Tissue refractive index as marker of disease

Efficient, gigapixel-scale, aberration-free whole slide scanner using angular ptychographic imaging with closed-form solution

Whole slide imaging provides a wide field-of-view (FOV) across cross-sections of biopsy or surgery samples, significantly facilitating pathological analysis and clinical diagnosis. Such high-quality images that enable detailed visualization of cellular and tissue structures are essential for effective patient care and treatment planning. To obtain such high-quality images for pathology applications, there is a need for scanners with high spatial bandwidth products, free from aberrations, and without the requirement for z-scanning. Here we report a whole slide imaging system based on angular ptychographic imaging with a closed-form solution (WSI-APIC), which offers efficient, tens-of-gigapixels, large-FOV, aberration-free imaging. WSI-APIC utilizes oblique incoherent illumination for initial high-level segmentation, thereby bypassing unnecessary scanning of the background regions and enhancing image acquisition efficiency. A GPU-accelerated APIC algorithm analytically reconstructs phase images with effective digital aberration corrections and improved optical resolutions. Moreover, an auto-stitching technique based on scale-invariant feature transform ensures the seamless concatenation of whole slide phase images. In our experiment, WSI-APIC achieved an optical resolution of 772 nm using a 10×/0.25 NA objective lens and captures 80-gigapixel aberration-free phase images for a standard 76.2 mm × 25.4 mm microscopic slide.

White Light Diffraction Phase Microscopy in Imaging of Breast and Colon Tissues

This paper reports results obtained using white light diffraction phase microscopy (wDPM) on captured images of breast and colon tissue samples, marking a contribution to the advancement in biomedical imaging. Unlike conventional brightfield microscopy, wDPM offers the capability to capture intricate details of biological specimens with enhanced clarity and precision. It combines high resolution, enhanced contrast, and quantitative capabilities with non-invasive, label-free imaging. These features make it a useful tool for tissue imaging, providing detailed and accurate insights into tissue structure and dynamics without compromising the integrity of the samples. Our findings underscore the potential of quantitative phase imaging in histopathology, in the context of automating the process of tissue analysis and diagnosis. Of particular note are the insights gained from the reconstructed phase images, which provide physical data regarding peripheral glandular cell membranes. These observations serve to focus attention on pathologies involving the basal membrane, such as early invasive carcinoma. Through our analysis, we aim to contribute to catalyzing further advancements in tissue (breast and colon) imaging.

Relationship between depth-wise refractive index and biomechanical properties of human articular cartilage

Significance

Optical properties of biological tissues, such as refractive index (RI), are fundamental properties, intrinsically linked to the tissue's composition and structure. We hypothesize that, as the RI and the functional properties of articular cartilage (AC) are dependent on the tissue's structure and composition, the RI of AC is related to its biomechanical properties.

Aim

This study aims to investigate the relationship between RI of human AC and its biomechanical properties.

Approach

Human cartilage samples ( n = 22 ) were extracted from the right knee joint of three cadaver donors (one female, aged 47 years, and two males, aged 64 and 68 years) obtained from a commercial biobank (Science Care, Phoenix, Arizona, United States). The samples were initially subjected to mechanical indentation testing to determine elastic [equilibrium modulus (EM) and instantaneous modulus (IM)] and dynamic [dynamic modulus (DM)] viscoelastic properties. An Abbemat 3200 automatic one-wavelength refractometer operating at 600 nm was used to measure the RI of the extracted sections. Similarly, Spearman's and Pearson's correlation coefficients were employed for non-normal and normal datasets, respectively, to determine the correlation between the depth-wise RI and biomechanical properties of the cartilage samples as a function of the collagen fibril orientation.

Results

A positive correlation with statistically significant relations ( p - values < 0.05 ) was observed between the RI and the biomechanical properties (EM, IM, and DM) along the tissue depth for each zone, e.g., superficial, middle, and deep zones. Likewise, a lower positive correlation with statistically significant relations ( p - values < 0.05 ) was also observed for collagen fibril orientation of all zones with the biomechanical properties.

Conclusions

The results indicate that, although the RI exhibits different levels of correlation with different biomechanical properties, the relationship varies as a function of the tissue depth. This knowledge paves the way for optically monitoring changes in AC biomechanical properties nondestructively via changes in the RI. Thus, the RI could be a potential biomarker for assessing the mechanical competency of AC, particularly in degenerative diseases, such as osteoarthritis.

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.

Perspective on quantitative phase imaging to improve precision cancer medicine

Significance

Quantitative phase imaging (QPI) offers a label-free approach to non-invasively characterize cellular processes by exploiting their refractive index based intrinsic contrast. QPI captures this contrast by translating refractive index associated phase shifts into intensity-based quantifiable data with nanoscale sensitivity. It holds significant potential for advancing precision cancer medicine by providing quantitative characterization of the biophysical properties of cells and tissue in their natural states.

Aim

This perspective aims to discuss the potential of QPI to increase our understanding of cancer development and its response to therapeutics. It also explores new developments in QPI methods towards advancing personalized cancer therapy and early detection.

Approach

We begin by detailing the technical advancements of QPI, examining its implementations across transmission and reflection geometries and phase retrieval methods, both interferometric and non-interferometric. The focus then shifts to QPI's applications in cancer research, including dynamic cell mass imaging for drug response assessment, cancer risk stratification, and in-vivo tissue imaging.

Results

QPI has emerged as a crucial tool in precision cancer medicine, offering insights into tumor biology and treatment efficacy. Its sensitivity to detecting nanoscale changes holds promise for enhancing cancer diagnostics, risk assessment, and prognostication. The future of QPI is envisioned in its integration with artificial intelligence, morpho-dynamics, and spatial biology, broadening its impact in cancer research.

Conclusions

QPI presents significant potential in advancing precision cancer medicine and redefining our approach to cancer diagnosis, monitoring, and treatment. Future directions include harnessing high-throughput dynamic imaging, 3D QPI for realistic tumor models, and combining artificial intelligence with multi-omics data to extend QPI's capabilities. As a result, QPI stands at the forefront of cancer research and clinical application in cancer care.

Quantitative phase imaging techniques for measuring scattering properties of cells and tissues: a review-part II

Significance

Quantitative phase imaging (QPI) is a non-invasive, label-free technique that provides intrinsic information about the sample under study. Such information includes the structure, function, and dynamics of the sample. QPI overcomes the limitations of conventional fluorescence microscopy in terms of phototoxicity to the sample and photobleaching of the fluorophore. As such, the application of QPI in estimating the three-dimensional (3D) structure and dynamics is well-suited for a range of samples from intracellular organelles to highly scattering multicellular samples while allowing for longer observation windows.

