Roadmap on Digital Holography-Based Quantitative Phase Imaging

Quantitative phase imaging based on holography: trends and new perspectives

In 1948, Dennis Gabor proposed the concept of holography, providing a pioneering solution to a quantitative description of the optical wavefront. After 75 years of development, holographic imaging has become a powerful tool for optical wavefront measurement and quantitative phase imaging. The emergence of this technology has given fresh energy to physics, biology, and materials science. Digital holography (DH) possesses the quantitative advantages of wide-field, non-contact, precise, and dynamic measurement capability for complex-waves. DH has unique capabilities for the propagation of optical fields by measuring light scattering with phase information. It offers quantitative visualization of the refractive index and thickness distribution of weak absorption samples, which plays a vital role in the pathophysiology of various diseases and the characterization of various materials. It provides a possibility to bridge the gap between the imaging and scattering disciplines. The propagation of wavefront is described by the complex amplitude. The complex-value in the complex-domain is reconstructed from the intensity-value measurement by camera in the real-domain. Here, we regard the process of holographic recording and reconstruction as a transformation between complex-domain and real-domain, and discuss the mathematics and physical principles of reconstruction. We review the DH in underlying principles, technical approaches, and the breadth of applications. We conclude with emerging challenges and opportunities based on combining holographic imaging with other methodologies that expand the scope and utility of holographic imaging even further. The multidisciplinary nature brings technology and application experts together in label-free cell biology, analytical chemistry, clinical sciences, wavefront sensing, and semiconductor production.

Viewing early life without labels: optical approaches for imaging the early embryo†

Embryo quality is an important determinant of successful implantation and a resultant live birth. Current clinical approaches for evaluating embryo quality rely on subjective morphology assessments or an invasive biopsy for genetic testing. However, both approaches can be inherently inaccurate and crucially, fail to improve the live birth rate following the transfer of in vitro produced embryos. Optical imaging offers a potential non-invasive and accurate avenue for assessing embryo viability. Recent advances in various label-free optical imaging approaches have garnered increased interest in the field of reproductive biology due to their ability to rapidly capture images at high resolution, delivering both morphological and molecular information. This burgeoning field holds immense potential for further development, with profound implications for clinical translation. Here, our review aims to: (1) describe the principles of various imaging systems, distinguishing between approaches that capture morphological and molecular information, (2) highlight the recent application of these technologies in the field of reproductive biology, and (3) assess their respective merits and limitations concerning the capacity to evaluate embryo quality. Additionally, the review summarizes challenges in the translation of optical imaging systems into routine clinical practice, providing recommendations for their future development. Finally, we identify suitable imaging approaches for interrogating the mechanisms underpinning successful embryo development.

Label-Free Three-Dimensional Morphological Characterization of Cell Death Using Holographic Tomography

This study presents a novel label-free approach for characterizing cell death states, eliminating the need for complex molecular labeling that may yield artificial or ambiguous results due to technical limitations in microscope resolution. The proposed holographic tomography technique offers a label-free avenue for capturing precise three-dimensional (3D) refractive index morphologies of cells and directly analyzing cellular parameters like area, height, volume, and nucleus/cytoplasm ratio within the 3D cellular model. We showcase holographic tomography results illustrating various cell death types and elucidate distinctive refractive index correlations with specific cell morphologies complemented by biochemical assays to verify cell death states. These findings hold promise for advancing in situ single cell state identification and diagnosis applications.

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.

Quantifying the Dynamics of Bacterial Biofilm Formation on the Surface of Soft Contact Lens Materials Using Digital Holographic Tomography to Advance Biofilm Research

The increase in bacterial resistance to antibiotics in recent years demands innovative strategies for the detection and combating of biofilms, which are notoriously resilient. Biofilms, particularly those on contact lenses, can lead to biofilm-related infections (e.g., conjunctivitis and keratitis), posing a significant risk to patients. Non-destructive and non-contact sensing techniques are essential in addressing this threat. Digital holographic tomography emerges as a promising solution. This allows for the 3D reconstruction of the refractive index distribution in biological samples, enabling label-free visualization and the quantitative analysis of biofilms. This tool provides insight into the dynamics of biofilm formation and maturation on the surface of transparent materials. Applying digital holographic tomography for biofilm examination has the potential to advance our ability to combat the antibiotic bacterial resistance crisis. A recent study focused on characterizing biofilm formation and maturation on six soft contact lens materials (three silicone hydrogels, three hydrogels), with a particular emphasis on Staphylococcus epidermis and Pseudomonas aeruginosa, both common culprits in ocular infections. The results revealed species- and time-dependent variations in the refractive indexes and volumes of biofilms, shedding light on cell dynamics, cell death, and contact lens material-related factors. The use of digital holographic tomography enables the quantitative analysis of biofilm dynamics, providing us with a better understanding and characterization of bacterial biofilms.

