Artificial intelligence-enabled quantitative phase imaging methods for life sciences.

Quantitative phase imaging, integrated with artificial intelligence, allows for the rapid and label-free investigation of the physiology and pathology of biological systems. This review presents the principles of various two-dimensional and three-dimensional label-free phase imaging techniques that exploit refractive index as an intrinsic optical imaging contrast. In particular, we discuss artificial intelligence-based analysis methodologies for biomedical studies including image enhancement, segmentation of cellular or subcellular structures, classification of types of biological samples and image translation to furnish subcellular and histochemical information from label-free phase images. We also discuss the advantages and challenges of artificial intelligence-enabled quantitative phase imaging analyses, summarize recent notable applications in the life sciences, and cover the potential of this field for basic and industrial research in the life sciences.

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.

Three-dimensional label-free visualization and quantification of polyhydroxyalkanoates in individual bacterial cell in its native state.

Polyhydroxyalkanoates (PHAs) are biodegradable polyesters that are intracellularly accumulated as distinct insoluble granules by various microorganisms. PHAs have attracted much attention as sustainable substitutes for petroleum-based plastics. However, the formation of PHA granules and their characteristics, such as localization, volume, weight, and density of granules, in an individual live bacterial cell are not well understood. Here, we report the results of three-dimensional (3D) quantitative label-free analysis of PHA granules in individual live bacterial cells through measuring the refractive index distributions by optical diffraction tomography (ODT). The formation and growth of PHA granules in the cells of Cupriavidus necator, the best-studied native PHA producer, and recombinant Escherichia coli harboring C. necator poly(3-hydroxybutyrate) (PHB) biosynthesis pathway are comparatively examined. Through the statistical ODT analyses of the bacterial cells, the distinctive characteristics for density and localization of PHB granules in vivo could be observed. The PHB granules in recombinant E. coli show higher density and localization polarity compared with those of C. necator, indicating that polymer chains are more densely packed and granules tend to be located at the cell poles, respectively. The cells were investigated in more detail through real-time 3D analyses, showing how differently PHA granules are processed in relation to the cell division process in native and nonnative PHA-producing strains. We also show that PHA granule-associated protein PhaM of C. necator plays a key role in making these differences between C. necator and recombinant E. coli strains. This study provides spatiotemporal insights into PHA accumulation inside the native and recombinant bacterial cells.

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.

Regularization of dielectric tensor tomography.

Dielectric tensor tomography reconstructs the three-dimensional dielectric tensors of microscopic objects and provides information about the crystalline structure orientations and principal refractive indices. Because dielectric tensor tomography is based on transmission measurement, it suffers from the missing cone problem, which causes poor axial resolution, underestimation of the refractive index, and halo artifacts. In this study, we study the application of total variation and positive semi-definiteness regularization to three-dimensional tensor distributions. In particular, we demonstrate the reduction of artifacts when applied to dielectric tensor tomography.

Vectorial inverse scattering for dielectric tensor tomography: overcoming challenges of reconstruction of highly scattering birefringent samples.

Many important microscopy samples, such as liquid crystals, biological tissue, or starches, are birefringent in nature. They scatter light differently depending on the polarization of the light and the orientation of the molecules. The complete characterization of a birefringent sample is a challenging task because its 3 × 3 dielectric tensor must be reconstructed at every three-dimensional position. Moreover, obtaining a birefringent tomogram is more arduous for thick samples, where multiple light scattering should also be considered. In this study, we developed a new dielectric tensor tomography algorithm that enables full characterization of highly scattering birefringent samples by solving the vectoral inverse scattering problem while accounting for multiple light scattering. We proposed a discrete image-processing theory to compute the error backpropagation of vectorially diffracting light. Finally, our theory was experimentally demonstrated using both synthetic and biologically birefringent samples.

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.

Wide-Field Super-Resolution Optical Fluctuation Imaging through Dynamic Near-Field Speckle Illumination.

Stochastic optical fluctuation imaging (SOFI) generates super-resolution fluorescence images by emphasizing the positions of fluorescent emitters via statistical analysis of their on-and-off blinking dynamics. In SOFI with speckle illumination (S-SOFI), the diffraction-limited grain size of the far-field speckles prevents independent blinking of closely located emitters, becoming a hurdle to realize the full super-resolution granted by SOFI processing. Here, we present a surface-sensitive super-resolution technique exploiting dynamic near-field speckle illumination to bring forth the full super-resolving power of SOFI without blinking fluorophores. With our near-field S-SOFI technique, up to 2.8- and 2.3-fold enhancements in lateral spatial resolution are demonstrated with computational and experimental fluorescent test targets labeled with conventional fluorophores, respectively. Fluorescent beads separated by 175 nm are also super-resolved by near-field speckles of 150 nm grain size, promising sub-100 nm resolution with speckle patterns of much smaller grain size.

Non-resonant lasing in a deep-hole scattering cavity.

