Refractive Index Tomograms Research Articles

GAN-based quantitative oblique back-illumination microscopy enables computationally efficient epi-mode refractive index tomography.

Quantitative oblique back-illumination microscopy (qOBM) is a novel imaging technology that enables epi-mode 3D quantitative phase imaging and refractive index (RI) tomography of thick scattering samples. The technology uses four oblique back illumination images captured at the same focal plane and a fast 2D deconvolution reconstruction algorithm to reconstruct 2D phase cross-sections of thick samples. Alternatively, a through-focus z-stack of oblique back illumination images can be used to recover 3D RI tomograms with improved RI quantitative fidelity at the cost of a more computationally expensive reconstruction algorithm. Here, we report on a generative adversarial network (GAN) assisted approach to reconstruct 3D RI tomograms with qOBM that achieves high fidelity and greatly reduces processing time. The proposed approach achieves high-fidelity 3D RI tomography using differential phase contrast images from three adjacent z-planes. A ∼9-fold improvement in volumetric reconstruction time is achieved. We further show that this technique provides high SNR RI tomograms with high quantitative fidelity, reduces motion artifacts, and generalizes to different tissue types. This work can lead to real-time, high-fidelity RI tomographic imaging for in-vivo pre-clinical and clinical applications.

Label-free morpho-molecular phenotyping of living cancer cells by combined Raman spectroscopy and phase tomography

Accurate, rapid and non-invasive cancer cell phenotyping is a pressing concern across the life sciences, as standard immuno-chemical imaging and omics require extended sample manipulation. Here we combine Raman micro-spectroscopy and phase tomography to achieve label-free morpho-molecular profiling of human colon cancer cells, following the adenoma, carcinoma, and metastasis disease progression, in living and unperturbed conditions. We describe how to decode and interpret quantitative chemical and co-registered morphological cell traits from Raman fingerprint spectra and refractive index tomograms. Our multimodal imaging strategy rapidly distinguishes cancer phenotypes, limiting observations to a low number of pristine cells in culture. This synergistic dataset allows us to study independent or correlated information in spectral and tomographic maps, and how it benefits cell type inference. This method is a valuable asset in biomedical research, particularly when biological material is in short supply, and it holds the potential for non-invasive monitoring of cancer progression in living organisms.

Single-exposure multi-wavelength optical diffraction tomography based on space-angle dual multiplexing holography.

We present a space-angle dual multiplexing holographic recording system for realizing single-exposure multi-wavelength optical diffraction tomographic (ODT) imaging. This system is achieved by combining the principle of single-exposure multi-wavelength holographic imaging technique based on angle-division multiplexing with the principle of single-exposure ODT imaging technique based on microlens array multi-angle illuminations and space-division multiplexing. Compared with the existing multi-wavelength ODT imaging methods, it enables the holographic recording of all the diffraction tomography information of a measured specimen at multiple illumination wavelengths in a single camera exposure without any scan mechanism. Using our proposed data processing method, the multi-wavelength three-dimensional (3D) refractive index tomograms of a specimen can be eventually reconstructed from single recorded multiplexing hologram. Experimental results of a static polystyrene bead and a living C. elegans worm demonstrate the feasibility of this system.

Bio‐Engineering Yeast Cells Biolenses by Reshaping Intracellular Vacuoles

AbstractAn intriguing field of research has recently emerged in which biological cells can be demonstrated to behave as photonics devices, such as optical microlenses. This research highlights yeast cells as promising candidates for engineering biolenses with customizable focal properties. Typically serving as positive biolenses due to their quasi‐spherical shape and positive refractive index (RI) contrast, yeast cells can achieve a negative lensing effect by manipulating their intracellular content, without altering their overall morphology. In fact, it shows that exposure to hypotonic conditions induces the formation of a large, roundish vacuole with lower RI values with respect to the surrounding cytoplasm, thus altering the cell's optical properties. This behavior is investigated by using 3D RI tomograms obtained through a holo‐tomographic phase imaging flow cytometry system, demonstrating that the anisotropic nature of yeast cells results in focal properties dependent on their specific orientations in respect to the incident light. Furthermore, Zemax OpticStudio is utilized to perform comprehensive assessments for optical design analysis of the obtained cell biolenses. The methods described here and the related results represent a pioneering investigation of biological cells’ metamorphoses via intracellular content manipulation for biolens applications.

