Spatial light interference microscopy: principle and applications to biomedicine

Dual Photonics Probing of Nano- to Submicron-Scale Structural Alterations in Human Brain Tissues/Cells and Chromatin/DNA with the Progression of Alzheimer's Disease

Understanding alterations in structural disorders in tissue/cells/building blocks, such as DNA/chromatin in the human brain, at the nano to submicron level provides us with efficient biomarkers for Alzheimer's detection. Here, we report a dual photonics technique to detect nano- to submicron-scale alterations in brain tissues/cells and DNA/chromatin due to the early to late progression of Alzheimer's disease in humans. Using a recently developed mesoscopic light transport technique, fine-focused nano-sensitive partial wave spectroscopy (PWS), we measure the degree of structural disorder in tissues. Furthermore, the chemical-specific inverse participation ratio technique (IPR) was used to measure the DNA/chromatin structural alterations. The results of the PWS and IPR experiments showed a significant increase in the degree of structural disorder at the nano to submicron scale at different stages of AD relative to their controls for both the tissue/cell and DNA cellular levels. The increase in the structural disorder in cells/tissues and DNA/chromatin in the nuclei can be attributed to higher mass density fluctuations in the tissue and DNA/chromatin damage in the nuclei caused by the rearrangements of macromolecules due to the deposition of the amyloid beta protein and damage in DNA/chromatin with the progress of AD.

Quantitative phase imaging endoscopy with a metalens

Quantitative phase imaging (QPI) recovers the exact wavefront of light from intensity measurements. Topographical and optical density maps of translucent microscopic bodies can be extracted from these quantified phase shifts. We demonstrate quantitative phase imaging at the tip of a coherent fiber bundle using chromatic aberrations inherent in a silicon nitride hyperboloid metalens. Our method leverages spectral multiplexing to recover phase from multiple defocus planes in a single capture using a color camera. Our 0.5 mm aperture metalens shows robust quantitative phase imaging capability with a28 ∘ field of view and 0. 2 π phase resolution ( ~ 0. 1 λ in air) for experiments with an endoscopic fiber bundle. Since the spectral functionality is encoded directly in the imaging lens, the metalens acts both as a focusing element and a spectral filter. The use of a simple computational backend will enable real-time operation. Key limitations in the adoption of phase imaging methods for endoscopy such as multiple acquisition, interferometric alignment or mechanical scanning are completely mitigated in the reported metalens based QPI.

Quantitative phase microscopies: accuracy comparison

Quantitative phase microscopies (QPMs) play a pivotal role in bio-imaging, offering unique insights that complement fluorescence imaging. They provide essential data on mass distribution and transport, inaccessible to fluorescence techniques. Additionally, QPMs are label-free, eliminating concerns of photobleaching and phototoxicity. However, navigating through the array of available QPM techniques can be complex, making it challenging to select the most suitable one for a particular application. This tutorial review presents a thorough comparison of the main QPM techniques, focusing on their accuracy in terms of measurement precision and trueness. We focus on 8 techniques, namely digital holographic microscopy (DHM), cross-grating wavefront microscopy (CGM), which is based on QLSI (quadriwave lateral shearing interferometry), diffraction phase microscopy (DPM), differential phase-contrast (DPC) microscopy, phase-shifting interferometry (PSI) imaging, Fourier phase microscopy (FPM), spatial light interference microscopy (SLIM), and transport-of-intensity equation (TIE) imaging. For this purpose, we used a home-made numerical toolbox based on discrete dipole approximation (IF-DDA). This toolbox is designed to compute the electromagnetic field at the sample plane of a microscope, irrespective of the object's complexity or the illumination conditions. We upgraded this toolbox to enable it to model any type of QPM, and to take into account shot noise. In a nutshell, the results show that DHM and PSI are inherently free from artefacts and rather suffer from coherent noise; In CGM, DPC, DPM and TIE, there is a trade-off between precision and trueness, which can be balanced by varying one experimental parameter; FPM and SLIM suffer from inherent artefacts that cannot be discarded experimentally in most cases, making the techniques not quantitative especially for large objects covering a large part of the field of view, such as eukaryotic cells.