Aim

We aim to provide a comprehensive review of 3D QPI and related phase-based measurement techniques along with a discussion of methods for the estimation of sample dynamics.

Approach

We present information collected from 106 publications that cover the theoretical description of 3D light scattering and the implementation of related measurement techniques for the study of the structure and dynamics of the sample. We conclude with a discussion of the applications of the reviewed techniques in the biomedical field.

Results

QPI has been successfully applied to 3D sample imaging. The scattering-based contrast provides measurements of intrinsic quantities of the sample that are indicative of disease state, stage of growth, or overall dynamics.

Conclusions

We reviewed state-of-the-art QPI techniques for 3D imaging and dynamics estimation of biological samples. Both theoretical and experimental aspects of various techniques were discussed. We also presented the applications of the discussed techniques as applied to biomedicine and biology research.

Automated Whole Slide Imaging for Label-Free Histology Using Photon Absorption Remote Sensing Microscopy

OBJECTIVE

Pathologists rely on histochemical stains to impart contrast in thin translucent tissue samples, revealing tissue features necessary for identifying pathological conditions. However, the chemical labeling process is destructive and often irreversible or challenging to undo, imposing practical limits on the number of stains that can be applied to the same tissue section. Here we present an automated label-free whole slide scanner using a PARS microscope designed for imaging thin, transmissible samples.

METHODS

Peak SNR and in-focus acquisitions are achieved across entire tissue sections using the scattering signal from the PARS detection beam to measure the optimal focal plane. Whole slide images (WSI) are seamlessly stitched together using a custom contrast leveling algorithm. Identical tissue sections are subsequently H&E stained and brightfield imaged. The one-to-one WSIs from both modalities are visually and quantitatively compared.

RESULTS

PARS WSIs are presented at standard 40x magnification in malignant human breast and skin samples. We show correspondence of subcellular diagnostic details in both PARS and H&E WSIs and demonstrate virtual H&E staining of an entire PARS WSI. The one-to-one WSI from both modalities show quantitative similarity in nuclear features and structural information.

CONCLUSION

PARS WSIs are compatible with existing digital pathology tools, and samples remain suitable for histochemical, immunohistochemical, and other staining techniques.

SIGNIFICANCE

This work is a critical advance for integrating label-free optical methods into standard histopathology workflows.

Quantitative phase imaging techniques for measuring scattering properties of cells and tissues: a review-part I

Significance

Quantitative phase imaging (QPI) techniques offer intrinsic information about the sample of interest in a label-free, noninvasive manner and have an enormous potential for wide biomedical applications with negligible perturbations to the natural state of the sample in vitro.

Aim

We aim to present an in-depth review of the scattering formulation of light-matter interactions as applied to biological samples such as cells and tissues, discuss the relevant quantitative phase measurement techniques, and present a summary of various reported applications.

Approach

We start with scattering theory and scattering properties of biological samples followed by an exploration of various microscopy configurations for 2D QPI for measurement of structure and dynamics.

Results

We reviewed 157 publications and presented a range of QPI techniques and discussed suitable applications for each. We also presented the theoretical frameworks for phase reconstruction associated with the discussed techniques and highlighted their domains of validity.

Conclusions

We provide detailed theoretical as well as system-level information for a wide range of QPI techniques. Our study can serve as a guideline for new researchers looking for an exhaustive literature review of QPI methods and relevant applications.

Tissue characterization using axicon probe-assisted common-path optical coherence tomography

In this work, a common-path optical coherence tomography (OCT) system is demonstrated for characterizing the tissue in terms of some optical properties. A negative axicon structure chemically etched inside the fiber tip is employed as optical probe in the OCT. This probe generates a quality Bessel beam owning a large depth-of-field, ∼700 µm and small central spot size, ∼3 µm. The OCT system is probing the sample without using any microscopic lens. For experimental validation, the OCT imaging of chicken tissue has been obtained along with estimation of its refractive index and optical attenuation coefficient. Afterwards, the cancerous tissue is differentiated from the normal tissue based on the OCT imaging, refractive index, and optical attenuation coefficient. The respective tissue samples are collected from the human liver and pancreas. This probe could be a useful tool for endoscopic or minimal-invasive inspection of malignancy inside the tissue either at early-stage or during surgery.

Grading of glioma tumors using digital holographic microscopy

Gliomas are the most common type of cerebral tumors; they occur with increasing incidence in the last decade and have a high rate of mortality. For efficient treatment, fast accurate diagnostic and grading of tumors are imperative. Presently, the grading of tumors is established by histopathological evaluation, which is a time-consuming procedure and relies on the pathologists' experience. Here we propose a supervised machine learning procedure for tumor grading which uses quantitative phase images of unstained tissue samples acquired by digital holographic microscopy. The algorithm is using an extensive set of statistical and texture parameters computed from these images. The procedure has been able to classify six classes of images (normal tissue and five glioma subtypes) and to distinguish between gliomas types from grades II to IV (with the highest sensitivity and specificity for grade II astrocytoma and grade III oligodendroglioma and very good scores in recognizing grade III anaplastic astrocytoma and grade IV glioblastoma). The procedure bolsters clinical diagnostic accuracy, offering a swift and reliable means of tumor characterization and grading, ultimately the enhancing treatment decision-making process.

Automated hyperspectral imaging for non-invasive characterization of human eye vasculature: A potential tool for ocular vascular evaluation

The vascular supply to the human eye plays a vital role in maintaining ocular health, making its non-invasive evaluation essential for diagnosing and managing various ocular disorders. This paper presents a novel approach utilizing hyperspectral imaging (HSI) to non-invasively characterize human eye vasculature. The proposed system aims to specifically identify the blood atrium and veins of the human eye at 470 nm and 750 nm, respectively, using quantitative phase analysis and k-means clustering. The study involved capturing diffused reflection spectra and hyperspectral images of the human eye at different wavelengths to reveal distinctive vascular features. The results of ten volunteers demonstrate promising capabilities in automated differentiation of atrium and veins, as well as the potential for mapping varicose veins in the lower limb. This non-invasive and non-contact imaging technique shows great promise in facilitating accurate and detailed evaluation of ocular blood flow, providing valuable information for clinical diagnosis and treatment in ophthalmology and vascular medicine fields.

