It's free imaging - label-free, that is

An enhanced multimode phase imaging method based on the transport of intensity equation

Label-free biological cell imaging relies on rapid multimode phase imaging of biological samples in natural settings. To improve image contrast, phase is encoded into intensity information using the differential interference contrast (DIC) and Zernike phase contrast (ZPC) techniques. To enable multimode contrast-enhanced observation of unstained specimens, this paper proposes an improved multimode phase imaging method based on the transport of intensity equation (TIE), which combines conventional microscopy with computational imaging. The ZPC imaging module based on adaptive aperture adjustment is applied when the quantitative phase results of biological samples have been obtained by solving the TIE. Simultaneously, a rotationally symmetric shear-based technique is used that can yield isotropic DIC. In this paper, we describe numerical simulation and optical experiments carried out to validate the accuracy and viability of this technology. The calculated Michelson contrast of the ZPC image in the resolution plate experiment increased from 0.196 to 0.394.

Label-free morpho-molecular phenotyping of living cancer cells by combined Raman spectroscopy and phase tomography

Accurate, rapid and non-invasive cancer cell phenotyping is a pressing concern across the life sciences, as standard immuno-chemical imaging and omics require extended sample manipulation. Here we combine Raman micro-spectroscopy and phase tomography to achieve label-free morpho-molecular profiling of human colon cancer cells, following the adenoma, carcinoma, and metastasis disease progression, in living and unperturbed conditions. We describe how to decode and interpret quantitative chemical and co-registered morphological cell traits from Raman fingerprint spectra and refractive index tomograms. Our multimodal imaging strategy rapidly distinguishes cancer phenotypes, limiting observations to a low number of pristine cells in culture. This synergistic dataset allows us to study independent or correlated information in spectral and tomographic maps, and how it benefits cell type inference. This method is a valuable asset in biomedical research, particularly when biological material is in short supply, and it holds the potential for non-invasive monitoring of cancer progression in living organisms.

Label-free optical imaging for brain cancer assessment

Advances in label-free optical imaging offer a promising avenue for brain cancer assessment, providing high-resolution, real-time insights without the need for radiation or exogeneous agents. These cost-effective and intricately detailed techniques overcome the limitations inherent in magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET) scans by offering superior resolution and more readily accessible imaging options. This comprehensive review explores a variety of such methods, including photoacoustic imaging (PAI), optical coherence tomography (OCT), Raman imaging, and IR microscopy. It focuses on their roles in the detection, diagnosis, and management of brain tumors. By highlighting recent advances in these imaging techniques, the review aims to underscore the importance of label-free optical imaging in enhancing early detection and refining therapeutic strategies for brain cancer.

Automated Whole Slide Imaging for Label-Free Histology Using Photon Absorption Remote Sensing Microscopy

OBJECTIVE

Pathologists rely on histochemical stains to impart contrast in thin translucent tissue samples, revealing tissue features necessary for identifying pathological conditions. However, the chemical labeling process is destructive and often irreversible or challenging to undo, imposing practical limits on the number of stains that can be applied to the same tissue section. Here we present an automated label-free whole slide scanner using a PARS microscope designed for imaging thin, transmissible samples.

METHODS

Peak SNR and in-focus acquisitions are achieved across entire tissue sections using the scattering signal from the PARS detection beam to measure the optimal focal plane. Whole slide images (WSI) are seamlessly stitched together using a custom contrast leveling algorithm. Identical tissue sections are subsequently H&E stained and brightfield imaged. The one-to-one WSIs from both modalities are visually and quantitatively compared.

RESULTS

PARS WSIs are presented at standard 40x magnification in malignant human breast and skin samples. We show correspondence of subcellular diagnostic details in both PARS and H&E WSIs and demonstrate virtual H&E staining of an entire PARS WSI. The one-to-one WSI from both modalities show quantitative similarity in nuclear features and structural information.

CONCLUSION

PARS WSIs are compatible with existing digital pathology tools, and samples remain suitable for histochemical, immunohistochemical, and other staining techniques.

SIGNIFICANCE

This work is a critical advance for integrating label-free optical methods into standard histopathology workflows.

Raman Flow Cytometry and Its Biomedical Applications

Raman flow cytometry (RFC) uniquely integrates the "label-free" capability of Raman spectroscopy with the "high-throughput" attribute of traditional flow cytometry (FCM), offering exceptional performance in cell characterization and sorting. Unlike conventional FCM, RFC stands out for its elimination of the dependency on fluorescent labels, thereby reducing interference with the natural state of cells. Furthermore, it significantly enhances the detection information, providing a more comprehensive chemical fingerprint of cells. This review thoroughly discusses the fundamental principles and technological advantages of RFC and elaborates on its various applications in the biomedical field, from identifying and characterizing cancer cells for in vivo cancer detection and surveillance to sorting stem cells, paving the way for cell therapy, and identifying metabolic products of microbial cells, enabling the differentiation of microbial subgroups. Moreover, we delve into the current challenges and future directions regarding the improvement in sensitivity and throughput. This holds significant implications for the field of cell analysis, especially for the advancement of metabolomics.