Single-shot spatial light interference microscopy for dynamic monitoring of membrane fluctuations

Single-shot spatial light interference microscopy (SS-SLIM) with a pair of non-polarizing beam splitters is proposed for substantially enhancing the speed and efficiency of conventional SLIM systems. Traditional methods are limited by the need for multiple-frame serial modulation and acquisition by spatial light modulators and detectors. Our approach integrates non-polarizing beam splitters to simultaneously capture four phase-shifted intensity images, increasing the imaging speed by at least fourfold while maintaining high quality. This capability is crucial for effectively monitoring the dynamic fluctuations of red blood cell membranes. Furthermore, the potential applications of the SS-SLIM system in biomedical research are demonstrated, particularly in scenarios requiring high temporal resolution and label-free imaging.

Quantitative phase imaging based on holography: trends and new perspectives

In 1948, Dennis Gabor proposed the concept of holography, providing a pioneering solution to a quantitative description of the optical wavefront. After 75 years of development, holographic imaging has become a powerful tool for optical wavefront measurement and quantitative phase imaging. The emergence of this technology has given fresh energy to physics, biology, and materials science. Digital holography (DH) possesses the quantitative advantages of wide-field, non-contact, precise, and dynamic measurement capability for complex-waves. DH has unique capabilities for the propagation of optical fields by measuring light scattering with phase information. It offers quantitative visualization of the refractive index and thickness distribution of weak absorption samples, which plays a vital role in the pathophysiology of various diseases and the characterization of various materials. It provides a possibility to bridge the gap between the imaging and scattering disciplines. The propagation of wavefront is described by the complex amplitude. The complex-value in the complex-domain is reconstructed from the intensity-value measurement by camera in the real-domain. Here, we regard the process of holographic recording and reconstruction as a transformation between complex-domain and real-domain, and discuss the mathematics and physical principles of reconstruction. We review the DH in underlying principles, technical approaches, and the breadth of applications. We conclude with emerging challenges and opportunities based on combining holographic imaging with other methodologies that expand the scope and utility of holographic imaging even further. The multidisciplinary nature brings technology and application experts together in label-free cell biology, analytical chemistry, clinical sciences, wavefront sensing, and semiconductor production.

Vibrational imaging of metabolites for improved microbial cell strains

Significance

Biomanufacturing utilizes modified microbial systems to sustainably produce commercially important biomolecules for use in agricultural, energy, food, material, and pharmaceutical industries. However, technological challenges related to non-destructive and high-throughput metabolite screening need to be addressed to fully unlock the potential of synthetic biology and sustainable biomanufacturing.

Aim

This perspective outlines current analytical screening tools used in industrial cell strain development programs and introduces label-free vibrational spectro-microscopy as an alternative contrast mechanism.

Approach

We provide an overview of the analytical instrumentation currently used in the "test" portion of the design, build, test, and learn cycle of synthetic biology. We then highlight recent progress in Raman scattering and infrared absorption imaging techniques, which have enabled improved molecular specificity and sensitivity.

Results

Recent developments in high-resolution chemical imaging methods allow for greater throughput without compromising the image contrast. We provide a roadmap of future work needed to support integration with microfluidics for rapid screening at the single-cell level.

Conclusions

Quantifying the net expression of metabolites allows for the identification of cells with metabolic pathways that result in increased biomolecule production, which is essential for improving the yield and reducing the cost of industrial biomanufacturing. Technological advancements in vibrational microscopy instrumentation will greatly benefit biofoundries as a complementary approach for non-destructive cell screening.

Quantitative phase imaging techniques for measuring scattering properties of cells and tissues: a review-part I

Significance

Quantitative phase imaging (QPI) techniques offer intrinsic information about the sample of interest in a label-free, noninvasive manner and have an enormous potential for wide biomedical applications with negligible perturbations to the natural state of the sample in vitro.

Aim

We aim to present an in-depth review of the scattering formulation of light-matter interactions as applied to biological samples such as cells and tissues, discuss the relevant quantitative phase measurement techniques, and present a summary of various reported applications.

Approach

We start with scattering theory and scattering properties of biological samples followed by an exploration of various microscopy configurations for 2D QPI for measurement of structure and dynamics.

Results

We reviewed 157 publications and presented a range of QPI techniques and discussed suitable applications for each. We also presented the theoretical frameworks for phase reconstruction associated with the discussed techniques and highlighted their domains of validity.

Conclusions

We provide detailed theoretical as well as system-level information for a wide range of QPI techniques. Our study can serve as a guideline for new researchers looking for an exhaustive literature review of QPI methods and relevant applications.

