Feasibility studies of multimodal nonlinear endoscopy using multicore fiber bundles for remote scanning from tissue sections to bulk organs.

Here, we report on the development and application of a compact multi-core fiber optical probe for multimodal non-linear imaging, combining the label-free modalities of Coherent Anti-Stokes Raman Scattering, Second Harmonic Generation, and Two-Photon Excited Fluorescence. Probes of this multi-core fiber design avoid moving and voltage-carrying parts at the distal end, thus providing promising improved compatibility with clinical requirements over competing implementations. The performance characteristics of the probe are established using thin cryo-sections and artificial targets before the applicability to clinically relevant samples is evaluated using ex vivo bulk human and porcine intestine tissues. After image reconstruction to counteract the data's inherently pixelated nature, the recorded images show high image quality and morpho-chemical conformity on the tissue level compared to multimodal non-linear images obtained with a laser-scanning microscope using a standard microscope objective. Furthermore, a simple yet effective reconstruction procedure is presented and demonstrated to yield satisfactory results. Finally, a clear pathway for further developments to facilitate a translation of the multimodal fiber probe into real-world clinical evaluation and application is outlined.

Design and test of a rigid endomicroscopic system for multimodal imaging and femtosecond laser ablation.

Significance: Conventional diagnosis of laryngeal cancer is normally made by a combination of endoscopic examination, a subsequent biopsy, and histopathology, but this requires several days and unnecessary biopsies can increase pathologist workload. Nonlinear imaging implemented through endoscopy can shorten this diagnosis time, and localize the margin of the cancerous area with high resolution. Aim: Develop a rigid endomicroscope for the head and neck region, aiming for in-vivo multimodal imaging with a large field of view (FOV) and tissue ablation. Approach: Three nonlinear imaging modalities, which are coherent anti-Stokes Raman scattering, two-photon excitation fluorescence, and second harmonic generation, as well as the single photon fluorescence of indocyanine green, are applied for multimodal endomicroscopic imaging. High-energy femtosecond laser pulses are transmitted for tissue ablation. Results: This endomicroscopic system consists of two major parts, one is the rigid endomicroscopic tube 250 mm in length and 6 mm in diameter, and the other is the scan-head (10×12×6 cm3 in size) for quasi-static scanning imaging. The final multimodal image accomplishes a maximum FOV up to 650 µm, and a resolution of 1 µm is achieved over 560 µm FOV. The optics can easily guide sub-picosecond pulses for ablation. Conclusions: The system exhibits large potential for helping real-time tissue diagnosis in surgery, by providing histological tissue information with a large FOV and high resolution, label-free. By guiding high-energy fs laser pulses, the system is even able to remove suspicious tissue areas, as has been shown for thin tissue sections in this study.

Multimodal nonlinear endomicroscopic imaging probe using a double-core double-clad fiber and focus-combining micro-optical concept.

Multimodal non-linear microscopy combining coherent anti-Stokes Raman scattering, second harmonic generation, and two-photon excited fluorescence has proved to be a versatile and powerful tool enabling the label-free investigation of tissue structure, molecular composition, and correlation with function and disease status. For a routine medical application, the implementation of this approach into an in vivo imaging endoscope is required. However, this is a difficult task due to the requirements of a multicolour ultrashort laser delivery from a compact and robust laser source through a fiber with low losses and temporal synchronization, the efficient signal collection in epi-direction, the need for small-diameter but highly corrected endomicroobjectives of high numerical aperture and compact scanners. Here, we introduce an ultra-compact fiber-scanning endoscope platform for multimodal non-linear endomicroscopy in combination with a compact four-wave mixing based fiber laser. The heart of this fiber-scanning endoscope is an in-house custom-designed, single mode, double clad, double core pure silica fiber in combination with a 2.4 mm diameter NIR-dual-waveband corrected endomicroscopic objective of 0.55 numerical aperture and 180 µm field of view for non-linear imaging, allowing a background free, low-loss, high peak power laser delivery, and an efficient signal collection in backward direction. A linear diffractive optical grating overlays pump and Stokes laser foci across the full field of view, such that diffraction-limited performance is demonstrated for tissue imaging at one frame per second with sub-micron spatial resolution and at a high transmission of 65% from the laser to the specimen using a distal resonant fiber scanner.

In vivo coherent anti-Stokes Raman scattering microscopy reveals vitamin A distribution in the liver.

Here we present a microscope setup for coherent anti-Stokes Raman scattering (CARS) imaging, devised to specifically address the challenges of in vivo experiments. We exemplify its capabilities by demonstrating how CARS microscopy can be used to identify vitamin A (VA) accumulations in the liver of a living mouse, marking the positions of hepatic stellate cells (HSCs). HSCs are the main source of extracellular matrix protein after hepatic injury and are therefore the main target of novel nanomedical strategies in the development of a treatment for liver fibrosis. Their role in the VA metabolism makes them an ideal target for a CARS-based approach as they store most of the body's VA, a class of compounds sharing a retinyl group as a structural motive, a moiety that is well known for its exceptionally high Raman cross section of the C═C stretching vibration of the conjugated backbone.

FLIM data analysis based on Laguerre polynomial decomposition and machine-learning.

SIGNIFICANCE: 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. CONCLUSIONS: The ML-based approach shows great performance in FLIM data analysis.

Comparison of standard and HD FT-IR with multimodal CARS/TPEF/SHG/FLIMS imaging in the detection of the early stage of pulmonary metastasis of murine breast cancer.