Optical diffraction tomography for assessing single cell models in angular light scattering.

Angularly resolved light scattering (ALS) has become a useful tool for assessing the size and refractive index of biological scatterers at cellular and organelle length scales. Sizing organelle populations with ALS relies on Mie scattering theory models, which require significant assumptions about the object, including spherical scatterers and a homogeneous medium. These assumptions may incur greater error at the single cell level, where there are fewer scatterers to be averaged over. We investigate the validity of these assumptions using 3D refractive index (RI) tomograms measured via optical diffraction tomography (ODT). We compute the angular scattering on digitally manipulated tomograms with increasingly strong model assumptions, including RI-matched immersion media, homogeneous cytosol, and spherical organelles. We also compare the tomogram-computed angular scattering to experimental measurements of angular scattering from the same cells to ensure that the ODT-based approach accurately models angular scattering. We show that enforced RI-matching with the immersion medium and a homogeneous cytosol significantly affects the angular scattering intensity shape, suggesting that these assumptions can reduce the accuracy of size distribution estimates.

3D Holo-tomographic Mapping of COVID-19 Microclots in Blood to Assess Disease Severity.

The coronavirus disease 2019 (COVID-19) has impacted health globally. Cumulative evidence points to long-term effects of COVID-19 such as cardiovascular and cognitive disorders, diagnosed in patients even after the recovery period. In particular, micrometer-sized blood clots and hyperactivated platelets have been identified as potential indicators of long COVID. Here, we resolve microclot structures in the plasma of patients with different subphenotypes of COVID-19 in a label-free manner, using 3D digital holo-tomographic microscopy (DHTM). Based on 3D refractive index (RI) tomograms, the size, dry mass, and prevalence of microclot composites were quantified and then parametrically differentiated from fibrin-rich microclots and platelet aggregates in the plasma of COVID-19 patients. Importantly, fewer microclots and platelet aggregates were detected in the plasma of healthy controls compared to COVID-19 patients. Our imaging and analysis workflow is built around a commercially available DHT microscope capable of operation in clinical settings with a 2 h time period from sample preparation and data acquisition to results.

Deep learning-based label-free hematology analysis framework using optical diffraction tomography

Hematology analysis, a common clinical test for screening various diseases, has conventionally required a chemical staining process that is time-consuming and labor-intensive. To reduce the costs of chemical staining, label-free imaging can be utilized in hematology analysis. In this work, we exploit optical diffraction tomography and the fully convolutional one-stage object detector or FCOS, a deep learning architecture for object detection, to develop a label-free hematology analysis framework. Detected cells are classified into four groups: red blood cell, abnormal red blood cell, platelet, and white blood cell. In the results, the trained object detection model showed superior detection performance for blood cells in refractive index tomograms (0.977 mAP) and also showed high accuracy in the four-class classification of blood cells (0.9708 weighted F1 score, 0.9712 total accuracy). For further verification, mean corpuscular volume (MCV) and mean corpuscular hemoglobin (MCH) were compared with values obtained from reference hematology equipment, with our results showing reasonable correlation in both MCV (0.905) and MCH (0.889). This study provides a successful demonstration of the proposed framework in detecting and classifying blood cells using optical diffraction tomography for label-free hematology analysis.

In-silico clearing approach for deep refractive index tomography by partial reconstruction and wave-backpropagation

Refractive index (RI) is considered to be a fundamental physical and biophysical parameter in biological imaging, as it governs light-matter interactions and light propagation while reflecting cellular properties. RI tomography enables volumetric visualization of RI distribution, allowing biologically relevant analysis of a sample. However, multiple scattering (MS) and sample-induced aberration (SIA) caused by the inhomogeneity in RI distribution of a thick sample make its visualization challenging. This paper proposes a deep RI tomographic approach to overcome MS and SIA and allow the enhanced reconstruction of thick samples compared to that enabled by conventional linear-model-based RI tomography. The proposed approach consists of partial RI reconstruction using multiple holograms acquired with angular diversity and their backpropagation using the reconstructed partial RI map, which unambiguously reconstructs the next partial volume. Repeating this operation efficiently reconstructs the entire RI tomogram while suppressing MS and SIA. We visualized a multicellular spheroid of diameter 140 µm within minutes of reconstruction, thereby demonstrating the enhanced deep visualization capability and computational efficiency of the proposed method compared to those of conventional RI tomography. Furthermore, we quantified the high-RI structures and morphological changes inside multicellular spheroids, indicating that the proposed method can retrieve biologically relevant information from the RI distribution. Benefitting from the excellent biological interpretability of RI distributions, the label-free deep visualization capability of the proposed method facilitates a noninvasive understanding of the architecture and time-course morphological changes of thick multicellular specimens.