Multispectral Holographic Intensity and Phase Imaging of Semitransparent Ultrathin Films

In this paper, we demonstrate a novel optical characterization method for ultrathin semitransparent and absorbing materials through multispectral intensity and phase imaging. The method is based on a lateral-shearing interferometric microscopy (LIM) technique, where phase-shifting allows extraction of both the intensity and the phase of transmitted optical fields. To demonstrate the performance in characterizing semitransparent thin films, we fabricated and measured cupric oxide (CuO) seeded gold ultrathin metal films (UTMFs) with mass-equivalent thicknesses from 2 to 27 nm on fused silica substrates. The optical properties were modeled using multilayer thin film interference and a parametric model of their complex refractive indices. The UTMF samples were imaged in the spectral range from 475 to 750 nm using the proposed LIM technique, and the model parameters were fitted to the measured data in order to determine the respective complex refractive indices for varying thicknesses. Overall, by using the combined intensity and phase not only for imaging and quality control but also for determining the material properties, such as complex refractive indices, this technique demonstrates a high potential for the characterization of the optical properties, of (semi-) transparent thin films.

Grading of glioma tumors using digital holographic microscopy

Gliomas are the most common type of cerebral tumors; they occur with increasing incidence in the last decade and have a high rate of mortality. For efficient treatment, fast accurate diagnostic and grading of tumors are imperative. Presently, the grading of tumors is established by histopathological evaluation, which is a time-consuming procedure and relies on the pathologists' experience. Here we propose a supervised machine learning procedure for tumor grading which uses quantitative phase images of unstained tissue samples acquired by digital holographic microscopy. The algorithm is using an extensive set of statistical and texture parameters computed from these images. The procedure has been able to classify six classes of images (normal tissue and five glioma subtypes) and to distinguish between gliomas types from grades II to IV (with the highest sensitivity and specificity for grade II astrocytoma and grade III oligodendroglioma and very good scores in recognizing grade III anaplastic astrocytoma and grade IV glioblastoma). The procedure bolsters clinical diagnostic accuracy, offering a swift and reliable means of tumor characterization and grading, ultimately the enhancing treatment decision-making process.

Neuronal innervation regulates the secretion of neurotrophic myokines and exosomes from skeletal muscle

Myokines and exosomes, originating from skeletal muscle, are shown to play a significant role in maintaining brain homeostasis. While exercise has been reported to promote muscle secretion, little is known about the effects of neuronal innervation and activity on the yield and molecular composition of biologically active molecules from muscle. As neuromuscular diseases and disabilities associated with denervation impact muscle metabolism, we hypothesize that neuronal innervation and firing may play a pivotal role in regulating secretion activities of skeletal muscles. We examined this hypothesis using an engineered neuromuscular tissue model consisting of skeletal muscles innervated by motor neurons. The innervated muscles displayed elevated expression of mRNAs encoding neurotrophic myokines, such as interleukin-6, brain-derived neurotrophic factor, and FDNC5, as well as the mRNA of peroxisome-proliferator-activated receptor γ coactivator 1α, a key regulator of muscle metabolism. Upon glutamate stimulation, the innervated muscles secreted higher levels of irisin and exosomes containing more diverse neurotrophic microRNAs than neuron-free muscles. Consequently, biological factors secreted by innervated muscles enhanced branching, axonal transport, and, ultimately, spontaneous network activities of primary hippocampal neurons in vitro. Overall, these results reveal the importance of neuronal innervation in modulating muscle-derived factors that promote neuronal function and suggest that the engineered neuromuscular tissue model holds significant promise as a platform for producing neurotrophic molecules.

Observing perineuronal nets like structures via coaxial scattering quantitative interference imaging at multiple wavelengths

Perineuronal nets (PNNs) are important functional structures on the surface of nerve cells. Observation of PNNs usually requires dyeing or fluorescent labeling. As a network structure with a micron grid and sub-wavelength thickness but no special optical properties, quantitative phase imaging (QPI) is the only purely optical method for high-resolution imaging of PNNs. We proposed a Scattering Quantitative Interference Imaging (SQII) method which measures the geometric rather than transmission or reflection phase during the scattering process to visualize PNNs. Different from QIP methods, SQII method is sensitive to scattering and not affected by wavelength changes. Via geometric phase shifting method, we simplify the phase shift operation. The SQII method not only focuses on interference phase, but also on the interference contrast. The singularity points and phase lines of the scattering geometric phase depict the edges of the network structure and can be found at the valley area of the interference contrast parameter SINDR under different wavelengths. Our SQII method has its unique imaging properties, is very simple and easy to implement and has more worth for promotion.

