Chapter 5 Quantitative Phase Imaging of Nanoscale Cell Structure and Dynamics

Noise correction in differential phase contrast for improving phase sensitivity

Differential phase contrast (DPC) imaging relies on computational analysis to extract quantitative phase information from phase gradient images. However, even modest noise level can introduce errors that propagate through the computational process, degrading the quality of the final phase result and further reducing phase sensitivity. Here, we introduce the noise-corrected DPC (ncDPC) to enhance phase sensitivity. This approach is based on a theoretical DPC model that effectively considers most relevant noise sources in the camera and non-uniform illumination in DPC. In particular, the dominating shot noise and readout noise variance can be jointly estimated using frequency analysis and further corrected by block-matching 3D (BM3D) method. Finally, the denoised images are used for phase retrieval based on the common Tikhonov inversion. Our results, based on both simulated and experimental data, demonstrate that ncDPC outperforms the traditional DPC (tDPC), enabling significant improvements in both phase reconstruction quality and phase sensitivity. Besides, we have demonstrated the broad applicability of ncDPC by showing its performance in various experimental datasets.

Label-Free Visualization and Morphological Profiling of Neuronal Differentiation and Axonal Degeneration through Quantitative Phase Imaging

Understanding the intricate processes of neuronal growth, degeneration, and neurotoxicity is paramount for unraveling nervous system function and holds significant promise in improving patient outcomes, especially in the context of chemotherapy-induced peripheral neuropathy (CIPN). These processes are influenced by a broad range of entwined events facilitated by chemical, electrical, and mechanical signals. The progress of each process is inherently linked to phenotypic changes in cells. Currently, the primary means of demonstrating morphological changes rely on measurements of neurite outgrowth and axon length. However, conventional techniques for monitoring these processes often require extensive preparation to enable manual or semi-automated measurements. Here, a label-free and non-invasive approach is employed for monitoring neuronal differentiation and degeneration using quantitative phase imaging (QPI). Operating on unlabeled specimens and offering little to no phototoxicity and photobleaching, QPI delivers quantitative maps of optical path length delays that provide an objective measure of cellular morphology and dynamics. This approach enables the visualization and quantification of axon length and other physical properties of dorsal root ganglion (DRG) neuronal cells, allowing greater understanding of neuronal responses to stimuli simulating CIPN conditions. This research paves new avenues for the development of more effective strategies in the clinical management of neurotoxicity.

Dielectric Metasurface Enabled Compact, Single-Shot Digital Holography for Quantitative Phase Imaging

Quantitative phase imaging (QPI) enables nondestructive, real-time, label-free imaging of transparent specimens and can reveal information about their fundamental properties such as cell size and morphology, mass density, particle dynamics, and cellular fluctuations. Development of high-performance and low-cost quantitative phase imaging systems is thus required in many fields, including on-site biomedical imaging and industrial inspection. Here, we propose an ultracompact, highly stable interferometer based on a single-layer dielectric metasurface for common path off-axis digital holography and experimentally demonstrate quantitative phase imaging. The interferometric imaging system leveraging an ultrathin multifunctional metasurface captures image plane holograms in a single shot and provides quantitative phase information on the test samples for extraction of its physical properties. With the benefits of planar engineering and high integrability, the proposed metasurface-based method establishes a stable miniaturized QPI system for reliable and cost-effective point-of-care devices, live cell imaging, 3D topography, and edge detection for optical computing.

Quantitative phase imaging of living red blood cells combining digital holographic microscopy and deep learning

Digital holographic microscopy as a non-contacting, non-invasive, and highly accurate measurement technology, is becoming a valuable method for quantitatively investigating cells and tissues. Reconstruction of phases from a digital hologram is a key step in quantitative phase imaging for biological and biomedical research. This study proposes a two-stage deep convolutional neural network named VY-Net, to realize the effective and robust phase reconstruction of living red blood cells. The VY-Net can obtain the phase information of an object directly from a single-shot off-axis digital hologram. We also propose two new indices to evaluate the reconstructed phases. In experiments, the mean of the structural similarity index of reconstructed phases can reach 0.9309, and the mean of the accuracy of reconstructions of reconstructed phases is as high as 91.54%. An unseen phase map of a living human white blood cell is successfully reconstructed by the trained VY-Net, demonstrating its strong generality.

Comparative analysis of Radachlorin accumulation, localization, and photobleaching in three cell lines by means of holographic and fluorescence microscopy

In this paper we compare the response of cells of established lines of different origin: HeLa, A549 and 3T3 to photodynamic treatment with Radachlorin photosensitizer. The analysis was performed on different aspects of the treatment procedure including photosensitizer accumulation, localization and photobleaching in cells and post-treatment dynamics of changes in cellular morphology at different treatment doses. It was shown that in the three cell lines Radachlorin accumulated in lysosomes to much greater extent than in mitochondria. The cells' response to treatment was analyzed by identification of their death pathways and evaluation of average phase shift dynamics using digital holographic microscopy. The analysis performed on the three cell lines allowed us to evaluate treatment doses specific for each pathway in each line. Among the three lines HeLa cells were found to be the most susceptible to treatment while 3T3 cells the most resistant. The comparison of these results with the data on Radachlorin accumulation, localization and photobleaching rates showed that the observed higher sensitivity of HeLa cells to photodynamic treatment correlated with higher photosensitizer uptake and more intensive photobleaching while lower sensitivity of 3T3 cells correlated with lower uptake and less intensive photobleaching.

