Full-angle tomographic phase microscopy of flowing quasi-spherical cells

Label-free spatiotemporal decoding of single-cell fate via acoustic driven 3D tomography

Label-free three-dimensional imaging plays a crucial role in unraveling the complexities of cellular functions and interactions in biomedical research. Conventional single-cell optical tomography techniques offer affordability and the convenience of bypassing laborious cell labelling protocols. However, these methods are encumbered by restricted illumination scanning ranges on abaxial plane, resulting in the loss of intricate cellular imaging details. The ability to fully control cellular rotation across all angles has emerged as an optimal solution for capturing comprehensive structural details of cells. Here, we introduce a label-free, cost-effective, and readily fabricated contactless acoustic-induced vibration system, specifically designed to enable multi-degree-of-freedom rotation of cells, ultimately attaining stable in-situ rotation. Furthermore, by integrating this system with advanced deep learning technologies, we perform 3D reconstruction and morphological analysis on diverse cell types, thus validating groups of high-precision cell identification. Notably, long-term observation of cells reveals distinct features associated with drug-induced apoptosis in both cancerous and normal cells populations. This methodology, based on deep learning-enabled cell 3D reconstruction, charts a novel trajectory for groups of real-time cellular visualization, offering promising advancements in the realms of drug screening and post-single-cell analysis, thereby addressing potential clinical requisites.

Recent Advances and Current Trends in Transmission Tomographic Diffraction Microscopy

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

AI-driven projection tomography with multicore fibre-optic cell rotation

Optical tomography has emerged as a non-invasive imaging method, providing three-dimensional insights into subcellular structures and thereby enabling a deeper understanding of cellular functions, interactions, and processes. Conventional optical tomography methods are constrained by a limited illumination scanning range, leading to anisotropic resolution and incomplete imaging of cellular structures. To overcome this problem, we employ a compact multi-core fibre-optic cell rotator system that facilitates precise optical manipulation of cells within a microfluidic chip, achieving full-angle projection tomography with isotropic resolution. Moreover, we demonstrate an AI-driven tomographic reconstruction workflow, which can be a paradigm shift from conventional computational methods, often demanding manual processing, to a fully autonomous process. The performance of the proposed cell rotation tomography approach is validated through the three-dimensional reconstruction of cell phantoms and HL60 human cancer cells. The versatility of this learning-based tomographic reconstruction workflow paves the way for its broad application across diverse tomographic imaging modalities, including but not limited to flow cytometry tomography and acoustic rotation tomography. Therefore, this AI-driven approach can propel advancements in cell biology, aiding in the inception of pioneering therapeutics, and augmenting early-stage cancer diagnostics.

Holographic flow scanning cytometry overcomes depth of focus limits and smartly adapts to microfluidic speed

Space-time digital holography (STDH) maps holograms in a hybrid space-time domain to achieve extended field of view, resolution enhanced, quantitative phase-contrast microscopy and velocimetry of flowing objects in a label-free modality. In STDH, area sensors can be replaced by compact and faster linear sensor arrays to augment the imaging throughput and to compress data from a microfluidic video sequence into one single hybrid hologram. However, in order to ensure proper imaging, the velocity of the objects in microfluidic channels has to be well-matched to the acquisition frame rate, which is the major constraint of the method. Also, imaging all the flowing samples in focus at the same time, while avoiding hydrodynamic focusing devices, is a highly desirable goal. Here we demonstrate a novel processing pipeline that addresses non-ideal flow conditions and is capable of returning the correct and extended focus phase contrast mapping of an entire microfluidic experiment in a single image. We apply this novel processing strategy to recover phase imaging of flowing HeLa cells in a lab-on-a-chip platform even when severely undersampled due to too fast flow while ensuring that all cells are in focus.

Label-free liquid biopsy through the identification of tumor cells by machine learning-powered tomographic phase imaging flow cytometry

Image-based identification of circulating tumor cells in microfluidic cytometry condition is one of the most challenging perspectives in the Liquid Biopsy scenario. Here we show a machine learning-powered tomographic phase imaging flow cytometry system capable to provide high-throughput 3D phase-contrast tomograms of each single cell. In fact, we show that discrimination of tumor cells against white blood cells is potentially achievable with the aid of artificial intelligence in a label-free flow-cyto-tomography method. We propose a hierarchical machine learning decision-maker, working on a set of features calculated from the 3D tomograms of the cells' refractive index. We prove that 3D morphological features are adequately distinctive to identify tumor cells versus the white blood cell background in the first stage and, moreover, in recognizing the tumor type at the second decision step. Proof-of-concept experiments are shown, in which two different tumor cell lines, namely neuroblastoma cancer cells and ovarian cancer cells, are used against monocytes. The reported results allow claiming the identification of tumor cells with a success rate higher than 97% and with an accuracy over 97% in discriminating between the two cancer cell types, thus opening in a near future the route to a new Liquid Biopsy tool for detecting and classifying circulating tumor cells in blood by stain-free method.

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

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

Stain-free identification of cell nuclei using tomographic phase microscopy in flow cytometry

Quantitative Phase Imaging (QPI) has gained popularity in bioimaging because it can avoid the need for cell staining, which in some cases is difficult or impossible. However, as a result, QPI does not provide labelling of various specific intracellular structures. Here we show a novel computational segmentation method based on statistical inference that makes it possible for QPI techniques to identify the cell nucleus. We demonstrate the approach with refractive index tomograms of stain-free cells reconstructed through the tomographic phase microscopy in flow cytometry mode. In particular, by means of numerical simulations and two cancer cell lines, we demonstrate that the nucleus can be accurately distinguished within the stain-free tomograms. We show that our experimental results are consistent with confocal fluorescence microscopy (FM) data and microfluidic cytofluorimeter outputs. This is a significant step towards extracting specific three-dimensional intracellular structures directly from the phase-contrast data in a typical flow cytometry configuration.

