Diabetes screening by telecentric digital holographic microscopy

Off-axis digital lensless holographic microscopy based on spatially multiplexed interferometry

Significance

Digital holographic microscopy (DHM) is a label-free microscopy technique that provides time-resolved quantitative phase imaging (QPI) by measuring the optical path delay of light induced by transparent biological samples. DHM has been utilized for various biomedical applications, such as cancer research and sperm cell assessment, as well as for in vitro drug or toxicity testing. Its lensless version, digital lensless holographic microscopy (DLHM), is an emerging technology that offers size-reduced, lightweight, and cost-effective imaging systems. These features make DLHM applicable, for example, in limited resource laboratories, remote areas, and point-of-care applications.

Aim

In addition to the abovementioned advantages, in-line arrangements for DLHM also include the limitation of the twin-image presence, which can restrict accurate QPI. We therefore propose a compact lensless common-path interferometric off-axis approach that is capable of quantitative imaging of fast-moving biological specimens, such as living cells in flow.

Approach

We suggest lensless spatially multiplexed interferometric microscopy (LESSMIM) as a lens-free variant of the previously reported spatially multiplexed interferometric microscopy (SMIM) concept. LESSMIM comprises a common-path interferometric architecture that is based on a single diffraction grating to achieve digital off-axis holography. From a series of single-shot off-axis holograms, twin-image free and time-resolved QPI is achieved by commonly used methods for Fourier filtering-based reconstruction, aberration compensation, and numerical propagation.

Results

Initially, the LESSMIM concept is experimentally demonstrated by results from a resolution test chart and investigations on temporal stability. Then, the accuracy of QPI and capabilities for imaging of living adherent cell cultures is characterized. Finally, utilizing a microfluidic channel, the cytometry of suspended cells in flow is evaluated.

Conclusions

LESSMIM overcomes several limitations of in-line DLHM and provides fast time-resolved QPI in a compact optical arrangement. In summary, LESSMIM represents a promising technique with potential biomedical applications for fast imaging such as in imaging flow cytometry or sperm cell analysis.

Investigation on lysosomal accumulation by a quantitative analysis of 2D phase-maps in digital holography microscopy

Lysosomes are the terminal end of catabolic pathways in the cell, as well as signaling centers performing important functions such as the recycling of macromolecules, organelles, and nutrient adaptation. The importance of lysosomes in human health is supported by the fact that the deficiency of most lysosomal genes causes monogenic diseases called as a group Lysosomal Storage Diseases (LSDs). A common phenotypic hallmark of LSDs is the expansion of the lysosomal compartment that can be detected by using conventional imaging methods based on immunofluorescence protocols or overexpression of tagged lysosomal proteins. These methods require the alteration of the cellular architecture (i.e., due to fixation methods), can alter the behavior of cells (i.e., by the overexpression of proteins), and require sample preparation and the accurate selection of compatible fluorescent markers in relation to the type of analysis, therefore limiting the possibility of characterizing cellular status with simplicity. Therefore, a quantitative and label-free methodology, such as Quantitative Phase Imaging through Digital Holographic (QPI-DH), for the microscopic imaging of lysosomes in health and disease conditions may represent an important advance to study and effectively diagnose the presence of lysosomal storage in human disease. Here we proof the effectiveness of the QPI-DH method in accomplishing the detection of the lysosomal compartment using mouse embryonic fibroblasts (MEFs) derived from a Mucopolysaccharidosis type III-A (MSP-IIIA) mouse model, and comparing them with wild-type (WT) MEFs. We found that it is possible to identify label-free biomarkers able to supply a first pre-screening of the two populations, thus showing that QPI-DH can be a suitable candidate to surpass fluorescent drawbacks in the detection of lysosomes dysfunction. An appropriate numerical procedure was developed for detecting and evaluate such cellular substructures from in vitro cells cultures. Results reported in this study are encouraging about the further development of the proposed QPI-DH approach for such type of investigations about LSDs.

