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    In-vivo Raman spectroscopy: from basics to applications
    (Bellingham, Wash. : SPIE, 2018) Cordero, Eliana; Latka, Ines; Matthäus, Christian; Schie, Iwan W.; Popp, Jürgen
    For more than two decades, Raman spectroscopy has found widespread use in biological and medical applications. The instrumentation and the statistical evaluation procedures have matured, enabling the lengthy transition from ex-vivo demonstration to in-vivo examinations. This transition goes hand-in-hand with many technological developments and tightly bound requirements for a successful implementation in a clinical environment, which are often difficult to assess for novice scientists in the field. This review outlines the required instrumentation and instrumentation parameters, designs, and developments of fiber optic probes for the in-vivo applications in a clinical setting. It aims at providing an overview of contemporary technology and clinical trials and attempts to identify future developments necessary to bring the emerging technology to the clinical end users. A comprehensive overview of in-vivo applications of fiber optic Raman probes to characterize different tissue and disease types is also given.
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    New perspectives for viability studies with high-content analysis Raman spectroscopy (HCA-RS)
    (Berlin : Nature Publishing, 2019) Mondol, Abdullah S.; Töpfer, Natalie; Rüger, Jan; Neugebauer, Ute; Popp, Jürgen; Schie, Iwan W.
    Raman spectroscopy has been widely used in clinical and molecular biological studies, providing high chemical specificity without the necessity of labels and with little-to-no sample preparation. However, currently performed Raman-based studies of eukaryotic cells are still very laborious and time-consuming, resulting in a low number of sampled cells and questionable statistical validations. Furthermore, the approach requires a trained specialist to perform and analyze the experiments, rendering the method less attractive for most laboratories. In this work, we present a new high-content analysis Raman spectroscopy (HCA-RS) platform that overcomes the current challenges of conventional Raman spectroscopy implementations. HCA-RS allows sampling of a large number of cells under different physiological conditions without any user interaction. The performance of the approach is successfully demonstrated by the development of a Raman-based cell viability assay, i.e., the effect of doxorubicin concentration on monocytic THP-1 cells. A statistical model, principal component analysis combined with support vector machine (PCA-SVM), was found to successfully predict the percentage of viable cells in a mixed population and is in good agreement to results obtained by a standard cell viability assay. This study demonstrates the potential of Raman spectroscopy as a standard high-throughput tool for clinical and biological applications.
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    Revealing the Chemical Composition of Birch Pollen Grains by Raman Spectroscopic Imaging
    (Basel : Molecular Diversity Preservation International (MDPI), 2022) Stiebing, Clara; Post, Nele; Schindler, Claudia; Göhrig, Bianca; Lux, Harald; Popp, Jürgen; Heutelbeck, Astrid; Schie, Iwan W.
    The investigation of the biochemical composition of pollen grains is of the utmost interest for several environmental aspects, such as their allergenic potential and their changes in growth conditions due to climatic factors. In order to fully understand the composition of pollen grains, not only is an in-depth analysis of their molecular components necessary but also spatial information of, e.g., the thickness of the outer shell, should be recorded. However, there is a lack of studies using molecular imaging methods for a spatially resolved biochemical composition on a single-grain level. In this study, Raman spectroscopy was implemented as an analytical tool to investigate birch pollen by imaging single pollen grains and analyzing their spectral profiles. The imaging modality allowed us to reveal the layered structure of pollen grains based on the biochemical information of the recorded Raman spectra. Seven different birch pollen species collected at two different locations in Germany were investigated and compared. Using chemometric algorithms such as hierarchical cluster analysis and multiple-curve resolution, several components of the grain wall, such as sporopollenin, as well as the inner core presenting high starch concentrations, were identified and quantified. Differences in the concentrations of, e.g., sporopollenin, lipids and proteins in the pollen species at the two different collection sites were found, and are discussed in connection with germination and other growth processes.
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    Application of High-Throughput Screening Raman Spectroscopy (HTS-RS) for Label-Free Identification and Molecular Characterization of Pollen
    (Basel : MDPI, 2019) Mondol, Abdullah S.; Patel, Milind D.; Rüger, Jan; Stiebing, Clara; Kleiber, Andreas; Henkel, Thomas; Popp, Jürgen; Schie, Iwan W.
    Pollen studies play a critical role in various fields of science. In the last couple of decades, replacement of manual identification of pollen by image-based methods using pollen morphological features was a great leap forward, but challenges for pollen with similar morphology remain, and additional approaches are required. Spectroscopy approaches for identification of pollen, such as Raman spectroscopy has potential benefits over traditional methods, due to the investigation of the intrinsic molecular composition of a sample. However, current Raman-based characterization of pollen is complex and time-consuming, resulting in low throughput and limiting the statistical significance of the acquired data. Previously demonstrated high-throughput screening Raman spectroscopy (HTS-RS) eliminates the complexity as well as human interaction by incorporation full automation of the data acquisition process. Here, we present a customization of HTS-RS for pollen identification, enabling sampling of a large number of pollen in comparison to other state-of-the-art Raman pollen investigations. We show that using Raman spectra we are able to provide a preliminary estimation of pollen types based on growth habits using hierarchical cluster analysis (HCA) as well as good taxonomy of 37 different Pollen using principal component analysis-support vector machine (PCA-SVM) with good accuracy even for the pollen specimens sharing similar morphological features. Our results suggest that HTS-RS platform meets the demands for automated pollen detection making it an alternative method for research concerning pollen.
