Detection of bladder cancer cells using quantitative interferometric label-free imaging flow cytometry.

Bladder cancer is one of the most common cancers with a high recurrence rate. Patients undergo mandatory yearly scrutinies, including cystoscopies, which makes bladder cancer highly distressing and costly. Here, we aim to develop a non-invasive, label-free method for the detection of bladder cancer cells in urine samples, which is based on interferometric imaging flow cytometry. Eight urothelial carcinoma and one normal urothelial cell lines, along with red and white blood cells, imaged quantitatively without staining by an interferometric phase microscopy module while flowing in a microfluidic chip, and classified by two machine-learning algorithms, based on deep-learning semantic segmentation convolutional neural network and extreme gradient boosting. Furthermore, urine samples obtained from bladder-cancer patients and healthy volunteers were imaged, and classified by the system. We achieved accuracy and area under the curve (AUC) of 99% and 97% for the cell lines on both machine-learning algorithms. For the real urine samples, the accuracy and AUC were 96% and 96% for the deep-learning algorithm and 95% and 93% for the gradient-boosting algorithm, respectively. By combining label-free interferometric imaging flow cytometry with high-end classification algorithms, we achieved high-performance differentiation between healthy and malignant cells. The proposed technique has the potential to supplant cystoscopy in the bladder cancer surveillance and diagnosis space.

Sperm-cell DNA fragmentation prediction using label-free quantitative phase imaging and deep learning.

In intracytoplasmic sperm injection (ICSI), a single sperm cell is selected and injected into an egg. The quality of the chosen sperm and specifically its DNA fragmentation have a significant effect on the fertilization success rate. However, there is no method today to measure the DNA fragmentation of live and unstained cells during ICSI. We present a new method to predict the DNA fragmentation of sperm cells using multi-layer stain-free imaging data, including quantitative phase imaging, and lightweight deep learning architectures. The DNA fragmentation ground truth is achieved by staining the cells with acridine orange and imaging them via fluorescence microscopy. Our prediction model is based on the MobileNet convolutional neural network architecture combined with confidence measurement determined by distances between vectors in the latent space. Our results show that the mean absolute error for cells with high prediction confidence is 0.05 and the 90th percentile mean absolute error is 0.1, where the range of DNA fragmentation score is [0,1]. In the future, this model may be applied to improve cell selection by embryologists during ICSI.

Holographic virtual staining of individual biological cells.

Many medical and biological protocols for analyzing individual biological cells involve morphological evaluation based on cell staining, designed to enhance imaging contrast and enable clinicians and biologists to differentiate between various cell organelles. However, cell staining is not always allowed in certain medical procedures. In other cases, staining may be time-consuming or expensive to implement. Staining protocols may be operator-sensitive, and hence may lead to varying analytical results, as well as cause artificial imaging artifacts or false heterogeneity. We present a deep-learning approach, called HoloStain, which converts images of isolated biological cells acquired without staining by holographic microscopy to their virtually stained images. We demonstrate this approach for human sperm cells, as there is a well-established protocol and global standardization for characterizing the morphology of stained human sperm cells for fertility evaluation, but, on the other hand, staining might be cytotoxic and thus is not allowed during human in vitro fertilization (IVF). After a training process, the deep neural network can take images of unseen sperm cells retrieved from holograms acquired without staining and convert them to their stainlike images. We obtained a fivefold recall improvement in the analysis results, demonstrating the advantage of using virtual staining for sperm cell analysis. With the introduction of simple holographic imaging methods in clinical settings, the proposed method has a great potential to become a common practice in human IVF procedures, as well as to significantly simplify and radically change other cell analyses and techniques such as imaging flow cytometry.

Real-Time Stain-Free Classification of Cancer Cells and Blood Cells Using Interferometric Phase Microscopy and Machine Learning.

We present a method for real-time visualization and automatic processing for detection and classification of untreated cancer cells in blood during stain-free imaging flow cytometry using digital holographic microscopy and machine learning in throughput of 15 cells per second. As a preliminary model for circulating tumor cells in the blood, following an initial label-free rapid enrichment stage based on the cell size, we applied our holographic imaging approach, providing the quantitative optical thickness profiles of the cells during flow. We automatically classified primary and metastatic colon cancer cells, where the two types of cancer cells were isolated from the same individual, as well as four types of blood cells. We used low-coherence off-axis interferometric phase microscopy and a microfluidic channel to image cells during flow quantitatively. The acquired images were processed and classified based on their morphology and quantitative phase features during the cell flow. We achieved high accuracy of 92.56% for distinguishing between the cells, enabling further automatic enrichment and cancer-cell grading from blood. © 2020 International Society for Advancement of Cytometry.