Dynamic structured illumination for confocal microscopy

Structured illumination enables the tailoring of an imaging device's optical transfer function to enhance resolution. We propose the incorporation of a temporal periodic modulation, specifically a rotating mask, to encode multiple transfer functions in the temporal domain. This approach is demonstrated using a confocal microscope configuration. At each scanning position, a temporal periodic signal is recorded. By filtering around each harmonic of the rotation frequency, multiple images of the same object can be constructed. The image carried by the nth harmonic is a convolution of the object with a phase vortex of topological charge n, similar to the outcome when using a vortex phase plate as an illumination. This enables the collection of chosen high spatial frequencies from the sample, thereby enhancing the spatial resolution of the confocal microscope.

Deep Learning Approach for the Localization and Analysis of Surface Plasmon Scattering

Surface plasmon resonance microscopy (SPRM) combines the principles of traditional microscopy with the versatility of surface plasmons to develop label-free imaging methods. This paper describes a proof-of-principles approach based on deep learning that utilized the Y-Net convolutional neural network model to improve the detection and analysis methodology of SPRM. A machine-learning based image analysis technique was used to provide a method for the one-shot analysis of SPRM images to estimate scattering parameters such as the scatterer location. The method was assessed by applying the approach to SPRM images and reconstructing an image from the network output for comparison with the original image. The results showed that deep learning can localize scatterers and predict other variables of scattering objects with high accuracy in a noisy environment. The results also confirmed that with a larger field of view, deep learning can be used to improve traditional SPRM such that it localizes and produces scatterer characteristics in one shot, considerably increasing the detection capabilities of SPRM.

Short-wavelength excitation two-photon intravital microscopy of endogenous fluorophores

The noninvasive two-photon excitation autofluorescence imaging of cellular and subcellular structure and dynamics in live tissue could provide critical in vivo information for biomedical studies. However, the two-photon microscopy of short-wavelength endogenous fluorophores, such as tryptophan and hemoglobin, is extremely limited due to the lack of suitable imaging techniques. In this study, we developed a short-wavelength excitation time- and spectrum-resolved two-photon microscopy system. A 520-nm femtosecond fiber laser was used as the excitation source, and a time-correlated single-photon counting module connected with a spectrograph was used to provide time- and spectrum-resolved detection capability. The system was specially designed for measuring ultraviolet and violet-blue fluorescence signals and thus was very suitable for imaging short-wavelength endogenous fluorophores. Using the system, we systematically compared the fluorescence spectra and fluorescence lifetimes of short-wavelength endogenous fluorophores, including the fluorescent molecules tyrosine, tryptophan, serotonin (5-HT), niacin (vitamin B3), pyridoxine (vitamin B6), and NADH and the protein group (keratin, elastin, and hemoglobin). Then, high-resolution three-dimensional (3D) label-free imaging of different biological tissues, including rat esophageal tissue, rat oral cheek tissue, and mouse ear skin, was performed in vivo or ex vivo. Finally, we conducted time-lapse imaging of leukocyte migration in the lipopolysaccharide injection immunization model and a mechanical trauma immunization model. The results indicate that the system can specifically characterize short-wavelength endogenous fluorophores and provide noninvasive label-free 3D visualization of fine structures and dynamics in biological systems. The microscopy system developed here can empower more flexible imaging of endogenous fluorophores and provide a novel method for the 3D monitoring of biological events in their native environment.

Spatially Resolved Protein Binding Kinetics Analysis in Microfluidic Photonic Crystal Sensors

Organ-on-a-Chip systems are emerging as an important in vitro analysis method for drug screening and medical research. For continuous biomolecular monitoring of the cell culture response, label-free detection within the microfluidic system or in the drainage tube is promising. We study photonic crystal slabs integrated with a microfluidic chip as an optical transducer for label-free biomarker detection with a non-contact readout of binding kinetics. This work analyzes the capability of same-channel reference for protein binding measurements by using a spectrometer and 1D spatially resolved data evaluation with a spatial resolution of 1.2 μm. A cross-correlation-based data-analysis procedure is implemented. First, an ethanol-water dilution series is used to obtain the limit of detection (LOD). The median of all row LODs is (2.3±0.4)×10-4 RIU with 10 s exposure time per image and (1.3±0.24)×10-4 RIU with 30 s exposure time. Next, we used a streptavidin-biotin binding process as a test system for binding kinetics. Time series of optical spectra were recorded while constantly injecting streptavidin in DPBS at concentrations of 1.6 nM, 3.3 nM, 16.6 nM and 33.3 nM into one channel half as well as the whole channel. The results show that localized binding within a microfluidic channel is achieved under laminar flow. Furthermore, binding kinetics are fading out at the microfluidic channel edge due to the velocity profile.

