Generalized quantification of three-dimensional resolution in optical diffraction tomography using the projection of maximal spatial bandwidths

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.

Three-dimensional tomographic reconstruction using Voronoi weighting

Three-dimensional tomographic reconstruction requires careful selection of the illumination angles, often under certain measurement constraints. When the angular distribution must be nonuniform, appropriate selection of the reconstruction weights is necessary. We show that Voronoi weighting can significantly improve the fidelity of optical diffraction tomography.

Fourier space aberration correction for high resolution refractive index imaging using incoherent light

An aberration correction method is introduced for 3D phase deconvolution microscopy. Our technique capitalizes on multiple illumination patterns to iteratively extract Fourier space aberrations, utilizing the overlapping information inherent in these patterns. By refining the point spread function based on the retrieved aberration data, we significantly improve the precision of refractive index deconvolution. We validate the effectiveness of our method on both synthetic and biological three-dimensional samples, achieving notable enhancements in resolution and measurement accuracy. The method's reliability in aberration retrieval is further confirmed through controlled experiments with intentionally induced spherical aberrations, underscoring its potential for wide-ranging applications in microscopy and biomedicine.

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.

Enhanced functionalities of immune cells separated by a microfluidic lattice: assessment based on holotomography

The isolation of white blood cells (WBCs) from whole blood constitutes a pivotal process for immunological studies, diagnosis of hematologic disorders, and the facilitation of immunotherapy. Despite the ubiquity of density gradient centrifugation in WBC isolation, its influence on WBC functionality remains inadequately understood. This research employs holotomography to explore the effects of two distinct WBC separation techniques, namely conventional centrifugation and microfluidic separation, on the functionality of the isolated cells. We utilize three-dimensional refractive index distribution and time-lapse dynamics to analyze individual WBCs in-depth, focusing on their morphology, motility, and phagocytic capabilities. Our observations highlight that centrifugal processes negatively impact WBC motility and phagocytic capacity, whereas microfluidic separation yields a more favorable outcome in preserving WBC functionality. These findings emphasize the potential of microfluidic separation techniques as a viable alternative to traditional centrifugation for WBC isolation, potentially enabling more precise analyses in immunology research and improving the accuracy of hematologic disorder diagnoses.

Hybrid machine-learning framework for volumetric segmentation and quantification of vacuoles in individual yeast cells using holotomography

The precise, quantitative evaluation of intracellular organelles in three-dimensional (3D) imaging data poses a significant challenge due to the inherent constraints of traditional microscopy techniques, the requirements of the use of exogenous labeling agents, and existing computational methods. To counter these challenges, we present a hybrid machine-learning framework exploiting correlative imaging of 3D quantitative phase imaging with 3D fluorescence imaging of labeled cells. The algorithm, which synergistically integrates a random-forest classifier with a deep neural network, is trained using the correlative imaging data set, and the trained network is then applied to 3D quantitative phase imaging of cell data. We applied this method to live budding yeast cells. The results revealed precise segmentation of vacuoles inside individual yeast cells, and also provided quantitative evaluations of biophysical parameters, including volumes, concentration, and dry masses of automatically segmented vacuoles.

Single-shot refractive index slice imaging using spectrally multiplexed optical transfer function reshaping

The refractive index (RI) of cells and tissues is crucial in pathophysiology as a noninvasive and quantitative imaging contrast. Although its measurements have been demonstrated using three-dimensional quantitative phase imaging methods, these methods often require bulky interferometric setups or multiple measurements, which limits the measurement sensitivity and speed. Here, we present a single-shot RI imaging method that visualizes the RI of the in-focus region of a sample. By exploiting spectral multiplexing and optical transfer function engineering, three color-coded intensity images of a sample with three optimized illuminations were simultaneously obtained in a single-shot measurement. The measured intensity images were then deconvoluted to obtain the RI image of the in-focus slice of the sample. As a proof of concept, a setup was built using Fresnel lenses and a liquid-crystal display. For validation purposes, we measured microspheres of known RI and cross-validated the results with simulated results. Various static and highly dynamic biological cells were imaged to demonstrate that the proposed method can conduct single-shot RI slice imaging of biological samples with subcellular resolution.