Six-pack holographic imaging for dynamic rejection of out-of-focus objects.

Six-pack holography is adapted to reject out-of-focus objects in dynamic samples, using a single camera exposure and without any scanning. By illuminating the sample from six different angles in parallel using a low-coherence source, out-of-focus objects are laterally shifted in six different directions when projected onto the focal plane. Then pixel-wise averaging of the six reconstructed images creates a significantly clearer image, with rejection of out-of-focus objects. Dynamic imaging results are shown for swimming microalgae and flowing microbeads, including numerical refocusing by Fresnel propagation. The averaged images reduced the contribution of out-of-focus objects by up to 83% in comparison to standard holograms captured using the same light source, further improving the system sectioning capabilities. Both simulation and experimental results are presented.

Roadmap on digital holography [Invited].

This Roadmap article on digital holography provides an overview of a vast array of research activities in the field of digital holography. The paper consists of a series of 25 sections from the prominent experts in digital holography presenting various aspects of the field on sensing, 3D imaging and displays, virtual and augmented reality, microscopy, cell identification, tomography, label-free live cell imaging, and other applications. Each section represents the vision of its author to describe the significant progress, potential impact, important developments, and challenging issues in the field of digital holography.

Polarization-independent differential interference contrast and off-axis holography combined module.

We present an external portable module for transforming bright-field microscopy to differential interference contrast (DIC) microscopy and digital holographic microscopy together. The module is composed of simple optical elements, positioned between the microscope output plane and the digital camera plane; thus, it can be integrated externally with existing microscopes. The proposed module enables polarization DIC imaging, without special polarization elements, under either white-light or coherent illumination, providing label-free imaging of biological samples, as recorded directly by the digital camera. In addition, by rotating one element inside the module, an off-axis hologram is created on the camera under coherent illumination, thus providing the possibility for reconstruction of the quantitative phase profile of the same sample. The method is demonstrated for imaging silica microspheres and biological cells.

Quantitative phase imaging by wide-field interferometry with variable shearing distance uncoupled from the off-axis angle.

We introduce a new shearing interferometry module for digital holographic microscopy, in which the off-axis angle, which defines the interference fringe frequency, is not coupled to the shearing distance, as is the case in most shearing interferometers. Thus, it enables the selection of shearing distance based on the spatial density of the sample, without losing spatial frequency content due to overlapping of the complex wave fronts in the spatial frequency domain. Our module is based on a 4f imaging unit and a diffraction grating, in which the hologram is generated from two mutually coherent, partially overlapping sample beams, with adjustable shearing distance, as defined by the position of the grating, but with a constant off-axis angle, as defined by the grating period. The module is simple, easy to align, and presents a nearly common-path geometry. By placing this module as an add-on unit at the exit port of an inverted microscope, quantitative phase imaging can easily be performed. The system is characterized by a 2.5 nm temporal stability and a 3.4 nm spatial stability, without using anti-vibration techniques. We provide quantitative phase imaging experiments of silica beads with different shearing distances, red blood cell fluctuations, and cancer cells flowing in a micro-channel, which demonstrate the capability and versatility of our approach in different imaging scenarios.

First experimental realization of six-pack holography and its application to dynamic synthetic aperture superresolution.

It has long been assumed that off-axis holography is less spatial bandwidth efficient than on-axis holography. Six-pack holography (6PH) is the first off-axis configuration that changes this paradigm. We present the first experimental realization of 6PH, an off-axis interferometric system capable of spatially multiplexing six complex wavefronts while using the same number of camera pixels needed for a single off-axis hologram. Each of the six parallel complex wavefronts is encoded using a different fringe orientation and can be fully reconstructed. This technique is especially useful for dynamic samples, as it allows the acquisition of six complex wavefronts simultaneously. There are many applications for the data that can be compressed into the six channels. Here, we utilize 6PH to increase resolution in dynamic synthetic aperture imaging, where each of the six optically compressed off-axis holograms encodes a different spatial frequency range of the imaged sample, yielding 1.62 × resolution enhancement.