Quality improvement to holographic microscopy reconstruction based on Kramers-Kronig relations and phase background fitting

Spectrum aliasing in off-axis digital holography may result in poor image reconstruction quality. This study proposes a method to eliminate the zero-order spectrum and enhance image quality based on Kramers-Kronig relations and phase background fitting. The Kramers-Kronig relations are employed to derive the quotient of the complex wavefront of object and the reference beam, and phase background fitting is performed in a compensatory way to yield the object complex wavefront. The effectiveness of the proposed approach is validated via simulations and experiments. The results show significantly improved off-axis digital holographic microscopy reconstruction quality, making the proposed method a promising option for holographic microscopy imaging.

High-resolution assessment of multidimensional cellular mechanics using label-free refractive-index traction force microscopy

A critical requirement for studying cell mechanics is three-dimensional assessment of cellular shapes and forces with high spatiotemporal resolution. Traction force microscopy with fluorescence imaging enables the measurement of cellular forces, but it is limited by photobleaching and a slow acquisition speed. Here, we present refractive-index traction force microscopy (RI-TFM), which simultaneously quantifies the volumetric morphology and traction force of cells using a high-speed illumination scheme with 0.5-Hz temporal resolution. Without labelling, our method enables quantitative analyses of dry-mass distributions and shear (in-plane) and normal (out-of-plane) tractions of single cells on the extracellular matrix. When combined with a constrained total variation-based deconvolution algorithm, it provides 0.55-Pa shear and 1.59-Pa normal traction sensitivity for a 1-kPa hydrogel substrate. We demonstrate its utility by assessing the effects of compromised intracellular stress and capturing the rapid dynamics of cellular junction formation in the spatiotemporal changes in non-planar traction components.

Simple high-resolution 3D microscopy by a dielectric microsphere: a proof of concept

We present a simple high-resolution approach for 3D and quantitative phase imaging (QPI). Our method makes the most of a glass microsphere (MS) for microscopy and a glass plate for lateral shearing self-referencing interferometry. The single MS serves all the functions of a microscope objective (MO) in digital holographic microscopy (DHM) while offering the advantages of compactness, lightness, and affordability. A proof-of-concept experiment is performed on a standard diffraction grating, and various effective parameters on the imaging performance are investigated. The results are validated by atomic force microscopy and Mirau-DHM, and 3D morphometric information of the sample under inspection is obtained. The technique is then applied for 3D quantitative measurement and visualization of a human red blood cell, proving the principle of our easy-to-implement and vibration-immune arrangement for high-contrast label-free QPI of biological samples, and its utility in cell morphology, identification, and classification.

How is Big Data reshaping preclinical aging research?

The exponential scientific and technological progress during the past 30 years has favored the comprehensive characterization of aging processes with their multivariate nature, leading to the advent of Big Data in preclinical aging research. Spanning from molecular omics to organism-level deep phenotyping, Big Data demands large computational resources for storage and analysis, as well as new analytical tools and conceptual frameworks to gain novel insights leading to discovery. Systems biology has emerged as a paradigm that utilizes Big Data to gain insightful information enabling a better understanding of living organisms, visualized as multilayered networks of interacting molecules, cells, tissues and organs at different spatiotemporal scales. In this framework, where aging, health and disease represent emergent states from an evolving dynamic complex system, context given by, for example, strain, sex and feeding times, becomes paramount for defining the biological trajectory of an organism. Using bioinformatics and artificial intelligence, the systems biology approach is leading to remarkable advances in our understanding of the underlying mechanism of aging biology and assisting in creative experimental study designs in animal models. Future in-depth knowledge acquisition will depend on the ability to fully integrate information from different spatiotemporal scales in organisms, which will probably require the adoption of theories and methods from the field of complex systems. Here we review state-of-the-art approaches in preclinical research, with a focus on rodent models, that are leading to conceptual and/or technical advances in leveraging Big Data to understand basic aging biology and its full translational potential.

Investigation of refractive index dynamics during in vitro embryo development using off-axis digital holographic microscopy

Embryo quality is a crucial factor affecting live birth outcomes. However, an accurate diagnostic for embryo quality remains elusive in the in vitro fertilization clinic. Determining physical parameters of the embryo may offer key information for this purpose. Here, we demonstrate that digital holographic microscopy (DHM) can rapidly and non-invasively assess the refractive index of mouse embryos. Murine embryos were cultured in either low- or high-lipid containing media and digital holograms recorded at various stages of development. The phase of the recorded hologram was numerically retrieved, from which the refractive index of the embryo was calculated. We showed that DHM can detect spatio-temporal changes in refractive index during embryo development that are reflective of its lipid content. As accumulation of intracellular lipid is known to compromise embryo health, DHM may prove beneficial in developing an accurate, non-invasive, multimodal diagnostic.

