Phenotyping neuroblastoma cells through intelligent scrutiny of stain-free biomarkers in holographic flow cytometry.

To efficiently tackle certain tumor types, finding new biomarkers for rapid and complete phenotyping of cancer cells is highly demanded. This is especially the case for the most common pediatric solid tumor of the sympathetic nervous system, namely, neuroblastoma (NB). Liquid biopsy is in principle a very promising tool for this purpose, but usually enrichment and isolation of circulating tumor cells in such patients remain difficult due to the unavailability of universal NB cell-specific surface markers. Here, we show that rapid screening and phenotyping of NB cells through stain-free biomarkers supported by artificial intelligence is a viable route for liquid biopsy. We demonstrate the concept through a flow cytometry based on label-free holographic quantitative phase-contrast microscopy empowered by machine learning. In detail, we exploit a hierarchical decision scheme where at first level NB cells are classified from monocytes with 97.9% accuracy. Then we demonstrate that different phenotypes are discriminated within NB class. Indeed, for each cell classified as NB its belonging to one of four NB sub-populations (i.e., CHP212, SKNBE2, SHSY5Y, and SKNSH) is evaluated thus achieving accuracy in the range 73.6%-89.1%. The achieved results solve the realistic problem related to the identification circulating tumor cell, i.e., the possibility to recognize and detect tumor cells morphologically similar to blood cells, which is the core issue in liquid biopsy based on stain-free microscopy. The presented approach operates at lab-on-chip scale and emulates real-world scenarios, thus representing a future route for liquid biopsy by exploiting intelligent biomedical imaging.

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.

On monocytes and lymphocytes biolens clustering by in flow holographic microscopy.

Live cells act as biological lenses and can be employed as real-world optical components in bio-hybrid systems. Imaging at nanoscale, optical tweezers, lithography and also photonic waveguiding are some of the already proven functionalities, boosted by the advantage that cells are fully biocompatible for intra-body applications. So far, various cell types have been studied for this purpose, such as red blood cells, bacterial cells, stem cells and yeast cells. White Blood Cells (WBCs) play a very important role in the regulation of the human body activities and are usually monitored for assessing its health. WBCs can be considered bio-lenses but, to the best of our knowledge, characterization of their optical properties have not been investigated yet. Here, we report for the first time an accurate study of two model classes of WBCs (i.e., monocytes and lymphocytes) by means of a digital holographic microscope coupled with a microfluidic system, assuming WBCs bio-lens characteristics. Thus, quantitative phase maps for many WBCs have been retrieved in flow-cytometry (FC) by achieving a significant statistical analysis to prove the enhancement in differentiation among sphere-like bio-lenses according to their sizes (i.e., diameter d) exploiting intensity parameters of the modulated light in proximity of the cell optical axis. We show that the measure of the low intensity area (S: I z < I th z ) in a fixed plane, is a feasible parameter for cell clustering, while achieving robustness against experimental misalignments and allowing to adjust the measurement sensitivity in post-processing. 2D scatterplots of the identified parameters (d-S) show better differentiation respect to the 1D case. The results show that the optical focusing properties of WBCs allow the clustering of the two populations by means of a mere morphological analysis, thus leading to the new concept of cell-optical-fingerprint avoiding fluorescent dyes. This perspective can open new routes in biomedical sciences, such as the chance to find optical-biomarkers at single cell level for label-free diagnosis.

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.

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.

Differential diagnosis of hereditary anemias from a fraction of blood drop by digital holography and hierarchical machine learning.

Anemia affects about the 25% of the global population and can provoke severe diseases, ranging from weakness and dizziness to pregnancy problems, arrhythmias and hearth failures. About 10% of the patients are affected by rare anemias of which 80% are hereditary. Early differential diagnosis of anemia enables prescribing patients a proper treatment and diet, which is effective to mitigate the associated symptoms. Nevertheless, the differential diagnosis of these conditions is often difficult due to shared and overlapping phenotypes. Indeed, the complete blood count and unaided peripheral blood smear observation cannot always provide a reliable differential diagnosis, so that biomedical assays and genetic tests are needed. These procedures are not error-free, require skilled personnel, and severely impact the financial resources of national health systems. Here we show a differential screening system for hereditary anemias that relies on holographic imaging and artificial intelligence. Label-free holographic imaging is aided by a hierarchical machine learning decider that works even in the presence of a very limited dataset but is enough accurate for discerning between different anemia classes with minimal morphological dissimilarities. It is worth to notice that only a few tens of cells from each patient are sufficient to obtain a correct diagnosis, with the advantage of significantly limiting the volume of blood drawn. This work paves the way to a wider use of home screening systems for point of care blood testing and telemedicine with lab-on-chip platforms.

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.

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.

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.

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.

