Bladder tissue characterization using probe-based Raman spectroscopy: Evaluation of tissue heterogeneity and influence on the model prediction

Eliana Cordero, Jan Rüger, Dominik Marti, Abdullah S. Mondol, Thomas Hasselager, Karin Mogensen, Gregers G. Hermann, Jürgen Popp, Iwan W. Schie*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

Existing approaches for early-stage bladder tumor diagnosis largely depend on invasive and time-consuming procedures, resulting in hospitalization, bleeding, bladder perforation, infection and other health risks for the patient. The reduction of current risk factors, while maintaining or even improving the diagnostic precision, is an underlying factor in clinical instrumentation re-search. Therefore, novel diagnostic modalities are required that can provide real-time in vivo tumor diagnosis. Raman spectroscopy provides biochemical information of tissue samples ex vivo and in vivo and without the need for complicated sample preparation and staining proce-dures. Bladder pathology has been previously studied, but only with little attention to aspects that can influence the diagnosis, such as tissue heterogeneity, data preprocessing, and model development. Here we present a study on bladder biopsies to characterize tumor grading ex vivo and an evaluation of the tissue heterogeneity of highly fluorescent bladder tissues, as a crucial step towards in vivo Raman endoscopy. This article is protected by copyright. All rights reserved.
Original languageEnglish
Article numbere201960025
Journaljournal of biophotonics
Volume13
Issue number2
ISSN1864-063X
DOIs
Publication statusPublished - 2020

Keywords

  • Raman spectroscopy
  • Bladder cancer
  • PLS-LDA
  • Raman probe
  • Imaging-based Raman

Cite this

Cordero, E., Rüger, J., Marti, D., Mondol, A. S., Hasselager, T., Mogensen, K., Hermann, G. G., Popp, J., & Schie, I. W. (2020). Bladder tissue characterization using probe-based Raman spectroscopy: Evaluation of tissue heterogeneity and influence on the model prediction. journal of biophotonics, 13(2), [e201960025]. https://doi.org/10.1002/jbio.201960025