Nanocapsule induced morphology and migration changes in single cell layers quantified with digital holographic microscopy

Inflammatory bowel diseases (IBD) are inflammatory disorders of the gastrointestinal tract characterized by a chronic relapsing disease course. As uncontrolled intestinal inflammation can result in severe disease complications, recent treatment targets of IBD evolved toward seeking the absence of mucosal and histological inflammation. However, this approach requires adequate histological evaluation of IBD disease activity. The diagnostic challenge of histological examination of intestinal inflammation is documented by the multitude of proposed histological scoring systems. In this context, we review quantitative phase imaging (QPI) techniques such as digital holographic microscopy (DHM) for characterizing intestinal inflammation. DHM determines optical path-length delays in a stain-free manner, thereby providing the tissue refractive index as a biophysical marker that directly correlates to tissue density. Recently, DHM has been successfully applied in cell biology, cancer cell research and infectious-induced cellular alterations. We summarized the capabilities of DHM and related QPI techniques to assess the severity of intestinal inflammation in experimental colitis as well as in colonic samples from human IBD patients. Moreover, we illustrate major advantages of DHM facilitated multimodal evaluation of epithelial wound healing processes as assessed by physical parameters like cell volume, density, thickness and dry mass in vitro. Furthermore, potential limitations of DHM and future utilities of QPI are discussed. In conclusion, DHM represents a promising, easy-to-use quantitative tool to provide accurate and objective assessment of intestinal inflammation and may pave the way towards automated label-free digital pathology and related in vitro cell culture analysis in future.

Digital holographic microscopy (DHM) is an important technique that may be used for quantitative phase imaging of unstained biological cell samples. Since the DHM technology is not commonly used in clinics or bioscience research labs, at present there is no well-accepted focusing criterion for unstained samples that users can follow while recording image plane digital holograms of cells. The usual sharpness metrics that are useful for auto-focusing of stained cells do not work well for unstained cells as there is no amplitude contrast. In this work, we report a practical method for estimating the best focus plane for unstained cells in the digital hologram domain. The method is based on an interesting observation that for the best focus plane the fringe pattern associated with individual unstained cells predominantly shows phase modulation effect in the form of bending of fringes and minimal amplitude modulation. This criterion when applied to unstained red blood cells shows that the central dip in the doughnut-like phase profile of cells is maximal in this plane. The proposed methodology is helpful for standardizing the usage of DHM technology across different users and application developmentefforts. LAY DESCRIPTION: Digital holographic microscopy (DHM) is slowly but steadily becoming an important microscopy modality and gaining acceptability for basic bio-science research as well as clinical usage. One of the important features of DHM is that it allows users to perform quantitative imaging of unstained transparent cells. Instead of using dyes or fluorescent labelling, DHM systems use quantitative phase as a contrast mechanism which depends on the natural refractive index variation within the cell samples. Since minimal wet lab processing is required in order to image cell samples with a DHM, cells can be imaged in their natural state. While DHM is gaining popularity among users, the imaging protocols across the labs or users need to be standardized in order to make sure that the same quantitative phase parameters are used for tasks such as quantitative phased based cellclassification. One of the important operational tasks for any microscopy work is to focus the sample under study. While focusing comes naturally to users of brightfield microscopes based on image contrast, the focusing is not straightforward when samples are unstained so that they do not offer any amplitude contrast. When performing quantitative phase imaging, defocus can actually change the phase profile of the cell due to near-zone (Fresnel) diffraction effects. So unless a standardized focusing methodology is used, it will be difficult for multiple DHM users (potentially at different sites) to agree on quantitative results out of their phase images. DHM literature has prior works which perform numerical focusing of recovered complex wave-field in the hologram plane to find the best focus plane. However such methods are not user friendly and do not allow user the same focusing experience as in a brightfield microscope. The numerical focusing is therefore a reasonably good method for an optics researcher but not necessarily so for a microscopy technician looking at cell samples with a DHM system in a clinicalsetting. The present work provides a simple focusing criterion for unstained samples that works directly in the hologram domain. The technique is based on an interesting observation that the when an unstained cell sample is in the best-focus plane, its corresponding hologram (or fringe pattern) predominantly shows phase modulation manifested by bending of fringes at the location of the cell. This criterion can be converted into a simple numerical method as we have used to find the best-focus plane using a stack of through focus holograms. We believe that the technique can be used manually by visually observing the holograms or can be converted to an auto-focus algorithm for a motorized DHMsystem.