Individual sperm selection by microfluidics integrated with interferometric phase microscopy.

The selection of sperm cells possessing normal morphology and motility is crucial for many assisted reproductive technologies (ART), especially for intracytoplasmic sperm injection (ICSI), as sperm quality directly affects the probability of inducing healthy pregnancy. We present a novel platform for real-time quantitative analysis and selection of individual sperm cells without staining. Towards this end, we developed an integrated approach, combining interferometric phase microscopy (IPM), for stain-free sperm imaging and real-time automatic analysis based on the sperm cell 3D morphology and contents, with a disposable microfluidic device, for sperm selection and enrichment. On testing the capabilities of the microfluidic device, we obtained successful selection of sperm cells with a selectivity of 89.5±3.5%, with no negative-decision sperm cells being inadvertently selected. In addition, we demonstrate the accuracy of sperm cell analysis using IPM by comparing the quantitative analysis produced by our IPM-based algorithm to the qualitative visual analysis performed independently by an experienced embryologist, which resulted in precision and specificity of 100%. We believe that the presented integrated approach has the potential to dramatically change the way sperm cells are selected for ICSI and other ART procedures, making the selection process more objective, quantitative and automatic, and thereby increasing success rates.

Is multiplexed off-axis holography for quantitative phase imaging more spatial bandwidth-efficient than on-axis holography? [Invited].

Digital holographic microcopy is a thriving imaging modality that attracts considerable research interest due to its ability not only to create excellent label-free contrast but also to supply valuable physical information regarding the density and dimensions of the sample with nanometer-scale axial sensitivity. Three basic holographic recording geometries currently exist, including on-axis, off-axis, and slightly off-axis holography, each of which enables a variety of architectures in terms of bandwidth use and compression capacity. Specifically, off-axis holography and slightly off-axis holography allow spatial hologram multiplexing, enabling one to compress more information into the same digital hologram. In this paper, we define an efficiency score to analyze the various possible architectures and compare the signal-to-noise ratio and the mean squared error obtained using each of them, thus determining the optimal holographic method.

Four dimensional phase unwrapping of dynamic objects in digital holography.

We present a new four-dimensional phase unwrapping approach for time-lapse quantitative phase microscopy, which allows reconstruction of optically thick objects that are optically thin in a certain temporal point and angular view. We thus use all four dimensions of the dynamic quantitative phase profile acquired, including the angular dimension and the temporal dimension, in addition to the x-y dimensions. We first demonstrate the capabilities of this algorithm on simulative data, enabling the quantification of the reconstruction quality relative to both the ground truth and existing unwrapping approaches. Then, we demonstrate the applicability of the proposed four-dimensional phase unwrapping algorithm by experimentally capturing a dual-angular dynamic off-axis hologram with simultaneous recording of two angular views, using multiplexing of two off-axis holograms into a single multiplexed hologram.

Optimal spatial bandwidth capacity in multiplexed off-axis holography for rapid quantitative phase reconstruction and visualization: erratum.

We correct a typo that repeated itself in several equations. Our previous results and conclusions are unchanged.

Flipping interferometry with doubled imaging area.

We present a new external off-axis holographic module that doubles the acquired complex wavefront field of view, based on using both holographic flipping and multiplexing. In contrast to previous designs, this design does not require spatial filtering (no pinhole or lenses) to create the reference beam externally. In addition, the overlap area between the fields of view, as well as the off-axis angle between the sample and reference beams, can be fully controlled. As we demonstrate experimentally, this approach is useful for quantitative phase microscopy of extended stationary and dynamic samples, such as cancer cells during rapid flow and beating cardiomyocytes.

Simultaneous off-axis multiplexed holography and regular fluorescence microscopy of biological cells.

We present a new technique for obtaining simultaneous multimodal quantitative phase and fluorescence microscopy of biological cells, providing both quantitative phase imaging and molecular specificity using a single camera. Our system is based on an interferometric multiplexing module, externally positioned at the exit of an optical microscope. In contrast to previous approaches, the presented technique allows conventional fluorescence imaging, rather than interferometric off-axis fluorescence imaging. We demonstrate the presented technique for imaging fluorescent beads and live biological cells.

Single-exposure full-field multi-depth imaging using low-coherence holographic multiplexing.