Lungs, due to their high oxygen availability and vascularization, are an ideal environment for cancer cell migration, metastasis and tumour formation. These processes are directly connected with extracellular matrix (ECM) remodelling, resulting from cancer cell infiltration and preparation of the environment suitable for tumour growth. Herein, we compare the potential of fast, label-free and non-destructive methods of Fourier-transform infrared spectroscopy (FT-IR) in standard and high definition (HD) modes with nonlinear coherent anti-Stokes Raman scattering (CARS), second harmonic generation (SHG), two-photon excited fluorescence (TPEF) and a fluorescence lifetime imaging (FLIM) technique for lung metastasis detection. We show their potential in the detection of lung macrometastasis, in which we already observed the ECM remodelling. The CARS image revealed a dense cell fraction typical of ECM remodeling and reduction of the TPEF signal together with an increase of fluorescence lifetime predominantly due to NAD(P)H suggesting metabolic changes in the metastatic foci. FT-IR spectroscopy allowed not only for macrometastasis detection but also their stage definition based mainly on the analysis of proteins, RNA and glycogen fractions. The multimodal approach additionally suggested partial enzymatic degradation of elastin in ECM and collagen remodelling.

Non-invasive Imaging Techniques: From Histology to In Vivo Imaging : Chapter of Imaging in Oncology.

In this chapter, we will introduce and review molecular-sensitive imaging techniques, which close the gap between ex vivo and in vivo analysis. In detail, we will introduce spontaneous Raman spectral imaging, coherent anti-Stokes Raman scattering (CARS), stimulated Raman scattering (SRS), second-harmonic generation (SHG) and third-harmonic generation (THG), two-photon excited fluorescence (TPEF), and fluorescence lifetime imaging (FLIM). After reviewing these imaging techniques, we shortly introduce chemometric methods and machine learning techniques, which are needed to use these imaging techniques in diagnostic applications.

Differential response of liver sinusoidal endothelial cells and hepatocytes to oleic and palmitic acid revealed by Raman and CARS imaging.

Excess circulating fatty acids contribute to endothelial dysfunction that subsequently aggravates the metabolic conditions such as fatty liver diseases. However, the exact mechanism of this event is not fully understood, and the investigation on the effect of a direct exposure to fatty acids together with their subsequent fate is of interest. In this work we employed a chemically specific and label-free techniques such as Raman and CARS microscopies, to investigate the process of lipid droplets (LDs) formation in endothelial cells and hepatocytes after exposure to oleic and palmitic acid. We aimed to observe the changes in the composition of LDs associated with metabolism and degradation of lipids. We were able to characterize the diversity in the formation of LDs in endothelium as compared to hepatocytes, as well as the differences in the formation of LDs and degradation manner with respect to the used fatty acid. Thus, for the first time the spectral characteristics of LDs formed in endothelial cells after incubation with oleic and palmitic acid is presented, including the time-dependent changes in their chemical composition.

Multimodal Nonlinear Microscopy for Therapy Monitoring of Cold Atmospheric Plasma Treatment.

Here we report on a non-linear spectroscopic method for visualization of cold atmospheric plasma (CAP)-induced changes in tissue for reaching a new quality level of CAP application in medicine via online monitoring of wound or cancer treatment. A combination of coherent anti-Stokes Raman scattering (CARS), two-photon fluorescence lifetime imaging (2P-FLIM) and second harmonic generation (SHG) microscopy has been used for non-invasive and label-free detection of CAP-induced changes on human skin and mucosa samples. By correlation with histochemical staining, the observed local increase in fluorescence could be assigned to melanin. CARS and SHG prove the integrity of the tissue structure, visualize tissue morphology and composition. The influence of plasma effects by variation of plasma parameters e.g., duration of treatment, gas composition and plasma source has been evaluated. Overall quantitative spectroscopic markers could be identified for a direct monitoring of CAP-treated tissue areas, which is very important for translating CAPs into clinical routine.

Nonlinear Multimodal Imaging Characteristics of Early Septic Liver Injury in a Mouse Model of Peritonitis.

Sepsis constitutes a life-threatening organ failure caused by a deregulated host response to infection. Identifying early biomolecular indicators of organ dysfunction may improve clinical decision-making and outcome of patients. Herein we utilized label-free nonlinear multimodal imaging, combining coherent anti-Stokes Raman scattering (CARS), two-photon excited autofluorescence (TPEF), and second-harmonic generation (SHG) to investigate the consequences of early septic liver injury in a murine model of polymicrobial abdominal infection. Liver tissue sections from mice with and without abdominal sepsis were analyzed using multimodal nonlinear microscopy, immunofluorescence, immunohistochemistry, and quantitative reverse transcription polymerase chain reaction (qRT-PCR). Twenty-four hours after the induction of sepsis, hepatic mRNA of inflammatory cytokines and acute phase proteins was upregulated, and liver-infiltrating myeloid cells could be visualized alongside hepatocellular cytoplasmic translocation of high mobility group box 1. According to the statistical analysis based on texture feature extraction followed by the combination of dimension reduction and linear discriminant analysis, CARS (AUC = 0.93) and TPEF (AUC = 0.83) showed an excellent discrimination between liver sections from septic mice and sham-treated mice in contrast to SHG (AUC = 0.49). Spatial analysis revealed no major differences in the distribution of sepsis-associated changes between periportal and pericentral zones. These data suggest early alterations in hepatic lipid distribution and metabolism during liver injury and confirm nonlinear multimodal imaging as a promising complementary method for the real-time, label-free study of septic liver damage.