Finding intracellular lipid droplets from the single-cell biolens' signature in a holographic flow-cytometry assay

In recent years, intracellular LDs have been discovered to play an important role in several pathologies. Therefore, detection of LDs would provide an in-demand diagnostic tool if coupled with flow-cytometry to give significant statistical analysis and especially if the diagnosis is made in full non-invasive mode. Here we combine the experimental results of in-flow tomographic phase microscopy with a suited numerical simulation to demonstrate that intracellular LDs can be easily detected through a label-free approach based on the direct analysis of the 2D quantitative phase maps recorded by a holographic flow cytometer. In fact, we demonstrate that the presence of LDs affects the optical focusing lensing features of the embracing cell, which can be considered a biological lens. The research was conducted on white blood cells (i.e., lymphocytes and monocytes) and ovarian cancer cells. Results show that the biolens properties of cells can be a rapid biomarker that aids in boosting the diagnosis of LDs-related pathologies by means of the holographic flow-cytometry assay for fast, non-destructive, and high-throughput screening of statistically significant number of cells.

Developing a Reliable Holographic Flow Cyto-Tomography Apparatus by Optimizing the Experimental Layout and Computational Processing

Digital Holographic Tomography (DHT) has recently been established as a means of retrieving the 3D refractive index mapping of single cells. To make DHT a viable system, it is necessary to develop a reliable and robust holographic apparatus in order that such technology can be utilized outside of specialized optics laboratories and operated in the in-flow modality. In this paper, we propose a quasi-common-path lateral-shearing holographic optical set-up to be used, for the first time, for DHT in a flow-cytometer modality. The proposed solution is able to withstand environmental vibrations that can severely affect the interference process. Furthermore, we have scaled down the system while ensuring that a full 360° rotation of the cells occurs in the field-of-view, in order to retrieve 3D phase-contrast tomograms of single cells flowing along a microfluidic channel. This was achieved by setting the camera sensor at 45° with respect to the microfluidic direction. Additional optimizations were made to the computational elements to ensure the reliable retrieval of 3D refractive index distributions by demonstrating an effective method of tomographic reconstruction, based on high-order total variation. The results were first demonstrated using realistic 3D numerical phantom cells to assess the performance of the proposed high-order total variation method in comparison with the gold-standard algorithm for tomographic reconstructions: namely, filtered back projection. Then, the proposed DHT system and the processing pipeline were experimentally validated for monocytes and mouse embryonic fibroblast NIH-3T3 cells lines. Moreover, the repeatability of these tomographic measurements was also investigated by recording the same cell multiple times and quantifying the ability to provide reliable and comparable tomographic reconstructions, as confirmed by a correlation coefficient greater than 95%. The reported results represent various steps forward in several key aspects of in-flow DHT, thus paving the way for its use in real-world applications.

Speeding up reconstruction of 3D tomograms in holographic flow cytometry via deep learning

Tomographic flow cytometry by digital holography is an emerging imaging modality capable of collecting multiple views of moving and rotating cells with the aim of recovering their refractive index distribution in 3D. Although this modality allows us to access high-resolution imaging with high-throughput, the huge amount of time-lapse holographic images to be processed (hundreds of digital holograms per cell) constitutes the actual bottleneck. This prevents the system from being suitable for lab-on-a-chip platforms in real-world applications, where fast analysis of measured data is mandatory. Here we demonstrate a significant speeding-up reconstruction of phase-contrast tomograms by introducing in the processing pipeline a multi-scale fully-convolutional context aggregation network. Although it was originally developed in the context of semantic image analysis, we demonstrate for the first time that it can be successfully adapted to a holographic lab-on-chip platform for achieving 3D tomograms through a faster computational process. We trained the network with input-output image pairs to reproduce the end-to-end holographic reconstruction process, i.e. recovering quantitative phase maps (QPMs) of single cells from their digital holograms. Then, the sequence of QPMs of the same rotating cell is used to perform the tomographic reconstruction. The proposed approach significantly reduces the computational time for retrieving tomograms, thus making them available in a few seconds instead of tens of minutes, while essentially preserving the high-content information of tomographic data. Moreover, we have accomplished a compact deep convolutional neural network parameterization that can fit into on-chip SRAM and a small memory footprint, thus demonstrating its possible exploitation to provide onboard computations for lab-on-chip devices with low processing hardware resources.

On-Chip Optical Nano-Tweezers for Culture-Less Fast Bacterial Viability Assessment

Because of antibiotics misuse, the dramatic growth of antibioresistance threatens public health. Tests are indeed culture-based, and require therefore one to two days. This long time-to-result implies the use of large-spectrum antibiotherapies as a first step, in absence of pathogen characterization. Here, a breakthrough approach for a culture-less fast assessment of bacterial response to stress is proposed. It is based on non-destructive on-chip optical tweezing. A laser loads an optical nanobeam cavity whose evanescent part of the resonant field acts as a nano-tweezer for bacteria surrounding the cavity. Once optically trapped, the bacterium-nanobeam cavity interaction induces a shift of the resonance driven by the bacterial cell wall optical index. The analysis of the wavelength shift yields an assessment of viability upon stress at the single-cell scale. As a proof of concept, bacteria are stressed by incursion, before optical trapping, at different temperatures (45, 51, and 70 °C). Optical index changes correlate with the degree of thermal stress allowing to sort viable and dead bacteria. With this disruptive diagnosis method, bacterial viability upon stress is probed much faster (typically less than 4 h) than with conventional culture-based enumeration methods (24 h).