Analysis of Deep Learning-Based Phase Retrieval Algorithm Performance for Quantitative Phase Imaging Microscopy

Quantitative phase imaging has been of interest to the science and engineering community and has been applied in multiple research fields and applications. Recently, the data-driven approach of artificial intelligence has been utilized in several optical applications, including phase retrieval. However, phase images recovered from artificial intelligence are questionable in their correctness and reliability. Here, we propose a theoretical framework to analyze and quantify the performance of a deep learning-based phase retrieval algorithm for quantitative phase imaging microscopy by comparing recovered phase images to their theoretical phase profile in terms of their correctness. This study has employed both lossless and lossy samples, including uniform plasmonic gold sensors and dielectric layer samples; the plasmonic samples are lossy, whereas the dielectric layers are lossless. The uniform samples enable us to quantify the theoretical phase since they are established and well understood. In addition, a context aggregation network has been employed to demonstrate the phase image regression. Several imaging planes have been simulated serving as input and the label for network training, including a back focal plane image, an image at the image plane, and images when the microscope sample is axially defocused. The back focal plane image plays an essential role in phase retrieval for the plasmonic samples, whereas the dielectric layer requires both image plane and back focal plane information to retrieve the phase profile correctly. Here, we demonstrate that phase images recovered using deep learning can be robust and reliable depending on the sample and the input to the deep learning.

Microscopy imaging of living cells in metabolic engineering

Microscopy imaging of living cells is becoming a pivotal, noninvasive, and highly specific tool in metabolic engineering to visualize molecular dynamics in industrial microorganisms. This review describes the different microscopy methods, from fluorescence to super resolution, with application in microbial bioengineering. Firstly, the role and importance of microscopy imaging is analyzed in the context of strain design. Then, the advantages and disadvantages of different microscopy technologies are discussed, including confocal laser scanning microscopy (CLSM), spatial light interference microscopy (SLIM), and super-resolution microscopy, followed by their applications in synthetic biology. Finally, the future perspectives of live-cell imaging and their potential to transform microbial systems are analyzed. This review provides theoretical guidance and highlights the importance of microscopy in understanding and engineering microbial metabolism.

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.

Correction and quantification of MTF in scanning laser microscopy

Observations using conventional microscopy often lack information related to the fine structures of an object, such as intensity and phase, because of limitations in the lens aperture. In this study, the intensity and phase information are appropriately converted into an electrical signal using laser scanning and photodetectors. Intensity and phase are completely separated, and the missing information is restored based on the frequency of the electrical signal. Using this method, the original intensity and phase information of the object to be observed can be correctly restored. Therefore, we propose a novel method to calculate the degree of intensity and phase modulation by calculating the direct and alternating current components obtained from the output of the sum and difference of the two photodetectors. The degree of spatial frequency modulation is corrected according to the electrical signal frequency to detect transparent or unstained cells. We first performed laser scanning of an object. Then, signals were detected using two photodetectors placed in the far-field, separated by the optical axis as the boundary. The output signals of the photodetectors were processed and the intensity and phase were unambiguously separated, thus allowing the visualization of the phase information of the transparent bodies and unstained cells. Spatial frequency correction was performed to correct the modulation. Our method successfully separated the information related to the intensity and optical path difference (OPD). In future work, by accurately correcting the intensity and OPD, it will be possible to separate the absorption rate from the ratio of the irradiation light intensity to the observed intensity and to separate the OPD into the refractive index and the thickness information. This method allows the accurate determination of these parameters in a noninvasive manner.

Demodulation of noisy interferograms with rapid phase variations and amplitude fluctuations using a surrogate principle-based optimization method

This paper presents an optimization-based method for phase extraction from interferograms corrupted with noise, rapid phase variations, and localized amplitude fluctuations. In the proposed method, the phase retrieval problem is addresed by modeling a cost function using non-convex non-smooth total generalized variational regularization. Further, the surrogate principle is used to transform the cost function into convex form for convenient optimization framework. Simulation results demonstrate the performance of the method. We also show the experimental utility of the proposed method for onion cell imaging using digital holographic microscopy.

Identification and Staging of B-Cell Acute Lymphoblastic Leukemia Using Quantitative Phase Imaging and Machine Learning

Identification and classification of leukemia cells in a rapid and label-free fashion is clinically challenging and thus presents a prime arena for implementing new diagnostic tools. Quantitative phase imaging, which maps optical path length delays introduced by the specimen, has been demonstrated to discern cellular phenotypes based on differential morphological attributes. Rapid acquisition capability and the availability of label-free images with high information content have enabled researchers to use machine learning (ML) to reveal latent features. We developed a set of ML classifiers, including convolutional neural networks, to discern healthy B cells from lymphoblasts and classify stages of B cell acute lymphoblastic leukemia. Here, we show that the average dry mass and volume of normal B cells are lower than those of cancerous cells and that these morphologic parameters increase further alongside disease progression. We find that the relaxed training requirements of a ML approach are conducive to the classification of cell type, with minimal space, training time, and memory requirements. Our findings pave the way for a larger study on clinical samples of acute lymphoblastic leukemia, with the overarching goal of its broader use in hematopathology, where the prospect of objective diagnoses with minimal sample preparation remains highly desirable.