Quantitative determination of rapid biomass formation on pyro-electrified polymer sheets.

The ability of a bacterial strain to form a biofilm is strictly related to its pathogenicity. Bacterial adherence and early biofilm formation are influenced by chemical, physical and biological factors that determine their pathogenic properties. We recently presented in literature the ability of pyro-electrified polymer sheets to promote rapid biofilm formation, based on what we called biofilm electrostatic test (BET) carriers. Here we performed a step forward by presenting a comprehensive characterization of the BET methodology through a quantitative evaluation of the biomass on the BET-carrier in the very early stages of incubation. Two bacterial suspensions of Escherichia coli were added to the surface of the BET-carrier, with one order of magnitude difference in initial optical density. The biofilms were stained at different incubation times, while the crystal violet assay and the live/dead reaction kit were used for evaluating the biomass and the viability, respectively. The BET-carrier systematically promoted a faster biofilm formation even in case of very diluted bacterial concentration. The results suggest that the BET-carrier could be used for evaluating rapidly the ability of bacteria to form biofilms and thus their inclination to pathogenicity, thanks to the challenging acceleration in biofilm formation.

Detecting Collagen Molecules at Picogram Level through Electric Field-Induced Accumulation.

The demand for sensors capable of measuring low-abundant collagen in human fluids has highly increased in recent years. Indeed, collagen is expected to be a biomarker for chronic diseases and could monitor their progression. Here we show detection of highly diluted samples of collagen at picogram level thanks to an innovative pyro-electrohydrodynamic jet (p-jet) system. Through the intense electric fields generated by the pyroelectric effect in a ferroelectric crystal, the collagen solution was concentrated on a small area of a slide that was appropriately functionalized to bind proteins. The collagen molecules were labeled by an appropriate fluorophore to show how the number of tiny droplets influences the limit of detection of the technique. The results show that the p-jet is extremely promising for overcoming the current detection limits of collagen-based products in human fluids, performing 10 times better than the enzyme-linked immunosorbent assay (ELISA) and thus paving the way for the early diagnosis of related chronic diseases.

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.

Pyro-Electrification of Freestanding Polymer Sheets: A New Tool for Cation-Free Manipulation of Cell Adhesion in vitro.

Localized electric fields have become, in recent years, a source of inspiration to researchers and laboratories thanks to a huge amount of applications derived from it, including positioning of microparticles as building blocks for electrical, optical, and magnetic devices. The possibility of producing polymeric materials with surface charge thus opens new perspectives for applications where process simplicity and cost-effectiveness of flexible electronics are of fundamental importance. In particular, the influence of surface charges is widely studied and is a critical issue especially when new materials and functional technologies are introduced. Here, we report a voltage-free pyro-electrification (PE) process able to induce a permanent dipole orientation into polymer sheets under both mono- and bipolar distribution. The technique makes use of the pyroelectric effect for generating electric potentials on the order of kilovolts by an easy-to-accomplish thermal treatment of ferroelectric lithium niobate (LN) crystals. The PE allows us to avoid the expensive and time-consuming fabrication of high-power electrical circuits, as occurs in traditional generator-based techniques. Since the technique is fully compatible with spin-coating-based procedures, the pyro-electrified polymer sheets are easily peeled off the surface of the LN crystal after PE completion, thus providing highly stable and freestanding charged sheets. We show the reliability of the technique for different polymers and for different applications ranging from live cell patterning to biofilm formation tests for bacteria linked to food-processing environments.

Biological Lenses as a Photomask for Writing Laser Spots into Ferroelectric Crystals.

Red blood cells on the surface of a lithium niobate crystal can be used as optical lenses for direct writing of laser-induced refractive index changes. The writing process by such a photomask made of biological lenses is due to the photorefractive effect. Wavefront analysis by a digital holographic microscope is performed for deep and accurate evaluation of local refractive index changes. Different focusing properties can be imprinted on the crystal depending on which type of RBC is employed, discocytes or spherical-like RBCs. The possibility to fix into a solid material the optical fingerprint of the RBCs will have an impact on both diagnostics and cell\material interfacing.

In vitro cytotoxicity evaluation of cadmium by label-free holographic microscopy.

Among all environmental pollutants, the toxic heavy metal cadmium is considered as a human carcinogen. Cadmium may induce cell death by apoptosis in various cell types, although the underlying mechanisms are still unclear. In this paper we show how a label-free digital holography (DH)-based technique is able to quantify the evolution of key biophysical parameters of cells during the exposure to cadmium for the first time. Murine embryonic fibroblasts NIH 3T3 are chosen here as cellular model for studying the cadmium effects. The results demonstrate that DH is able to retrieve the temporal evolution of different key parameters such as cell volume, projected area, cell thickness and dry mass, thus providing a full quantitative characterization of the cell physical behaviour during cadmium exposure. Our results show that the label-free character of the technique would allow biologists to perform systematic and reliable studies on cell death process induced by cadmium and we believe that more in general this can be easily extended to others heavy metals, thus avoiding the time-consuming, expensive and invasive label-based procedures used nowadays in the field. In fact, pollution by heavy metals is severe issue that needs rapid and reliable methods to be settled.

