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

dc.contributor.authorKreiss, Lucas
dc.contributor.authorGanzleben, Ingo
dc.contributor.authorMühlberg, Alexander
dc.contributor.authorRitter, Paul
dc.contributor.authorSchneidereit, Dominik
dc.contributor.authorBecker, Christoph
dc.contributor.authorNeurath, Markus F.
dc.contributor.authorFriedrich, Oliver
dc.contributor.authorSchürmann, Sebastian
dc.contributor.authorWaldner, Maximilian
dc.date.accessioned2022-10-25
dc.date.available2023-10-16T19:55:59Z
dc.date.created2022
dc.date.issued2022-10-25
dc.description.abstractAbstract 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.en
dc.identifier.citationJournal of Biophotonics 15.9 (2022): e202200073. <https://onlinelibrary.wiley.com/doi/10.1002/jbio.202200073>
dc.identifier.doihttps://doi.org/10.1002/jbio.202200073
dc.identifier.opus-id20341
dc.identifier.urihttps://open.fau.de/handle/openfau/20341
dc.identifier.urnurn:nbn:de:bvb:29-opus4-203411
dc.language.isoen
dc.publisherWILEY‐VCH Verlag GmbH & Co. KGaA
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/deed.de
dc.subjectinflammatory fibrogenesis
dc.subjectlabel‐free
dc.subjectlung fibrosis
dc.subjectmachine learning
dc.subjectmultiphoton microscopy
dc.subjectRaman spectroscopy
dc.subject.ddcDDC Classification::6 Technik, Medizin, angewandte Wissenschaften :: 60 Technik :: 600 Technik, Technologie
dc.titleLabel‐free analysis of inflammatory tissue remodeling in murine lung tissue based on multiphoton microscopy, Raman spectroscopy and machine learningen
dc.typearticle
dcterms.publisherFriedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
local.date.prevpublished2022-09-05
local.document.articlenumbere202200073
local.journal.issue9
local.journal.titleJournal of Biophotonics
local.journal.volume15
local.publisherplaceWeinheim
local.sendToDnbfree*
local.subject.fakultaetTechnische Fakultät
local.subject.importimport
local.subject.sammlungUniversität Erlangen-Nürnberg / Eingespielte Open Access Artikel / Eingespielte Open Access Artikel 2022
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