P-TDHM: Open-source portable telecentric digital holographic microscope

We present the design of a low-cost, portable telecentric digital holographic microscope (P-TDHM) that utilizes off-the-shelf components. We describe the system's hardware and software elements and evaluate its performance by imaging samples ranging from nano-printed targets to live HeLa cells, HEK293 cells, and Dolichospermum via both in-line and off-axis modes. Our results demonstrate that the system can acquire high quality quantitative phase images with nanometer axial and sub-micron lateral resolution in a small form factor, making it a promising candidate for resource-limited settings and remote locations. Our design represents a significant step forward in making telecentric digital holographic microscopy accessible and affordable to the broader community.

pyDHM: A Python library for applications in digital holographic microscopy

pyDHM is an open-source Python library aimed at Digital Holographic Microscopy (DHM) applications. The pyDHM is a user-friendly library written in the robust programming language of Python that provides a set of numerical processing algorithms for reconstructing amplitude and phase images for a broad range of optical DHM configurations. The pyDHM implements phase-shifting approaches for in-line and slightly off-axis systems and enables phase compensation for telecentric and non-telecentric systems. In addition, pyDHM includes three propagation algorithms for numerical focusing complex amplitude distributions in DHM and digital holography (DH) setups. We have validated the library using numerical and experimental holograms.

COVID-19 screening with digital holographic microscopy using intra-patient probability functions of spatio-temporal bio-optical attributes

We present an automated method for COVID-19 screening using the intra-patient population distributions of bio-optical attributes extracted from digital holographic microscopy reconstructed red blood cells. Whereas previous approaches have aimed to identify infection by classifying individual cells, here, we propose an approach to incorporate the attribute distribution information from the population of a given human subjects' cells into our classification scheme and directly classify subjects at the patient level. To capture the intra-patient distribution information in a generalized way, we propose an approach based on the Bag-of-Features (BoF) methodology to transform histograms of bio-optical attribute distributions into feature vectors for classification via a linear support vector machine. We compare our approach with simpler classifiers directly using summary statistics such as mean, standard deviation, skewness, and kurtosis of the distributions. We also compare to a k-nearest neighbor classifier using the Kolmogorov-Smirnov distance as a distance metric between the attribute distributions of each subject. We lastly compare our approach to previously published methods for classification of individual red blood cells. In each case, the methodology proposed in this paper provides the highest patient classification performance, correctly classifying 22 out of 24 individuals and achieving 91.67% classification accuracy with 90.00% sensitivity and 92.86% specificity. The incorporation of distribution information for classification additionally led to the identification of a singular temporal-based bio-optical attribute capable of highly accurate patient classification. To the best of our knowledge, this is the first report of a machine learning approach using the intra-patient probability distribution information of bio-optical attributes obtained from digital holographic microscopy for disease screening.

An Efficient Method of Observing Diatom Frustules via Digital Holographic Microscopy

Herein, we propose a convenient method to enable pretreatment of target objects using digital holographic microscopy (DHM). As a test sample, we used diatom frustules (Nitzschia sp.) as the target objects. In the generally used sample preparation method, the frustule suspension is added dropwise onto a glass substrate or into a glass chamber. While our work confirms good observation of purified frustules using the typical sample preparation method, we also demonstrate a new procedure to observe unseparated structures of frustules prepared by baking them on a mica surface. The baked frustules on the mica surface were transferred to a glass chamber with 1% sodium dodecyl sulfate solution. In this manner, the unseparated structures of the diatom frustules were clearly observed. Furthermore, metal-coated frustules prepared by sputtering onto them on a mica surface were also clearly observed using the same procedure. Our method can be applied for the observation of any target object that is pretreated on a solid surface. We expect our proposed method to be a basis for establishing DHM techniques for microscopic observations of biomaterials.

Single-Shot 3D Topography of Transmissive and Reflective Samples with a Dual-Mode Telecentric-Based Digital Holographic Microscope

Common path DHM systems are the most robust DHM systems as they are based on self-interference and are thus less prone to external fluctuations. A common issue amongst these DHM systems is that the two replicas of the sample’s information overlay due to self-interference, making them only suitable for imaging sparse samples. This overlay has restricted the use of common-path DHM systems in material science. The overlay can be overcome by limiting the sample’s field of view to occupy only half of the imaging field of view or by using an optical spatial filter. In this work, we have implemented optical spatial filtering in a common-path DHM system using a Fresnel biprism. We have analyzed the optimal pinhole size by evaluating the frequency content of the reconstructed phase images of a star target. We have also measured the accuracy of the system and the sensitivity to noise for different pinhole sizes. Finally, we have proposed the first dual-mode common-path DHM system using a Fresnel biprism. The performance of the dual-model DHM system has been evaluated experimentally using transmissive and reflective microscopic samples.