Recent Advances and Current Trends in Transmission Tomographic Diffraction Microscopy

Optical microscopy techniques are among the most used methods in biomedical sample characterization. In their more advanced realization, optical microscopes demonstrate resolution down to the nanometric scale. These methods rely on the use of fluorescent sample labeling in order to break the diffraction limit. However, fluorescent molecules' phototoxicity or photobleaching is not always compatible with the investigated samples. To overcome this limitation, quantitative phase imaging techniques have been proposed. Among these, holographic imaging has demonstrated its ability to image living microscopic samples without staining. However, for a 3D assessment of samples, tomographic acquisitions are needed. Tomographic Diffraction Microscopy (TDM) combines holographic acquisitions with tomographic reconstructions. Relying on a 3D synthetic aperture process, TDM allows for 3D quantitative measurements of the complex refractive index of the investigated sample. Since its initial proposition by Emil Wolf in 1969, the concept of TDM has found a lot of applications and has become one of the hot topics in biomedical imaging. This review focuses on recent achievements in TDM development. Current trends and perspectives of the technique are also discussed.

Single-image phase retrieval for off-the-shelf Zernike phase-contrast microscopes

Quantitative phase imaging (QPI), such as digital holography, is considered a promising tool in the field of life science due to its noninvasive and quantitative visualization capabilities without the need for fluorescence labeling. However, the popularity of QPI systems is limited due to the cost and complexity of their hardware. In contrast, Zernike phase-contrast microscopy (ZPM) has been widely used in practical scenarios but has not been categorized as QPI, owing to halo and shade-off artifacts and the weak phase condition. Here, we present a single-image phase retrieval method for ZPM that addresses these issues without requiring hardware modifications. By employing a rigorous physical model of ZPM and a gradient descent algorithm for its inversion, we achieve single-shot QPI with an off-the-shelf ZPM system. Our approach is validated in simulations and experiments, demonstrating QPI of a polymer microbead and biological cells. The quantitative nature of our method for single-cell imaging is confirmed through comparisons with observations from an established QPI technique conducted through digital holography. This study paves the way for transforming non-QPI ZPM systems into QPI systems.

Multi-harmonic structured illumination-based optical diffraction tomography

Imaging speed and spatial resolution are key factors in optical diffraction tomography (ODT), while they are mutually exclusive in 3D refractive index imaging. This paper presents a multi-harmonic structured illumination-based optical diffraction tomography (MHSI-ODT) to acquire 3D refractive index (RI) maps of transparent samples. MHSI-ODT utilizes a digital micromirror device (DMD) to generate structured illumination containing multiple harmonics. For each structured illumination orientation, four spherical spectral crowns are solved from five phase-shifted holograms, meaning that the acquisition of each spectral crown costs 1.25 raw images. Compared to conventional SI-ODT, which retrieves two spectral crowns from three phase-shifted raw images, MHSI-ODT enhances the imaging speed by 16.7% in 3D RI imaging. Meanwhile, MHSI-ODT exploits both the 1st-order and the 2nd-order harmonics; therefore, it has a better intensity utilization of structured illumination. We demonstrated the performance of MHSI-ODT by rendering the 3D RI distributions of 5 µm polystyrene (PS) microspheres and biological samples.

Roadmap on Label-Free Super-Resolution Imaging

Label-free super-resolution (LFSR) imaging relies on light-scattering processes in nanoscale objects without a need for fluorescent (FL) staining required in super-resolved FL microscopy. The objectives of this Roadmap are to present a comprehensive vision of the developments, the state-of-the-art in this field, and to discuss the resolution boundaries and hurdles which need to be overcome to break the classical diffraction limit of the LFSR imaging. The scope of this Roadmap spans from the advanced interference detection techniques, where the diffraction-limited lateral resolution is combined with unsurpassed axial and temporal resolution, to techniques with true lateral super-resolution capability which are based on understanding resolution as an information science problem, on using novel structured illumination, near-field scanning, and nonlinear optics approaches, and on designing superlenses based on nanoplasmonics, metamaterials, transformation optics, and microsphere-assisted approaches. To this end, this Roadmap brings under the same umbrella researchers from the physics and biomedical optics communities in which such studies have often been developing separately. The ultimate intent of this paper is to create a vision for the current and future developments of LFSR imaging based on its physical mechanisms and to create a great opening for the series of articles in this field.