Microfluidic Single-Cell Analytics

What is the impact of cellular heterogeneity on process performance? How do individual cells contribute to averaged process productivity? Single-cell analysis is a key technology for answering such key questions of biotechnology, beyond bulky measurements with populations. The analysis of cellular individuality, its origins, and the dependency of process performance on cellular heterogeneity has tremendous potential for optimizing biotechnological processes in terms of metabolic, reaction, and process engineering. Microfluidics offer unmatched environmental control of the cellular environment and allow massively parallelized cultivation of single cells. However, the analytical accessibility to a cell's physiology is of crucial importance for obtaining the desired information on the single-cell production phenotype. Highly sensitive analytics are required to detect and quantify the minute amounts of target analytes and small physiological changes in a single cell. For their application to biotechnological questions, single-cell analytics must evolve toward the measurement of kinetics and specific rates of the smallest catalytic unit, the single cell. In this chapter, we focus on an introduction to the latest single-cell analytics and their application for obtaining physiological parameters in a biotechnological context from single cells. We present and discuss recent advancements in single-cell analytics that enable the analysis of cell-specific growth, uptake, and production kinetics, as well as the gene expression and regulatory mechanisms at a single-cell level.

Quantitative assessment of changes in cellular morphology at photodynamic treatment in vitro by means of digital holographic microscopy

Temporal dependence of changes in the morphological characteristics of cells of two cultured lines of cancer origin, HeLa and A549, induced by photodynamic treatment with Radachlorin photosensitizer, have been monitored using digital holographic microscopy during first two hours after short-term irradiation. The observed post-treatment early dynamics of the phase shift in the transmitted wavefront indicated several distinct scenarios of cell behavior depending upon the irradiation dose. In particular the phase shift increased at low doses, which can be associated with apoptosis, while at high doses it decreased, which can be associated with necrosis. As shown, the two cell types responded differently to similar irradiation doses. Although the sequence of death scenarios with the increase of the irradiation dose was the same, each scenario was realized at substantially different doses. These findings suggest that the average phase shift of the transmitted wavefront can be used for quantitative non-invasive cell death characterization. The conclusions made were cofirmed by commonly used test assays using confocal fluorescent microscopy.

Reagent-Free and Rapid Assessment of T Cell Activation State Using Diffraction Phase Microscopy and Deep Learning

CD8+ T cells constitute an essential compartment of the adaptive immune system. During immune responses, naı̈ve T cells become functional, as they are primed with their cognate determinants by the antigen presenting cells. Current methods of identifying activated CD8+ T cells are laborious, time-consuming and expensive due to the extensive list of required reagents. Here, we demonstrate an optical imaging approach featuring quantitative phase imaging to distinguish activated CD8+ T cells from naı̈ve CD8+ T cells in a rapid and reagent-free manner. We measured the dry mass of live cells and employed transport-based morphometry to better understand their differential morphological attributes. Our results reveal that, upon activation, the dry cell mass of T cells increases significantly in comparison to that of unstimulated cells. By employing deep learning formalism, we are able to accurately predict the population ratios of unknown mixed population based on the acquired quantitative phase images. We envision that, with further refinement, this label-free method of T cell phenotyping will lead to a rapid and cost-effective platform for assaying T cell responses to candidate antigens in the near future.

Morphological changes in the ovarian carcinoma cells of Wistar rats induced by chemotherapy with cisplatin and dioxadet

The development of new express methods for the analysis of the efficacy of anti-cancer therapy on the cellular level is highly desirable for the analysis of chemotherapeutic agent performance. In this paper we suggest the use of parameters of cell morphology determined by holographic microscopy and tomography for the effective label free quantitative analysis of cell viability under antitumor chemotherapy and thus of cytostatic agent efficacy. As shown, measured phase shifts and cell morphology change dramatically as a result of chemotherapy and depend strongly on the cell type and agent applied. Experimentally, a comparative analysis of the antitumor efficacy of the two cytostatics, cisplatin and dioxadet, that are commonly used for chemotherapy of disseminated ovarian carcinoma has been performed. The experiments were carried out on the Wistar rat model. An essential difference in the morphology of cells, both normal (erythrocytes) and cancerous, present in ascitic fluid taken from the non-treated group of rats and the groups treated with either dioxadet or cisplatin, has been observed. The results obtained can be interpreted as an indication of the antitumor performance of both cytostatics at the cellular level and as a demonstration of the higher efficacy of therapy with dioxadet as compared to that with cisplatin. Differences in cell morphology are suggested to be applied as quantitative markers of cell viability and cytostatic agent efficacy. The conclusions made are supported by a comparison with the results of recent experiments based on survival rates of laboratory animals treated with these agents..