In vivo tracking of unlabelled mesenchymal stromal cells by mannose-weighted chemical exchange saturation transfer MRI

The tracking of the in vivo biodistribution of transplanted human mesenchymal stromal cells (hMSCs) relies on reporter genes or on the addition of exogenous imaging agents. However, reporter genes and exogenous labels may require bespoke manufacturing and regulatory processes if used in cell therapies, and the labels may alter the cells' properties and are diluted on cellular division. Here we show that high-mannose N-linked glycans, which are abundantly expressed on the surface of hMSCs, can serve as a biomarker for the label-free tracking of transplanted hMSCs by mannose-weighted chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI). For live mice with luciferase-transfected hMSCs transplanted into their brains, post-mortem fluorescence staining with a mannose-specific lectin showed that increases in the CEST MRI signal, which correlated well with the bioluminescence intensity of viable hMSCs for 14 days, corresponded to the presence of mannose. In vitro, osteogenically differentiated hMSCs led to lower CEST MRI signal intensities owing to the concomitantly reduced expression of mannose. The label-free imaging of hMSCs may facilitate the development and testing of cell therapies.

Label-free metabolic and structural profiling of dynamic biological samples using multimodal optical microscopy with sensorless adaptive optics

Label-free optical microscopy has matured as a noninvasive tool for biological imaging; yet, it is criticized for its lack of specificity, slow acquisition and processing times, and weak and noisy optical signals that lead to inaccuracies in quantification. We introduce FOCALS (Fast Optical Coherence, Autofluorescence Lifetime imaging, and Second harmonic generation) microscopy capable of generating NAD(P)H fluorescence lifetime, second harmonic generation (SHG), and polarization-sensitive optical coherence microscopy (OCM) images simultaneously. Multimodal imaging generates quantitative metabolic and morphological profiles of biological samples in vitro, ex vivo, and in vivo. Fast analog detection of fluorescence lifetime and real-time processing on a graphical processing unit enables longitudinal imaging of biological dynamics. We detail the effect of optical aberrations on the accuracy of FLIM beyond the context of undistorting image features. To compensate for the sample-induced aberrations, we implemented a closed-loop single-shot sensorless adaptive optics solution, which uses computational adaptive optics of OCM for wavefront estimation within 2 s and improves the quality of quantitative fluorescence imaging in thick tissues. Multimodal imaging with complementary contrasts improves the specificity and enables multidimensional quantification of the optical signatures in vitro, ex vivo, and in vivo, fast acquisition and real-time processing improve imaging speed by 4-40 × while maintaining enough signal for quantitative nonlinear microscopy, and adaptive optics improves the overall versatility, which enable FOCALS microscopy to overcome the limits of traditional label-free imaging techniques.

Practical considerations for quantitative and reproducible measurements with stimulated Raman scattering microscopy

This tutorial review presents the most important practical considerations for sample preparation, instrument set-up, image acquisition and data analysis to obtain reproducible SRS measurements.

Fast Label-Free Nanoscale Composition Mapping of Eukaryotic Cells Via Scanning Dielectric Force Volume Microscopy and Machine Learning

Mapping the biochemical composition of eukaryotic cells without the use of exogenous labels is a long-sought objective in cell biology. Recently, it has been shown that composition maps on dry single bacterial cells with nanoscale spatial resolution can be inferred from quantitative nanoscale dielectric constant maps obtained with the scanning dielectric microscope. Here, it is shown that this approach can also be applied to the much more challenging case of fixed and dry eukaryotic cells, which are highly heterogeneous and show micrometric topographic variations. More importantly, it is demonstrated that the main bottleneck of the technique (the long computation times required to extract the nanoscale dielectric constant maps) can be shortcut by using supervised neural networks, decreasing them from weeks to seconds in a wokstation computer. This easy-to-use data-driven approach opens the door for in situ and on-the-fly label free nanoscale composition mapping of eukaryotic cells with scanning dielectric microscopy.

Simultaneous 4-phase-shifted full-field optical coherence microscopy

A new method is presented for full-field optical coherence tomography imaging, which permits capturing single shot phase sensitive imaging through simultaneous acquisition of four phase-shifted images with a single camera using unpolarized light for object illumination. Our method retains the full dynamic range of the camera by using different areas of a single camera sensor to capture each image. We demonstrate the performance of our method by imaging phantoms and live cultures of fibroblast, cancer, and macrophage cells to achieve 59 dB sensitivity with isotropic resolution down to 1 μm, and displacement sensitivity down to 0.1 nm. Our method can serve as a platform for developing high resolution imaging systems because when used in conjunction with broadband spatially incoherent light sources, the resolution is not affected by optical aberrations or speckle noise.