Polarization differential interference contrast microscopy with physics-inspired plug-and-play denoiser for single-shot high-performance quantitative phase imaging

We present single-shot high-performance quantitative phase imaging with a physics-inspired plug-and-play denoiser for polarization differential interference contrast (PDIC) microscopy. The quantitative phase is recovered by the alternating direction method of multipliers (ADMM), balancing total variance regularization and a pre-trained dense residual U-net (DRUNet) denoiser. The custom DRUNet uses the Tanh activation function to guarantee the symmetry requirement for phase retrieval. In addition, we introduce an adaptive strategy accelerating convergence and explicitly incorporating measurement noise. After validating this deep denoiser-enhanced PDIC microscopy on simulated data and phantom experiments, we demonstrated high-performance phase imaging of histological tissue sections. The phase retrieval by the denoiser-enhanced PDIC microscopy achieves significantly higher quality and accuracy than the solution based on Fourier transforms or the iterative solution with total variance regularization alone.

Panoramic quantitative phase imaging of adherent live cells in a microfluidic environment

Understanding how cells respond to external stimuli is crucial. However, there are a lack of inspection systems capable of simultaneously stimulating and imaging cells, especially in their natural states. This study presents a novel microfluidic stimulation and observation system equipped with flat-fielding quantitative phase contrast microscopy (FF-QPCM). This system allowed us to track the behavior of organelles in live cells experiencing controlled microfluidic stimulation. Using this innovative imaging platform, we successfully quantified the cellular response to shear stress including directional cellular shrinkage and mitochondrial distribution change in a label-free manner. Additionally, we detected and characterized the cellular response, particularly mitochondrial behavior, under varying fluidic conditions such as temperature and drug induction time. The proposed imaging platform is highly suitable for various microfluidic applications at the organelle level. We advocate that this platform will significantly facilitate life science research in microfluidic environments.

Image reconstruction for low cost spatial light interference microscopy with fixed and arbitrary phase modulation

During the past decade, spatial light interference microscopy (SLIM) has undergone rapid development, evidenced by its broadening applications in biology and medicine. However, the need for an expensive spatial light modulator (SLM) may limit its adoption, and the requirement for multiple images per plane limits its speed in volumetric imaging. Here we propose to address these issues by replacing the SLM with a mask fabricated from a low cost optical density (OD) filter, and recover high contrast images computationally rather than through phase-shifting. This is done using a specially constructed Wiener filter to recover the object scattering potential. A crucial part of the Wiener filter is estimating the arbitrary phase introduced by the OD filter. Our results demonstrate that not only were we able to estimate the OD filter's phase modulation in situ, but also the contrast of the reconstructed images is greatly improved. Comparisons with other related methods are also performed, with the conclusion that the combination of an inexpensive OD mask and modified Wiener filtering leads to results that are closest to the traditional SLIM setup. Thus, we have demonstrated the feasibility of a low cost, high speed SLIM system utilizing computational phase reconstruction, paving the way for wider adoption of high resolution phase microscopy.

Reflectional quantitative differential phase microscopy using polarized wavefront phase modulation

Quantitative phase microscopy (QPM), as a label-free and nondestructive technique, has been playing an indispensable tool in biomedical imaging and industrial inspection. Herein, we introduce a reflectional quantitative differential phase microscopy (termed RQDPM) based on polarized wavefront phase modulation and partially coherent full-aperture illumination, which has high spatial resolution and spatio-temporal phase sensitivity and is applicable to opaque surfaces and turbid biological specimens. RQDPM does not require additional polarized devices and can be easily switched from reflectional mode to transmission mode. In addition, RQDPM inherits the characteristic of high axial resolution of differential interference contrast microscope, thereby providing topography for opaque surfaces. We experimentally demonstrate the reflectional phase imaging ability of RQDPM with several samples: semiconductor wafer, thick biological tissues, red blood cells, and Hela cells. Furthermore, we dynamically monitor the flow state of microspheres in a self-built microfluidic channel by using RQDPM converted into the transmission mode.

