Modern medicine faces a major challenge in preventing, diagnosing, and treating cancer, especially in its early stages. Current tools for early detection and minimally invasive treatment are insufficient. Laser-based nonlinear endoscopy combining CARS, SHG, and TPEF emerges as a promising solution for cancer diagnostics by detecting molecular changes in tissue for differentiating cancer from healthy tissue. We developed an endomicroscopic system for head and neck cancer diagnosis and femtosecond laser ablation of tissue. The system has been validated through ex-vivo measurements on patient tissue slices and machine learning methods are being developed for quantitative comparison with standard H&E histopathology. Acknowledgements: Funding from the European Community’s Horizon 2020 Programme under the grant agreement No. 860185 (PHAST), No 101016923 (CRIMSON) and from the German Federal Ministry of Education and Research (BMBF): within the project TheraOptik (FKZ 13GW0370E) and LPI (Grant Number 13N15467) is acknowledged.

The latest fiber solutions to be described for innovative applications in chemical process control, remote environment monitoring and biomedical diagnostics. Advanced fiber probes based on 4 different fiber types will be presented for their applications in very broad range of spectra 0.3-16µm – designed for all key spectroscopy methods: Transmission/ Reflection, ATR-absorption, Raman and fluorescence, - plus for their various combinations.
The great synergy effect in fusion of spectral data from 2 (or more) spectral methods is available now when the advanced combi-fiber probes collect spectra from the same spot: Raman+DRS (Diffuse Reflection Scattering), Raman+Fluorescence, Near+Mid IR-absorption, Fluorescence + Mid ATR-absorption. Advantages of combi-probe enhanced accuracy to be presented, including the demo of the smallest diameter Raman/Fluorescence probe with <200µm diameter.

Raman microscopy provides a variety of insights into molecular composition, chemical state, and environmental conditions in biological samples. However, biological imaging with Raman microscopy have faced challenges such a low signal-to-noise ratio, mainly due to the low scattering efficiency of Raman scattering. To overcome this limitation, we developed a cryo-Raman microscope integrated with a cryostat capable of rapid freezing of biological samples and low-temperature Raman imaging. The spatiotemporal cryofixation of biological samples allows long exposure measurements to accumulate signals without photodamage. We observed both reduction of photobleaching in resonant Raman scattering of cytochromes in cryofixed HeLa cells, and the preservation of redox states of cytochromes in rat heart tissue by cryofixation.

Probe-based Raman systems are widely used for in-situ measurements. However, the intrinsically weak Raman signals limit its applications. A common approach to collect more Raman photons is by including more collection fibers with taller detectors. However, it is costly and requires modification of the spectrograph.

Most Raman spectra have broad silent spectral regions. Here, we increase the throughput by introducing horizontally shifted collection fibers rather than vertically. Our machine learning technique successfully deconvoluted the original spectra and improved the limit of detection. Our approach is a simple, cost-effective, and universal method to increase the throughput without modifying existing Raman spectrometers.

We report on the development of a simultaneous fingerprint and high-wavenumber (FP/HW) Raman endoscopy platform for real-time, in vivo diagnosis of bladder cancer during transurethral resection of bladder tumor (TURBT). Significant tissue Raman spectral differences are observed in both FP (i.e., 800 – 1800 cm^-1) and HW (i.e., 2800 – 3600 cm^-1) regions between normal and cancer as well as between normal and carcinoma in situ (CIS) tissue sites, indicating the biomolecular differences among cancer, CIS and normal tissue sites. A cancer diagnosis model has been developed based on partial-least-squares linear-discriminant-analysis (PLS-LDA) with leave-one-tissue site-out cross-validation (LOOCV). The diagnosis model yields the diagnostic accuracy of > 90 % for identifying both cancer and CIS sites from normal bladder tissue. Through this work, we demonstrate that in vivo FP/HW fiberoptic Raman endoscopy is a promising and effective clinical tool for rapid diagnosis of cancer and pre-cancer tissue sites during TURBT from biomolecular level.

Our study introduced a custom-built portable Raman system to non-invasively evaluate hepatic steatosis, specifically macrovesicular steatosis, in human liver samples. Using a dual-validation approach with both biochemical and histopathological methods, our preliminary results showed promising correlations between Raman-derived measurements and traditional metrics. Additionally, by integrating supplementary reflectance data, we devised a predictive model that effectively pinpointed discrepancies in liver fat content assessments. This method promises to enhance the accuracy of donor liver evaluations, potentially improving transplant outcomes.

Low frequency Raman spectroscopy finds various applications in pharmaceutical and biomedical research. Simple systems consisting of ultra-narrow volume holographic grating filters combined with a single-stage spectrometer are now available and suitable for a large range of measurements. Nevertheless, complex multi-stage spectrometers still achieve superior performances in terms of contrast and usable spectral range, remaining advantageous for certain samples. We propose a novel low frequency Raman spectrometer scheme which combines the simplicity, compactness, and cost of volume holographic grating-based systems with performances comparable to large multi-stage spectrometers in the range of interest. It consists of a cross-dispersed grating spectrometer combined with serialized fiber Bragg grating filters. We present simulations, proof-of-concept measurements, and discuss considerations for potential deployments outside research laboratories.