Long-term label-free assessments of individual bacteria using three-dimensional quantitative phase imaging and hydrogel-based immobilization

Three-dimensional (3D) quantitative phase imaging (QPI) enables long-term label-free tomographic imaging and quantitative analysis of live individual bacteria. However, the Brownian motion or motility of bacteria in a liquid medium produces motion artifacts during 3D measurements and hinders precise cell imaging and analysis. Meanwhile, existing cell immobilization methods produce noisy backgrounds and even alter cellular physiology. Here, we introduce a protocol that utilizes hydrogels for high-quality 3D QPI of live bacteria maintaining bacterial physiology. We demonstrate long-term high-resolution quantitative imaging and analysis of individual bacteria, including measuring the biophysical parameters of bacteria and responses to antibiotic treatments.

High-fidelity optical diffraction tomography of live organisms using iodixanol refractive index matching

Optical diffraction tomography (ODT) enables the three-dimensional (3D) refractive index (RI) reconstruction. However, when the RI difference between a sample and a medium increases, the effects of light scattering become significant, preventing the acquisition of high-quality and accurate RI reconstructions. Herein, we present a method for high-fidelity ODT by introducing non-toxic RI matching media. Optimally reducing the RI contrast enhances the fidelity and accuracy of 3D RI reconstruction, enabling visualization of the morphology and intra-organization of live biological samples without producing toxic effects. We validate our method using various biological organisms, including C. albicans and C. elegans.

Ring stage classification of Babesia microti and Plasmodium falciparum using optical diffraction 3D tomographic technique

Background

Babesia is an intraerythrocytic parasite often misdiagnosed as a malaria parasite, leading to inappropriate treatment of the disease especially in co-endemic areas. In recent years, optical diffraction tomography (ODT) has shown great potential in the field of pathogen detection by quantification of three-dimensional (3D) imaging tomograms. The 3D imaging of biological cells is crucial to investigate and provide valuable information about the mechanisms behind the pathophysiology of cells and tissues.

Methods

The early ring stage of P. falciparum were obtained from stored stock of infected RBCs and of B. microti were obtained from infected patients during diagnosis. The ODT technique was applied to analyze and characterize detailed differences between P. falciparum and B. microti ring stage at the single cell level. Based on 3D quantitative information, accurate measurement was performed of morphological, biochemical, and biophysical parameters.

Results

Accurate measurements of morphological parameters indicated that the host cell surface area at the ring stage in B. microti was significantly smaller (140.2 ± 17.1 µm2) than that in P. falciparum (159.0 ± 15.2 µm2), and sphericities showed higher levels in B. microti-parasitized cells (0.66 ± 0.05) than in P. falciparum (0.60 ± 0.04). Based on biochemical parameters, host cell hemoglobin level was significantly higher and membrane fluctuations were respectively more active in P. falciparum-infected cells (30.25 ± 2.96 pg; 141.3 ± 24.68 nm) than in B. microti (27.28 ± 3.52 pg; 110.1 ± 38.83 nm). The result indicates that P. falciparum more actively altered host RBCs than B. microti.

Conclusion

Although P. falciparum and B. microti often show confusable characteristics under the microscope, and the actual three-dimensional properties are different. These differences could be used in differential clinical diagnosis of erythrocytes infected with B. microti and P. falciparum.

Graphical Abstract

Rapid species identification of pathogenic bacteria from a minute quantity exploiting three-dimensional quantitative phase imaging and artificial neural network

The healthcare industry is in dire need of rapid microbial identification techniques for treating microbial infections. Microbial infections are a major healthcare issue worldwide, as these widespread diseases often develop into deadly symptoms. While studies have shown that an early appropriate antibiotic treatment significantly reduces the mortality of an infection, this effective treatment is difficult to practice. The main obstacle to early appropriate antibiotic treatments is the long turnaround time of the routine microbial identification, which includes time-consuming sample growth. Here, we propose a microscopy-based framework that identifies the pathogen from single to few cells. Our framework obtains and exploits the morphology of the limited sample by incorporating three-dimensional quantitative phase imaging and an artificial neural network. We demonstrate the identification of 19 bacterial species that cause bloodstream infections, achieving an accuracy of 82.5% from an individual bacterial cell or cluster. This performance, comparable to that of the gold standard mass spectroscopy under a sufficient amount of sample, underpins the effectiveness of our framework in clinical applications. Furthermore, our accuracy increases with multiple measurements, reaching 99.9% with seven different measurements of cells or clusters. We believe that our framework can serve as a beneficial advisory tool for clinicians during the initial treatment of infections.