Single-shot refractive index slice imaging using spectrally multiplexed optical transfer function reshaping

The refractive index (RI) of cells and tissues is crucial in pathophysiology as a noninvasive and quantitative imaging contrast. Although its measurements have been demonstrated using three-dimensional quantitative phase imaging methods, these methods often require bulky interferometric setups or multiple measurements, which limits the measurement sensitivity and speed. Here, we present a single-shot RI imaging method that visualizes the RI of the in-focus region of a sample. By exploiting spectral multiplexing and optical transfer function engineering, three color-coded intensity images of a sample with three optimized illuminations were simultaneously obtained in a single-shot measurement. The measured intensity images were then deconvoluted to obtain the RI image of the in-focus slice of the sample. As a proof of concept, a setup was built using Fresnel lenses and a liquid-crystal display. For validation purposes, we measured microspheres of known RI and cross-validated the results with simulated results. Various static and highly dynamic biological cells were imaged to demonstrate that the proposed method can conduct single-shot RI slice imaging of biological samples with subcellular resolution.

3D full-wave multi-scattering forward solver for coherent microscopes

A rigorous forward model solver for conventional coherent microscope is presented. The forward model is derived from Maxwell's equations and models the wave behaviour of light matter interaction. Vectorial waves and multiple-scattering effect are considered in this model. Scattered field can be calculated with given distribution of the refractive index of the biological sample. Bright field images can be obtained by combining the scattered field and reflected illumination, and experimental validation is included. Insights into the utility of the full-wave multi-scattering (FWMS) solver and comparison with the conventional Born approximation based solver are presented. The model is also generalizable to the other forms of label-free coherent microscopes, such as quantitative phase microscope and dark-field microscope.

Non-Invasive and Minute-Frequency 3D Tomographic Imaging Enabling Long-Term Spatiotemporal Observation of Single Cell Fate

Non-invasive and rapid imaging technique at subcellular resolution is significantly important for multiple biological applications such as cell fate study. Label-free refractive-index (RI)-based 3D tomographic imaging constitutes an excellent candidate for 3D imaging of cellular structures, but its full potential in long-term spatiotemporal cell fate observation is locked due to the lack of an efficient integrated system. Here, a long-term 3D RI imaging system incorporating a cutting-edge white light diffraction phase microscopy module with spatiotemporal stability, and an acoustofluidic device to roll and culture single cells in a customized live cell culture chamber is reported. Using this system, 3D RI imaging experiments are conducted for 250 cells and demonstrate efficient cell identification with high accuracy. Importantly, long-term and frequency-on-demand 3D RI imaging of K562 and MCF-7 cancer cells reveal different characteristics during normal cell growth, drug-induced cell apoptosis, and necrosis of drug-treated cells. Overall, it is believed that the proposed 3D tomographic imaging technique opens up a new avenue for visualizing intracellular structures and will find many applications such as disease diagnosis and nanomedicine.

Quantitative phase gradient metrology using diffraction phase microscopy and deep learning

In quantitative phase microscopy, measurement of the phase gradient is an important problem for biological cell morphological studies. In this paper, we propose a method based on a deep learning approach that is capable of direct estimation of the phase gradient without the requirement of phase unwrapping and numerical differentiation operations. We show the robustness of the proposed method using numerical simulations under severe noise conditions. Further, we demonstrate the method's utility for imaging different biological cells using diffraction phase microscopy setup.

Artificial confocal microscopy for deep label-free imaging

Widefield microscopy of optically thick specimens typically features reduced contrast due to "spatial crosstalk", in which the signal at each point in the field of view is the result of a superposition from neighbouring points that are simultaneously illuminated. In 1955, Marvin Minsky proposed confocal microscopy as a solution to this problem. Today, laser scanning confocal fluorescence microscopy is broadly used due to its high depth resolution and sensitivity, but comes at the price of photobleaching, chemical, and photo-toxicity. Here, we present artificial confocal microscopy (ACM) to achieve confocal-level depth sectioning, sensitivity, and chemical specificity, on unlabeled specimens, nondestructively. We equipped a commercial laser scanning confocal instrument with a quantitative phase imaging module, which provides optical path-length maps of the specimen in the same field of view as the fluorescence channel. Using pairs of phase and fluorescence images, we trained a convolution neural network to translate the former into the latter. The training to infer a new tag is very practical as the input and ground truth data are intrinsically registered, and the data acquisition is automated. The ACM images present significantly stronger depth sectioning than the input (phase) images, enabling us to recover confocal-like tomographic volumes of microspheres, hippocampal neurons in culture, and 3D liver cancer spheroids. By training on nucleus-specific tags, ACM allows for segmenting individual nuclei within dense spheroids for both cell counting and volume measurements. In summary, ACM can provide quantitative, dynamic data, nondestructively from thick samples, while chemical specificity is recovered computationally.

