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- ItemIn-vivo Raman spectroscopy: from basics to applications(Bellingham, Wash. : SPIE, 2018) Cordero, Eliana; Latka, Ines; Matthäus, Christian; Schie, Iwan W.; Popp, JürgenFor 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.
- ItemUse of polymers as wavenumber calibration standards in deep-UVRR(Amsterdam [u.a.] : Elsevier Science, 2022) Pistiki, Aikaterini; Ryabchykov, Oleg; Bocklitz, Thomas W.; Rösch, Petra; Popp, JürgenDeep-UV resonance Raman spectroscopy (UVRR) allows the classification of bacterial species with high accuracy and is a promising tool to be developed for clinical application. For this attempt, the optimization of the wavenumber calibration is required to correct the overtime changes of the Raman setup. In the present study, different polymers were investigated as potential calibration agents. The ones with many sharp bands within the spectral range 400–1900 cm−1 were selected and used for wavenumber calibration of bacterial spectra. Classification models were built using a training cross-validation dataset that was then evaluated with an independent test dataset obtained after 4 months. Without calibration, the training cross-validation dataset provided an accuracy for differentiation above 99 % that dropped to 51.2 % after test evaluation. Applying the test evaluation with PET and Teflon calibration allowed correct assignment of all spectra of Gram-positive isolates. Calibration with PS and PEI leads to misclassifications that could be overcome with majority voting. Concerning the very closely related and similar in genome and cell biochemistry Enterobacteriaceae species, all spectra of the training cross-validation dataset were correctly classified but were misclassified in test evaluation. These results show the importance of selecting the most suitable calibration agent in the classification of bacterial species and help in the optimization of the deep-UVRR technique.
- ItemA rigid coherent anti-Stokes Raman scattering endoscope with high resolution and a large field of view(College Park : American Institute of Physics, 2018) Zirak, P.; Matz, Gregor; Messerschmidt, Bernhard; Meyer, Tobias; Schmitt, Michael; Popp, Jürgen; Uckermann, Ortrud; Galli, R.; Kirsch, Matthias; Winterhalder, M.J.; Zumbusch, A.Nonlinear optical endoscopy is an attractive technique for biomedical imaging since it promises to give access to high resolution imaging in vivo. Among the various techniques used for endoscopic contrast generation, coherent anti-Stokes Raman scattering (CARS) is especially interesting. CARS endoscopy allows molecule specific imaging of unlabeled samples. In this contribution, we describe the design, implementation, and experimental characterization of a rigid, compact CARS endoscope with a spatial resolution of 750 nm over a field of view of roughly 250 μm. Omission of the relay optics and use of a gradient index lens specifically designed for this application allow one to realize these specifications in an endoscopic unit which is 2.2 mm wide over a length of 187 mm, making clinical applications during surgical interventions possible. Multimodal use of the endoscope is demonstrated with images of samples with neurosurgical relevance.Nonlinear optical endoscopy is an attractive technique for biomedical imaging since it promises to give access to high resolution imaging in vivo. Among the various techniques used for endoscopic contrast generation, coherent anti-Stokes Raman scattering (CARS) is especially interesting. CARS endoscopy allows molecule specific imaging of unlabeled samples. In this contribution, we describe the design, implementation, and experimental characterization of a rigid, compact CARS endoscope with a spatial resolution of 750 nm over a field of view of roughly 250 μm. Omission of the relay optics and use of a gradient index lens specifically designed for this application allow one to realize these specifications in an endoscopic unit which is 2.2 mm wide over a length of 187 mm, making clinical applications during surgical interventions possible. Multimodal use of the endoscope is demonstrated with images of samples with neurosurgical relevance.
- ItemLiquid-Core Microstructured Polymer Optical Fiber as Fiber-Enhanced Raman Spectroscopy Probe for Glucose Sensing(Washington, DC : OSA, 2020) Azkune, Mikel; Frosch, Timea; Arrospide, Eneko; Aldabaldetreku, Gotzon; Bikandi, Iñaki; Zubia, Joseba; Popp, Jürgen; Frosch, TorstenThis work reports the development and application of two liquid-core microstructured polymer optical fibers (LC-mPOF) with different microstructure sizes. They are used in a fiber-enhanced Raman spectroscopy sensing platform, with the aim of detecting glucose in aqueous solutions in the clinically relevant range for sodium-glucose cotransporter 2 inhibitor therapy. The sensing platform is tested for low-concentration glucose solutions using each LC-mPOF. Results confirm that a significant enhancement of the Raman signal is achieved in comparison to conventional Raman spectroscopy. Additional measurements are carried out to obtain the valid measurement range, the resolution, and the limit of detection, showing that the LC-mPOF with 66-µm-diameter central hollow core has the highest potential for future clinical applications. Finally, preliminary tests successfully demonstrate glucose identification in urine. © 1983-2012 IEEE.
- ItemCombination 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, AngelikaWe 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.