.Significance: Machine learning is increasingly being applied to the classification of microscopic data. In order to detect some complex and dynamic cellular processes, time-resolved live-cell imaging might be necessary. Incorporating the temporal information into the classification process may allow for a better and more specific classification.Aim: We propose a methodology for cell classification based on the time-lapse quantitative phase images (QPIs) gained by digital holographic microscopy (DHM) with the goal of increasing performance of classification of dynamic cellular processes.Approach: The methodology was demonstrated by studying epithelial–mesenchymal transition (EMT) which entails major and distinct time-dependent morphological changes. The time-lapse QPIs of EMT were obtained over a 48-h period and specific novel features representing the dynamic cell behavior were extracted. The two distinct end-state phenotypes were classified by several supervised machine learning algorithms and the results were compared with the classification performed on single-time-point images.Results: In comparison to the single-time-point approach, our data suggest the incorporation of temporal information into the classification of cell phenotypes during EMT improves performance by nearly 9% in terms of accuracy, and further indicate the potential of DHM to monitor cellular morphological changes.Conclusions: Proposed approach based on the time-lapse images gained by DHM could improve the monitoring of live cell behavior in an automated fashion and could be further developed into a tool for high-throughput automated analysis of unique cell behavior.

Motility, or co-ordinated movement, of cells is fundamental for the development of many processes, such as formation of the embryo, the immune response, inflammation, wound healing, and metastasis of cancer cells 1. Cells often migrate in response to specific external signals, but they can also move spontaneously. Aberrant cell motility can be fatal in cancer diseases when cells start to metastasize 2. Metastasis is strictly associated with tissue invasion of the primary tumor cells, and occurs as a multistep progress 3. The first phase of cancer cell metastasis involves the physical translocation of the cell to a distant organ, whereas the second phase implicates the ability of the cancer cell to develop into a metastatic lesion at that distant site 4. For skin cancer melanoma, the main cause of death is widespread metastases 5. Melanoma cells may travel along external vessel lattices. After settling in the metastatic sites, melanoma cells develop mechanisms that protect them against the attack of the immune system. It is, therefore, of great interest and importance to investigate, monitor, and understand the principles of tumor cell invasion and migration. The development of novel therapeutic applications that have the ability to block migratory processes is crucial. For in vitro studies, the cell culture wound-closure, and the transwell migration and invasion assays can provide data for an understanding how well a particular cell type can migrate 6. The wound healing assay is also called a scratch assay because it is performed by making a scratch in the cell monolayer (Fig. 1A). The transwell migration assay is a commonly used test to study the migratory response of endothelial cells to angiogenic inducers or inhibitors (Fig. 1B). This assay is also known as the Boyden or modified Boyden chamber assay. These assays have been frequently used to study movement of cells. Weckmann et al. developed an interesting system to monitor and quantify neutrophils on single cell level, by utilizing commercially available tissue culture hardware, simple video microscopic equipment, and standardized tracking 7. However, the interest for novel standardized real-time analyses using quantitative phase imaging (QPI) for cell tracking is growing (Fig. 2). More than 10 years ago, the digital holographic (DH) microscopy methodology of QPI became known to a larger audience and the technique has since then successfully been applied for label-free monitoring of live cells undergoing cell division, cell proliferation, cell death, and cell migration over time 8-10. By QPI, studies associated with both cellular thickness and refractive index fluctuations have been performed. The possibilities for utilizing QPI for cancer diagnostics have increased 11. Cellular behavior and phenotypes are other parameters that can be measured 12. For two human osteosarcoma cell types, the motility pattern, but not the proliferative pattern, was different. Early migration studies using DH microscopy showed fibroblast migration 13 and HT-1080 fibrosarcoma cells embedded in a 3D collagen gel 14. Alm et al. and Persson et al. also presented data on movement of different cell types and cell sizes 15 as well as demonstrated the correlation of cell movement with cell morphology 16. In the recent article published in the November 2018 issue of Cytometry Part A by Zhang et al., (pages 1125–1131) commercially available DH cytometry platforms equipped with semi-automated image acquisition, segmentation, and analysis software packages for assessing cell behavior are used and discussed. The motility data was obtained with QPI/cytometry using "Track cells module" and "Wound healing module," respectively, and with transwell migration assays determining migration and invasion, respectively. The different techniques assessing motility were compared. The two melanoma cell lines, WM793 and 1205Lu, used in the study were reported to have different metastatic capacity, resulting in differences in proliferation and motility. The motility measured with the "Track cells module" and "Wound healing module," using DH cytometry equipment housed in an incubator, produced highly correlated relative motilities, even when compared to the standard transwell migration and invasion assays. Images acquired with DH are from the same position in a cell culture vessel, making it possible to study individual cells. This is a strong advantage, since most studies of effects of new drugs on proliferation and migration of cancer cells in culture are performed on a population level. In a recent study by Kamlund et al., cell images were captured every fifth minute for a total of up to 72 h 17. For cell movement studies, the semi-automated algorithm attempts to find each tracked cell in the next frame by selecting the closest cell based on the centroid position. The advantages of the Track cells and Wound healing modules over the transwell migration and invasion assays in the paper by Zhang et al., included the possibility to use the cells in the experiment for other purposes after completing the measurement. DH microscopy also benefits from the fact that morphology analysis can be performed of each cell. Indeed, this opens up for almost unlimited possibilities to perform cell morphology analysis using the QPI methodology, since each image is very rich in cellular information. As discussed in a review by El-Schich et al., automated analysis and machine learning is one approach to handle the large amount of morphological data that can now be generated when analyzing cells with QPI 8. Only the computer resources and the training speed will set the limitations.