Wide-field anti-aliased quantitative differential phase contrast microscopy

Differential phase contrast (DPC) microscopy is a popular methodology to recover quantitative phase information of thin transparent samples under multi-axis asymmetric illumination patterns. Based on spatially partially coherent illuminations, DPC provides high-quality, speckle-free 3D reconstructions with lateral resolution up to twice the coherent diffraction limit, under the precondition that the pixel size of the imaging sensor is small enough to prevent spatial aliasing/undersampling. However, microscope cameras are in general designed to have a large pixel size so that the intensity information transmitted by the optical system cannot be adequately sampled or digitized. On the other hand, using an image sensor with a smaller pixel size or adding a magnification camera adapter to the camera can resolve the undersampling at the expense of a reduced field of view (FOV). To solve this tradeoff, we introduce a new variation of quantitative DPC approach, termed anti-aliased DPC (AADPC), which uses several aliased intensity images under asymmetric illuminations to recover wide-field aliasing-free phase images. Besides, phase transfer functions under different illumination patterns in DPC are analyzed to design an illumination scheme with better phase transfer characteristics. AADPC starts from an initial phase estimate obtained by a DPC-like deconvolution based on the system's weak phase transfer function under discrete half-annular illumination. Then the obtained initial phase map is further refined by the iterative de-multiplexing algorithm to overcome pixel-aliasing and improve the imaging resolution. The data redundancy requirement as well as the optimal illumination scheme of AADPC are analyzed and discussed based on several simulations, suggesting that the spatial undersampling can be mitigated through the iterative algorithm that uses only 4 images, yielding a nearly 4-fold increase in the space-bandwidth product (SBP) compared to the conventional DPC approach. We experimentally verify that AADPC can achieve a half-pitch imaging resolution of 345 nm, corresponding to 1.88× of the theoretical Nyquist-Shannon sampling resolution limit imposed by the sensor pixel size. The high-speed, high-throughput quantitative phase imaging capabilities of AADPC are also demonstrated by imaging HeLa cells mitosis in vitro, achieving a full-pitch lateral resolution of 665 nm across a wide FOV of 1.77mm² at 25 fps.

Response to Comment on "Is the nuclear refractive index lower than cytoplasm? Validation of phase measurements and implications for light scattering technologies": A Comment on "How a phase image of a cell with nucleus refractive index smaller than that of the cytoplasm should look like?", e201800033

Recently, Maxim A. Yurkin commented on our paper "Is the nuclear refractive index lower than cytoplasm? Validation of phase measurements and implications for light scattering technologies" as well as on a complementary study "Cell nuclei have lower refractive index and mass density than cytoplasm" from Schürmann et al. In his comment, Yurkin concluded that quantitative phase images of cells with nuclei that are less optically dense than the cytoplasm must exhibit a characteristic concavity, the absence of which is evidence against our conclusion of a less-dense nucleus. In this response, we suggest that Yurkin's conclusion is reached through an oversimplification of the spatial refractive index distribution within cells, which does not account for high index inclusions such as the nucleolus. We further cite recent studies in 3-dimensional refractive index imaging, in which the preponderance of studies supports our conclusion. Finally, we comment on the current state of knowledge regarding subcellular refractive index distributions in living cells.

A Rapid Detection Method for Morphological Characteristics of Biological Cells Based on Phase Imaging

This paper presents a rapid label-free method for the identification of morphological characteristics of biological cells. Based on quantitative phase microscopy as well as the connotation of phase value, the gradient operator of phase and the associated analytic processing are employed to determine the edge of different parts of the samples. A heterogeneous biological cell model is established by simulation to show the mechanism of this method and a polystyrene bead is selected as a sample to confirm its validity by optical experiment. The result agrees well with the actual situation and this approach is proved to have good antinoise ability. Furthermore, a neutrophil is investigated by this method. Based on the optical experiment and the related analysis, the basic structure characteristics of the cell are obtained. It is indicated that the method presented in this paper could be applied to rapid identification and classification of living cells.

High-speed Fourier ptychographic microscopy based on programmable annular illuminations

High-throughput quantitative phase imaging (QPI) is essential to cellular phenotypes characterization as it allows high-content cell analysis and avoids adverse effects of staining reagents on cellular viability and cell signaling. Among different approaches, Fourier ptychographic microscopy (FPM) is probably the most promising technique to realize high-throughput QPI by synthesizing a wide-field, high-resolution complex image from multiple angle-variably illuminated, low-resolution images. However, the large dataset requirement in conventional FPM significantly limits its imaging speed, resulting in low temporal throughput. Moreover, the underlying theoretical mechanism as well as optimum illumination scheme for high-accuracy phase imaging in FPM remains unclear. Herein, we report a high-speed FPM technique based on programmable annular illuminations (AIFPM). The optical-transfer-function (OTF) analysis of FPM reveals that the low-frequency phase information can only be correctly recovered if the LEDs are precisely located at the edge of the objective numerical aperture (NA) in the frequency space. By using only 4 low-resolution images corresponding to 4 tilted illuminations matching a 10×, 0.4 NA objective, we present the high-speed imaging results of in vitro Hela cells mitosis and apoptosis at a frame rate of 25 Hz with a full-pitch resolution of 655 nm at a wavelength of 525 nm (effective NA = 0.8) across a wide field-of-view (FOV) of 1.77 mm², corresponding to a space-bandwidth-time product of 411 megapixels per second. Our work reveals an important capability of FPM towards high-speed high-throughput imaging of in vitro live cells, achieving video-rate QPI performance across a wide range of scales, both spatial and temporal.

Reconstituting donor T cells increase their biomass following hematopoietic stem cell transplantation

In this study, we used a rapid, highly-sensitive, single-cell biomass measurement method, Live Cell Interferometry (LCI), to measure biomass in populations of CD3 + T cells isolated from hematopoietic stem cell transplant (SCT) patients at various times pre- and post-transplant (days 0–100).