Label-Free Assessment of the Drug Resistance of Epithelial Ovarian Cancer Cells in a Microfluidic Holographic Flow Cytometer Boosted through Machine Learning

About 75% of epithelial ovarian cancer (EOC) patients suffer from relapsing and develop drug resistance after primary chemotherapy. The commonly used clinical examinations and biological tumor tissue models for chemotherapeutic sensitivity are time-consuming and expensive. Research studies showed that the cell morphology-based method is promising to be a new route for chemotherapeutic sensitivity evaluation. Here, we offer how the drug resistance of EOC cells can be assessed through a label-free and high-throughput microfluidic flow cytometer equipped with a digital holographic microscope reinforced by machine learning. It is the first time that such type of assessment is performed to the best of our knowledge. Several morphologic and texture features at a single-cell level have been extracted from the quantitative phase images. In addition, we compared four common machine learning algorithms, including naive Bayes, decision tree, K-nearest neighbors, support vector machine (SVM), and fully connected network. The result shows that the SVM classifier achieves the optimal performance with an accuracy of 92.2% and an area under the curve of 0.96. This study demonstrates that the proposed method achieves high-accuracy, high-throughput, and label-free assessment of the drug resistance of EOC cells. Furthermore, it reflects strong potentialities to develop data-driven individualized chemotherapy treatments in the future.

Muscope: a miniature on-chip lensless microscope

We report the Muscope, a miniature lensless holographic microscope suitable for on-chip integration. The prototype of the Muscope measured approximately only 7 mm × 4 mm × 4 mm, and was capable of offering a sub-micron half-pitch resolution. We have used, for the first time, a microLED display as the light source in a microscope. The individual pixels of a microLED display chip are used as programmable, microscopic and intense LEDs which can be spatially moved in a two-dimensional plane with a 5 μm pitch. This unique feature set of the display was used to implement computational super-resolution and wide-field imaging without any extra hardware, unlike many other lensless microscopes. We also report a new method to evaluate the magnification in our setting. The Muscope surpasses the existing lensless microscopes in compactness, scalability for production, automated operation and system integration. It provides exciting opportunities for a new class of devices with in-built optical imaging and monitoring and/or sensing capabilities.

Acoustic Standing Wave Aided Multiparametric Photoacoustic Imaging Flow Cytometry

Photoacoustic imaging reveals great potential for the study of individual cells due to the rich imaging contrast for both label-free and labeled cells. However, previously reported photoacoustic imaging flow cytometry configuration suffers from inadequate imaging quality and challenge to distinguish multiple cells. In order to solve such issues, we propose a novel acoustic standing wave aided multiparametric photoacoustic imaging flow cytometry (MPAFC) system. The acoustic standing wave is introduced to improve the imaging quality and speed. Multispectral illumination along with cell geometry, photoacoustic amplitude, and acoustic frequency spectrum enables the proposed system to precisely identify multiple types of cells with one scanning. On the basis of the identification, elimination of melanoma cells, and targeted labeled glioma cells have been performed with an elimination efficiency of >95%. Additionally, the MPAFC system is able to image and capture melanoma cells at a lowest concentration of 100 cells mL^-1 in pure blood. Current results suggest that the proposed MPAFC may provide a precise and efficient tool for cell detection, manipulation, and elimination in both fundamental and clinical studies.

Review: tomographic imaging flow cytometry

Within the last decades, conventional flow cytometry (FC) has evolved as a powerful measurement method in clinical diagnostics, biology, life sciences and healthcare. Imaging flow cytometry (IFC) extends the power of traditional FC by adding high resolution optical and spectroscopic information. However, the conventional IFC only provides a 2D projection of a 3D object. To overcome this limitation, tomographic imaging flow cytometry (tIFC) was developed to access 3D information about the target particles. The goal of tIFC is to visualize surfaces and internal structures in a holistic way. This review article gives an overview of the past and current developments in tIFC.

Adaptive Parameter Model for Quasi-Spherical Cell Size Measurement Based on Lensless Imaging System

Many biological cells appear quasi-spherical, such as red blood cells, white blood cells, egg cells, cancer cells, etc. Cell size is an important basis for medical diagnosis. The traditional method is to use a microscope or flow cytometer to obtain the cell size. Either it depends on professionals and cannot be automated, or it is expensive and bulky, which are not suitable for point-of-care test. Lab-on-a-chip technology using a lensless imaging system gives a better solution for obtaining the cell size. In order to deal with the diffraction in the lensless imaging system, the distance between the light source and the cell, the distance between the cell and the CMOS image sensor and optical wavelength need to be accurately measured or controlled, which will greatly increase the complexity of the system, making it difficult to truly apply to point-of-care test. In this paper, an adaptive parameter model for quasi-spherical cell size measurement based on lensless imaging system is given. First, the diffraction theory used in the model is explained. Then, the adaptive algorithm of the system parameter is given. To illustrate the practicality of the algorithm, a quasi-spherical cell size measurement method and a super-resolution algorithm are given. Finally, the experiment proves that the adaptive parameter model is effective can meet the needs of quasi-spherical cell size measurement.