Multi-wavelength interference phase imaging for automatic breast cancer detection and delineation using diffuse reflection imaging

Millions of women globally are impacted by the major health problem of breast cancer (BC). Early detection of BC is critical for successful treatment and improved survival rates. In this study, we provide a progressive approach for BC detection using multi-wavelength interference (MWI) phase imaging based on diffuse reflection hyperspectral (HS) imaging. The proposed findings are based on the measurement of the interference pattern between the blue (446.6 nm) and red (632 nm) wavelengths. We consider implementing a comprehensive image processing and categorization method based on the use of Fast Fourier (FF) transform analysis pertaining to a change in the refractive index between tumor and normal tissue. We observed that cancer growth affects tissue organization dramatically, as seen by persistently increased refractive index variance in tumors compared normal areas. Both malignant and normal tissue had different depth data collected from it that was analyzed. To enhance the categorization of ex-vivo BC tissue, we developed and validated a training classifier algorithm specifically designed for categorizing HS cube data. Following the application of signal normalization with the FF transform algorithm, our methodology achieved a high level of performance with a specificity (Spec) of 94% and a sensitivity (Sen) of 90.9% for the 632 nm acquired image categorization, based on preliminary findings from breast specimens under investigation. Notably, we successfully leveraged unstained tissue samples to create 3D phase-resolved images that effectively highlight the distinctions in diffuse reflectance features between cancerous and healthy tissue. Preliminary data revealed that our imaging method might be able to assist specialists in safely excising malignant areas and assessing the tumor bed following resection automatically at different depths. This preliminary investigation might result in an effective "in-vivo" disease description utilizing optical technology using a typical RGB camera with wavelength-specific operation with our quantitative phase MWI imaging methodology.

Refractive index of human articular cartilage varies with tissue structure and composition

Optical properties of biological tissues, such as refractive index, are fundamental properties, intrinsically linked to a tissue's composition and structure. This study aims to investigate the variation of refractive index (RI) of human articular cartilage along the tissue depth (via collagen fibril orientation and optical density) and integrity (based on Mankin and Osteoarthritis Research Society International (OARSI) scores). The results show the relationship between RI and PG content (p=0.042), collagen orientation (p=0.037), and OARSI score (p=0.072). When taken into account, the outcome of this study suggests that the RI of healthy cartilage differs from that of pathological cartilage (p=0.072). This could potentially provide knowledge on how progressive tissue degeneration, such as osteoarthritis, affects changes in cartilage RI, which can, in turn, be used as a potential optical biomarker of tissue pathology.

Random Lasing for Bimodal Imaging and Detection of Tumor

The interaction of light with biological tissues is an intriguing area of research that has led to the development of numerous techniques and technologies. The randomness inherent in biological tissues can trap light through multiple scattering events and provide optical feedback to generate random lasing emission. The emerging random lasing signals carry sensitive information about the scattering dynamics of the medium, which can help in identifying abnormalities in tissues, while simultaneously functioning as an illumination source for imaging. The early detection and imaging of tumor regions are crucial for the successful treatment of cancer, which is one of the major causes of mortality worldwide. In this paper, a bimodal spectroscopic and imaging system, capable of identifying and imaging tumor polyps as small as 1 mm2, is proposed and illustrated using a phantom sample for the early diagnosis of tumor growth. The far-field imaging capabilities of the developed system can enable non-contact in vivo inspections. The integration of random lasing principles with sensing and imaging modalities has the potential to provide an efficient, minimally invasive, and cost-effective means of early detection and treatment of various diseases, including cancer.

Polarization differential interference contrast microscopy with physics-inspired plug-and-play denoiser for single-shot high-performance quantitative phase imaging

We present single-shot high-performance quantitative phase imaging with a physics-inspired plug-and-play denoiser for polarization differential interference contrast (PDIC) microscopy. The quantitative phase is recovered by the alternating direction method of multipliers (ADMM), balancing total variance regularization and a pre-trained dense residual U-net (DRUNet) denoiser. The custom DRUNet uses the Tanh activation function to guarantee the symmetry requirement for phase retrieval. In addition, we introduce an adaptive strategy accelerating convergence and explicitly incorporating measurement noise. After validating this deep denoiser-enhanced PDIC microscopy on simulated data and phantom experiments, we demonstrated high-performance phase imaging of histological tissue sections. The phase retrieval by the denoiser-enhanced PDIC microscopy achieves significantly higher quality and accuracy than the solution based on Fourier transforms or the iterative solution with total variance regularization alone.

Influence of hematoxylin and eosin staining on linear birefringence measurement of fibrous tissue structures in polarization microscopy

Significance

For microscopic polarization imaging of tissue slices, two types of samples are often prepared: one unstained tissue section for polarization imaging to avoid possible influence from staining dyes quantitatively and one hematoxylin-eosin (H&E) stained adjacent tissue section for histological diagnosis and structural feature identification. However, this sample preparation strategy requires high-quality adjacent tissue sections, and labeling the structural features on unstained tissue sections is impossible. With the fast development of data driven-based polarimetric analysis, which requires a large amount of pixel labeled images, a possible method is to directly use H&E stained slices, which are standard samples archived in clinical hospitals for polarization measurement.

Aim

We aim to study the influence of hematoxylin and eosin staining on the linear birefringence measurement of fibrous tissue structures.

Approach

We examine the linear birefringence properties of four pieces of adjacent bone tissue slices with abundant collagen fibers that are unstained, H&E stained, hematoxylin (H) stained, and eosin (E) stained. After obtaining the spatial maps of linear retardance values for the four tissue samples, we carry out a comparative study using a frequency distribution histogram and similarity analysis based on the Bhattacharyya coefficient to investigate how H&E staining affects the linear birefringence measurement of bone tissues.

Results

Linear retardance increased after H&E, H, or E staining (41.7%, 40.8%, and 72.5% increase, respectively). However, there is no significant change in the imaging contrast of linear retardance in bone tissues.

Conclusions

The linear retardance values induced by birefringent collagen fibers can be enhanced after H&E, H, or E staining. However, the structural imaging contrasts based on linear retardance did not change significantly or the staining did not generate linear birefringence on the sample area without collagen. Therefore, it can be acceptable to prepare H&E stained slices for clinical applications of polarimetry based on such a mapping relationship.