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    Evaluation of shifted excitation Raman difference spectroscopy and comparison to computational background correction methods applied to biochemical Raman spectra
    (Basel : MDPI, 2017) Cordero, Eliana; Korinth, Florian; Stiebing, Clara; Krafft, Christoph; Schie, Iwan W.; Popp, Jürgen
    Raman spectroscopy provides label-free biochemical information from tissue samples without complicated sample preparation. The clinical capability of Raman spectroscopy has been demonstrated in a wide range of in vitro and in vivo applications. However, a challenge for in vivo applications is the simultaneous excitation of auto-fluorescence in the majority of tissues of interest, such as liver, bladder, brain, and others. Raman bands are then superimposed on a fluorescence background, which can be several orders of magnitude larger than the Raman signal. To eliminate the disturbing fluorescence background, several approaches are available. Among instrumentational methods shifted excitation Raman difference spectroscopy (SERDS) has been widely applied and studied. Similarly, computational techniques, for instance extended multiplicative scatter correction (EMSC), have also been employed to remove undesired background contributions. Here, we present a theoretical and experimental evaluation and comparison of fluorescence background removal approaches for Raman spectra based on SERDS and EMSC.
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    Nonresonant Raman spectroscopy of isolated human retina samples complying with laser safety regulations for in vivo measurements
    (Bellingham, Wash. : SPIE, 2019) Stiebing, Clara; Schie, Iwan W.; Knorr, Florian; Schmitt, Michael; Keijzer, Nanda; Kleemann, Robert; Jahn, Izabella J.; Jahn, Martin; Kiliaan, Amanda J.; Ginner, Laurin; Lichtenegger, Antonia; Drexler, Wolfgang; Leitgeb, Rainer A.; Popp, Jürgen
    Retinal diseases, such as age-related macular degeneration, are leading causes of vision impairment, increasing in incidence worldwide due to an aging society. If diagnosed early, most cases could be prevented. In contrast to standard ophthalmic diagnostic tools, Raman spectroscopy can provide a comprehensive overview of the biochemical composition of the retina in a label-free manner. A proof of concept study of the applicability of nonresonant Raman spectroscopy for retinal investigations is presented. Raman imaging provides valuable insights into the molecular composition of an isolated ex vivo human retina sample by probing the entire molecular fingerprint, i.e., the lipid, protein, carotenoid, and nucleic acid content. The results are compared to morphological information obtained by optical coherence tomography of the sample. The challenges of in vivo Raman studies due to laser safety limitations and predefined optical parameters given by the eye itself are explored. An in-house built setup simulating the optical pathway in the human eye was developed and used to demonstrate that even under laser safety regulations and the above-mentioned optical restrictions, Raman spectra of isolated ex vivo human retinas can be recorded. The results strongly support that in vivo studies using nonresonant Raman spectroscopy are feasible and that these studies provide comprehensive molecular information of the human retina. © The Authors. Published by SPIE.
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    Bladder tissue characterization using probe-based Raman spectroscopy: Evaluation of tissue heterogeneity and influence on the model prediction
    (Weinheim : Wiley-VCH-Verl., 2020) Cordero, Eliana; Rüger, Jan; Marti, Dominik; Mondol, Abdullah S.; Hasselager, Thomas; Mogensen, Karin; Hermann, Gregers G.; Popp, Jürgen; Schie, Iwan W.
    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 research. For example, for clinic surveillance of patients with a history of noninvasive bladder tumors real-time tumor diagnosis can enable immediate laser-based removal of tumors using flexible cystoscopes in the outpatient clinic. 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 procedures. For the past decade there has been a rise in applications to diagnose and characterize early cancer in different organs, such as in head and neck, colon and stomach, but also different pathologies, for example, inflammation and atherosclerotic plaques. Bladder pathology has also been studied but only with little attention to aspects that can influence the diagnosis, such as tissue heterogeneity, data preprocessing and model development. The present study presents a clinical investigative study on bladder biopsies to characterize the tumor grading ex vivo, using a compact fiber probe-based imaging Raman system, as a crucial step towards in vivo Raman endoscopy. Furthermore, this study presents an evaluation of the tissue heterogeneity of highly fluorescent bladder tissues, and the multivariate statistical analysis for discrimination between nontumor tissue, and low- and high-grade tumor. © 2019 The Authors. Journal of Biophotonics published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
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    Morpho-molecular signal correlation between optical coherence tomography and Raman spectroscopy for superior image interpretation and clinical diagnosis
    ([London] : Macmillan Publishers Limited, part of Springer Nature, 2021) Schie, Iwan W.; Placzek, Fabian; Knorr, Florian; Cordero, Eliana; Wurster, Lara M.; Hermann, Gregers G.; Mogensen, Karin; Hasselager, Thomas; Drexler, Wolfgang; Popp, Jürgen; Leitgeb, Rainer A.