Three-Dimensional Quantitative Intracellular Visualization of Graphene Oxide Nanoparticles by Tomographic Flow Cytometry

Interaction of nanoparticles (NPs) with cells is of fundamental importance in biology and biomedical sciences. NPs can be taken up by cells, thus interacting with their intracellular elements, modifying the life cycle pathways, and possibly inducing death. Therefore, there is a great interest in understanding and visualizing the process of cellular uptake itself or even secondary effects, for example, toxicity. Nowadays, no method is reported yet in which 3D imaging of NPs distribution can be achieved for suspended cells in flow-cytometry. Here we show that, by means of label-free tomographic flow-cytometry, it is possible to obtain full 3D quantitative spatial distribution of nanographene oxide (nGO) inside each single flowing cell. This can allow the setting of a class of biomarkers that characterize the 3D spatial intracellular deployment of nGO or other NPs clusters, thus opening the route for quantitative descriptions to discover new insights in the realm of NP-cell interactions.

Limited-angle tomographic phase microscopy utilizing confocal scanning fluorescence microscopy

We present a multimodal imaging technique, combining tomographic phase microscopy with limited angular projection range and number, and two-channel spinning-disk confocal scanning fluorescence microscopy. This technique allows high-accuracy 3D refractive index (RI) profiling of live cells in spite of the missing projections. The cellular outer shape and its interior organelles measured by the confocal fluorescence imaging not only specify the cell in molecular levels, but also provide the 3D distributions of the whole cell as well as its organelles. We take these additional 3D morphological details as constraints in Gerchberg-Papoulis-based optical diffraction tomography algorithm. We then obtain an accurate 3D RI tomogram, even with a sparse angular range having a small number of perspective projections, otherwise providing low-accuracy RI reconstruction. Then, we obtain both cellular molecular specificity and inner RI values of the cell and its organelles. We compare the reconstructed 3D RI profiles of various samples, demonstrating the superiority of the proposed technique.

Visually precise, low-damage, single-cell spatial manipulation with single-pixel resolution

The analysis of single living cells, including intracellular delivery and extraction, is essential for monitoring their dynamic biochemical processes and exploring intracellular heterogeneity. However, owing to the 2D view in bright-field microscopy and optical distortions caused by the cell shape and the variation in the refractive index both inside and around the cells, achieving spatially undistorted imaging for high-precision manipulation within a cell is challenging. Here, an accurate and visual system is developed for single-cell spatial manipulation by correcting the aberration for simultaneous bright-field triple-view imaging. Stereo information from the triple view enables higher spatial resolution that facilitates the precise manipulation of single cells. In the bright field, we resolved the spatial locations of subcellular structures of a single cell suspended in a medium and measured the random spatial rotation angle of the cell with a precision of ±5°. Furthermore, we demonstrated the visual manipulation of a probe to an arbitrary spatial point of a cell with an accuracy of <1 pixel. This novel system is more accurate and less destructive for subcellular content extraction and drug delivery.

We achieved the low-damage spatial puncture of single cells at specific visual points with an accuracy of <65 nm.

Rolling angle recovery of flowing cells in holographic tomography exploiting the phase similarity

Holographic tomography allows the 3D mapping of the refractive index of biological samples thanks to reconstruction methods based on the knowledge of illumination directions or rotation angles of the imaged sample. Recently, phase contrast tomographic flow cytometry by digital holography has been demonstrated to reconstruct the three-dimensional refractive index distribution of single cells while they are flowing along microfluidic channels. In this system, the illumination direction is fixed while the sample's rotation is not deterministically known a priori but induced by hydrodynamic forces. We propose here a technique to retrieve the rolling angles, based on a new phase images similarity metric that is capable of identifying a cell's orientations from its 3D positioning while it is flowing along the microfluidic channel. The method is experimentally tested and also validated through appropriate numerical simulations. We provide demonstration of concept by achieving reconstruction of breast cancer cells tomography.

Imaging microphysiological systems: a review

Microphysiological systems (MPS), often referred to as "organ-on-chips," are microfluidic-based in vitro models that aim to recapitulate the dynamic chemical and mechanical microenvironment of living organs. MPS promise to bridge the gap between in vitro and in vivo models and ultimately improve the translation from preclinical animal studies to clinical trials. However, despite the explosion of interest in this area in recent years, and the obvious rewards for such models that could improve R&D efficiency and reduce drug attrition in the clinic, the pharmaceutical industry has been slow to fully adopt this technology. The ability to extract robust, quantitative information from MPS at scale is a key requirement if these models are to impact drug discovery and the subsequent drug development process. Microscopy imaging remains a core technology that enables the capture of information at the single-cell level and with subcellular resolution. Furthermore, such imaging techniques can be automated, increasing throughput and enabling compound screening. In this review, we discuss a range of imaging techniques that have been applied to MPS of varying focus, such as organoids and organ-chip-type models. We outline the opportunities these technologies can bring in terms of understanding mechanistic biology, but also how they could be used in higher-throughput screens, widening the scope of their impact in drug discovery. We discuss the associated challenges of imaging these complex models and the steps required to enable full exploitation. Finally, we discuss the requirements for MPS, if they are to be applied at a scale necessary to support drug discovery projects.