Mixing rule for calculating the effective refractive index beyond the limit of small particles

Considering light transport in disordered media, the medium is often treated as an effective medium requiring accurate evaluation of an effective refractive index. Because of its simplicity, the Maxwell-Garnett (MG) mixing rule is widely used, although its restriction to particles much smaller than the wavelength is rarely satisfied. Using 3D finite-difference time-domain simulations, we show that the MG theory indeed fails for large particles. Systematic investigation of size effects reveals that the effective refractive index can be instead approximated by a quadratic polynomial whose coefficients are given by an empirical formula. Hence, a simple mixing rule is derived which clearly outperforms established mixing rules for composite media containing large particles, a common condition in natural disordered media.

Mapping nanoscale topographic features in thick tissues with speckle diffraction tomography

Resolving three-dimensional morphological features in thick specimens remains a significant challenge for label-free imaging. We report a new speckle diffraction tomography (SDT) approach that can image thick biological specimens with ~500 nm lateral resolution and ~1 μm axial resolution in a reflection geometry. In SDT, multiple-scattering background is rejected through spatiotemporal gating provided by dynamic speckle-field interferometry, while depth-resolved refractive index maps are reconstructed by developing a comprehensive inverse-scattering model that also considers specimen-induced aberrations. Benefiting from the high-resolution and full-field quantitative imaging capabilities of SDT, we successfully imaged red blood cells and quantified their membrane fluctuations behind a turbid medium with a thickness of 2.8 scattering mean-free paths. Most importantly, we performed volumetric imaging of cornea inside an ex vivo rat eye and quantified its optical properties, including the mapping of nanoscale topographic features of Dua's and Descemet's membranes that had not been previously visualized.

Quantitative Phase Imaging Using Digital Holographic Microscopy to Assess the Degree of Intestinal Inflammation in Patients with Ulcerative Colitis

Ulcerative colitis (UC) is characterized by chronic inflammation of the colorectum. Histological remission has emerged as a potential future treatment goal; however, the histopathological assessment of intestinal inflammation in UC remains challenging with a multitude of available scoring systems and the need for a pathologist with expertise in inflammatory bowel disease (IBD). In previous studies, quantitative phase imaging (QPI) including digital holographic microscopy (DHM) was successfully applied as an objective method for stain-free quantification of the degree of inflammation in tissue sections. Here, we evaluated the application of DHM for the quantitative assessment of histopathological inflammation in patients with UC. In our study, endoscopically obtained colonic and rectal mucosal biopsy samples from 21 patients with UC were analyzed by capturing DHM-based QPI images that were subsequently evaluated using the subepithelial refractive index (RI). The retrieved RI data were correlated with established histological scoring systems including the Nancy index (NI) as well as with endoscopic and clinical findings. As a primary endpoint, we found a significant correlation between the DHM-based retrieved RI and the NI (R² = 0.251, p < 0.001). Furthermore, RI values correlated with the Mayo endoscopic subscore (MES; R² = 0.176, p < 0.001). An area under the receiver operating characteristics (ROC) curve of 0.820 confirms the subepithelial RI as a reliable parameter to distinguish biopsies with histologically active UC from biopsies without evidence of active disease as determined by conventional histopathological examination. An RI higher than 1.3488 was found to be the most sensitive and specific cut-off value to identify histologically active UC (sensitivity of 84% and specificity of 72%). In conclusion, our data demonstrate DHM to be a reliable tool for the quantitative assessment of mucosal inflammation in patients with UC.

Targeted Enzyme Activity Imaging with Quantitative Phase Microscopy

Quantitative phase imaging (QPI) is a powerful optical imaging modality for label-free, rapid, and three-dimensional (3D) monitoring of cells and tissues. However, molecular imaging of important intracellular biomolecules such as enzymes remains a largely unexplored area for QPI. Herein, we introduce a fundamentally new approach by designing QPI contrast agents that allow sensitive detection of intracellular biomolecules. We report a new class of bio-orthogonal QPI-nanoprobes for in situ high-contrast refractive index (RI) imaging of enzyme activity. The nanoprobes feature silica nanoparticles (SiO2 NPs) having higher RI than endogenous cellular components and surface-anchored cyanobenzothiazole-cysteine (CBT-Cys) conjugated enzyme-responsive peptide sequences. The nanoprobes specifically aggregated in cells with target enzyme activity, increasing intracellular RI and enabling precise visualization of intracellular enzyme activity. We envision that this general design of QPI-nanoprobes could open doors for spatial-temporal mapping of enzyme activity with direct implications for disease diagnosis and evaluating the therapeutic efficacy.

Quantification of structural heterogeneity in H&E stained clear cell renal cell carcinoma using refractive index tomography

Clear cell renal cell carcinoma (ccRCC) is a common histopathological subtype of renal cancer and is notorious for its poor prognosis. Its accurate diagnosis by histopathology, which relies on manual microscopic inspection of stained slides, is challenging. Here, we present a correlative approach to utilize stained images and refractive index (RI) tomography and demonstrate quantitative assessments of the structural heterogeneities of ccRCC slides obtained from human patients. Machine-learning-assisted segmentation of nuclei and cytoplasm enabled the quantification at the subcellular level. Compared to benign regions, malignant regions exhibited a considerable increase in structural heterogeneities. The results demonstrate that RI tomography provides quantitative information in synergy with stained images on the structural heterogeneities in ccRCC.

Terahertz refractive phenotype of living cells

Cellular refractive index is a vital phenotypic parameter for understanding the cell functional activities. So far, there remains technical challenges to obtain refractive index of viable cells at the terahertz frequency in which contains rich information closely related to their physiological status. Here we introduce a label-free optical platform for interrogating cellular phenotypes to measure the refractive index of living cells in near-physiological environments by using terahertz spectroscopy with the combination of cellular encapsulation in a confined solution droplet. The key technical feature with cells encapsulated in aqueous droplets allows for keeping cellular viability while eliminating the strong adsorption of solvent water to terahertz signal. The obtained high signal-to-noise ratio enables to differentiate different cell types (e.g., E. coli, stem cell and cancer cell) and their states under stress conditions. The integrating of terahertz spectroscopy to droplet microfluidic further realizes automated and high-through sample preparation and detection, providing a practical toolkit for potential application in cellular health evaluation and phenotypic drug discovery.