Tomographic measurement of dielectric tensors at optical frequency

The dielectric tensor is a physical descriptor of fundamental light-matter interactions, characterizing anisotropic materials with principal refractive indices and optic axes. Despite its importance in scientific and industrial applications ranging from material science to soft matter physics, the direct measurement of the three-dimensional dielectric tensor has been limited by the vectorial and inhomogeneous nature of light scattering from anisotropic materials. Here, we present a dielectric tensor tomographic approach to directly measure dielectric tensors of anisotropic structures including the spatial variations of principal refractive indices and directors. The anisotropic structure is illuminated with a polarized plane wave with various angles and polarization states. Then, the scattered fields are holographically measured and converted into vectorial diffracted field components. Finally, by inversely solving a vectorial wave equation, the three-dimensional dielectric tensor is reconstructed. Using this approach, we demonstrate quantitative tomographic measurements of various nematic liquid-crystal structures and their fast three-dimensional non-equilibrium dynamics.

Characterizing Organelles in Live Stem Cells Using Label-Free Optical Diffraction Tomography

Label-free optical diffraction tomography (ODT), an imaging technology that does not require fluorescent labeling or other pre-processing, can overcome the limitations of conventional cell imaging technologies, such as fluorescence and electron microscopy. In this study, we used ODT to characterize the cellular organelles of three different stem cells-namely, human liver derived stem cell, human umbilical cord matrix derived mesenchymal stem cell, and human induced pluripotent stem cell-based on their refractive index and volume of organelles. The physical property of each stem cell was compared with that of fibroblast. Based on our findings, the characteristic physical properties of specific stem cells can be quantitatively distinguished based on their refractive index and volume of cellular organelles. Altogether, the method employed herein could aid in the distinction of living stem cells from normal cells without the use of fluorescence or specific biomarkers.

Roadmap on Digital Holography-Based Quantitative Phase Imaging

Quantitative Phase Imaging (QPI) provides unique means for the imaging of biological or technical microstructures, merging beneficial features identified with microscopy, interferometry, holography, and numerical computations. This roadmap article reviews several digital holography-based QPI approaches developed by prominent research groups. It also briefly discusses the present and future perspectives of 2D and 3D QPI research based on digital holographic microscopy, holographic tomography, and their applications.

DeepRegularizer: Rapid Resolution Enhancement of Tomographic Imaging Using Deep Learning

Optical diffraction tomography measures the three-dimensional refractive index map of a specimen and visualizes biochemical phenomena at the nanoscale in a non-destructive manner. One major drawback of optical diffraction tomography is poor axial resolution due to limited access to the three-dimensional optical transfer function. This missing cone problem has been addressed through regularization algorithms that use a priori information, such as non-negativity and sample smoothness. However, the iterative nature of these algorithms and their parameter dependency make real-time visualization impossible. In this article, we propose and experimentally demonstrate a deep neural network, which we term DeepRegularizer, that rapidly improves the resolution of a three-dimensional refractive index map. Trained with pairs of datasets (a raw refractive index tomogram and a resolution-enhanced refractive index tomogram via the iterative total variation algorithm), the three-dimensional U-net-based convolutional neural network learns a transformation between the two tomogram domains. The feasibility and generalizability of our network are demonstrated using bacterial cells and a human leukaemic cell line, and by validating the model across different samples. DeepRegularizer offers more than an order of magnitude faster regularization performance compared to the conventional iterative method. We envision that the proposed data-driven approach can bypass the high time complexity of various image reconstructions in other imaging modalities.