We present a new interferometric imaging approach that allows for multiple-depth imaging in a single acquisition, using off-axis low-coherence holographic multiplexing. This technique enables sectioned imaging of multiple slices within a thick sample, in a single image acquisition. Each slice has a distinct off-axis interference fringe orientation indicative of its axial location, and the camera acquires the multiplexed hologram containing the different slices at once. We demonstrate the proposed technique for amplitude and phase imaging of optically thick samples.

Simultaneous three-wavelength unwrapping using external digital holographic multiplexing module.

We present an external interferometric setup that is able to simultaneously acquire three wavelengths of the same sample instance without scanning or multiple exposures. This setup projects onto the monochrome digital camera three off-axis holograms with rotated fringe orientations, each from a different wavelength channel, without overlap in the spatial-frequency domain, and thus allows the full reconstruction of the three complex wavefronts from the three wavelength channels. We use this new setup for three-wavelength phase unwrapping, allowing phase imaging of thicker objects than possible with a single wavelength, but without the increased level of noise. We demonstrate the proposed technique for micro-channel profiling and label-free cell imaging.

Wafer defect detection by a polarization-insensitive external differential interference contrast module.

We present a system that is based on a new external, polarization-insensitive differential interference contrast (DIC) module specifically adapted for detecting defects in semiconductor wafers. We obtained defect signal enhancement relative to the surrounding wafer pattern when compared with bright-field imaging. The new DIC module proposed is based on a shearing interferometer that connects externally at the output port of an optical microscope and enables imaging thin samples, such as wafer defects. This module does not require polarization optics (such as Wollaston or Nomarski prisms) and is insensitive to polarization, unlike traditional DIC techniques. In addition, it provides full control of the DIC shear and orientation, which allows obtaining a differential phase image directly on the camera (with no further digital processing) while enhancing defect detection capabilities, even if the size of the defect is smaller than the resolution limit. Our technique has the potential of future integration into semiconductor production lines.

Automated analysis of individual sperm cells using stain-free interferometric phase microscopy and machine learning.

Currently, the delicate process of selecting sperm cells to be used for in vitro fertilization (IVF) is still based on the subjective, qualitative analysis of experienced clinicians using non-quantitative optical microscopy techniques. In this work, a method was developed for the automated analysis of sperm cells based on the quantitative phase maps acquired through use of interferometric phase microscopy (IPM). Over 1,400 human sperm cells from 8 donors were imaged using IPM, and an algorithm was designed to digitally isolate sperm cell heads from the quantitative phase maps while taking into consideration both the cell 3D morphology and contents, as well as acquire features describing sperm head morphology. A subset of these features was used to train a support vector machine (SVM) classifier to automatically classify sperm of good and bad morphology. The SVM achieves an area under the receiver operating characteristic curve of 88.59% and an area under the precision-recall curve of 88.67%, as well as precisions of 90% or higher. We believe that our automatic analysis can become the basis for objective and automatic sperm cell selection in IVF. © 2017 International Society for Advancement of Cytometry.

Quantitative phase microscopy spatial signatures of cancer cells.

We present cytometric classification of live healthy and cancerous cells by using the spatial morphological and textural information found in the label-free quantitative phase images of the cells. We compare both healthy cells to primary tumor cells and primary tumor cells to metastatic cancer cells, where tumor biopsies and normal tissues were isolated from the same individuals. To mimic analysis of liquid biopsies by flow cytometry, the cells were imaged while unattached to the substrate. We used low-coherence off-axis interferometric phase microscopy setup, which allows a single-exposure acquisition mode, and thus is suitable for quantitative imaging of dynamic cells during flow. After acquisition, the optical path delay maps of the cells were extracted and then used to calculate 15 parameters derived from the cellular 3D morphology and texture. Upon analyzing tens of cells in each group, we found high statistical significance in the difference between the groups in most of the parameters calculated, with the same trends for all statistically significant parameters. Furthermore, a specially designed machine learning algorithm, implemented on the phase map extracted features, classified the correct cell type (healthy/cancer/metastatic) with 81-93% sensitivity and 81-99% specificity. The quantitative phase imaging approach for liquid biopsies presented in this paper could be the basis for advanced techniques of staging freshly isolated live cancer cells in imaging flow cytometers. © 2017 International Society for Advancement of Cytometry.