Refractive Index of Hemoglobin Analysis: A Comparison of Alternating Conditional Expectations and Computational Intelligence Models

Hemoglobin is one of the most important blood elements, and its optical properties will determine all other optical properties of human blood. Since the refractive index (RI) of hemoglobin plays a vital role as a non-invasive indicator of some illnesses, accurate calculation of it would be of great importance. Moreover, measurement of the RI of hemoglobin in the laboratory is time-consuming and expensive; thus, developing a smart approach to estimate this parameter is necessary. In this research, four viable strategies were used to make a quantitative correlation between the RI of hemoglobin and its influencing parameters including the concentration, wavelength, and temperature. First, alternating conditional expectations (ACE), a statistical approach, was employed to generate a correlation to predict the RI of hemoglobin. Then, three different optimized intelligent techniques-optimized neural network (ONN), optimized fuzzy inference system (OFIS), and optimized support vector regression (OSVR)-were used to model the RI. A bat-inspired (BA) algorithm was embedded in the formulation of intelligent models to obtain the optimal values of weights and biases of an artificial neural network, membership functions of the fuzzy inference system, and free parameters of support vector regression. The coefficient of determination, root-mean-square error, average absolute relative error, and symmetric mean absolute percentage error for each of the ACE, ONN, OFIS, and OSVR were found as the measure of each model's accuracy. Results showed that ACE and optimized models (ONN, OFIS, and OSVR) have promising results in the estimation of hemoglobin's RI. Collectively, ACE outperformed ONN, OFIS, and OSVR, while sensitivity analysis indicated that the concentration, wavelength, and, lastly, temperature would have the highest impact on the RI.

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.

Differentiation of otitis media-causing bacteria and biofilms via Raman spectroscopy and optical coherence tomography

In the management of otitis media (OM), identification of causative bacterial pathogens and knowledge of their biofilm formation can provide more targeted treatment approaches. Current clinical diagnostic methods rely on the visualization of the tympanic membrane and lack real-time assessment of the causative pathogen(s) and the nature of any biofilm that may reside behind the membrane and within the middle ear cavity. In recent years, optical coherence tomography (OCT) has been demonstrated as an improved in vivo diagnostic tool for visualization and morphological characterization of OM biofilms and middle ear effusions; but lacks specificity about the causative bacterial species. This study proposes the combination of OCT and Raman spectroscopy (RS) to examine differences in the refractive index, optical attenuation, and biochemical composition of Haemophilus influenzae, Streptococcus pneumoniae, Moraxella catarrhalis, and Pseudomonas aeruginosa; four of the leading otopathogens in OM. This combination provides a dual optical approach for identifying and differentiating OM-causing bacterial species under three different in vitro growth environments (i.e., agar-grown colonies, planktonic cells from liquid cultures, and biofilms). This study showed that RS was able to identify key biochemical variations to differentiate all four OM-causing bacteria. Additionally, biochemical spectral changes (RS) and differences in the mean attenuation coefficient (OCT) were able to distinguish the growth environment for each bacterial species.

Quantitative phase imaging through an ultra-thin lensless fiber endoscope

Quantitative phase imaging (QPI) is a label-free technique providing both morphology and quantitative biophysical information in biomedicine. However, applying such a powerful technique to in vivo pathological diagnosis remains challenging. Multi-core fiber bundles (MCFs) enable ultra-thin probes for in vivo imaging, but current MCF imaging techniques are limited to amplitude imaging modalities. We demonstrate a computational lensless microendoscope that uses an ultra-thin bare MCF to perform quantitative phase imaging with microscale lateral resolution and nanoscale axial sensitivity of the optical path length. The incident complex light field at the measurement side is precisely reconstructed from the far-field speckle pattern at the detection side, enabling digital refocusing in a multi-layer sample without any mechanical movement. The accuracy of the quantitative phase reconstruction is validated by imaging the phase target and hydrogel beads through the MCF. With the proposed imaging modality, three-dimensional imaging of human cancer cells is achieved through the ultra-thin fiber endoscope, promising widespread clinical applications.

Development of multimodal micro-endoscopic system with oblique illumination for simultaneous fluorescence imaging and spectroscopy of oral cancer

Multimodality of an optical system implies the use of one or more optical techniques to improve the system's overall performance and maximum utility. In this article, we demonstrate a multimodal system with oblique illumination that combines two different techniques; fluorescence micro-endoscopy and spectroscopy simultaneously and can be utilized to obtain diverse information from the same location of biological sample. In present system, use of graded index (GRIN) rod-lens makes it highly compact and oblique incidence decouples illumination geometry with collection geometry, preventing CCD cameras from saturation and reduces number of optical elements, thereby making system further miniaturized and field-portable. It also overcomes the disadvantages of undesired reflections from different optical elements. The experimental results of simultaneous imaging and spectroscopy of the biological samples are presented along with quantitative spectroscopic parameters; peak wavelength shift, area under the curve and full width half maximum (FWHM). The spatial resolution, spectral resolution and field of view of the system are found to be 4.38 μm, 0.5 nm and 2.071×1.548mm2 , respectively. Furthermore, we have obtained the red shift for cancerous oral tissue with respect to normal oral tissue 5.79 ± 1.071 nm. This could be important indicator for oral cancer screening.

Complex refractive index of freshly excised human breast tissue as a marker of disease

We report differences in the refractive index of healthy and tumorous freshly excised human breast tissue as determined from reflectance profile measurements at five wavelengths (432 nm, 532 nm, 633 nm, 964 nm, 1551 nm) in the visible and near-infrared using a standard prism-coupling refractometer. These refractive index differences, particularly in the near-infrared, can be used to distinguish fibroadenomas and cancerous growths not only from normal breast tissue but also from each other.

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

Background

Imaging techniques are commonly used to understand disease mechanisms and their biological features in the microenvironment of the cell. Many studies have added to our understanding of the biology of the malaria parasite Plasmodium knowlesi from functional in vitro and imaging analysis using serial block-face scanning electron microscopy (SEM). However, sample fixation and metal coating during SEM analysis can alter the parasite membrane.

Methods

In this study, we used noninvasive diffraction optical tomography (DOT), also known as holotomography, to explore the morphological, biochemical, and mechanical alterations of each stage of P. knowlesi-infected red blood cells (RBCs). Each stage of the parasite was synchronized using Nycodenz and magnetic-activated cell sorting (MACS) for P. knowlesi and P. falciparum, respectively. Holotomography was applied to measure individual three-dimensional refractive index tomograms without metal coating, fixation, or additional dye agent.