Random lasers are promising in the spectral regime, wherein conventional lasers are unavailable, with advantages of low fabrication costs and applicability of diverse gain materials. However, their practical application is hindered by high threshold powers, low power efficiency, and difficulties in light collection. Here, we demonstrate a power-efficient easy-to-fabricate non-resonant laser using a deep hole on a porous gain material. The laser action in this counterintuitive cavity was enabled by non-resonant feedback from strong diffuse reflections on the inner surface. Additionally, significant enhancements in slope efficiency, threshold power, and directionality were obtained from cavities fabricated on a porous Nd:YAG ceramic.

Spatially multiplexed dielectric tensor tomography.

Dielectric tensor tomography (DTT) enables the reconstruction of three-dimensional (3D) dielectric tensors, which provides a physical measure of 3D optical anisotropy. Herein, we present a cost-effective and robust method of DTT using spatial multiplexing. Exploiting two orthogonally polarized reference beams with different angles in an off-axis interferometer, two polarization-sensitive interferograms were multiplexed and recorded using a single camera. Then, the two interferograms were demultiplexed in the Fourier domain. By measuring the polarization-sensitive fields for various illumination angles, 3D dielectric tensor tomograms were reconstructed. The proposed method was experimentally demonstrated by reconstructing the 3D dielectric tensors of various liquid-crystal (LC) particles with radial and bipolar orientational configurations.

Single-shot wide-field topography measurement using spectrally multiplexed reflection intensity holography via space-domain Kramers-Kronig relations.

Surface topology measurements of micro- or nanostructures are essential for both scientific and industrial applications. However, high-throughput measurements remain challenging in surface metrology. We present single-shot full-field surface topography measurement using Kramers-Kronig holographic imaging and spectral multiplexing. Three different intensity images at different incident angles were simultaneously measured with three different colors, from which a quantitative phase image was retrieved using spatial Kramers-Kronig relations. A high-resolution topographic image of the sample was then reconstructed using synthetic aperture holography. Various patterned structures at the nanometer scale were measured and cross-validated using atomic force microscopy.

A One-Stage Ensemble Framework Based on Convolutional Autoencoder for Remaining Useful Life Estimation.

As the legislative pressure to reduce energy consumption is increasing, data analysis of power consumption is critical in the production planning of manufacturing facilities. In legacy studies, a machine conducting a single continuous operation has been mainly observed for power estimation. However, the production machine of a modularized line, which conducts complex discrete operations, is more like the actual factory system than an identical simple machine. During the information collection of this kind of production line, it is important to interpret mixed signals from multiple machines to ensure that there is no reduction in the information quality due to noise and signal fusion and discrete events. A data pipeline-from data collection (from different sources) to preprocessing, data conversion, synchronization, and deep learning classification-to estimate the total power use of the future process plan, is proposed herein. The pipeline also establishes an auto-labeled data set of individual operations that contributes to building an power estimation model without manual data preprocessing. The proposed system is applied to a modular factory, connected with machine controllers, using standardized protocols individually and linked to a centralized power monitoring system. Specifically, a robot arm cell was investigated to evaluate the pipeline, with the result of the power profile being synchronized with the robot program.

Alpha-Lipoic Acid Attenuates Apoptosis and Ferroptosis in Cisplatin-Induced Ototoxicity via the Reduction of Intracellular Lipid Droplets.

Alpha-lipoic acid (α-LA) is a potent antioxidant that can prevent apoptosis associated with cisplatin-induced ototoxicity through ROS. Ferroptosis is defined as an iron-dependent cell death pathway that has recently been highlighted and is associated with the accumulation of intracellular lipid droplets (LDs) due to an inflammatory process. Herein, we investigated the impact of α-LA on ferroptosis and analyzed the characteristics of LDs in auditory hair cells treated with cisplatin using high-resolution 3D quantitative-phase imaging with reconstruction of the refractive index (RI) distribution. HEI-OC1 cells were treated with 500 µM α-LA for 24 h and then with 15 µM cisplatin for 48 h. With 3D optical diffraction tomography (3D-ODT), the RI values of treated cells were analyzed. Regions with high RI values were considered to be LDs and labelled to measure the count, mass, and volume of LDs. The expression of LC3-B, P62, GPX4, 4-hydroxynonenal (4-HNE), and xCT was evaluated by Western blotting. HEI-OC1 cells damaged by cisplatin showed lipid peroxidation, depletion of xCT, and abnormal accumulation of 4-HNE. Additionally, the count, mass, and volume of LDs increased in the cells. Cells treated with α-LA had inhibited expression of 4-HNE, while the expression of xCT and GPX4 was recovered, which restored LDs to a level that was similar to that in the control group. Our research on LDs with 3D-ODT offers biological evidence of ferroptosis and provides insights on additional approaches for investigating the molecular pathways.

Interactions of Nanoparticles with Macrophages and Feasibility of Drug Delivery for Asthma.

