, multi‐class classification was improved by integrated data sets.

Journal Title
Journal of Biophotonics
Volume
15
Issue
9
Citation
Journal of Biophotonics 15.9 (2022): e202200073. <https://onlinelibrary.wiley.com/doi/10.1002/jbio.202200073>
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