Results

Distinct profiles were found on the surface area and hemoglobin content of the two parasites. The surface area of P. knowlesi-infected RBCs showed significant expansion, while P. falciparum-infected RBCs did not show any changes compared to uninfected RBCs. In terms of hemoglobin consumption, P. falciparum tended to consume hemoglobin more than P. knowlesi. The observed profile of P. knowlesi-infected RBCs generally showed similar results to other studies, proving that this technique is unbiased.

Conclusions

The observed profile of the surface area and hemoglobin content of malaria infected-RBCs can potentially be used as a diagnostic parameter to distinguish P. knowlesi and P. falciparum infection. In addition, we showed that holotomography could be used to study each Plasmodium species in greater depth, supporting strategies for the development of diagnostic and treatment strategies for malaria.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13071-022-05182-1.

Automatic Colorectal Cancer Screening Using Deep Learning in Spatial Light Interference Microscopy Data

The surgical pathology workflow currently adopted by clinics uses staining to reveal tissue architecture within thin sections. A trained pathologist then conducts a visual examination of these slices and, since the investigation is based on an empirical assessment, a certain amount of subjectivity is unavoidable. Furthermore, the reliance on external contrast agents such as hematoxylin and eosin (H&E), albeit being well-established methods, makes it difficult to standardize color balance, staining strength, and imaging conditions, hindering automated computational analysis. In response to these challenges, we applied spatial light interference microscopy (SLIM), a label-free method that generates contrast based on intrinsic tissue refractive index signatures. Thus, we reduce human bias and make imaging data comparable across instruments and clinics. We applied a mask R-CNN deep learning algorithm to the SLIM data to achieve an automated colorectal cancer screening procedure, i.e., classifying normal vs. cancerous specimens. Our results, obtained on a tissue microarray consisting of specimens from 132 patients, resulted in 91% accuracy for gland detection, 99.71% accuracy in gland-level classification, and 97% accuracy in core-level classification. A SLIM tissue scanner accompanied by an application-specific deep learning algorithm may become a valuable clinical tool, enabling faster and more accurate assessments by pathologists.

Multiple-scattering suppressive refractive index tomography for the label-free quantitative assessment of multicellular spheroids

Refractive index (RI) tomography is a quantitative tomographic technique used to visualize the intrinsic contrast of unlabeled biological samples. Conventional RI reconstruction algorithms are based on weak-scattering approximation, such as the Born or Rytov approximation. Although these linear algorithms are computationally efficient, they are invalid when the fields are strongly distorted by multiple scattering (MS) of specimens. Herein, we propose an approach to reconstruct the RI distributions of MS objects even under weak-scattering approximation using an MS-suppressive operation. The operation converts the distorted fields into MS-suppressed fields, where weak-scattering approximation is applicable. Using this approach, we reconstructed a whole multicellular spheroid and successfully visualized its internal subcellular structures. Our work facilitates the realization of RI tomography of MS specimens and label-free quantitative analysis of 3D multicellular specimens.

Polarization memory rate as a metric to differentiate benign and malignant tissues

Non-invasive optical methods for cancer diagnostics, such as microscopy, spectroscopy, and polarimetry, are rapidly advancing. In this respect, finding new and powerful optical metrics is an indispensable task. Here we introduce polarization memory rate (PMR) as a sensitive metric for optical cancer diagnostics. PMR characterizes the preservation of circularly polarized light relative to linearly polarized light as light propagates in a medium. We hypothesize that because of well-known indicators associated with the morphological changes of cancer cells, like an enlarged nucleus size and higher chromatin density, PMR should be greater for cancerous than for the non-cancerous tissues. A thorough literature review reveals how this difference arises from the anomalous depolarization behaviour of many biological tissues. In physical terms, though most biological tissue primarily exhibits Mie scattering, it typically exhibits Rayleigh depolarization. However, in cancerous tissue the Mie depolarization regime becomes more prominent than Rayleigh. Experimental evidence of this metric is found in a preliminary clinical study using a novel Stokes polarimetry probe. We conducted in vivo measurements of 20 benign, 28 malignant and 59 normal skin sites with a 660 nm laser diode. The median PMR values for cancer vs non-cancer are significantly higher for cancer which supports our hypothesis. The reported fundamental differences in depolarization may persist for other types of cancer and create a conceptual basis for further developments in polarimetry applications for cancer detection.

The effect of pupil transmittance on axial resolution of reflection phase microscopy

A reflection phase microscope (RPM) can be equipped with the capability of depth selection by employing a gating mechanism. However, it is difficult to achieve an axial resolution close to the diffraction limit in real implementation. Here, we systematically investigated the uneven interference contrast produced by pupil transmittance of the objective lens and found that it was the main cause of the practical limit that prevents the axial resolution from reaching its diffraction limit. Then we modulated the power of illumination light to obtain a uniform interference contrast over the entire pupil. Consequently, we could achieve an axial resolution fairly close to the diffraction limit set by the experimental conditions.

Colorimetric histology using plasmonically active microscope slides

The human eye can distinguish as many as 10,000 different colours but is far less sensitive to variations in intensity¹, meaning that colour is highly desirable when interpreting images. However, most biological samples are essentially transparent, and nearly invisible when viewed using a standard optical microscope². It is therefore highly desirable to be able to produce coloured images without needing to add any stains or dyes, which can alter the sample properties. Here we demonstrate that colorimetric histology images can be generated using full-sized plasmonically active microscope slides. These slides translate subtle changes in the dielectric constant into striking colour contrast when samples are placed upon them. We demonstrate the biomedical potential of this technique, which we term histoplasmonics, by distinguishing neoplastic cells from normal breast epithelium during the earliest stages of tumorigenesis in the mouse MMTV-PyMT mammary tumour model. We then apply this method to human diagnostic tissue and validate its utility in distinguishing normal epithelium, usual ductal hyperplasia, and early-stage breast cancer (ductal carcinoma in situ). The colorimetric output of the image pixels is compared to conventional histopathology. The results we report here support the hypothesis that histoplasmonics can be used as a novel alternative or adjunct to general staining. The widespread availability of this technique and its incorporation into standard laboratory workflows may prove transformative for applications extending well beyond tissue diagnostics. This work also highlights opportunities for improvements to digital pathology that have yet to be explored.