We developed a fast Raman spectroscopic discrimination system based on a slit-scanning confocal microscope and machine learning. The speed of discrimination was improved by reducing the number of measurements, without measuring all points in the field of view. During discrimination, the system continues to evaluate the spectra already obtained, which guarantees the accuracy of the discrimination and enables early detection of anomalies by optimizing the measurement positions. We performed discrimination using a mixture of polystyrene (PS) and polymethyl methacrylate (PMMA) microbeads as a sample to mimic cancer tissue and that of fatty liver tissue using mouse liver tissue samples. The results showed that the discrimination was about 2-11 times faster than that by slit scanning confocal microscopy.

We report on the development of multi-needle fiberoptic Raman spectroscopy (MNF-RS) technique for simultaneous multi-site deep tissue Raman measurements of brain. High quality tissue Raman spectra within the range of fingerprint (FP, 800 – 1800 cm^-1) and high-wavenumber (HW, 2800 – 3300 cm^-1) are collected within sub-second integration time using the MNF-RS technique from different tissue types (e.g., muscle, fat, gray matter and white matter from porcine brain). We advance the MNF-RS probes into deep porcine brain for validating its simultaneous Raman spectra acquisition capability from different brain regions (e.g., cortex, thalamus, midbrain and cerebellum). The distinct biochemical differences are identified among different brain locations, indicating the promising potential of MNF-RS technique for label-free neuroscience study at the molecular level.

Two main obstacles preventing widespread use of Raman spectroscopy in medical fields are slow acquisition times and poor classification model transferability. We present techniques for improving data acquisition using minimal sampling or other modalities for rapid pre-screening and an area based dimension reduction technique with improved transferability. We illustrate the strengths and weaknesses of these methods in comparison with common practices. Our investigation is based on microplastic samples. While these samples are not biological, they model problems Raman spectroscopy faces in the medical field on a stable time scale, allowing many measurements for detailed analysis of methods.

The absence of early diagnosis contributes to oesophageal cancer being the sixth most common cause of global cancer-associated deaths, with a five-year survival rate of <20%. Barrett’s oesophagus (BO) is the main pre-cancerous condition to oesophageal adenocarcinoma (OAC) development, characterised by the morphological transition of oesophageal squamous epithelium to metaplastic columnar epithelium. Current diagnostic methods involve invasive techniques such as endoscopies, and with few identified biomarkers of disease progression, OAC detection is costly and challenging. In this work, single-cell Raman spectroscopy was combined with microfluidic techniques to characterise the development of OAC through the progression of healthy epithelial, BO and OAC cell lines. Principal component analysis and linear discriminant analysis were used to classify the different stages of cancer progression. with the ability to differentiate between healthy and cancerous cells with an accuracy of 97%. These results highlight the potential for rapid and reliable diagnostic screening of BO patients.

Lung cancer is difficult to detect using Raman spectroscopy, particularly due to tar fluorescence. We demonstrate improved performance for Raman classifiers by using fixed tissue sections and compare results with immunohistochemistry and hematoxylin and eosin (H&E) staining. In addition to eliminating fluorescence, fixed samples provide the flexibility of additional measurements and provide greater detail in borderline cases. Reliable classifiers based on Raman features would provide an additional tool to detect lung cancer during medical procedures would benefit patients and save medical resources.

Nanomedicine has brought significant advancements to healthcare by utilizing nanotechnology in medicine. Engineered nanoparticles, specifically nanocarriers, have the potential to overcome limitations of conventional drug delivery systems, improving solubility, circulation time, and transport across biological barriers. However, the development of nanocarriers for clinical use has been hindered by a lack of understanding of nano-bio interactions. Conventional imaging methods have limitations in resolution, sensitivity and specificity. Here we introduce stimulated Raman scattering (SRS) microscopy to image nanocarriers with single-particle sensitivity. We demonstrated quantitative analysis of nanocarrier biodistribution and degradation across different tissues including brain, This method provides a powerful tool for studying nanocarriers and quantitatively visualizing their distribution, interaction and clearance in vivo.

A method for trace gas analysis is presented based on stimulated Raman scattering of the analyte in a hollow core photonic crystal fiber. A single beam pulsed laser excitation was used which realized both fiber enhanced Raman scattering and stimulated Raman scattering, that have significant advantages for improving the detection limit. A system was successfully developed based on the method and tested on hydrogen, carbon dioxide, and propene (C₃H₆) gases. From the results we suggest the method has great potential for analyzing trace complex gases such as volatile organic compounds, which can serve as biomarkers in human breath for lung cancer detection.