Label-free nanoscale characterization of red blood cell structure and dynamics using single-shot transport of intensity equation

We report the results of characterization of red blood cell (RBC) structure and its dynamics with nanometric sensitivity using transport of intensity equation microscopy (TIEM). Conventional transport of intensity technique requires three intensity images and hence is not suitable for studying real-time dynamics of live biological samples. However, assuming the sample to be homogeneous, phase retrieval using transport of intensity equation has been demonstrated with single defocused measurement with x-rays. We adopt this technique for quantitative phase light microscopy of homogenous cells like RBCs. The main merits of this technique are its simplicity, cost-effectiveness, and ease of implementation on a conventional microscope. The phase information can be easily merged with regular bright-field and fluorescence images to provide multidimensional (three-dimensional spatial and temporal) information without any extra complexity in the setup. The phase measurement from the TIEM has been characterized using polymeric microbeads and the noise stability of the system has been analyzed. We explore the structure and real-time dynamics of RBCs and the subdomain membrane fluctuations using this technique.

High-resolution transport-of-intensity quantitative phase microscopy with annular illumination

For quantitative phase imaging (QPI) based on transport-of-intensity equation (TIE), partially coherent illumination provides speckle-free imaging, compatibility with brightfield microscopy, and transverse resolution beyond coherent diffraction limit. Unfortunately, in a conventional microscope with circular illumination aperture, partial coherence tends to diminish the phase contrast, exacerbating the inherent noise-to-resolution tradeoff in TIE imaging, resulting in strong low-frequency artifacts and compromised imaging resolution. Here, we demonstrate how these issues can be effectively addressed by replacing the conventional circular illumination aperture with an annular one. The matched annular illumination not only strongly boosts the phase contrast for low spatial frequencies, but significantly improves the practical imaging resolution to near the incoherent diffraction limit. By incorporating high-numerical aperture (NA) illumination as well as high-NA objective, it is shown, for the first time, that TIE phase imaging can achieve a transverse resolution up to 208 nm, corresponding to an effective NA of 2.66. Time-lapse imaging of in vitro Hela cells revealing cellular morphology and subcellular dynamics during cells mitosis and apoptosis is exemplified. Given its capability for high-resolution QPI as well as the compatibility with widely available brightfield microscopy hardware, the proposed approach is expected to be adopted by the wider biology and medicine community.

Changes in optical properties of electroporated cells as revealed by digital holographic microscopy

Changes in optical and shape-related characteristics of B16F10 cells after electroporation were investigated using digital holographic microscopy (DHM). Bipolar rectangular pulses specific for electrochemotherapy were used. Electroporation was performed in an "off-axis" DHM set-up without using exogenous markers. Two types of cell parameters were monitored seconds and minutes after pulse train application: parameters addressing a specifically defined area of the cell (refractive index and cell height) and global cell parameters (projected area, optical phase shift profile and dry mass). The biphasic behavior of cellular parameters was explained by water and mannitol dynamics through the electropermeabilized cell membrane.

Review of interferometric spectroscopy of scattered light for the quantification of subdiffractional structure of biomaterials

Optical microscopy is the staple technique in the examination of microscale material structure in basic science and applied research. Of particular importance to biology and medical research is the visualization and analysis of the weakly scattering biological cells and tissues. However, the resolution of optical microscopy is limited to ? 200 ?? nm due to the fundamental diffraction limit of light. We review one distinct form of the spectroscopic microscopy (SM) method, which is founded in the analysis of the second-order spectral statistic of a wavelength-dependent bright-field far-zone reflected-light microscope image. This technique offers clear advantages for biomedical research by alleviating two notorious challenges of the optical evaluation of biomaterials: the diffraction limit of light and the lack of sensitivity to biological, optically transparent structures. Addressing the first issue, it has been shown that the spectroscopic content of a bright-field microscope image quantifies structural composition of samples at arbitrarily small length scales, limited by the signal-to-noise ratio of the detector, without necessarily resolving them. Addressing the second issue, SM utilizes a reference arm, sample arm interference scheme, which allows us to elevate the weak scattering signal from biomaterials above the instrument noise floor.

Digital holographic microscopy in label-free analysis of cultured cells' response to photodynamic treatment

A methodology providing noninvasive monitoring and evaluation of the effect of photodynamic treatment on live cells in vitro is presented. Variations in morphological characteristics of cells in the course and after treatment are recorded by means of digital holographic microscopy. High-precision measurements of phase shift gained by probe radiation in HeLa and human endometrial mesenchymal stem cell cultures demonstrate for the first time changes of their volume occurred in response to treatment.

Generalized total variation iterative constraint strategy in limited angle optical diffraction tomography

Due to incompleteness of input data inherent to Limited Angle Tomography (LAT), specific additional constraints are usually employed to suppress image artifacts. In this work we demonstrate a new two-stage regularization strategy, named Generalized Total Variation Iterative Constraint (GTVIC), dedicated to semi-piecewise-constant objects. It has been successfully applied as a supplementary module for two different reconstruction algorithms: an X-ray type solver and a diffraction-wise solver. Numerical tests performed on a detailed phantom of a biological cell under conical illumination pattern show significant reduction of axial blurring in the reconstructed refractive index distribution after GTVIC is added. Analogous results were obtained with experimental data.