Machine learning of diffraction image patterns for accurate classification of cells modeled with different nuclear sizes

Measurement of nuclear-to-cytoplasm (N:C) ratios plays an important role in detection of atypical and tumor cells. Yet, current clinical methods rely heavily on immunofluroescent staining and manual reading. To achieve the goal of rapid and label-free cell classification, realistic optical cell models (OCMs) have been developed for simulation of diffraction imaging by single cells. A total of 1892 OCMs were obtained with varied nuclear volumes and orientations to calculate cross-polarized diffraction image (p-DI) pairs divided into three nuclear size groups of OCM_S , OCM_O and OCM_L based on three prostate cell structures. Binary classifications were conducted among the three groups with image parameters extracted by the algorithm of gray-level co-occurrence matrix. The averaged accuracy of support vector machine (SVM) classifier on test dataset of p-DI was found to be 98.8% and 97.5% respectively for binary classifications of OCM_S vs OCM_O and OCM_O vs OCM_L for the prostate cancer cell structure. The values remain about the same at 98.9% and 97.8% for the smaller prostate normal cell structures. The robust performance of SVM over clustering classifiers suggests that the high-order correlations of diffraction patterns are potentially useful for label-free detection of single cells with large N:C ratios.

AI on a chip

Artificial intelligence (AI) has dramatically changed the landscape of science, industry, defence, and medicine in the last several years. Supported by considerably enhanced computational power and cloud storage, the field of AI has shifted from mostly theoretical studies in the discipline of computer science to diverse real-life applications such as drug design, material discovery, speech recognition, self-driving cars, advertising, finance, medical imaging, and astronomical observation, where AI-produced outcomes have been proven to be comparable or even superior to the performance of human experts. In these applications, what is essentially important for the development of AI is the data needed for machine learning. Despite its prominent importance, the very first process of the AI development, namely data collection and data preparation, is typically the most laborious task and is often a limiting factor of constructing functional AI algorithms. Lab-on-a-chip technology, in particular microfluidics, is a powerful platform for both the construction and implementation of AI in a large-scale, cost-effective, high-throughput, automated, and multiplexed manner, thereby overcoming the above bottleneck. On this platform, high-throughput imaging is a critical tool as it can generate high-content information (e.g., size, shape, structure, composition, interaction) of objects on a large scale. High-throughput imaging can also be paired with sorting and DNA/RNA sequencing to conduct a massive survey of phenotype-genotype relations whose data is too complex to analyze with traditional computational tools, but is analyzable with the power of AI. In addition to its function as a data provider, lab-on-a-chip technology can also be employed to implement the developed AI for accurate identification, characterization, classification, and prediction of objects in mixed, heterogeneous, or unknown samples. In this review article, motivated by the excellent synergy between AI and lab-on-a-chip technology, we outline fundamental elements, recent advances, future challenges, and emerging opportunities of AI with lab-on-a-chip technology or "AI on a chip" for short.

Polarization holographic microscope slide for birefringence imaging of anisotropic samples in microfluidics

Birefringence is an important optical property of anisotropic materials arising from anisotropies of tissue microstructures. Birefringence parameters have been found to be important to understand optical anisotropic architecture of many materials and polarization imaging has been applied in many researches in the field of biology and medicine. Here, we propose a scheme to miniaturize a double-channel polarization holographic interferometer optics to create a polarization holographic microscope slide (P-HMS) suitable for integrating with microfluidic lab-on-a-chip (LoC) systems. Based on the P-HMS combined with a simple reconstruction algorithm described in the paper, we can not only simultaneously realize holographic imaging of two orthogonal polarization components of dynamic samples in a microfluidic channel but also quantitative measurement of 2D birefringence information, both including the birefringence phase retardation and optic-axis orientation. This chip interferometer allows for off-axis double-channel polarization digital holographic recording using only a single illumination beam without need of any beam splitter or mirror. Its quasi-common path configuration and self-aligned design also make it tolerant to vibrations and misalignment. This work about the P-HMS could play a positive role in promoting the application of birefringence imaging in microfluidic LoC technology.

3-Step flow focusing enables multidirectional imaging of bioparticles for imaging flow cytometry

Multidirectional imaging flow cytometry (mIFC) extends conventional imaging flow cytometry (IFC) for the image-based measurement of 3D-geometrical features of particles. The innovative core is a flow rotation unit in which a vertical sample lamella is incrementally rotated by 90 degrees into a horizontal lamella. The required multidirectional views are generated by guiding all particles at a controllable shear flow position of the parabolic velocity profile of the capillary slit detection chamber. All particles pass the detection chamber in a two-dimensional sheet under controlled rotation while each particle is imaged multiple times. This generates new options for automated particle analysis. In an experimental application, we used our system for the accurate classification of 15 species of pollen based on 3D-morphological information. We demonstrate how the combination of multi directional imaging with advanced machine learning algorithms can improve the accuracy of automated bio-particle classification. As an additional benefit, we significantly decrease the number of false positives in the classification of foreign particles, i.e. those elements which do not belong to one of the trained classes by the 3D-extension of the classification algorithm.