Label-Free Digital Holotomography Reveals Ibuprofen-Induced Morphological Changes to Red Blood Cells.

Understanding the dose-dependent effect of over-the-counter drugs on red blood cells (RBCs) is crucial for hematology and digital pathology. Yet, it is challenging to continuously record the real-time, drug-induced shape changes of RBCs in a label-free manner. Here, we demonstrate digital holotomography (DHTM)-enabled real-time, label-free concentration-dependent and time-dependent monitoring of ibuprofen on RBCs from a healthy donor. The RBCs are segmented based on three-dimensional (3D) and four-dimensional (4D) refractive index tomograms, and their morphological and chemical parameters are retrieved with their shapes classified using machine learning. We directly observed the formation and motion of spicules on the RBC membrane when aqueous solutions of ibuprofen were drop-cast on wet blood, creating rough-membraned echinocyte forms. At low concentrations of 0.25-0.50 mM, the ibuprofen-induced morphological change was transient, but at high concentrations (1-3 mM) the spiculated RBC remained over a period of up to 1.5 h. Molecular simulations confirmed that aggregates of ibuprofen molecules at high concentrations significantly disrupted the RBC membrane structural integrity and lipid order but produced negligible effect at low ibuprofen concentrations. Control experiments on the effect of urea, hydrogen peroxide, and aqueous solutions on RBCs showed zero spicule formation. Our work clarifies the dose-dependent chemical effects on RBCs using label-free microscopes that can be deployed for the rapid detection of overdosage of over-the-counter and prescribed drugs.

Standardizing image assessment in optical diffraction tomography.

Optical diffraction tomography (ODT) has gradually become a popular label-free imaging technique that offers diffraction-limited resolution by mapping an object's three-dimensional (3D) refractive index (RI) distribution. However, there is a lack of comprehensive quantitative image assessment metrics in ODT for studying how various experimental conditions influence image quality, and subsequently optimizing the experimental conditions. In this Letter, we propose to standardize the image assessment in ODT by proposing a set of metrics, including signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and structural distinguishability (SD). To test the feasibility of the metrics, we performed experiments on angle-scanning ODT by varying the number of illumination angles, RI contrast of samples, sample feature sizes, and sample types (e.g., standard polystyrene beads and 3D printed structures) and evaluated the RI tomograms with SNR, CNR, and SD. We further quantitatively studied how image quality can be improved, and tested the image assessment metrics on subcellular structures of living cells. We envision the proposed image assessment metrics may greatly benefit end-users for assessing the RI tomograms, as well as experimentalists for optimizing ODT instruments.

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

Quantitative phase imaging 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, quantitative phase imaging does not provide the labelling of various specific intracellular structures. Here we show a novel computational segmentation method based on statistical inference that makes it possible for quantitative phase imaging techniques to identify the cell nucleus. We demonstrate the approach with refractive index tomograms of stain-free cells reconstructed using tomographic phase microscopy in the 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 data and microfluidic cyto-fluorimeter outputs. This is a remarkable step towards directly extracting specific three-dimensional intracellular structures from the phase contrast data in a typical flow cytometry configuration.

Quantitative refractive index tomography of millimeter-scale objects using single-pixel wavefront sampling

Optical diffraction tomography (ODT) is broadly employed to study 3D structures of transparent objects in a stain-free manner. ODT is commonly implemented with an interferometric setup, but its applications on mesoscopic objects have been challenging due to its limited phase detection range. We introduce an ODT method capable of producing 3D refractive index (RI) distribution via a single-pixel detector. Our method exploits a single-pixel wavefront sensor to measure two-dimensional complex information of millimeter-scale weakly absorbing objects at various projection angles. The application of the Fourier diffraction (or slice) theorem to the acquired complex images results in an RI tomogram of transparent objects. The experiments with calibrated objects and zebrafish larvae demonstrate its promise for measuring the RI tomogram of large and weakly absorbing objects beyond the visible spectral range.