ADMM approach for efficient iterative tomographic deconvolution reconstruction of 3D quantitative phase images

Tomographic deconvolution phase microscopy (TDPM) is a promising approach for 3D quantitative imaging of phase objects such as biological cells and optical fibers. In the present work, the alternating direction method of multipliers (ADMM) is applied to TDPM to shorten its image acquisition and processing times while simultaneously improving its accuracy. ADMM-TDPM is used to optimize the image fidelity by minimizing Gaussian noise and by using total variation regularization with the constraints of nonnegativity and known zeros. ADMM-TDPM can reconstruct phase objects that are shift variant in three spatial dimensions. ADMM-TDPM achieves speedups of 5x in image acquisition time and greater than 10x in image processing time with accompanying higher accuracy compared to TDPM.

Spatial light interference microscopy: principle and applications to biomedicine

In this paper, we review spatial light interference microscopy (SLIM), a common-path, phase-shifting interferometer, built onto a phase-contrast microscope, with white-light illumination. As one of the most sensitive quantitative phase imaging (QPI) methods, SLIM allows for speckle-free phase reconstruction with sub-nanometer path-length stability. We first review image formation in QPI, scattering, and full-field methods. Then, we outline SLIM imaging from theory and instrumentation to diffraction tomography. Zernike's phase-contrast microscopy, phase retrieval in SLIM, and halo removal algorithms are discussed. Next, we discuss the requirements for operation, with a focus on software developed in-house for SLIM that enables high-throughput acquisition, whole slide scanning, mosaic tile registration, and imaging with a color camera. We introduce two methods for solving the inverse problem using SLIM, white-light tomography, and Wolf phase tomography. Lastly, we review the applications of SLIM in basic science and clinical studies. SLIM can study cell dynamics, cell growth and proliferation, cell migration, mass transport, etc. In clinical settings, SLIM can assist with cancer studies, reproductive technology, blood testing, etc. Finally, we review an emerging trend, where SLIM imaging in conjunction with artificial intelligence brings computational specificity and, in turn, offers new solutions to outstanding challenges in cell biology and pathology.

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.

Refractive index of biological tissues: Review, measurement techniques, and applications

Refractive index (RI) is a characteristic optical variable that controls the propagation of light in the medium (e.g., biological tissues). Basic research with the aim to investigate the RI of biological tissues is of paramount importance for biomedical optics and associated applications. Herein, we reviewed and summarized the RI data of biological tissues and the associated insights. Different techniques for the measurement of RI of biological tissues are also discussed. Moreover, several examples of the RI applications from basic research, clinics and optics industry are outlined. This study may provide a comprehensive reference for RI data of biological tissues for the biomedical research and beyond.

Malignant cell characterization via mathematical analysis of bio impedance and optical properties

Diagnosis in the early stage of breast cancer is crucial for the onset of preliminary treatment. Non-radiative bioimpedance measurement in the microwave frequency range can contribute to electrode-medium interface error and the malaise of electrode placement on the patient to take measurements. These reasons account for alternate diagnosis procedure and improved reliability of retrieved mensuration. Non-invasive optical diagnosis in the near infra-red (NIR) and visible light of the electromagnetic range is the shifting paradigm for healthcare diagnosis. An accurate quantitative measurement is unparalleled to circumvent false positives. The focus of this paper is to perform quantitative mathematical analysis for bioimpedance and optical properties for sample breast cancer cells for meticulous interpretation of malignant cell diagnosis. The analytical solution of the Cole-Cole plot, relaxation frequency, and capacitance measurement showed reliability with previous experimental findings. The dissimilitude of the frequency-dependent refractive index measurement of the malignant and healthy cell can be used by clinicians for pronouncement. The diffusion theory is also used to interpret the pathlength of the source light particle and the absorption property of the malignant cell. The synergistic analytical solutions of the bioimpedance and optical parameters can be used by licensed Physicians or Clinical Practitioners (CP) to meticulously interpret the diagnosis result. The quantitative parameters obtained from the dispersed bandwidth range from microwave to visible light offers a comprehensive understanding of the biophysical properties of the malignant cell.

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.

Phase imaging with computational specificity (PICS) for measuring dry mass changes in sub-cellular compartments

Due to its specificity, fluorescence microscopy has become a quintessential imaging tool in cell biology. However, photobleaching, phototoxicity, and related artifacts continue to limit fluorescence microscopy's utility. Recently, it has been shown that artificial intelligence (AI) can transform one form of contrast into another. We present phase imaging with computational specificity (PICS), a combination of quantitative phase imaging and AI, which provides information about unlabeled live cells with high specificity. Our imaging system allows for automatic training, while inference is built into the acquisition software and runs in real-time. Applying the computed fluorescence maps back to the quantitative phase imaging (QPI) data, we measured the growth of both nuclei and cytoplasm independently, over many days, without loss of viability. Using a QPI method that suppresses multiple scattering, we measured the dry mass content of individual cell nuclei within spheroids. In its current implementation, PICS offers a versatile quantitative technique for continuous simultaneous monitoring of individual cellular components in biological applications where long-term label-free imaging is desirable.

Quantifying myelin content in brain tissue using color Spatial Light Interference Microscopy (cSLIM)

Deficient myelination of the brain is associated with neurodevelopmental delays, particularly in high-risk infants, such as those born small in relation to their gestational age (SGA). New methods are needed to further study this condition. Here, we employ Color Spatial Light Interference Microscopy (cSLIM), which uses a brightfield objective and RGB camera to generate pathlength-maps with nanoscale sensitivity in conjunction with a regular brightfield image. Using tissue sections stained with Luxol Fast Blue, the myelin structures were segmented from a brightfield image. Using a binary mask, those portions were quantitatively analyzed in the corresponding phase maps. We first used the CLARITY method to remove tissue lipids and validate the sensitivity of cSLIM to lipid content. We then applied cSLIM to brain histology slices. These specimens are from a previous MRI study, which demonstrated that appropriate for gestational age (AGA) piglets have increased internal capsule myelination (ICM) compared to small for gestational age (SGA) piglets and that a hydrolyzed fat diet improved ICM in both. The identity of samples was blinded until after statistical analyses.