Review of quantitative phase-digital holographic microscopy: promising novel imaging technique to resolve neuronal network activity and identify cellular biomarkers of psychiatric disorders

Quantitative phase microscopy (QPM) has recently emerged as a new powerful quantitative imaging technique well suited to noninvasively explore a transparent specimen with a nanometric axial sensitivity. In this review, we expose the recent developments of quantitative phase-digital holographic microscopy (QP-DHM). Quantitative phase-digital holographic microscopy (QP-DHM) represents an important and efficient quantitative phase method to explore cell structure and dynamics. In a second part, the most relevant QPM applications in the field of cell biology are summarized. A particular emphasis is placed on the original biological information, which can be derived from the quantitative phase signal. In a third part, recent applications obtained, with QP-DHM in the field of cellular neuroscience, namely the possibility to optically resolve neuronal network activity and spine dynamics, are presented. Furthermore, potential applications of QPM related to psychiatry through the identification of new and original cell biomarkers that, when combined with a range of other biomarkers, could significantly contribute to the determination of high risk developmental trajectories for psychiatric disorders, are discussed.

Common-path configuration in total internal reflection digital holography microscopy

Total Internal Reflection Digital Holographic Microscopy (TIRDHM) is recognized to be a powerful tool for retrieving quantitative phase images of cell-substrate interfaces, adhesions, and tissue structures close to the prism surface. In this Letter, we develop an improved TIRDHM system, taking advantage of a refractive index mismatch between the prism and the sample substrate, to allow phase-shifting DH with just a single-beam interferometric configuration. Instead of the traditional off-axis method, phase-shift method is used to retrieve amplitude and phase images in coherent light and TIR modality. Essentially, the substrate-prism interface acts like a beam splitter generating a reference beam, where the phase-shift dependence on the incident angle is exploited in this common-path configuration. With the aim to demonstrate the technique's validity, some experiments are performed to establish the advantage of this compact and simple configuration, in which the reference arm in the setup is avoided.

Imaging through scattering microfluidic channels by digital holography for information recovery in lab on chip

We tackle the problem of information recovery and imaging through scattering microfluidic chips by means of digital holography (DH). In many cases the chip can become opalescent due to residual deposits settling down the inner channel faces, biofilm formation, scattering particle uptake by the channel cladding or its damaging by corrosive substances, or even by condensing effect on the exterior channels walls. In these cases white-light imaging is severely degraded and no information is obtainable at all about the flowing samples. Here we investigate the problem of counting and estimating velocity of cells flowing inside a scattering chip. Moreover we propose and test a method based on the recording of multiple digital holograms to retrieve improved phase-contrast images despite the strong scattering effect. This method helps, thanks to DH, to recover information which, otherwise, would be completely lost.

Performance enhancement and background removal to improve dynamic phase imaging of biological organisms

This paper describes recent advances in enhancing optical imaging performance and removal of background shape for a new, novel interference dynamic microscope system. The specially designed optical system enables instantaneous 4-dimensional video measurements of dynamic motions within and among live cells without the need for labels or contrast agents. This instrument utilizes a pixelated phase mask enabling simultaneous measurement of multiple interference patterns. It incorporates the polarization properties of light to capture phase image movies in real time at video rates enabling tracking of dynamic motions and volumetric changes. Optical thickness data are obtained from phase images after processing to remove the background surface shape to quantify changes in cell position and volume. Data from a number of different biological organisms will be presented. These data highlight examples of the optical image quality and image processing.

Fast phase reconstruction in white light diffraction phase microscopy

In off-axis interferometry, we usually have to deal with the unwrapping process, which is very computationally intensive and prevents us from real time phase reconstruction. The wrapping problem usually occurs when imaging thick objects, which introduce phase shifts of more than 2π radians. However, in off-axis interferometry, the nonzero angle of interference of the two beams creates a ramp in the phase across the image that can produce phase wrapping errors. In this paper, we propose a simple technique that avoids the need for the unwrapping step in reconstructing quantitative phase images in white light diffraction phase microscopy of thin samples. We show that this approach can improve significantly the phase reconstruction speed and allow high impact applications, such as real-time blood testing.

Revolutionary impact of nanodrug delivery on neuroscience

Brain research is the most expanding interdisciplinary research that is using the state of the art techniques to overcome limitations in order to conduct more accurate and effective experiments. Drug delivery to the target site in the central nervous system (CNS) is one of the most difficult steps in neuroscience researches and therapies. Taking advantage of the nanoscale structure of neural cells (both neurons and glia); nanodrug delivery (second generation of biotechnological products) has a potential revolutionary impact into the basic understanding, visualization and therapeutic applications of neuroscience. Current review article firstly provides an overview of preparation and characterization, purification and separation, loading and delivering of nanodrugs. Different types of nanoparticle bioproducts and a number of methods for their fabrication and delivery systems including (carbon) nanotubes are explained. In the second part, neuroscience and nervous system drugs are deeply investigated. Different mechanisms in which nanoparticles enhance the uptake and clearance of molecules form cerebrospinal fluid (CSF) are discussed. The focus is on nanodrugs that are being used or have potential to improve neural researches, diagnosis and therapy of neurodegenerative disorders.