Different interferometric techniques were developed last decade to obtain full field, quantitative, and absolute phase imaging, such as phase-shifting, Fourier phase microscopy, Hilbert phase microscopy or digital holographic microscopy (DHM). Although, these techniques are very similar, DHM combines several advantages. In contrast, to phase shifting, DHM is indeed capable of single-shot hologram recording allowing a real-time absolute phase imaging. On the other hand, unlike to Fourier phase or Hilbert phase microscopy, DHM does not require to record in focus images of the specimen on the digital detector (CCD or CMOS camera), because a numerical focalization adjustment can be performed by a numerical wavefront propagation. Consequently, the depth of view of high NA microscope objectives is numerically extended. For example, two different biological cells, floating at different depths in a liquid, can be focalized numerically from the same digital hologram. Moreover, the numerical propagation associated to digital optics and automatic fitting procedures, permits vibrations insensitive full- field phase imaging and the complete compensation for a priori any image distortion or/and phase aberrations introduced for example by imperfections of holders or perfusion chamber. Examples of real-time full-field phase images of biological cells have been demonstrated.

Differential phase contrast (DPC) is a non-interferometric quantitative phase imaging method achieved by using an asymmetric imaging procedure. We report a pupil modulation differential phase contrast (PMDPC) imaging method by filtering a sample's Fourier domain with half-circle pupils. A phase gradient image is captured with each half-circle pupil, and a quantitative high resolution phase image is obtained after a deconvolution process with a minimum of two phase gradient images. Here, we introduce PMDPC quantitative phase image reconstruction algorithm and realize it experimentally in a 4f system with an SLM placed at the pupil plane. In our current experimental setup with the numerical aperture of 0.36, we obtain a quantitative phase image with a resolution of 1.73μm after computationally removing system aberrations and refocusing. We also extend the depth of field digitally by 20 times to ±50μm with a resolution of 1.76μm.

Intestinal strictures are a frequent complication in patients with Crohn’s Disease (CD) and the presence of fibrosis within strictures impacts the therapeutic treatment approach. Here, we evaluate quantitative phase imaging (QPI) using digital holographic microscopy (DHM) for the evaluation of fibrosis within CD strictures. 30 full thickness resection specimens were obtained from non-stenotic and stenotic tissue areas of 15 CD patients. Cryostat sections were analyzed by DHM to measure the spatial distribution of the refractive index (RI) to quantify tissue density. Complementary, histopathological evaluation of H&E staining and immunofluorescence (IF) targeting fibrosis markers served as the gold standard. Moreover, tissue stiffness was evaluated by elastography. RI values assessed by DHM were significantly higher in stenotic compared to non-stenotic tissue areas (p < 0.001). Histopathological analysis using H&E staining and IF confirmed the elevated expression of fibrosis markers in stenotic compared to non-stenotic tissue (all p < 0.001). The RI retrieved by DHM strongly correlated with the amount of fibrosis as determined by IF (p < 0.001; R2 = 0.48). Furthermore, elastography detected a significantly higher tissue stiffness in stenotic as compared to non-stenotic tissue sections (p < 0.001). In conclusion, QPI using DHM accurately assesses fibrotic properties of CD-associated strictures and may improve the characterization of CD strictures.