Dynamic Tomographic Phase Microscopy by Double Six-Pack Holography.

Three-dimensional (3D) optical imaging of rapidly moving biological cells is difficult to achieve as such samples cannot be scanned over time. Here, we present a dynamic scan-free optical tomography approach for stain-free 3D imaging of biological cells using our new double six-pack tomography technique, whereby 12 off-axis holograms are captured in a single camera exposure without sacrificing resolution or field of view. The proposed system illuminates the sample from 12 angles simultaneously, and 3D refractive index (RI) tomograms are reconstructed from each recorded video frame of the dynamic sample. The technique is verified experimentally by recording flowing silica beads, 3 μm in diameter, with the resulting tomogram RI accuracy being 98.5%. A live swimming sperm cell is also imaged, and dynamic 3D imaging results for both beads and sperm cell are presented. The proposed technique represents a 12-fold increase in dynamic holographic data for tomography.

In-depth biological analysis of alteration in Plasmodium knowlesi-infected red blood cells using a noninvasive optical imaging technique

BackgroundImaging techniques are commonly used to understand disease mechanisms and their biological features in the microenvironment of the cell. Many studies have added to our understanding of the biology of the malaria parasite Plasmodium knowlesi from functional in vitro and imaging analysis using serial block-face scanning electron microscopy (SEM). However, sample fixation and metal coating during SEM analysis can alter the parasite membrane.MethodsIn this study, we used noninvasive diffraction optical tomography (DOT), also known as holotomography, to explore the morphological, biochemical, and mechanical alterations of each stage of P. knowlesi-infected red blood cells (RBCs). Each stage of the parasite was synchronized using Nycodenz and magnetic-activated cell sorting (MACS) for P. knowlesi and P. falciparum, respectively. Holotomography was applied to measure individual three-dimensional refractive index tomograms without metal coating, fixation, or additional dye agent.ResultsDistinct profiles were found on the surface area and hemoglobin content of the two parasites. The surface area of P. knowlesi-infected RBCs showed significant expansion, while P. falciparum-infected RBCs did not show any changes compared to uninfected RBCs. In terms of hemoglobin consumption, P. falciparum tended to consume hemoglobin more than P. knowlesi. The observed profile of P. knowlesi-infected RBCs generally showed similar results to other studies, proving that this technique is unbiased.ConclusionsThe observed profile of the surface area and hemoglobin content of malaria infected-RBCs can potentially be used as a diagnostic parameter to distinguish P. knowlesi and P. falciparum infection. In addition, we showed that holotomography could be used to study each Plasmodium species in greater depth, supporting strategies for the development of diagnostic and treatment strategies for malaria.Graphical

Label-free multiplexed microtomography of endogenous subcellular dynamics using generalizable deep learning.

Simultaneous imaging of various facets of intact biological systems across multiple spatiotemporal scales is a long-standing goal in biology and medicine, for which progress is hindered by limits of conventional imaging modalities. Here we propose using the refractive index (RI), an intrinsic quantity governing light-matter interaction, as a means for such measurement. We show that major endogenous subcellular structures, which are conventionally accessed via exogenous fluorescence labelling, are encoded in three-dimensional (3D) RI tomograms. We decode this information in a data-driven manner, with a deep learning-based model that infers multiple 3D fluorescence tomograms from RI measurements of the corresponding subcellular targets, thereby achieving multiplexed microtomography. This approach, called RI2FL for refractive index to fluorescence, inherits the advantages of both high-specificity fluorescence imaging and label-free RI imaging. Importantly, full 3D modelling of absolute and unbiased RI improves generalization, such that the approach is applicable to a broad range of new samples without retraining to facilitate immediate applicability. The performance, reliability and scalability of this technology are extensively characterized, and its various applications within single-cell profiling at unprecedented scales (which can generate new experimentally testable hypotheses) are demonstrated.

Label-free monitoring of 3D cortical neuronal growth in vitro using optical diffraction tomography.