Optical imaging techniques in microfluidics and their applications

Microfluidic devices have undergone rapid development in recent years and provide a lab-on-a-chip solution for many biomedical and chemical applications. Optical imaging techniques are essential in microfluidics for observing and extracting information from biological or chemical samples. Traditionally, imaging in microfluidics is achieved by bench-top conventional microscopes or other bulky imaging systems. More recently, many novel compact microscopic techniques have been developed to provide a low-cost and portable solution. In this review, we provide an overview of optical imaging techniques used in microfluidics followed with their applications. We first discuss bulky imaging systems including microscopes and interferometer-based techniques, then we focus on compact imaging systems that can be better integrated with microfluidic devices, including digital in-line holography and scanning-based imaging techniques. The applications in biomedicine or chemistry are also discussed along with the specific imaging techniques.

Dynamic 4-dimensional microscope system with automated background leveling

This paper describes recent advances in developing an automatic background leveling algorithm for a new, novel interference microscope system and presents images and data of live biological samples. The specially designed optical system enables instantaneous 4-dimensional video measurements of dynamic motions within and among live cells without the need for contrast agents. "Label-free" measurements of biological objects in reflection using harmless light levels are possible without the need for scanning and vibration isolation. This instrument utilizes a pixelated phase mask enabling simultaneous measurement of multiple interference patterns taking advantage of the polarization properties of light enabling phase image movies in real time at video rates to track dynamic motions and volumetric changes. Optical thickness data are derived from phase images. This data is processed with an automatic background leveling routine which separates the objects from the background by thresholding the calculated gradient magnitude of the optical thickness data. Low-order Zernike surfaces are fit to the unmasked background pixels and the resulting background shape is removed. This method effectively eliminates background shape for datasets containing both large and small objects. By applying this method to many sequential frames, it results in all the frames having the same mean background value across all frames which is essential for quantitatively montoring time-dependent processes.

Generalized cell morphological parameters based on interferometric phase microscopy and their application to cell life cycle characterization

We present analysis tools which are formulated using wide-field interferometric phase microscopy measurements, and show their ability to uniquely quantify the life cycle of live cancer cells. These parameters are based directly on the optical path delay profile of the sample and do not necessitate decoupling the refractive index and the thickness in the cell interferometric phase profile, and thus can be calculated using a single-frame acquisition. To demonstrate the use of these parameters, we have constructed a wide-field interferometric phase microscopy setup and closely traced the full lifecycle of HeLa cancer cells. These initial results show the potential of the parameters to distinguish between the different phases of the cell lifecycle, as well others biological phenomena.

Optical quantification of cellular mass, volume, and density of circulating tumor cells identified in an ovarian cancer patient

Clinical studies have demonstrated that circulating tumor cells (CTCs) are present in the blood of cancer patients with known metastatic disease across the major types of epithelial malignancies. Recent studies have shown that the concentration of CTCs in the blood is prognostic of overall survival in breast, prostate, colorectal, and non-small cell lung cancer. This study characterizes CTCs identified using the high-definition (HD)-CTC assay in an ovarian cancer patient with stage IIIC disease. We characterized the physical properties of 31 HD-CTCs and 50 normal leukocytes from a single blood draw taken just prior to the initial debulking surgery. We utilized a non-interferometric quantitative phase microscopy technique using brightfield imagery to measure cellular dry mass. Next we used a quantitative differential interference contrast microscopy technique to measure cellular volume. These techniques were combined to determine cellular dry mass density. We found that HD-CTCs were more massive than leukocytes: 33.6 ± 3.2 pg (HD-CTC) compared to 18.7 ± 0.6 pg (leukocytes), p < 0.001; had greater volumes: 518.3 ± 24.5 fL (HD-CTC) compared to 230.9 ± 78.5 fL (leukocyte), p < 0.001; and possessed a decreased dry mass density with respect to leukocytes: 0.065 ± 0.006 pg/fL (HD-CTC) compared to 0.085 ± 0.004 pg/fL (leukocyte), p < 0.006. Quantification of HD-CTC dry mass content and volume provide key insights into the fluid dynamics of cancer, and may provide the rationale for strategies to isolate, monitor or target CTCs based on their physical properties. The parameters reported here can also be incorporated into blood cell flow models to better understand metastasis.

Dissecting eukaryotic cells by coherent phase microscopy: quantitative analysis of quiescent and activated T lymphocytes

We present a concept for quantitative characterization of a functional state of an individual eukaryotic cell based on interference imaging. The informative parameters of the phase images of quiescent and mitogen-activated T lymphocytes included the phase thickness, phase volume, the area, and the size of organelles. These parameters were obtained without a special hypothesis about cell structure. Combinations of these parameters generated a "phase portrait" of the cell. A simplified spherical multilayer optic model of a T lymphocyte was used to calculate the refractivity profile, to identify structural elements of the image with the organelles, and to interpret the parameters of the phase portrait. The values of phase image parameters underwent characteristic changes in the course of mitogenic stimulation of T cells; thereby, the functional state of individual cells can be described using these parameters. Because the values of the components of the phase portrait are measured in absolute units, it is possible to compare the parameters of images obtained with different interference microscopes. Thus, the analysis of phase portraits provides a new and perspective approach for quantitative, real-time analysis of subcellular structure and physiologic state of an individual cell.