    The combination of manifold optical imaging modalities resulting in multimodal optical systems allows to discover a larger number of biomarkers than using a single modality. The goal of multimodal imaging systems is to increase the diagnostic performance through the combination of complementary modalities, e.g. optical coherence tomography (OCT) and Raman spectroscopy (RS). The physical signal origins of OCT and RS are distinctly different, i.e. in OCT it is elastic back scattering of photons, due to a change in refractive index, while in RS it is the inelastic scattering between photons and molecules. Despite those diverse characteristics both modalities are also linked via scattering properties and molecular composition of tissue. Here, we investigate for the first time the relation of co-registered OCT and RS signals of human bladder tissue, to demonstrate that the signals of these complementary modalities are inherently intertwined, enabling a direct but more importantly improved interpretation and better understanding of the other modality. This work demonstrates that the benefit for using two complementary imaging approaches is, not only the increased diagnostic value, but the increased information and better understanding of the signal origins of both modalities. This evaluation confirms the advantages for using multimodal imaging systems and also paves the way for significant further improved understanding and clinically interpretation of both modalities in the future.
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    Combination of high-resolution optical coherence tomography and raman spectroscopy for improved staging and grading in bladder cancer
    (Basel : MDPI, 2018) Bovenkamp, Daniela; Sentosa, Ryan; Rank, Elisabet; Erkkilä, Mikael T.; Placzek, Fabian; Püls, Jeremias; Drexler, Wolfgang; Leitgeb, Rainer Andreas; Garstka, Nathalie; Shariat, Shahrokh F.; Stiebing, Clara; Schie, Iwan W.; Popp, Jürgen; Andreana, Marco; Unterhuber, Angelika
    We present a combination of optical coherence tomography (OCT) and Raman spectroscopy (RS) for improved diagnosis and discrimination of different stages and grades of bladder cancer ex vivo by linking the complementary information provided by these two techniques. Bladder samples were obtained from biopsies dissected via transurethral resection of the bladder tumor (TURBT). As OCT provides structural information rapidly, it was used as a red-flag technology to scan the bladder wall for suspicious lesions with the ability to discriminate malignant tissue from healthy urothelium. Upon identification of degenerated tissue via OCT, RS was implemented to determine the molecular characteristics via point measurements at suspicious sites. Combining the complementary information of both modalities allows not only for staging, but also for differentiation of low-grade and high-grade cancer based on a multivariate statistical analysis. OCT was able to clearly differentiate between healthy and malignant tissue by tomogram inspection and achieved an accuracy of 71% in the staging of the tumor, from pTa to pT2, through texture analysis followed by k-nearest neighbor classification. RS yielded an accuracy of 93% in discriminating low-grade from high-grade lesions via principal component analysis followed by k-nearest neighbor classification. In this study, we show the potential of a multi-modal approach with OCT for fast pre-screening and staging of cancerous lesions followed by RS for enhanced discrimination of low-grade and high-grade bladder cancer in a non-destructive, label-free and non-invasive way.
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    Surface-enhanced Raman spectroscopy of cell lysates mixed with silver nanoparticles for tumor classification
    (Frankfurt, M. : Beilstein-Institut zur Förderung der Chemischen Wissenschaften, 2017) Hassoun, Mohamed; Schie, Iwan W.; Tolstik, Tatiana; Stanca, Sarmiza E.; Krafft, Christoph; Popp, Jürgen
    The throughput of spontaneous Raman spectroscopy for cell identification applications is limited to the range of one cell per second because of the relatively low sensitivity. Surface-enhanced Raman scattering (SERS) is a widespread way to amplify the intensity of Raman signals by several orders of magnitude and, consequently, to improve the sensitivity and throughput. SERS protocols using immuno-functionalized nanoparticles turned out to be challenging for cell identification because they require complex preparation procedures. Here, a new SERS strategy is presented for cell classification using non-functionalized silver nanoparticles and potassium chloride to induce aggregation. To demonstrate the principle, cell lysates were prepared by ultrasonication that disrupts the cell membrane and enables interaction of released cellular biomolecules to nanoparticles. This approach was applied to distinguish four cell lines – Capan-1, HepG2, Sk-Hep1 and MCF-7 – using SERS at 785 nm excitation. Six independent batches were prepared per cell line to check the reproducibility. Principal component analysis was applied for data reduction and assessment of spectral variations that were assigned to proteins, nucleotides and carbohydrates. Four principal components were selected as input for classification models based on support vector machines. Leave-three-batches-out cross validation recognized four cell lines with sensitivities, specificities and accuracies above 96%. We conclude that this reproducible and specific SERS approach offers prospects for cell identification using easily preparable silver nanoparticles.