Digital holographic microscopy (DHM), which provides quantitative phase imaging (QPI), has been widely applied in material and biological applications. The performance of DHM technologies relies heavily on computational reconstruction methods to provide accurate phase measurements. For example, non-telecentric DHM systems should compensate for the spherical wavefront associated with a non-telecentric configuration. The size of the ±1 diffraction orders in the hologram spectrum depends inversely on the radius of the curvature of the spherical wavefront introduced by the non-telecentric DHM system. Therefore, one can estimate the radius of curvature of the spherical wavefront by analyzing the hologram spectrum. Here, we outline the steps for the automatic reconstruction of phase images without distortions and with minimum user input from a hologram recorded in a non-telecentric DHM system. The proposed reconstruction approach can be divided into six main steps. The first step automatically selects the +1 diffraction order in the hologram spectrum. Secondly, the spherical wavefront parameters and the interference angle are estimated by analyzing the size and position of the selected +1 order. The third and fourth steps are the spatial filtering of the +1 order and the compensation of the interference angle, respectively. The next step involves the estimation of the center of the spherical wavefront. Finally, there is a fine-tuning step to optimize the estimated parameters and provide a phase image with minimum phase distortions. We have identified the relevant metrics in each step, compared multiple approaches, and selected the one with the higher performance for all our experimental holograms.

In digital holographic microscopy (DHM) scattering patterns and parasitic interference fringes due to internal reflections that are caused by coherent laser light affect quantitative phase imaging (QPI). We present an approach for the reduction coherence induced disturbances. Therefore, the sample illumination is modulated by an electrically focus tunable lens while a series of digital off-axis holograms is recorded from which subsequently averaged QPI images are retrieved. The principle is compatible with Mach-Zehnder interferometer-based off-axis DHM and capable to be integrated into commercial research microscopes. The performance of our approach is demonstrated by results from living porcine epithelia cells and mouse fibroblasts.

Dielectric metasurfaces have recently attracted much attention due to their ability to efficiently control light propagation, that is, its amplitude, phase and polarization, on micro- and macro- levels. Such metasurfaces also naturally allow for integration in compact optical setups due to their small sizes. An important issue of energy losses is also addressed by employing all-dielectric platform. Advancements in nanofabrication have enabled realization of metasurface-based high-resolution wavefront engineering devices, which have been employed in different imaging applications, for example, as metalenses, polarization filters, metaholograms, etc. Quantitative phase imaging is a powerful tool for the optical inspection of transparent samples in connection with biological and technical applications. By measuring thickness and/or refractive index profiles, phase imaging facilitates, for example, the observation of dynamic events in unstained cells. As such, it has become indispensable in biological imaging, wavefront correction and metrology. However, conventional cameras and photodetectors are inherently not sensitive to the phase of an incident lightwave. As a consequence, direct phase detection is challenging. Only by multiple intensity measurements or application of specialized interferometric schemes, the phase profile of an object can be in principle reconstructed. In this paper, we report on the ability of metasurfaces to contribute to quantitative phase imaging by independent control of the phase profiles in two orthogonal polarization states of an incident beam.

We explored a Mask Region-based Convolutional Neural Network (Mask R-CNN) to detect macrophages in quantitative phase images, which were acquired by digital holographic microscopy (DHM), an interferometry-based variant of quantitative phase imaging (QPI). The Mask R-CNN deep learning architecture is capable to detect and segment single macrophage cells in quantitative phase images and allows to perform both tasks in a multi-stage process. Our results show that the combined detection and segmentation of cells through Mask R-CNN-based automated evaluation prospects a fast and robust screening in label-free high throughput microscopy.

Digital Holographic Microscopy (DHM) is an emerging label-free modality for quantitative imaging of semi-transparent biological specimens. DHM provides Quantitative Phase Imaging (QPI) of the light transmitted or scattered by an object, which allows to extract information about morphology and dynamics of investigated specimens. DHM can be implemented with other optical microscopy techniques like Bright Field (BF) or fluorescence, for example, to provide complementary information about cellular processes. Multimodal microscopy is often achieved by sequential acquisition of information from different imaging modalities or simultaneously by capturing images with different acquisition devices. However, such arrangements can be cost-intensive and/or limited in speed for imaging of dynamic processes. Here, we investigate a single-snapshot multimodal approach that enables simultaneous acquisition of DHM-based QPI and BF images and is compatible with common optical microscopes for the analysis of living cells. The technique is based on spatially multiplexed interferometric microscopy (SMIM), where off-axis holograms are generated by spatial multiplexing of the illuminated sample plane utilizing a diffraction grating, which is extended by additional superposition of complementary white-light image information. Image separation is achieved by Fourier-transformation-based numerical demultiplexing procedures. The technique is firstly characterized by investigations on microspheres. Then, the application on living adherent and suspended cells is illustrated.