- ItemPeriodic array-based substrates for surface-enhanced infrared spectroscopy(Berlin : de Gruyter, 2017-7-29) Mayerhöfer, Thomas G.; Popp, JürgenAt the beginning of the 1980s, the first reports of surface-enhanced infrared spectroscopy (SEIRS) surfaced. Probably due to signal-enhancement factors of only 101 to 103, which are modest compared to those of surface-enhanced Raman spectroscopy (SERS), SEIRS did not reach the same significance up to date. However, taking the compared to Raman scattering much larger cross-sections of infrared absorptions and the enhancement factors together, SEIRS reaches about the same sensitivity for molecular species on a surface in terms of the cross-sections as SERS and, due to the complementary nature of both techniques, can valuably augment information gained by SERS. For the first 20 years since its discovery, SEIRS relied completely on metal island films, fabricated by either vapor or electrochemical deposition. The resulting films showed a strong variance concerning their structure, which was essentially random. Therefore, the increase in the corresponding signal-enhancement factors of these structures stagnated in the last years. In the very same years, however, the development of periodic array-based substrates helped SEIRS to gather momentum. This development was supported by technological progress concerning electromagnetic field solvers, which help to understand plasmonic properties and allow targeted design. In addition, the strong progress concerning modern fabrication methods allowed to implement these designs into practice. The aim of this contribution is to critically review the development of these engineered surfaces for SEIRS, to compare the different approaches with regard to their performance where possible, and report further gain of knowledge around and in relation to these structures.
- ItemFLIM data analysis based on Laguerre polynomial decomposition and machine-learning(Bellingham, Wash. : SPIE, 2021) Guo, Shuxia; Silge, Anja; Bae, Hyeonsoo; Tolstik, Tatiana; Meyer, Tobias; Matziolis, Georg; Schmitt, Michael; Popp, Jürgen; Bocklitz, ThomasSignificance: The potential of fluorescence lifetime imaging microscopy (FLIM) is recently being recognized, especially in biological studies. However, FLIM does not directly measure the lifetimes, rather it records the fluorescence decay traces. The lifetimes and/or abundances have to be estimated from these traces during the phase of data processing. To precisely estimate these parameters is challenging and requires a well-designed computer program. Conventionally employed methods, which are based on curve fitting, are computationally expensive and limited in performance especially for highly noisy FLIM data. The graphical analysis, while free of fit, requires calibration samples for a quantitative analysis. Aim: We propose to extract the lifetimes and abundances directly from the decay traces through machine learning (ML). Approach: The ML-based approach was verified with simulated testing data in which the lifetimes and abundances were known exactly. Thereafter, we compared its performance with the commercial software SPCImage based on datasets measured from biological samples on a time-correlated single photon counting system. We reconstructed the decay traces using the lifetime and abundance values estimated by ML and SPCImage methods and utilized the root-mean-squared-error (RMSE) as marker. Results: The RMSE, which represents the difference between the reconstructed and measured decay traces, was observed to be lower for ML than for SPCImage. In addition, we could demonstrate with a three-component analysis the high potential and flexibility of the ML method to deal with more than two lifetime components.
- ItemFiber-based SORS-SERDS system and chemometrics for the diagnostics and therapy monitoring of psoriasis inflammatory disease in vivo(Washington, DC : Optica, 2021-1-28) Schleusener, Johannes; Guo, Shuxia; Darvin, Maxim E.; Thiede, Gisela; Chernavskaia, Olga; Knorr, Florian; Lademann, Jürgen; Popp, Jürgen; Bocklitz, Thomas W.Psoriasis is considered a widespread dermatological disease that can strongly affect the quality of life. Currently, the treatment is continued until the skin surface appears clinically healed. However, lesions appearing normal may contain modifications in deeper layers. To terminate the treatment too early can highly increase the risk of relapses. Therefore, techniques are needed for a better knowledge of the treatment process, especially to detect the lesion modifications in deeper layers. In this study, we developed a fiber-based SORS-SERDS system in combination with machine learning algorithms to non-invasively determine the treatment efficiency of psoriasis. The system was designed to acquire Raman spectra from three different depths into the skin, which provide rich information about the skin modifications in deeper layers. This way, it is expected to prevent the occurrence of relapses in case of a too short treatment. The method was verified with a study of 24 patients upon their two visits: the data is acquired at the beginning of a standard treatment (visit 1) and four months afterwards (visit 2). A mean sensitivity of ≥85% was achieved to distinguish psoriasis from normal skin at visit 1. At visit 2, where the patients were healed according to the clinical appearance, the mean sensitivity was ≈65%.
- ItemLooking for a perfect match: multimodal combinations of Raman spectroscopy for biomedical applications(Bellingham, Wash. : SPIE, 2021) Schie, Iwan; Stiebing, Clara; Popp, JürgenRaman spectroscopy has shown very promising results in medical diagnostics by providing label-free and highly specific molecular information of pathological tissue ex vivo and in vivo. Nevertheless, the high specificity of Raman spectroscopy comes at a price, i.e., low acquisition rate, no direct access to depth information, and limited sampling areas. However, a similar case regarding advantages and disadvantages can also be made for other highly regarded optical modalities, such as optical coherence tomography, autofluorescence imaging and fluorescence spectroscopy, fluorescence lifetime microscopy, second-harmonic generation, and others. While in these modalities the acquisition speed is significantly higher, they have no or only limited molecular specificity and are only sensitive to a small group of molecules. It can be safely stated that a single modality provides only a limited view on a specific aspect of a biological specimen and cannot assess the entire complexity of a sample. To solve this issue, multimodal optical systems, which combine different optical modalities tailored to a particular need, become more and more common in translational research and will be indispensable diagnostic tools in clinical pathology in the near future. These systems can assess different and partially complementary aspects of a sample and provide a distinct set of independent biomarkers. Here, we want to give an overview on the development of multimodal systems that use RS in combination with other optical modalities to improve the diagnostic performance.