Investigating Morphological Changes of T-lymphocytes after Exposure with Bacterial Determinants for Early Detection of Septic Conditions

Sepsis is a leading cause of morbidity and mortality, annually affecting millions of people worldwide. Immediate treatment initiation is crucial to improve the outcome but despite great progress, early identification of septic patients remains a challenge. Recently, white blood cell morphology was proposed as a new biomarker for sepsis diagnosis. In this proof-of-concept study, we aimed to investigate the effect of different bacteria and their determinants on T-lymphocytes by digital holographic microscopy (DHM). We hypothesize that species- and strain-specific morphological changes occur, which may offer a new approach for early sepsis diagnosis and identification of the causative agent. Jurkat cells as a model system were exposed to different S. aureus or E. coli strains either using sterile determinants or living bacteria. Time-lapse DHM was applied to analyze cellular morphological changes. There were not only living bacteria but also membrane vesicles and sterile culture supernatant-induced changes of cell area, circularity, and mean phase contrast. Interestingly, different cellular responses occurred depending on both the species and strain of the causative bacteria. Our findings suggest that investigation of T-lymphocyte morphology might provide a promising tool for the early identification of bacterial infections and possibly discrimination between different causative agents. Distinguishing gram-positive from gram-negative infection would already offer a great benefit for the proper administration of antibiotics.

COVID-19 detection from red blood cells using highly comparative time-series analysis (HCTSA) in digital holographic microscopy

We present an automated method for COVID-19 screening based on reconstructed phase profiles of red blood cells (RBCs) and a highly comparative time-series analysis (HCTSA). Video digital holographic data -was obtained using a compact, field-portable shearing microscope to capture the temporal fluctuations and spatio-temporal dynamics of live RBCs. After numerical reconstruction of the digital holographic data, the optical volume is calculated at each timeframe of the reconstructed data to produce a time-series signal for each cell in our dataset. Over 6000 features are extracted on the time-varying optical volume sequences using the HCTSA to quantify the spatio-temporal behavior of the RBCs, then a linear support vector machine is used for classification of individual RBCs. Human subjects are then classified for COVID-19 based on the consensus of their cells' classifications. The proposed method is tested on a dataset of 1472 RBCs from 24 human subjects (10 COVID-19 positive, 14 healthy) collected at UConn Health Center. Following a cross-validation procedure, our system achieves 82.13% accuracy, with 92.72% sensitivity, and 73.21% specificity (area under the receiver operating characteristic curve: 0.8357). Furthermore, the proposed system resulted in 21 out of 24 human subjects correctly labeled. To the best of our knowledge this is the first report of a highly comparative time-series analysis using digital holographic microscopy data.

Video-Rate Quantitative Phase Imaging Using a Digital Holographic Microscope and a Generative Adversarial Network

The conventional reconstruction method of off-axis digital holographic microscopy (DHM) relies on computational processing that involves spatial filtering of the sample spectrum and tilt compensation between the interfering waves to accurately reconstruct the phase of a biological sample. Additional computational procedures such as numerical focusing may be needed to reconstruct free-of-distortion quantitative phase images based on the optical configuration of the DHM system. Regardless of the implementation, any DHM computational processing leads to long processing times, hampering the use of DHM for video-rate renderings of dynamic biological processes. In this study, we report on a conditional generative adversarial network (cGAN) for robust and fast quantitative phase imaging in DHM. The reconstructed phase images provided by the GAN model present stable background levels, enhancing the visualization of the specimens for different experimental conditions in which the conventional approach often fails. The proposed learning-based method was trained and validated using human red blood cells recorded on an off-axis Mach–Zehnder DHM system. After proper training, the proposed GAN yields a computationally efficient method, reconstructing DHM images seven times faster than conventional computational approaches.

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.