Interferometric imaging with ring-shaped apertures

We use a scattering model for image formation to demonstrate how to simulate images formed by ring-shaped illumination. The description assumes weakly scattering samples, such as phase objects of broad interest in live cell imaging, which also makes no angular approximations and covers forward and backward scattering, single-angle and angle-averaged illumination, as well as monochromatic and broadband light. The numerical experiments reveal the image formation behavior that is consistent with recent experiments reported in the literature, which shows this model can be applied to different imaging systems that are based on ring-shaped illumination with good performance, by considering the incident as a plane wave incident originating at the ring aperture.

Bond-selective intensity diffraction tomography

Recovering molecular information remains a grand challenge in the widely used holographic and computational imaging technologies. To address this challenge, we developed a computational mid-infrared photothermal microscope, termed Bond-selective Intensity Diffraction Tomography (BS-IDT). Based on a low-cost brightfield microscope with an add-on pulsed light source, BS-IDT recovers both infrared spectra and bond-selective 3D refractive index maps from intensity-only measurements. High-fidelity infrared fingerprint spectra extraction is validated. Volumetric chemical imaging of biological cells is demonstrated at a speed of ~20 s per volume, with a lateral and axial resolution of ~350 nm and ~1.1 µm, respectively. BS-IDT's application potential is investigated by chemically quantifying lipids stored in cancer cells and volumetric chemical imaging on Caenorhabditis elegans with a large field of view (~100 µm x 100 µm).

Research on partially coherent spatial light interference microscopy

Based on partial coherence theory, this study rigorously deduces the principle of spatial light interference microscopy (SLIM) and improves the calculation method of SLIM. The main problem we found with SLIM is that it simply defaults the phase of the direct light to 0. To address this problem, we propose and experimentally demonstrate a double four-step phase shift method. Simulation results show that this method can reduce the relative error of oil-immersed microsphere reconstruction to about 3.7%, and for red blood cell reconstruction, the relative error can be reduced to about 13%.

Digital Histopathological Discrimination of Label-Free Tumoral Tissues by Artificial Intelligence Phase-Imaging Microscopy

Histopathology is the gold standard for disease diagnosis. The use of digital histology on fresh samples can reduce processing time and potential image artifacts, as label-free samples do not need to be fixed nor stained. This fact allows for a faster diagnosis, increasing the speed of the process and the impact on patient prognosis. This work proposes, implements, and validates a novel digital diagnosis procedure of fresh label-free histological samples. The procedure is based on advanced phase-imaging microscopy parameters and artificial intelligence. Fresh human histological samples of healthy and tumoral liver, kidney, ganglion, testicle and brain were collected and imaged with phase-imaging microscopy. Advanced phase parameters were calculated from the images. The statistical significance of each parameter for each tissue type was evaluated at different magnifications of 10×, 20× and 40×. Several classification algorithms based on artificial intelligence were applied and evaluated. Artificial Neural Network and Decision Tree approaches provided the best general sensibility and specificity results, with values over 90% for the majority of biological tissues at some magnifications. These results show the potential to provide a label-free automatic significant diagnosis of fresh histological samples with advanced parameters of phase-imaging microscopy. This approach can complement the present clinical procedures.

Quantitative phase imaging based on polarization encoding

Most optical characterization methods rely on measuring the complex optical fields emerging from the interaction between light and material systems. Nevertheless, inherent scattering and absorption cause ambiguities in both interferometric and noninterferometric attempts to measure phase. Here we demonstrate that the complete information about a probe optical field can be encoded into the states of polarization, and develop a topography measurement method by blindly varying the ambient refractive index surrounding the sample in a wedged cuvette, which is capable of simultaneously measuring the thickness and the ambient refractive index of the sample in real time, as well as extending the measurement range of the sample thickness. With the method, we have successfully measured the topography of a 136.7 µm thick coverslip by blindly changing the ambient refractive index by 0.001246, resulting in the thickest sample characterization ever achieved by quantitative phase imaging, to the best of our knowledge. An efficient and complete characterization of optical fields is critical for any high-resolution imaging approach and the technique demonstrated here should prove attractive for applications ranging from microscopy to remote sensing. Thanks to the high precision and fast response speed, this method may pave a new way for measuring the topography of the thick samples, such as biological tissues.