Dynamic phase imaging for in vitro process monitoring and cell tracking

This paper describes a new, novel quantitative interference microscope system and presents images, videos and data of live biological samples. The specially designed optical system enables instantaneous 4-dimensional video measurements of dynamic motions within and among live cells without the need for contrast agents. This "label-free", vibration insensitive imaging system enables measurement of biological objects in reflection using harmless light levels with a variety of magnifications and wavelengths with fields of view from several hundred microns up to a millimeter. At the core of the instrument is a phase measurement camera (PMC) enabling simultaneous measurement of multiple interference patterns utilizing a pixelated phase mask taking advantage of the polarization properties of light. Phase values are converted to optical thickness data enabling volumetric, motion and morphological studies. Data from organisms such as flagellates and rotifers will be presented, as will measurements of human breast cancer cells with the addition of various agents that break down the cells. These data highlight examples of monitoring different biological processes and cellular motions.

Tissue refractive index as marker of disease

The gold standard in histopathology relies on manual investigation of stained tissue biopsies. A sensitive and quantitative method for in situ tissue specimen inspection is highly desirable, as it would allow early disease diagnosis and automatic screening. Here we demonstrate that quantitative phase imaging of entire unstained biopsies has the potential to fulfill this requirement. Our data indicates that the refractive index distribution of histopathology slides, which contains information about the molecular scale organization of tissue, reveals prostate tumors and breast calcifications. These optical maps report on subtle, nanoscale morphological properties of tissues and cells that cannot be recovered by common stains, including hematoxylin and eosin. We found that cancer progression significantly alters the tissue organization, as exhibited by consistently higher refractive index variance in prostate tumors versus normal regions. Furthermore, using the quantitative phase information, we obtained the spatially resolved scattering mean free path and anisotropy factor g for entire biopsies and demonstrated their direct correlation with tumor presence. In essence, our results show that the tissue refractive index reports on the nanoscale tissue architecture and, in principle, can be used as an intrinsic marker for cancer diagnosis.

One-dimensional deterministic transport in neurons measured by dispersion-relation phase spectroscopy

We studied the active transport of intracellular components along neuron processes using a new method developed in our laboratory: dispersion-relation phase spectroscopy. This method is able to quantitatively map spatially the heterogeneous dynamics of the concentration field of the cargos at submicron resolution without the need for tracking individual components. The results in terms of density correlation function reveal that the decay rate is linear in wavenumber, which is consistent with a narrow Lorentzian distribution of cargo velocity.

Deconvolved spatial light interference microscopy for live cell imaging

Spatial light interference microscopy (SLIM) is a recently developed method for the label-free imaging of live cells, using the quantitative optical path length through the sample as an endogenous source of contrast. In conventional SLIM, spatial resolution is limited by diffraction and aberrations. This paper describes a novel constrained deconvolution method for improving resolution in SLIM. Constrained deconvolution is enabled by experimental measurement of the system point-spread function and the modeling of coherent image formation in SLIM. Results using simulated and experimental data demonstrate that the proposed method leads to significant improvements in the resolution and contrast of SLIM images. The proposed method should prove useful for high-resolution label-free studies of biological cells and subcellular processes.

Label-free intracellular transport measured by spatial light interference microscopy

We show that applying the Laplace operator to a speckle-free quantitative phase image reveals an unprecedented level of detail in cell structure, without the gradient artifacts associated with differential interference contrast microscopy, or photobleaching and phototoxicity limitations common in fluorescence microscopy. This method, referred to as Laplace phase microscopy, is an efficient tool for tracking vesicles and organelles in living cells. The principle is demonstrated by tracking organelles in cardiomyocytes and vesicles in neurites of hippocampal neurons, which to our knowledge are the first label-free diffusion measurements of the organelles in such cells.

Label-free high-resolution imaging of live cells with deconvolved spatial light interference microscopy

Spatial light interference microscopy (SLIM) is a powerful new quantitative phase optical imaging technique that can be used for studying live cells without the need for exogenous contrast agents. This paper proposes a novel deconvolution-based approach to reconstructing SLIM data, which dramatically improves the visual quality of the images. The proposed deconvolution formulation is tailored to the physics of SLIM imaging of biological samples, and a new fast algorithm is designed for computationally-efficient image reconstruction in this setting. Simulation and experimental results demonstrate that deconvolution can reduce the width of the point-spread function by at least 20%, and can significantly improve the contrast of high-resolution features. Temporally-resolved SLIM imaging with the high spatial resolution enabled by deconvolution provides new opportunities for studying the dynamics of cellular and sub-cellular processes.

The metabolic component of cellular refractivity and its importance for optical cytometry

Initially, it has been shown that the phase thickness and refractivity (the latter interpreted as the difference of the refractivity indices of an object and surrounding medium) depend on the functional state of mitochondria. The refractivity of various objects decreased in response to energy depletion. This dependence was then demonstrated for other biological objects such as cyanobacteria, chloroplasts and human cells. This general response brought about the hypothesis of a certain "universal" factor that links the variable (or metabolic) component of refractivity with the object's functional state. However, the origin of this phenomenon remains unknown. Our hypothesis is founded on the dependence of polarization of bound water molecules and the activity of metabolic processes. Here, we show the results of measurements of metabolic component of refractivity different bio-objects (mitochondria, chloroplasts, spores, cancer cells) obtained using the Coherent Phase Microscope "Airyscan". Estimations indicated high (up to n approximately = 1.41-1.45) values for the equivalent refractive index of structured water in cells.