Digital holographic deep learning of red blood cells for field-portable, rapid COVID-19 screening

Rapid screening of red blood cells for active infection of COVID-19 is presented using a compact and field-portable, 3D-printed shearing digital holographic microscope. Video holograms of thin blood smears are recorded, individual red blood cells are segmented for feature extraction, then a bi-directional long short-term memory network is used to classify between healthy and COVID positive red blood cells based on their spatiotemporal behavior. Individuals are then classified based on the simple majority of their cells' classifications. The proposed system may be beneficial for under-resourced healthcare systems. To the best of our knowledge, this is the first report of digital holographic microscopy for rapid screening of COVID-19.

Deep learning-based cell identification and disease diagnosis using spatio-temporal cellular dynamics in compact digital holographic microscopy

We demonstrate a successful deep learning strategy for cell identification and disease diagnosis using spatio-temporal cell information recorded by a digital holographic microscopy system. Shearing digital holographic microscopy is employed using a low-cost, compact, field-portable and 3D-printed microscopy system to record video-rate data of live biological cells with nanometer sensitivity in terms of axial membrane fluctuations, then features are extracted from the reconstructed phase profiles of segmented cells at each time instance for classification. The time-varying data of each extracted feature is input into a recurrent bi-directional long short-term memory (Bi-LSTM) network which learns to classify cells based on their time-varying behavior. Our approach is presented for cell identification between the morphologically similar cases of cow and horse red blood cells. Furthermore, the proposed deep learning strategy is demonstrated as having improved performance over conventional machine learning approaches on a clinically relevant dataset of human red blood cells from healthy individuals and those with sickle cell disease. The results are presented at both the cell and patient levels. To the best of our knowledge, this is the first report of deep learning for spatio-temporal-based cell identification and disease detection using a digital holographic microscopy system.

Common-path phase-shift microscope based on measurement of Stokes parameters S2 and S3 for 3D phase extraction

In this paper, we report a common-path, phase-shift optical microscope based on measurement of Stokes parameters S₂ and S₃ to extract the three-dimensional (3D) phase map of transparent objects with high precision. The microscope employs three polarizers and two identical quarter-wave plates to extract S₂ and S₃. The reference phase in the absence of the object is subtracted from the total phase in the presence of the object to extract the 3D phase of the object. The microscope is tested on imaging a USAF resolution test target and a reticle test pattern with excellent results. To the best of our knowledge, this is the first report of a common-path phase-shift optical microscope for 3D phase extraction based on measurement of Stokes parameters S₂ and S₃.

Multimodal Optical Diagnostics of Glycated Biological Tissues

Diabetes mellitus is a metabolic disorder characterized by chronic hyperglycemia accompanied by the disruption of carbohydrate, lipid, and proteins metabolism and development of long-term microvascular, macrovascular, and neuropathic changes. This review presents the results of spectroscopic studies on the glycation of tissues and cell proteins in organisms with naturally developing and model diabetes and in vitro glycated samples in a wide range of electromagnetic waves, from visible light to terahertz radiation. Experiments on the refractometric measurements of glycated and oxygenated hemoglobin in broad wavelength and temperature ranges using digital holographic microscopy and diffraction tomography are discussed, as well as possible application of these methods in the diabetes diagnostics. It is shown that the development and implementation of multimodal approaches based on a combination of phase diagnostics with other methods is another promising direction in the diabetes diagnostics. The possibilities of using optical clearing agents for monitoring the diffusion of substances in the glycated tissues and blood flow dynamics in the pancreas of animals with induced diabetes have also been analyzed.

Structured illumination in compact and field-portable 3D-printed shearing digital holographic microscopy for resolution enhancement

A compact and field-portable three-dimensional (3D)-printed structured illumination (SI) digital holographic microscope based on shearing geometry is presented. By illuminating the sample using a SI pattern, the lateral resolution in both reconstructed phase and amplitude images can be improved up to twice the resolution provided by conventional illumination. The use of a 3D-printed system and shearing geometry reduces the complexity of the system, while providing high temporal stability. The experimental results for the USAF resolution target show a resolution improvement of a factor of two which corroborates the theoretical prediction. Resolution enhancement in phase imaging is also demonstrated by imaging a biological sample. To the best of our knowledge, this is the first report of a compact and field-portable SI digital holographic system based on shearing geometry.