Circadian Volume Changes in Hippocampal Glia Studied by Label-Free Interferometric Imaging

Complex brain functions, including learning and memory, arise in part from the modulatory role of astrocytes on neuronal circuits. Functionally, the dentate gyrus (DG) exhibits differences in the acquisition of long-term potentiation (LTP) between day and night. We hypothesize that the dynamic nature of astrocyte morphology plays an important role in the functional circuitry of hippocampal learning and memory, specifically in the DG. Standard microscopy techniques, such as differential interference contrast (DIC), present insufficient contrast for detecting changes in astrocyte structure and function and are unable to inform on the intrinsic structure of the sample in a quantitative manner. Recently, gradient light interference microscopy (GLIM) has been developed to upgrade a DIC microscope with quantitative capabilities such as single-cell dry mass and volume characterization. Here, we present a methodology for combining GLIM and electrophysiology to quantify the astrocyte morphological behavior over the day-night cycle. Colocalized measurements of GLIM and fluorescence allowed us to quantify the dry masses and volumes of hundreds of astrocytes. Our results indicate that, on average, there is a 25% cell volume reduction during the nocturnal cycle. Remarkably, this cell volume change takes place at constant dry mass, which suggests that the volume regulation occurs primarily through aqueous medium exchange with the environment.

Reflectional quantitative phase-contrast microscopy (RQPCM) with annular epi-illumination

Quantitative phase microscopy (QPM) is a label-free microscopic technique that exploits the phase of a wave passing through a sample; hence, it has been applied to many fields, including biomedical research and industrial inspection. However, the high spatiotemporal resolution imaging of reflective samples still challenges conventional transmission QPM. In this paper, we propose reflectional quantitative phase-contrast microscopy based on annular epi-illumination of light-emitting diodes. The unscattered wave from the sample is successively phase-retarded by 0, π/2, π, and 3π/2 through a spatial light modulator, and high-resolution phase-contrast images are obtained, revealing the finer structure or three-dimensional tomography of reflective samples. With this system, we have quantitatively obtained the contour of tissue slices and silicon semiconductor wafers. We believe that the proposed system will be very helpful for the high-resolution imaging of industrial devices and biomedical dynamics.

Physical Cytometry: Detecting Mass-Related Properties of Single Cells

The physical properties of a single cell, such as mass, volume, and density, are important indications of the cell's metabolic characteristics and homeostasis. Precise measurement of a single cell's mass has long been a challenge due to its minute size. It is only in the past 10 years that a variety of instruments for measuring living cellular mass have emerged with the development of MEMS, microfluidics, and optics technologies. In this review, we discuss the current developments of physical cytometry for quantifying mass-related physical properties of single cells, highlighting the working principle, applications, and unique merits. The review mainly covers these measurement methods: single-cell mass cytometry, levitation image cytometry, suspended microchannel resonator, phase-shifting interferometry, and opto-electrokinetics cell manipulation. Comparisons are made between these methods in terms of throughput, content, invasiveness, compatibility, and precision. Some typical applications of these methods in pathological diagnosis, drug efficacy evaluation, disease treatment, and other related fields are also discussed in this work.

Machine Learning Assisted Classification of Cell Lines and Cell States on Quantitative Phase Images

In this report, we present implementation and validation of machine-learning classifiers for distinguishing between cell types (HeLa, A549, 3T3 cell lines) and states (live, necrosis, apoptosis) based on the analysis of optical parameters derived from cell phase images. Validation of the developed classifier shows the accuracy for distinguishing between the three cell types of about 93% and between different cell states of the same cell line of about 89%. In the field test of the developed algorithm, we demonstrate successful evaluation of the temporal dynamics of relative amounts of live, apoptotic and necrotic cells after photodynamic treatment at different doses.

Optimizing sample illumination scanning for reflection and 4Pi tomographic diffractive microscopy

Tomographic diffractive microscopy (TDM) is increasingly gaining attention, owing to its high-resolution, label-free imaging capability. Fast acquisitions necessitate limiting the number of holograms to be recorded. Reconstructions then rely on optimal Fourier space filling to retain image quality and resolution, that is, they rely on optimal scanning of the tomographic illuminations. In this work, we theoretically study reflection TDM, and then the 4Pi TDM, a combination of transmission and reflection systems. Image simulations are conducted to determine optimal angular sweeping. We found that three-dimensional uniform scanning fills Fourier space the best for both reflection and 4Pi configurations, providing a better refractive index estimation for the observed sample.