Structured illumination phase and fluorescence microscopy for bioimaging

This study presents a dual-modality microscopic imaging approach that combines quantitative phase microscopy and fluorescence microscopy based on structured illumination (SI) to provide structural and functional information for the same sample. As the first imaging modality, structured illumination digital holographic microscopy (SI-DHM) is implemented along the transmission beam path. SI-DHM acts as a label-free, noninvasive approach and provides high-contrast and quantitative phase images utilizing the refractive index contrast of the inner structures of samples against the background. As the second imaging modality, structured illumination (fluorescence) microscopy (SIM) is constructed along the reflection beam path. SIM utilizes fluorescent labeling and provides super-resolution images for specific functional structures of samples. We first experimentally demonstrated phase imaging of SI-DHM on rice leaves and fluorescence (SIM) imaging on mouse kidney sections. Then, we demonstrated dual-modality imaging of biological samples, using DHM to acquire the overall cell morphology and SIM to obtain specific functional structures. These results prove that the proposed technique is of great importance in biomedical studies, such as providing insight into cell physiology by visualizing and quantifying subcellular structures.

Automated Dual-Mode Cell Monitoring To Simultaneously Explore Calcium Dynamics and Contraction-Relaxation Kinetics within Drug-Treated Stem Cell-Derived Cardiomyocytes

This manuscript proposes a new dual-mode cell imaging system for studying the relationships between calcium dynamics and the contractility process of cardiomyocytes derived from human-induced pluripotent stem cells. Practically, this dual-mode cell imaging system provides simultaneously both live cell calcium imaging and quantitative phase imaging based on digital holographic microscopy. Specifically, thanks to the development of a robust automated image analysis, simultaneous measurements of both intracellular calcium, a key player of excitation-contraction coupling, and the quantitative phase image-derived dry mass redistribution, reflecting the effective contractility, namely, the contraction and relaxation processes, were achieved. Practically, the relationships between calcium dynamics and the contraction-relaxation kinetics were investigated in particular through the application of two drugs─namely, isoprenaline and E-4031─known to act precisely on calcium dynamics. Specifically, this new dual-mode cell imaging system enabled us to establish that calcium regulation can be divided into two phases, an early phase influencing the occurrence of the relaxation process followed by a late phase, which although not having a significant influence on the relaxation process affects significantly the beat frequency. In combination with cutting-edge technologies allowing the generation of human stem cell-derived cardiomyocytes, this dual-mode cell monitoring approach therefore represents a very promising technique, particularly in the fields of drug discovery and personalized medicine, to identify compounds likely to act more selectively on specific steps that compose the cardiomyocyte contractility.

Phase unwrapping using deep learning in holographic tomography

Holographic tomography (HT) is a measurement technique that generates phase images, often containing high noise levels and irregularities. Due to the nature of phase retrieval algorithms within the HT data processing, the phase has to be unwrapped before tomographic reconstruction. Conventional algorithms lack noise robustness, reliability, speed, and possible automation. In order to address these problems, this work proposes a convolutional neural network based pipeline consisting of two steps: denoising and unwrapping. Both steps are carried out under the umbrella of a U-Net architecture; however, unwrapping is aided by introducing Attention Gates (AG) and Residual Blocks (RB) to the architecture. Through the experiments, the proposed pipeline makes possible the phase unwrapping of highly irregular, noisy, and complex experimental phase images captured in HT. This work proposes phase unwrapping carried out by segmentation with a U-Net network, that is aided by a pre-processing denoising step. It also discusses the implementation of the AGs and RBs in an ablation study. What is more, this is the first deep learning based solution that is trained solely on real images acquired with HT.

Quantitative Phase Imaging: Recent Advances and Expanding Potential in Biomedicine

Quantitative phase imaging (QPI) is a label-free, wide-field microscopy approach with significant opportunities for biomedical applications. QPI uses the natural phase shift of light as it passes through a transparent object, such as a mammalian cell, to quantify biomass distribution and spatial and temporal changes in biomass. Reported in cell studies more than 60 years ago, ongoing advances in QPI hardware and software are leading to numerous applications in biology, with a dramatic expansion in utility over the past two decades. Today, investigations of cell size, morphology, behavior, cellular viscoelasticity, drug efficacy, biomass accumulation and turnover, and transport mechanics are supporting studies of development, physiology, neural activity, cancer, and additional physiological processes and diseases. Here, we review the field of QPI in biology starting with underlying principles, followed by a discussion of technical approaches currently available or being developed, and end with an examination of the breadth of applications in use or under development. We comment on strengths and shortcomings for the deployment of QPI in key biomedical contexts and conclude with emerging challenges and opportunities based on combining QPI with other methodologies that expand the scope and utility of QPI even further.