The highly complex central nervous systems of mammals are often studied using three-dimensional (3D) in vitro primary neuronal cultures. A coupled confocal microscopy and immunofluorescence labeling are widely utilized for visualizing the 3D structures of neurons. However, this requires fixation of the neurons and is not suitable for monitoring an identical sample at multiple time points. Thus, we propose a label-free monitoring method for 3D neuronal growth based on refractive index tomograms obtained by optical diffraction tomography. The 3D morphology of the neurons was clearly visualized, and the developmental processes of neurite outgrowth in 3D spaces were analyzed for individual neurons.

Artificial Intelligence-Powered Automated Holotomographic Microscopy Enables Label-Free Quantitative Biology

Abstract:Holotomographic microscopy (HTM) measures the refractive index (RI) tomograms of living cells and tissues in three dimensions. The ability to observe biological processes at high spatial and temporal resolution opens uncharted territories for cell biologists, however, current HTM devices have a limited throughput. We show here the first automated multi-well plate-compatible HTM device, the CX-A. Thanks to state-of-the-art environment control and a new type of autofocus, the CX-A can record multiple conditions in parallel over large fields of view, while its software EVE supports automated single-cell segmentation and quantification. This opens the door to new applications for HTM, from drug screening to systems biology.

Reagent- and actuator-free analysis of individual erythrocytes using three-dimensional quantitative phase imaging and capillary microfluidics

Histopathological examination of blood cells plays a crucial role in the diagnosis of various diseases. However, it involves time-consuming and laborious staining procedures required for microscopic review by medical experts and is not directly applicable for point-of-care diagnosis in resource-limited locations. This study reports a dilution-, actuation- and label-free method for the analysis of individual red blood cells (RBCs) using a capillary microfluidic device and quantitative phase imaging. Blood, without any sample treatment, is directly loaded into a micrometer-thick channel such that it forms a quasi-monolayer inside the channel. The morphological and biochemical properties of RBCs, including hemoglobin concentration, hemoglobin content, and corpuscular volume, were retrieved using the refractive index tomograms of individual RBCs measured using 3D quantitative phase imaging. The deformability of individual RBCs was also obtained by measuring the dynamic membrane fluctuations. The proposed framework applies to other imaging modalities and biomedical applications, facilitating rapid and cost-effective diagnosis and prognosis of diseases.

Label‐Free Quantitative Analysis of Coacervates via 3D Phase Imaging

AbstractCoacervation is considered as a ubiquitous mechanism for assembling biomolecular materials outside cells and organizing membraneless organelles inside cells. Despite the importance of mapping binodals to understand the driving forces and thermodynamics of coacervate, quantifying protein concentration within a droplet is significantly challenging owing to its dynamic and viscous nature. A direct imaging‐based method is presented to quantify coacervate using real‐time 3D quantitative phase imaging. The proposed method utilizes the measurements of the refractive index tomograms of individual coacervates and retrieves the protein concentration and volume of individual protein droplets exploiting light‐scattering analysis. The retrievals of accurate protein concentrations are demonstrated in droplets, whereas conventional fluorescence‐based techniques present underestimations. With its simple, direct, real‐time, and quantitative analysis capability, the present method can be utilized in various protein analyses and quantifications for the study of coacervation both in vitro and in vivo.

Detection of intracellular monosodium urate crystals in gout synovial fluid using optical diffraction tomography

Optical diffraction tomography (ODT) enables imaging of unlabeled intracellular components by measuring the three-dimensional (3D) refractive index (RI). We aimed to detect intracellular monosodium urate (MSU) crystals in synovial leukocytes derived from gout patients using ODT. The 3D RI values of the synthetic MSU crystals, measured by ODT, ranged between 1.383 and 1.440. After adding synthetic MSU crystals to a macrophage, RI tomograms were reconstructed using ODT, and the reconstructed RI tomograms discerned intracellular and extracellular MSU crystals. We observed unlabeled synthetic MSU crystal entry into the cytoplasm of a macrophage through time-lapse imaging. Furthermore, using gout patient-derived synovial leukocytes, we successfully obtained RI tomogram images of intracellular MSU crystals. The 3D RI identification of MSU crystals was verified with birefringence through polarization-sensitive ODT measurements. Together, our results provide evidence that this novel ODT can identify birefringent MSU crystals in synovial leukocytes of patients with gout.