Alignment-tolerant single-shot digital holographic microscopy based on computer-controlled telecentricity

An alignment-tolerant telecentric digital holographic microscopy (AT-T-DHM) system based on computer-controlled telecentricity is proposed. It consists of a three-step process-optical recording, computational compensation, and retrieving processes. With a tube-lens-based two-beam interferometer, phase information of the object is recorded on the hologram, where another optical quadratic phase error (O-QPE) due to the misalignment of the tube lens happens to be added. In the computational compensation process, this phase error can be estimated, by which the O-QPE is balanced out from the recorded hologram. Then, only the phase information of the object can be retrieved from the O-QPE-compensated hologram. This computational compensation process makes the proposed system virtually operate in a telecentric imaging mode, which enables implementing a practical AT-T-DHM. Wave-optical analysis and experiments with a test object confirm the feasibility of the proposed system.

Evaluation of the metastatic potential of malignant cells by image processing of digital holographic microscopy data

The cell refractive index has been proposed as a putative cancer biomarker of great potential, being correlated with cell content and morphology, cell division rate and membrane permeability. We used digital holographic microscopy to compare the refractive index and dry mass density of two B16 murine melanoma sublines of different metastatic potential. Using statistical methods, the distribution of phase shifts within the reconstructed quantitative phase images was analyzed by the method of bimodality coefficients. The observed correlation of refractive index, dry mass density and bimodality profile with the metastatic potential of the cells was validated by real time impedance-based assay and clonogenic tests. We suggest that the refractive index and bimodality analysis of quantitative phase image histograms could be developed as optical biomarkers useful in label-free detection and quantitative evaluation of cell metastatic potential.

Refractive index tomograms and dynamic membrane fluctuations of red blood cells from patients with diabetes mellitus

In this paper, we present the optical characterisations of diabetic red blood cells (RBCs) in a non-invasive manner employing three-dimensional (3-D) quantitative phase imaging. By measuring 3-D refractive index tomograms and 2-D time-series phase images, the morphological (volume, surface area and sphericity), biochemical (haemoglobin concentration and content) and mechanical (membrane fluctuation) parameters were quantitatively retrieved at the individual cell level. With simultaneous measurements of individual cell properties, systematic correlative analyses on retrieved RBC parameters were also performed. Our measurements show there exist no statistically significant alterations in morphological and biochemical parameters of diabetic RBCs, compared to those of healthy (non-diabetic) RBCs. In contrast, membrane deformability of diabetic RBCs is significantly lower than that of healthy, non-diabetic RBCs. Interestingly, non-diabetic RBCs exhibit strong correlations between the elevated glycated haemoglobin in RBC cytoplasm and decreased cell deformability, whereas diabetic RBCs do not show correlations. Our observations strongly support the idea that slow and irreversible glycation of haemoglobin and membrane proteins of RBCs by hyperglycaemia significantly compromises RBC deformability in diabetic patients.

Single-shot digital holographic microscopy with a modified lateral-shearing interferometer based on computational telecentricity

Single-shot digital holographic microscopy (SS-DHM) with a modified lateral-shearing interferometer (MLSI) based on computational telecentricity is proposed. The proposed system is composed of three-step processes such as optical recording, digital compensation and numerical reconstruction processes. In the 1st step, the object beam is optically recorded with the MLSI, where a tube lens is set to be located at the slightly shorter distance than its focal length from the objective lens. Then, another phase factor due to the deviated locating of the tube lens from its focal length is additionally generated, which is called an additional quadratic phase factor (AQPF). However, in the 2nd step, this AQPF can be balanced out with the computer-generated version of the AQPF. In the 3rd step, the three-dimensional (3-D) object can be finally reconstructed from this AQPF-compensated hologram. Thus, by combined use of the optical recording and digital compensation processes of the AQPF, the proposed system can be made virtually operate in a so-called computational telecentricity, which enables us to implement a MLSI-based SS-DHM system. Wave-optical analysis and successful experiments with actual 3-D objects confirm the feasibility of the proposed system in the practical application fields.