Real-Time Phase Retrieval Based on Cube-Corner Prisms Single Exposure

The phase retrieval method based on the Transport of Intensity Equation needs to record the light intensity information on two or more planes perpendicular to the optical axis propagating along the optical axis. Usually, a single CCD camera is moved back and forth for recording, which not only brings the corresponding mechanical errors, but also has a certain time difference between the collected intensity images, which cannot meet the real-time requirements. In this paper, a single phase retrieval technique based on cube-corner prisms is proposed. This method can simultaneously collect the required initial intensity image in a single exposure, and then calculate the phase after registration and repair, so as to obtain high-precision results. According to the parallel reflection characteristics of the cube-corner prisms, the experimental system designed correspondingly can not only stagger the two beams separated by the beam splitter, but also ensure that the upper and lower propagation distances of a single beam are equal. Finally, the accuracy and effectiveness of the proposed method are fully verified by simulation experiments and experimental measurements.

A Tribute to Sergey Odinokov

“My main goal was to point out new phenomena and spread the ideas, which will become the starting points for new research” (Nikola Tesla) [...]

Single-Shot On-Axis Fizeau Polarization Phase-Shifting Digital Holography for Complex-Valued Dynamic Object Imaging

Digital holography assisted with inline phase-shifting methods has the benefit of a large field of view and a high resolution, but it is limited in dynamic imaging due to sequential detection of multiple holograms. Here we propose and experimentally demonstrate a single-shot phase-shifting digital holography system based on a highly stable on-axis Fizeau-type polarization interferometry. The compact on-axis design of the system with the capability of instantaneous recording of multiple phase-shifted holograms and with robust stability features makes the technique a novel tool for the imaging of complex-valued dynamic objects. The efficacy of the approach is demonstrated experimentally by complex field imaging of various kinds of reflecting-type static and dynamic objects. Moreover, a quantitative analysis on the robust phase stability and sensitivity of the technique is evaluated by comparing the approach with conventional phase-shifting methods. The high phase stability and dynamic imaging potential of the technique are expected to make the system an ideal tool for quantitative phase imaging and real-time imaging of dynamic samples.

Automatic Detection of Age-Related Macular Degeneration Based on Deep Learning and Local Outlier Factor Algorithm

Age-related macular degeneration (AMD) is a retinal disorder affecting the elderly, and society’s aging population means that the disease is becoming increasingly prevalent. The vision in patients with early AMD is usually unaffected or nearly normal but central vision may be weakened or even lost if timely treatment is not performed. Therefore, early diagnosis is particularly important to prevent the further exacerbation of AMD. This paper proposed a novel automatic detection method of AMD from optical coherence tomography (OCT) images based on deep learning and a local outlier factor (LOF) algorithm. A ResNet-50 model with L2-constrained softmax loss was retrained to extract features from OCT images and the LOF algorithm was used as the classifier. The proposed method was trained on the UCSD dataset and tested on both the UCSD dataset and Duke dataset, with an accuracy of 99.87% and 97.56%, respectively. Even though the model was only trained on the UCSD dataset, it obtained good detection accuracy when tested on another dataset. Comparison with other methods also indicates the efficiency of the proposed method in detecting AMD.

Linearity and Optimum-Sampling in Photon-Counting Digital Holographic Microscopy

In the image plane configurations frequently used in digital holographic microscopy (DHM) systems, interference patterns are captured by a photo-sensitive array detector located at the image plane of an input object. The object information in these patterns is localized and thus extremely sensitive to phase errors caused by nonlinear hologram recordings (grating profiles are either square or saturated sinusoidal) or inadequate sampling regarding the information coverage (undersampled around the Nyquist frequency or arbitrarily oversampled). Here, we propose a solution for both hologram recording problems through implementing a photon-counting detector (PCD) mounted on a motorized XY translation stage. In such a way, inherently linear (because of a wide dynamic range of PCD) and optimum sampled (due to adjustable steps) digital holograms in the image plane configuration are recorded. Optimum sampling is estimated based on numerical analysis. The validity of the proposed approach is confirmed experimentally.