Compact off-axis holographic slide microscope: design guidelines

Holographic microscopes are emerging as suitable tools for in situ diagnostics and environmental monitoring, providing high-throughput, label-free, quantitative imaging capabilities through small and compact devices. In-line holographic microscopes can be realized at contained costs, trading off complexity in the phase retrieval process and being limited to sparse samples. Here we present a 3D printed, cost effective and field portable off-axis holographic microscope based on the concept of holographic microfluidic slide. Our scheme removes complexity from the reconstruction process, as phase retrieval is non iterative and obtainable by hologram demodulation. The configuration we introduce ensures flexibility in the definition of the optical scheme, exploitable to realize modular devices with different features. We discuss trade-offs and design rules of thumb to follow for developing DH microscopes based on the proposed solution. Using our prototype, we image flowing marine microalgae, polystyrene beads, E.coli bacteria and microplastics. We detail the effect on the performance and costs of each parameter, design, and hardware choice, guiding readers toward the realization of optimized devices that can be employed out of the lab by non-expert users for point of care testing.

High-resolution 4-D acquisition of freely swimming human sperm cells without staining

We present a new acquisition method that enables high-resolution, fine-detail full reconstruction of the three-dimensional movement and structure of individual human sperm cells swimming freely. We achieve both retrieval of the three-dimensional refractive-index profile of the sperm head, revealing its fine internal organelles and time-varying orientation, and the detailed four-dimensional localization of the thin, highly-dynamic flagellum of the sperm cell. Live human sperm cells were acquired during free swim using a high-speed off-axis holographic system that does not require any moving elements or cell staining. The reconstruction is based solely on the natural movement of the sperm cell and a novel set of algorithms, enabling the detailed four-dimensional recovery. Using this refractive-index imaging approach, we believe that we have detected an area in the cell that is attributed to the centriole. This method has great potential for both biological assays and clinical use of intact sperm cells.

Acoustic tweezers based on circular, slanted-finger interdigital transducers for dynamic manipulation of micro-objects

Acoustic tweezing technologies are gaining significant attention from the scientific communities due to their versatility and biocompatibility. This study presents acoustic tweezers based on circular, slanted-finger interdigital transducers (CSFITs), which can steer the propagation direction of surface acoustic waves (SAWs) by tuning the excitation frequency. The CSFITs based acoustic tweezers enable dynamic and reconfigurable manipulation of micro-objects using multi-tone excitation signals. Compared to traditional interdigital transducers that generate and control SAWs along one axis, the CSFITs allow for simultaneously generating and independently controlling SAWs propagating along multiple axes by changing the frequency composition and the phase information in a multi-tone excitation signal. Moreover, the CSFITs based acoustic tweezers can be used for patterning cells/particles in various distributions and translating them along complex paths. We believe that our design is valuable for cellular-scale biological applications, in which on-chip, contactless, biocompatible handling of bioparticles is needed.

Assembling and rotating erythrocyte aggregates by acoustofluidic pressure enabling full phase-contrast tomography

The combined use of ultrasound radiation and microfluidics is a promising tool for aiding the development of lab-on-a-chip devices. In this study, we show that the rotation of linear aggregates of micro-particles can be achieved under the action of acoustic field pressure. This novel manipulation is investigated by tracking polystyrene beads of different sizes through the 3D imaging features of digital holography (DH). From our analysis it is understood that the positioning of the micro-particles and their aggregations are associated with the effect of bulk acoustic radiation forces. The observed rotation is instead found to be compatible with the presence of acoustic streaming patterns as evidenced by our modelling and the resulting numerical simulation. Furthermore, the rotation frequency is shown to depend on the input voltage applied on the acoustic device. Finally, we demonstrate that we can take full advantage of such rotation by combining it with quantitative phase imaging of DH for a significant lab-on-a-chip biomedical application. In fact, we demonstrate that it is possible to put in rotation a linear aggregate of erythrocytes and rely on holographic imaging to achieve a full phase-contrast tomography of the aforementioned aggregate.

Reconstruction of bovine spermatozoa substances distribution and morphological differences between Holstein and Korean native cattle using three-dimensional refractive index tomography

Measurements of the three-dimensional (3D) structure of spermatozoon are crucial for the study of developmental biology and for the evaluation of in vitro fertilization. Here, we present 3D label-free imaging of individual spermatozoon and perform quantitative analysis of bovine, porcine, and mouse spermatozoa morphologies using refractive index tomography. Various morphological and biophysical properties were determined, including the internal structure, volume, surface area, concentration, and dry matter mass of individual spermatozoon. Furthermore, Holstein cows and Korean native cattle spermatozoa were systematically analyzed and revealed significant differences in spermatozoa head length, head width, midpiece length, and tail length between the two breeds. This label-free imaging approach provides a new technique for understanding the physiology of spermatozoa.

Measurements on ATP induced cellular fluctuations using real-time dual view transport of intensity phase microscopy

Dual view transport of intensity phase microscopy is adopted to quantitatively study the regulation of adenosine triphosphate (ATP) on cellular mechanics. It extracts cell phases in real time from simultaneously captured under- and over-focus images. By computing the root-mean-square phase and correlation time, it is found that the cellular fluctuation amplitude and speed increased with ATP compared to those with ATP depletion. Besides, when adenylyl-imidodiphosphate (AMP-PNP) was introduced, it competed with ATP to bind to the ATP binding site, and the cellular fluctuation amplitude and speed decreased. The results prove that ATP is a factor in the regulation of cellular mechanics. To our best knowledge, it is the first time that the dual view transport of intensity phase microscopy was used for live cell phase imaging and analysis. Our work not only provides direct measurements on cellular fluctuations to study ATP regulation on cellular mechanics, but it also proves that our proposed dual view transport of intensity phase microscopy can be well used, especially in quantitative phase imaging of live cells in biological and medical applications.