Label-Free Optical Marker for Red-Blood-Cell Phenotyping of Inherited Anemias.

The gold-standard methods for anemia diagnosis are complete blood counts and peripheral-smear observations. However, these do not allow for a complete differential diagnosis as that requires biochemical assays, which are label-dependent techniques. On the other hand, recent studies focus on label-free quantitative phase imaging (QPI) of blood samples to investigate blood diseases by using video-based morphological methods. However, when sick cells are very similar to healthy ones in terms of morphometric features, identification of a blood disease becomes challenging even with QPI. Here, we introduce a label-free optical marker (LOM) to detect red-blood-cell (RBC) phenotypes, demonstrating that a single set of all-optical parameters can clearly identify a signature directly related to an erythrocyte disease through modeling each RBC as a biological lens. We tested this novel biophotonic analysis by proving that several inherited anemias, such as iron-deficiency anemia, thalassemia, hereditary spherocytosis, and congenital dyserythropoietic anemia, can be identified and sorted, thus opening a novel route for blood diagnosis on a completely different concept based on LOMs.

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

We report a reliable full-angle tomographic phase microscopy (FA-TPM) method for flowing quasi-spherical cells along microfluidic channels. This method lies in a completely passive optical system, i.e. mechanical scanning or multi-direction probing of the sample is avoided. It exploits the engineered rolling of cells while they are flowing along a microfluidic channel. Here we demonstrate significant progress with respect to the state of the art of in-flow TPM by showing a general extension to cells having almost spherical shapes while they are flowing in suspension. In fact, the adopted strategy allows the accurate retrieval of rotation angles through a theoretical model of the cells' rotation in a dynamic microfluidic flow by matching it with phase-contrast images resulting from holographic reconstructions. So far, the proposed method is the first and the only one that permits to get in-flow TPM by probing the cells with full-angle, achieving accurate 3D refractive index mapping and the simplest optical setup, simultaneously. Proof of concept experiments were performed successfully on human breast adenocarcinoma MCF-7 cells, opening the way for the full characterization of circulating tumor cells (CTCs) in the new paradigm of liquid biopsy.

Holographic microscope slide in a spatio-temporal imaging modality for reliable 3D cell counting.

In the current trend of miniaturization and simplification of imaging flow cytometry, Lab-on-a-Chip (LoC) microfluidic devices represent an innovative and cost-effective solution. In this framework, we propose for the first time a novel platform based on the compactness of a holographic microscope slide (HMS) in combination with the new computational features of space-time digital holography (STDH) that uses a 1D linear sensor array (LSA) instead of 2D CCD or CMOS cameras to respond to real diagnostic needs. In this LoC platform, computational methods, holography, and microfluidics are intertwined in order to provide an imaging system with a reduced amount of optical components and capability to achieve reliable cell counting even in the absence of very accurate flow control. STDH exploits the sample motion into the microfluidic channel to obtain an unlimited field-of-view along the flow direction, independent of the magnification factor. Furthermore, numerical refocusing typical of a holographic modality allows imaging and visualization of the entire volume of the channel, thus avoiding loss of information due to the limited depth of focus of standard microscopes. Consequently, we believe that this platform could open new perspectives for enhancing the throughput by 3D volumetric imaging.

Biolens behavior of RBCs under optically-induced mechanical stress.

In this work, the optical behavior of Red Blood Cells (RBCs) under an optically-induced mechanical stress was studied. Exploiting the new findings concerning the optical lens-like behavior of RBCs, the variations of the wavefront refracted by optically-deformed RBCs were further investigated. Experimental analysis have been performed through the combination of digital holography and numerical analysis based on Zernike polynomials, while the biological lens is deformed under the action of multiple dynamic optical tweezers. Detailed wavefront analysis provides comprehensive information about the aberrations induced by the applied mechanical stress. By this approach it was shown that the optical properties of RBCs in their discocyte form can be affected in a different way depending on the geometry of the deformation. In analogy to classical optical testing procedures, optical parameters can be correlated to a particular mechanical deformation. This could open new routes for analyzing cell elasticity by examining optical parameters instead of direct but with low resolution strain analysis, thanks to the high sensitivity of the interferometric tool. Future application of this approach could lead to early detection and diagnosis of blood diseases through a single-step wavefront analysis for evaluating different cells elasticity. © 2017 International Society for Advancement of Cytometry.