Raman Spectroscopic Imaging of Human Bladder Resectates towards Intraoperative Cancer Assessment

ORCID
0000-0003-1049-0560
Affiliation
Leibniz Institute of Photonic Technology, Member of Leibniz Health Technologies and Member of the Leibniz Centre for Photonics in Infection Research, 07745 Jena, Germany
Krafft, Christoph;
GND
131701819
ORCID
0000-0003-4257-593X
Affiliation
Leibniz Institute of Photonic Technology, Member of Leibniz Health Technologies and Member of the Leibniz Centre for Photonics in Infection Research, 07745 Jena, Germany
Popp, Jürgen;
ORCID
0000-0001-8558-0347
Affiliation
Medical Center, Faculty of Medicine, Institute of Surgical Pathology, University of Freiburg, 79106 Freiburg, Germany
Bronsert, Peter;
Affiliation
Medical Center, Faculty of Medicine, Department of Urology, University of Freiburg, 79106 Freiburg, Germany
Miernik, Arkadiusz

Simple Summary Bladder cancer is the sixth most incident neoplasm, and the average five-year survival rate drops to 5% for patients with the metastatic disease. Raman spectroscopy probes molecular vibrations by inelastic scattering of laser light. In a retrospective study, control and cancer specimens were prepared from ten human bladder resectates and label-free assessed by Raman microspectroscopic imaging. A data analysis workflow without preprocessing identified the locations and signatures of normal bladder, bladder cancer, necrosis, epithelium, and lipid inclusions. Furthermore, microplastic particles, pigments or carotenoids were detected in 13 out of 20 specimens inside tissue and near tissue margins and their identity was confirmed by spectral library surveys. Hypotheses about the origin of these foreign materials are discussed. Our approach with minimal user interference offers prospects for future clinical translation such as intraoperative tumor detection and label-free material identification in complex matrices. Abstract Raman spectroscopy offers label-free assessment of bladder tissue for in vivo and ex vivo intraoperative applications. In a retrospective study, control and cancer specimens were prepared from ten human bladder resectates. Raman microspectroscopic images were collected from whole tissue samples in a closed chamber at 785 nm laser excitation using a 20× objective lens and 250 µm step size. Without further preprocessing, Raman images were decomposed by the hyperspectral unmixing algorithm vertex component analysis into endmember spectra and their abundancies. Hierarchical cluster analysis distinguished endmember Raman spectra that were assigned to normal bladder, bladder cancer, necrosis, epithelium and lipid inclusions. Interestingly, Raman spectra of microplastic particles, pigments or carotenoids were detected in 13 out of 20 specimens inside tissue and near tissue margins and their identity was confirmed by spectral library surveys. Hypotheses about the origin of these foreign materials are discussed. In conclusion, our Raman workflow and data processing protocol with minimal user interference offers advantages for future clinical translation such as intraoperative tumor detection and label-free material identification in complex matrices.

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