Holographic tomography: techniques and biomedical applications [Invited]

Holographic tomography (HT) is an advanced label-free optical microscopic imaging method used for biological studies. HT uses digital holographic microscopy to record the complex amplitudes of a biological sample as digital holograms and then numerically reconstruct the sample's refractive index (RI) distribution in three dimensions. The RI values are a key parameter for label-free bio-examination, which correlate with metabolic activities and spatiotemporal distribution of biophysical parameters of cells and their internal organelles, tissues, and small-scale biological objects. This article provides insight on this rapidly growing HT field of research and its applications in biology. We present a review summary of the HT principle and highlight recent technical advancement in HT and its applications.

Optimizing sample illumination scanning in transmission tomographic diffractive microscopy

Due to the sequential nature of data acquisition, it is preferable to limit the number of illuminations to be used in tomographic diffractive microscopy experiments, especially if fast imaging is foreseen. On the other hand, for high-quality, high-resolution imaging, the Fourier space has to be optimally filled. Up to now, the problem of optimal Fourier space filling has not been investigated in itself. In this paper, we perform a comparative study to analyze the effect of sample scanning patterns on Fourier space filling for a transmission setup. Optical transfer functions for several illumination patterns are studied. Simulation as well as experiments are conducted to compare associated image reconstructions. We found that 3D uniform angular sweeping best fills the Fourier space, leading to better quality images.

Label-free three-dimensional observations and quantitative characterisation of on-chip vasculogenesis using optical diffraction tomography

Label-free, three-dimensional (3D) quantitative observations of on-chip vasculogenesis were achieved using optical diffraction tomography. Exploiting 3D refractive index maps as an intrinsic imaging contrast, the vascular structures, multicellular activities, and subcellular organelles of endothelial cells were imaged and analysed throughout vasculogenesis to characterise mature vascular networks without exogenous labelling.

Holotomography: Refractive Index as an Intrinsic Imaging Contrast for 3-D Label-Free Live Cell Imaging

Live cell imaging provides essential information in the investigation of cell biology and related pathophysiology. Refractive index (RI) can serve as intrinsic optical imaging contrast for 3-D label-free and quantitative live cell imaging, and provide invaluable information to understand various dynamics of cells and tissues for the study of numerous fields. Recently significant advances have been made in imaging methods and analysis approaches utilizing RI, which are now being transferred to biological and medical research fields, providing novel approaches to investigate the pathophysiology of cells. To provide insight into how RI can be used as an imaging contrast for imaging of biological specimens, here we provide the basic principle of RI-based imaging techniques and summarize recent progress on applications, ranging from microbiology, hematology, infectious diseases, hematology, and histopathology.

Deep-learning-based three-dimensional label-free tracking and analysis of immunological synapses of CAR-T cells

The immunological synapse (IS) is a cell-cell junction between a T cell and a professional antigen-presenting cell. Since the IS formation is a critical step for the initiation of an antigen-specific immune response, various live-cell imaging techniques, most of which rely on fluorescence microscopy, have been used to study the dynamics of IS. However, the inherent limitations associated with the fluorescence-based imaging, such as photo-bleaching and photo-toxicity, prevent the long-term assessment of dynamic changes of IS with high frequency. Here, we propose and experimentally validate a label-free, volumetric, and automated assessment method for IS dynamics using a combinational approach of optical diffraction tomography and deep learning-based segmentation. The proposed method enables an automatic and quantitative spatiotemporal analysis of IS kinetics of morphological and biochemical parameters associated with IS dynamics, providing a new option for immunological research.

Three-dimensional phase optical transfer function in axially symmetric microscopic quantitative phase imaging

Three-dimensional quantitative phase imaging (3D QPI) is widely recognized as a potentially high-impact microscopic modality. Central to determining the resolution capability of 3D QPI is the phase optical transfer function (POTF). The magnitude of the POTF over its spatial frequency coverage (SFC) specifies the intensity of the response for each allowed spatial frequency. In this paper, a detailed analysis of the POTF for an axially symmetric optical configuration is presented. First, a useful geometric interpretation of the SFC, which enables its visualization, is presented. Second, a closed-form 1D integral expression is derived for the POTF in the general nonparaxial case, which enables rapid calculation of the POTF. Third, this formulation is applied to disk, annular, multi-annuli, and Gaussian illuminations as well as to an annular objective. Taken together, these contributions enable the visualization and simplified calculation of the 3D axially symmetric POTF and provide a basis for optimizing QPI in a wide range of applications.