Large-scale high-sensitivity optical diffraction tomography of zebrafish

In this work we demonstrate large-scale high-sensitivity optical diffraction tomography (ODT) of zebrafish. We make this possible by three improvements. First, we obtain a large field of view while still maintaining a high resolution by using a high magnification over numerical aperture ratio digital holography set-up. With the inclusion of phase shifting we operate close to the optimum magnification over numerical aperture ratio. Second, we decrease the noise in the reconstructed images by implementing off-axis sample placement and numerical focus tracking in combination with the acquisition of a large number of projections. Although both techniques lead to an increase in sensitivity independently, we show that combining them is necessary in order to make optimal use of the potential gain offered by each respective method and obtain a refractive index (RI) sensitivity of 8 ⋅ 10 - 5 . Third, we optimize the optical clearing procedure to prevent scattering and refraction to occur. We demonstrate our technique by imaging a zebrafish larva over 13 mm 3 field of view with 4 micrometer resolution. Finally, we demonstrate a clinical application of our technique by imaging an entire adult cryoinjured zebrafish heart.

On-chip refractive index cytometry for whole-cell deformability discrimination

On-chip high-throughput phenotyping of single cells has gained a lot of interest recently due to the discrimination capability of label-free biomarkers such as whole-cell deformability and refractive index. Here we present on-chip refractive index cytometry (RIC) for whole-cell deformability at a high measurement rate. We have further exploited a previously published on-chip optical characterization method which enhances cellular discrimination through the refractive index measurement of single cells. The proposed on-chip RIC can simultaneously probe the cellular refractive index, effective volume and whole-cell deformability while reaching a measurement rate up to 5000 cells per second. Additionally, the relative position of the nucleus inside the cell is reflected by the asymmetry of the measured curve. This particular finding is confirmed by our numerical simulation model and emphasized by a modified cytoskeleton HL-60 cells model. Furthermore, the proposed device discriminated HL-60 derived myeloid cells such as neutrophils, basophils and promyelocytes, which are indistinguishable using flow cytometry. To our knowledge, this is the first integrated device to simultaneously characterize the cellular refractive index and whole-cell deformability, yielding enhanced discrimination of large myeloid cell populations.

Microfluidic engineering for continuous in-flow cyto-tomography

The possibility to investigate cells in microfluidic flow by using a full 3D morphometry analysis is highly demanded to achieve information about their healthiness. Recently, the tomographic flow cytometry by digital holography has been demonstrated to monitor red blood cells in microfluidics environment by simply applying flux pressure to induce random self-rotation of flowing cells. Here, we provide a microfluidic solution to engineer the flow with the aim to ensure the full 360 degree of angle rotation of all cells in the field of view. We test the proposed methods for circulating tumour cells.

High-throughput label-free flow cytometry based on matched-filter compressive imaging

We present a fast label-free computational flow cytometer based on a strategy of compressive imaging. Scattered light from flowing objects is sub-divided into user-defined basis patterns by a deformable mirror and routed to different detectors associated with each pattern. The patterns can be optimized to be matched to the object features of interest, thus facilitating object identification and separation. Compared to conventional scanning flow cytometers, our technique provides increased information capacity without sacrificing flow velocity. Unique features of our matched-filter strategy are that it can simultaneously probe multiple objects throughout large fields of view with long depths of field. In our proof-of-concept demonstrations, we achieve throughputs of over 10,000 particles/s, working at flow velocities of over 1m/s.

Enhancement of optical resolution in three-dimensional refractive-index tomograms of biological samples by employing micromirror-embedded coverslips

Optical diffraction tomography (ODT) enables the reconstruction of the three-dimensional (3D) refractive-index (RI) distribution of a biological cell, which provides invaluable information for cellular and subcellular structures in a non-invasive manner. However, ODT suffers from an inferior axial resolution, due to the limited accessible angles imposed by the numerical aperture of the objective lens. In this study, we propose and experimentally demonstrate an approach to enhance the 3D reconstruction performance in ODT. By employing trapezoidal micromirrors, side scattered signals from the sample are measured for various side plane-wave-illumination angles. By combining the side scattered fields with the forward scattered fields, the axial resolution and 3D image quality of ODT are improved, without changing optical instruments. The feasibility and applicability of the proposed method are demonstrated by reconstructing the 3D RI distribution of a red blood cell and HeLa cells in hydrogel. We also present systematic analyses of the improved 3D imaging performance using numerical simulations and experimental measurements for the 3D transfer function, a point object, and a microsphere. The analyses demonstrate an improved axial resolution of 0.31 μm, 4.8 times smaller than that of the conventional method. The proposed method enables the non-invasive and accurate 3D imaging of 3D cultured cells, which is crucial for cell biology studies.

Measurements of three-dimensional refractive index tomography and membrane deformability of live erythrocytes from Pelophylax nigromaculatus

Unlike mammalian erythrocytes, amphibian erythrocytes have distinct morphological features including large cell sizes and the presence of nuclei. The sizes of the cytoplasm and nuclei of erythrocytes vary significantly over different species, their environments, or pathophysiology, which makes hematological studies important for investigating amphibian species. Here, we present a label-free three-dimensional optical quantification of individual amphibian erythrocytes from frogs Pelophylax nigromaculatus (Rana nigromaculata). Using optical diffraction tomography, we measured three-dimensional refractive index (RI) tomograms of the cells, which clearly distinguished the cytoplasm and nuclei of the erythrocytes. From the measured RI tomograms, we extracted the relevant biochemical parameters of the cells, including hemoglobin contents and hemoglobin concentrations. Furthermore, we measured dynamic membrane fluctuations and investigated the mechanical properties of the cell membrane. From the statistical and correlative analysis of these retrieved parameters, we investigated interspecific differences between frogs and previously studied mammals.