We employ spectral focusing hyperspectral stimulated Raman scattering (SRS) imaging for longitudinal 3D label-free visualization of microplastics (MP) and biomolecules within live zebrafish throughout the development process. We investigated the uptake routes and size-dependent bioaccumulation of MP in various zebrafish organs across different developmental stages. The altered lipid metabolic dynamics identified by biorthogonal hyperspectral SRS imaging further reveal the hepatic inflammation and energy metabolism disruptions in MP-exposed zebrafish, thus shedding new light on the fate and potential impacts of MP on diverse living organisms.

Vibrational sum-frequency generation (SFG) microscopy is a highly sensitive and selective optical imaging technique capable of retrieving information on the molecular structure of proteins. In this study, we determined the achiral tensor elements Х_ijk^((2)) associated with the the symmetric and asymmetric methylene (CH2) stretching modes of collagen type I through polarization-sensitive SFG measurements, and compared the results with computational modeling based on the crystal structure information from the Protein Data Bank. These findings contribute to our understanding of protein structure and pave the way to predict proteins' non-linear optical properties directly from their crystal structure.

We report a z-scan-free stimulated Raman scattering tomography enabled by generation of ultraslow Bessel beams (B2-SRST) for rapid and deeper label-free volumetric chemical imaging. We demonstrate the utility of B2-SRST in a variety of samples (e.g., polymer beads phantoms and biotissues) for rapid label-free deeper tissue 3D chemical imaging.

Hyperspectral Stimulated Raman Imaging (SRS) has shown great promise as a label-free chemical imaging technique in biomedical and medical research. We present recent developments in SRS integrating a compact and portable all-fiber laser with balanced detection into an imaging system, aiming to enhance ease-of-use, specificity, and reliability in acquiring high-speed, multicolor chemical images. The system's adaptability is highlighted by integrating the entire microscopy system into a clinical cart, ensuring clinical compatibility as well as its seamless integration with a Nikon Eclipse Ti widefield microscope, providing a compact and robust extension for varied imaging setups. The system incorporates a balanced detector to enable shot-noise-limited measurements, accommodating over 100mW of Stokes power on the detector.

Contemporary literature lacks a classical explanation for the infrared and vibrational circular dichroism (VCD) spectra of chiral molecules. VCD spectra are primarily used to determine the absolute configuration of a chiral molecule by comparing experimental data with quantum mechanical calculations. However, classical treatments of IR and VCD spectra can offer some insights, such as the observation that the area of all bands of wavenumber-normalized absorbance above zero must be equal to the area below zero. Advanced techniques like dispersion analysis, which uses wave optics and dispersion theory, can be used to analyze the spectra of chiral substances.

Here, we present vFLETCHERS (visible fluorescence-encoded time-domain coherent Raman spectroscopy), which operates in the visible excitation region and overcomes the previous limitation of detectable fluorophores. vFLETCHERS employs a non-collinear optical parametric amplifier as a femtosecond excitation source. As a proof-of-concept demonstration, we acquired low-frequency Raman spectra (<1000 cm^-1) of solutions containing commercial fluorophores with the absorption peaks in the 600-700 nm region. These results highlight the potential of vFLETCHERS as a versatile multiplexed imaging technique, opening up new opportunities for research in biology.

We developed a simple and convenient magnetic bead-based sample preparation scheme for enabling a Raman spectroscopic differentiation of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) positive and negative samples. By utilizing the angiotensin-converting enzyme 2 (ACE2) receptor protein as selective recognition element, we avoid having to identify the virus species based on its specific Raman signature. Instead we only need to verify the presence of the virus, which is significantly less difficult. For quantitative evaluation of the spectra, we calculated the Pearson coefficient and the Normalized Cross Correlation coefficient.

Atomic force microscopy-infrared spectroscopy (AFM-IR) is a technique that combines the nanoscale spatial resolution of AFM with the chemical specificity of IR spectroscopy. However, conventional AFM-IR methods suffer from low signal-to-noise ratio (SNR), nonchemical artifacts, and inaccurate spectra. A recent advance, null-deflection AFM-IR (NDIR), overcomes these limitations and enables high-fidelity nanoscale chemical imaging of biological samples.

Small molecule imaging plays a crucial role in comprehending biological structures, functions, and disease mechanisms. In this presentation, we will show the effectiveness of this imaging technique through the exploration of different biological samples, such as the intricate visualizations of cellular ultrastructure in thin sections of breast cancer cells. Challenges posed by the extension of this technique to different types of samples and ongoing efforts to make instrumental enhancements will be discussed as well.

Water absorption of mid-infrared (MIR) radiation severely limits the options for vibrational spectroscopy of the analytes – including live biological cells – that must be probed in aqueous environments. I will describe a live cell biosensing platform based on metallic nanoantennas fabricated atop elevated dielectric pillars. When cells are cultured on such metasurfaces integrated with standard bottomless microwells, inverted MIR microscopy can be carried out in reflection mode. Results of hyperspectral real-time imaging of live cells during their attachment, spreading, and chemically-induced apoptosis will be presented. Applications to label-free high-content drug screening will be discussed.