Three-dimensional label-free imaging and quantification of migrating cells during wound healing

The wound-healing assay is a simple but effective tool for studying collective cell migration (CCM) that is widely used in biophysical studies and high-throughput screening. However, conventional imaging and analysis methods only address two-dimensional (2D) properties in a wound healing assay, such as gap closure rate. This is unfortunate because biological cells are complex 3D structures, and their dynamics provide significant information about cell physiology. Here, we presented 3D label-free imaging for wound healing assays and investigated the 3D dynamics of CCM using optical diffraction tomography. High-resolution subcellular structures as well as their collective dynamics were imaged and analyzed quantitatively.

3D morphological and biophysical changes in a single tachyzoite and its infected cells using three-dimensional quantitative phase imaging

Toxoplasma gondii is an apicomplexan parasite that causes toxoplasmosis in the human body and commonly infects warm-blooded organisms. Pathophysiology of its diseases is still an interesting issue to be studied since T gondii can infect nearly all nucleated cells. Imaging techniques are crucial for studying its pathophysiology. In T gondii-infected cells structural and biochemical alterations occurred. To study that modification, we use digital holotomography to investigate the structure and biochemical alteration of single tachyzoite and its infected cells in a label-free and quantitative manner. Quantification analysis was done by measuring the refractive index distribution, which provides information about the concentration and dry mass of individual cells. This study showed that holotomography could be effectively used to identify the structural and biochemical alteration in tremendously different cells in supporting pathophysiological research in particular for T gondii-caused diseases.

Three-dimensional label-free observation of individual bacteria upon antibiotic treatment using optical diffraction tomography

Measuring alterations in bacteria upon antibiotic application is important for basic studies in microbiology, drug discovery, clinical diagnosis, and disease treatment. However, imaging and 3D time-lapse response analysis of individual bacteria upon antibiotic application remain largely unexplored mainly due to limitations in imaging techniques. Here, we present a method to systematically investigate the alterations in individual bacteria in 3D and quantitatively analyze the effects of antibiotics. Using optical diffraction tomography, in-situ responses of Escherichia coli and Bacillus subtilis to various concentrations of ampicillin were investigated in a label-free and quantitative manner. The presented method reconstructs the dynamic changes in the 3D refractive-index distributions of living bacteria in response to antibiotics at sub-micrometer spatial resolution.

3D-printed biological cell phantom for testing 3D quantitative phase imaging systems

As the 3D quantitative phase imaging (QPI) methods mature, their further development calls for reliable tools and methods to characterize and compare their metrological parameters. We use refractive index engineering during two-photon laser photolithography to fabricate a life-scale phantom of a biological cell with internal structures that mimic optical and structural properties of mammalian cells. After verification with a number of reference techniques, the phantom is used to characterize the performance of a limited-angle holographic tomography microscope.

Versatile transmission/reflection tomographic diffractive microscopy approach

Tomographic diffractive microscopy (TDM) has gained interest in recent years due to its ability to deliver high-resolution, three-dimensional images of unlabeled samples. It has been applied to transparent samples in transmission mode, as well as to surface studies in reflection mode. Mudry et al. [Opt. Lett.35, 1857 (2010)OPLEDP0146-959210.1364/OL.35.001857] introduced the concept of mirror-assisted TDM (MA-TDM), an elegant approach for achieving quasi-isotropic-resolution microscopic imaging, but which is still to be experimentally applied. In this work, we show that a simplified version of MA-TDM allows for transforming a reflective TDM setup into a more versatile instrument, also capable of observing transparent samples in transmission mode if using specific sample holders made out of a mirror and coated with a low-thickness transparent spacer.

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.