Super-resolution three-dimensional fluorescence and optical diffraction tomography of live cells using structured illumination generated by a digital micromirror device

We present a multimodal approach for measuring the three-dimensional (3D) refractive index (RI) and fluorescence distributions of live cells by combining optical diffraction tomography (ODT) and 3D structured illumination microscopy (SIM). A digital micromirror device is utilized to generate structured illumination patterns for both ODT and SIM, which enables fast and stable measurements. To verify its feasibility and applicability, the proposed method is used to measure the 3D RI distribution and 3D fluorescence image of various samples, including a cluster of fluorescent beads, and the time-lapse 3D RI dynamics of fluorescent beads inside a HeLa cell, from which the trajectory of the beads in the HeLa cell is analyzed using spatiotemporal correlations.

Label-free, high-throughput detection of P. falciparum infection in sphered erythrocytes with digital holographic microscopy

Effective malaria treatment requires rapid and accurate diagnosis of infecting species and actual parasitemia. Despite the recent success of rapid tests, the analysis of thick and thin blood smears remains the gold standard for routine malaria diagnosis in endemic areas. For non-endemic regions, sample preparation and analysis of blood smears are an issue due to low microscopy expertise and few cases of imported malaria. Automation of microscopy results could be beneficial to quickly confirm suspected infections in such conditions. Here, we present a label-free, high-throughput method for early malaria detection with the potential to reduce inter-observer variation by reducing sample preparation and analysis effort. We used differential digital holographic microscopy in combination with two-dimensional hydrodynamic focusing for the label-free detection of P. falciparum infection in sphered erythrocytes, with a parasitemia detection limit of 0.01%. Moreover, the achieved differentiation of P. falciparum ring-, trophozoite- and schizont life cycle stages in synchronized cultures demonstrates the potential for future discrimination of even malaria species.

Three-dimensional tomographic microscopy technique with multi-frequency combination with partially coherent illuminations

We demonstrate a three-dimensional (3D) optical diffraction tomographic technique with multi-frequency combination (MFC-ODT) for the 3D quantitative phase imaging of unlabeled specimens. Three sets of through-focus intensity images are captured under an annular aperture and two circular apertures with different coherence parameters. The 3D phase optical transfer functions (POTF) corresponding to different illumination apertures are combined to obtain a synthesized frequency response, achieving high-quality, low-noise 3D reconstructions with imaging resolution up to the incoherent diffraction limit. Besides, the expression of 3D POTF for arbitrary illumination pupils is derived and analyzed, and the 3D imaging performance of annular illumination is explored. It is shown that the phase-contrast washout effect in high-NA circular apertures can be effectively addressed by introducing a complementary annular aperture, which strongly boosts the phase contrast and improves the imaging resolution. By incorporating high-NA illumination as well as high-NA detection, MFC-ODT can achieve a theoretical transverse resolution up to 200 nm and an axial resolution of 645 nm. To test the feasibility of the proposed MFC-ODT technique, the 3D refractive index reconstruction results are based on a simulated 3D resolution target and experimental investigations of micro polystyrene bead and unstained biological samples are presented. Due to its capability for high-resolution 3D phase imaging as well as the compatibility with a widely available commercial microscope, the MFC-ODT is expected to find versatile applications in biological and biomedical research.

Integral refractive index imaging of flowing cell nuclei using quantitative phase microscopy combined with fluorescence microscopy

We suggest a new multimodal imaging technique for quantitatively measuring the integral (thickness-average) refractive index of the nuclei of live biological cells in suspension. For this aim, we combined quantitative phase microscopy with simultaneous 2-D fluorescence microscopy. We used 2-D fluorescence microscopy to localize the nucleus inside the quantitative phase map of the cell, as well as for measuring the nucleus radii. As verified offline by both 3-D confocal fluorescence microscopy and 2-D fluorescence microscopy while rotating the cells during flow, the nucleus of cells in suspension that are not during division can be assumed to be an ellipsoid. The entire shape of a cell in suspension can be assumed to be a sphere. Then, the cell and nucleus 3-D shapes can be evaluated based on their in-plain radii available from the 2-D phase and fluorescent measurements, respectively. Finally, the nucleus integral refractive index profile is calculated. We demonstrate the new technique on cancer cells, obtaining nucleus refractive index values that are lower than those of the cytoplasm, coinciding with recent findings. We believe that the proposed technique has the potential to be used for flow cytometry, where full 3-D refractive index tomography is too slow to be implemented during flow.

Three-dimensional label-free imaging and analysis of Pinus pollen grains using optical diffraction tomography

The structure of pollen grains is related to the reproductive function of the plants. Here, three-dimensional (3D) refractive index maps were obtained for individual conifer pollen grains using optical diffraction tomography (ODT). The 3D morphological features of pollen grains from pine trees were investigated using measured refractive index maps, in which distinct substructures were clearly distinguished and analyzed. Morphological and physiochemical parameters of the pollen grains were quantified from the obtained refractive index (RI) maps and used to quantitatively study the interspecific differences of pollen grains from different strains. Our results demonstrate that ODT can assess the structure of pollen grains. This label-free and rapid 3D imaging approach may provide a new platform for understanding the physiology of pollen grains.