A dual mode microscope is developed to study morphological evolution of mouse myoblast cells under simulated microgravity in real time. Microscope operates in Digital Holographic Microscopy (DHM) and widefield epifluorescence microscopy modes in a time sequential basis. DHM provides information on real time cellular morphology. EGFP transfected actin filaments in mouse myoblast cells function as the reporter for the fluorescence microscopy mode. Experimental setup is fixed in the RPM to observe microgravity induced dynamic changes in live cells. Initial results revealed two different modifications. Disorganized structures become visible in the formed lamellipodias, and proteins accumulate in the perinuclear region.

Achieving high-contrast, label-free imaging with minimal impact on live cell culture behavior remains a primary challenge in quantitative phase imaging (QPI). By enabling imaging under low illumination intensities (low photon budget, LPB), it is possible to minimize cell photostimulation, phototoxicity, and photodamage while supporting long-term and high-speed observations. However, LPB imaging introduces significant difficulties in QPI due to high levels of camera shot noise and quantification noise. Digital in-line holographic microscopy (DIHM) is a QPI technique known for its robustness against LPB data. However, simultaneous minimization of shot noise and inherent in DIHM twin image perturbation remains a critical challenge. In this study, we present the iterative Gabor averaging (IGA) algorithm, a novel approach that integrates iterative phase retrieval with frame averaging to effectively suppress both twin image disturbance and shot noise in multiframe DIHM. The IGA algorithm achieves this by leveraging an iterative process that reconstructs high-fidelity phase images while selectively averaging camera shot noise across frames. Our simulations demonstrate that IGA consistently outperforms conventional methods, achieving superior reconstruction accuracy, particularly under high-noise conditions. Experimental validations involving high-speed imaging of dynamic sperm cells and a static phase test target measurement under low illumination further confirmed IGA's efficacy. The algorithm also proved successful for optically thin samples, which often yield low signal-to-noise holograms even at high photon budgets. These advancements make IGA a powerful tool for photostimulation-free, high-speed imaging of dynamic biological samples and enhance the ability to image samples with extremely low optical thickness, potentially transforming biomedical and environmental applications in low-light settings.

Quantitative phase microscopy (QPM) is a label-free imaging technique often employed for long-term, high-contrast imaging of live bio-samples. Yet, QPM is not specific to a certain subcellular organelle. As a remedy, fluorescence microscopy can visualize specific subcellular organelles once being labeled with fluorescent markers. In this paper, a high-resolution phase/fluorescence dual-modality microscopic imaging method based on structured light illumination is proposed. In a dual-modality microscopic system, periodic stripes are generated by a digital micromirror array (DMD), and are used as the common illumination for both modalities. For QPM imaging, the holograms of the sample under structured light illuminations from different directions and phase shifts are recorded, from which a quantitative phase image with resolution enhancement can be reconstructed via a synthetic aperture procedure. Furthermore, a numerical approach is proposed to compensate for the environmental disturbances that often challenge aperture synthesis of phase imaging. This method determines each time the phase distortions caused by environmental disturbances through using the spectrum of the 0th order of the structured light illumination, and the phase distortions are removed from the phase distributions of the waves along the 0th and the ±1st diffraction orders. Resolution enhancement of QPM imaging is realized by synthesizing the spectra of all the waves along different diffraction orders of the structured light illuminations of different orientations. With phase images, three-dimensional shapes, inner structures, or refractive index distributions of transparent and translucent samples can be obtained. For fluorescence imaging, intensity images (morie patterns) of the sample under different structured light illuminations are recorded. The spectra along different diffraction orders are separated by using a phase shifting reconstruction algorithm, and are shifted to their original positions, forming a synthesized spectrum that is much broader than the spectra of raw intensity images (NA-limited spectra). An inverse Fourier transform on the synthesized spectrum yields a super-resolution fluorescence image of the sample. With the reconstructed fluorescence images, specific subcellular organelles labeled with fluorescent markers can be visualized. The combination of quantitative phase microscopy and fluorescence microscopy can obtain multidimensional information about the sample. In this dual-mode imaging system, the spatial resolution of quantitative phase imaging and fluorescence imaging are 840 nm and 440 nm, respectively. The proposed dual-mode microscopy imaging technique has been demonstrated for imaging fluorescent beads, fly wings, spring/rice leaves, mouse tail transection, and fluorescence-stained SiHa cells. We envisage that this method can be further applied to many fields, such as biomedicine, industry, and chemistry.