Understanding the interaction between nanoparticles and immune cells is essential for the evaluation of nanotoxicity and development of nanomedicines. However, to date, there is little data on the membrane microstructure and biochemical changes in nanoparticle-loaded immune cells. In this study, we observed the microstructure of nanoparticle-loaded macrophages and changes in lipid droplets using holotomography analysis. Quantitatively analyzing the refractive index distribution of nanoparticle-loaded macrophages, we identified the interactions between nanoparticles and macrophages. The results showed that, when nanoparticles were phagocytized by macrophages, the number of lipid droplets and cell volume increased. The volume and mass of the lipid droplets slightly increased, owing to the absorption of nanoparticles. Meanwhile, the number of lipid droplets increased more conspicuously than the other factors. Furthermore, alveolar macrophages are involved in the development and progression of asthma. Studies have shown that macrophages play an essential role in the maintenance of asthma-related inflammation and tissue damage, suggesting that macrophage cells may be applied to asthma target delivery strategies. Therefore, we investigated the target delivery efficiency of gold nanoparticle-loaded macrophages at the biodistribution level, using an ovalbumin-induced asthma mouse model. Normal and severe asthma models were selected to determine the difference in the level of inflammation in the lung. Consequently, macrophages had increased mobility in models of severe asthma, compared to those of normal asthma disease. In this regard, the detection of observable differences in nanoparticle-loaded macrophages may be of primary interest, as an essential endpoint analysis for investigating nanomedical applications and immunotheragnostic strategies.

Optimizing illumination in three-dimensional deconvolution microscopy for accurate refractive index tomography.

In light transmission microscopy, axial scanning does not directly provide tomographic reconstruction of specimen. Phase deconvolution microscopy can convert a raw intensity image stack into a refractive index tomogram, the intrinsic sample contrast which can be exploited for quantitative morphological analysis. However, this technique is limited by reconstruction artifacts due to unoptimized optical conditions, which leads to a sparse and non-uniform optical transfer function. Here, we propose an optimization method based on simulated annealing to systematically obtain optimal illumination schemes that enable artifact-free deconvolution. The proposed method showed precise tomographic reconstruction of unlabeled biological samples.

Pupil-aberration calibration with controlled illumination for quantitative phase imaging.

Quantitative phase imaging (QPI) exploits sample-induced changes in the optical field to analyze biological specimens in a label-free manner. However, the quantitative nature of QPI makes it susceptible to optical aberrations. We propose a method for calibrating pupil aberrations by imaging a sample of interest. The proposed method recovers pupil information by utilizing the cross-spectral density between optical fields at different incident angles and allows both thin and weakly scattering three-dimensional samples for calibration. We experimentally validate the proposed method by imaging various samples, including a resolution target, breast tissue, and a polystyrene bead, and demonstrate aberration-free two- and three-dimensional QPI.

Roadmap on digital holography [Invited].

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

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.

Secondarily estimated cure fraction and five-year recurrence-free conditional survival probabilities among patients undergoing surgical resection for hepatocellular carcinoma presenting with minor gross vascular invasion.

BACKGROUND: Surgical resection (SR) has been selectively applied in hepatocellular carcinoma (HCC) presenting with minor gross vascular invasion (mGVI) which is defined when tumor invasion is confined to second-order portal branches or segmental branches of hepatic vein. However, little data of long-term outcomes are available for supporting the role of SR as a potentially curable therapeutic option for HCC presenting with mGVI. This study is aimed to estimate a statistical cure fraction and the improvement of recurrence-free conditional survival (RFCS) over time among patients undergoing SR for HCC presenting with mGVI. METHODS: The literature search was conducted focusing on previous studies that investigated the long-term survival rates of patients after SR for HCC presenting with mGVI. The reference cohort was extracted from a study including patients undergoing SR for HCC without vascular invasion. A non-mixture cure model was adopted to estimate the statistical cure fraction. The 5-year RFCS probabilities were also calculated. RESULTS: Three retrospective studies were secondarily analyzed. The probability of being statistically cured after SR for HCC presenting with mGVI was 7.3% (95% confidence interval, 4.4%-11.2%) in the mGVI group, lower than that of the reference cohort (hazard ratio, 1.81; 95% confidence interval, 1.59-2.05). The estimated 5-year RFCS probabilities improved with each additional year of survival. Moreover, 1 year after SR, the 5-year RFCS probabilities of patients with HCC presenting with mGVI was essentially the same as that of the reference cohort. CONCLUSIONS: This study shows that a cure can be expected in around seven percent of patients undergoing SR for HCC presenting with mGVI. Furthermore, recurrence-free survival expectancy improves dramatically over time among those patients who do not have recurrence. Overall, these findings suggest that SR should be considered as a potentially curable treatment for patients with HCC presenting with mGVI.

Low-coherence optical diffraction tomography using a ferroelectric liquid crystal spatial light modulator.

Optical diffraction tomography (ODT) is a three-dimensional (3D) label-free imaging technique. The 3D refractive index distribution of a sample can be reconstructed from multiple two-dimensional optical field images via ODT. Herein, we introduce a temporally low-coherence ODT technique using a ferroelectric liquid crystal spatial light modulator (FLC SLM). The fast binary-phase modulation provided by the FLC SLM ensures the high spatiotemporal resolution. To reduce coherent noise, a superluminescent light-emitting diode is used as an economic low-coherence light source. We demonstrate the performance of the proposed system using various samples, including colloidal microspheres and live epithelial cells.