Cell refractive index: Models, insights, applications and future perspectives

Cell refractive index (RI) is an intrinsic optical parameter that governs the propagation of light (i.e., scattering and absorption) in the cell matrix. The RI of cell is sensitively correlated with its mass distribution and thereby has the capability to provide important insights for diverse biological models. Herein, we review the cell refractive index and the fundamental models for measurement of cell RI, summarize the published RI data of cell and cell organelles and discuss the associated insights. Illustrative applications of cell RI in cell biology are also outlined. Finally, future research trends and applications of cell RI, including novel imaging techniques, reshaping flow cytometry and microfluidic platforms for single cell manipulation are discussed. The rapid technological advances in optical imaging integrated with microfluidic regime seems to enable deeper understanding of subcellular dynamics with high spatio-temporal resolution in real time.

Real-time Jones phase microscopy for studying transparent and birefringent specimens

Tissue birefringence is an intrinsic marker of potential value for cancer diagnosis. Traditionally, birefringence properties have been studied by using intensity-based formalisms, through the Mueller matrix algebra. On the other hand, the Jones matrix description allows for a direct assessment of the sample's anisotropic response. However, because Jones algebra is based on complex fields, requiring measurements of both phase and amplitude, it is less commonly used. Here we propose a real-time imaging method for measuring Jones matrices by quantitative phase imaging. We combine a broadband phase imaging system with a polarization-sensitive detector to obtain Jones matrices at each point in a megapixel scale image, with near video rate capture speeds. To validate the utility of our approach, we measured standard targets, partially birefringent samples, dynamic specimens, and thinly sliced histopathological tissue.

Laser-induced autofluorescence assisted by multivariate techniques discriminates a cataractous lens from healthy lens tissues of Sprague-Dawley rats

Laser-induced autofluorescence (LIAF), combined with multivariate techniques, has been used to discriminate a cataractous lens from healthy lens tissues. In this study, 405 nm and 445 nm were used as excitation sources to induce the autofluorescence. Results show higher autofluorescence intensity in cataractous lens tissues than in healthy ones. Cataractous lens tissues show a red shift of 0.9 nm and 1.2 nm at 405 nm and 445 nm excitations, respectively. Using principal component analysis (PCA), three principal components (PCs) gave more than 99% variability for both 405 nm and 445 nm excitation sources. Based on the three PCs, Fisher's linear discriminant model was developed. An accuracy of 100% was obtained in classifying the lens tissues using Fisher's linear discriminant analysis (FLDA). The LIAF technique assisted by PCA and FLDA may be used for objective discrimination of cataractous lens from healthy lens tissues of Sprague-Dawley rats.

Multispectral sensing of biological liquids with hollow-core microstructured optical fibres

The state of the art in optical biosensing is focused on reaching high sensitivity at a single wavelength by using any type of optical resonance. This common strategy, however, disregards the promising possibility of simultaneous measurements of a bioanalyte's refractive index over a broadband spectral domain. Here, we address this issue by introducing the approach of in-fibre multispectral optical sensing (IMOS). The operating principle relies on detecting changes in the transmission of a hollow-core microstructured optical fibre when a bioanalyte is streamed through it via liquid cells. IMOS offers a unique opportunity to measure the refractive index at 42 wavelengths, with a sensitivity up to ~3000 nm per refractive index unit (RIU) and a figure of merit reaching 99 RIU-1 in the visible and near-infra-red spectral ranges. We apply this technique to determine the concentration and refractive index dispersion for bovine serum albumin and show that the accuracy meets clinical needs.

Wolf phase tomography (WPT) of transparent structures using partially coherent illumination

In 1969, Emil Wolf proposed diffraction tomography using coherent holographic imaging to extract 3D information from transparent, inhomogeneous objects. In the same era, the Wolf equations were first used to describe the propagation correlations associated with partially coherent fields. Combining these two concepts, we present Wolf phase tomography (WPT), which is a method for performing diffraction tomography using partially coherent fields. WPT reconstruction works directly in the space-time domain, without the need for Fourier transformation, and decouples the refractive index (RI) distribution from the thickness of the sample. We demonstrate the WPT principle using the data acquired by a quantitative-phase-imaging method that upgrades an existing phase-contrast microscope by introducing controlled phase shifts between the incident and scattered fields. The illumination field in WPT is partially spatially coherent (emerging from a ring-shaped pupil function) and of low temporal coherence (white light), and as such, it is well suited for the Wolf equations. From three intensity measurements corresponding to different phase-contrast frames, the 3D RI distribution is obtained immediately by computing the Laplacian and second time derivative of the measured complex correlation function. We validate WPT with measurements of standard samples (microbeads), spermatozoa, and live neural cultures. The high throughput and simplicity of this method enables the study of 3D, dynamic events in living cells across the entire multiwell plate, with an RI sensitivity on the order of 10^-5.

Wolf phase tomography (WPT) of transparent structures using partially coherent illumination

In 1969, Emil Wolf proposed diffraction tomography using coherent holographic imaging to extract 3D information from transparent, inhomogeneous objects. In the same era, the Wolf equations were first used to describe the propagation correlations associated with partially coherent fields. Combining these two concepts, we present Wolf phase tomography (WPT), which is a method for performing diffraction tomography using partially coherent fields. WPT reconstruction works directly in the space-time domain, without the need for Fourier transformation, and decouples the refractive index (RI) distribution from the thickness of the sample. We demonstrate the WPT principle using the data acquired by a quantitative-phase-imaging method that upgrades an existing phase-contrast microscope by introducing controlled phase shifts between the incident and scattered fields. The illumination field in WPT is partially spatially coherent (emerging from a ring-shaped pupil function) and of low temporal coherence (white light), and as such, it is well suited for the Wolf equations. From three intensity measurements corresponding to different phase-contrast frames, the 3D RI distribution is obtained immediately by computing the Laplacian and second time derivative of the measured complex correlation function. We validate WPT with measurements of standard samples (microbeads), spermatozoa, and live neural cultures. The high throughput and simplicity of this method enables the study of 3D, dynamic events in living cells across the entire multiwell plate, with an RI sensitivity on the order of 10-5.

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.

Feasibility and Safety of a Coaxial Dual-Wavelength Optical Coherence Tomography Apparatus

PURPOSE

To evaluate the feasibility and safety of a coaxial dual-wavelength optical coherence tomography (OCT) device (marked as Hydra-OCT).

METHODS

Healthy participants without ocular pathology underwent retinal imaging using the Hydra-OCT allowing for simultaneous measurement of retinal scanning of 840 and 1,072 nm wavelength. Before and after measurement, best-corrected visual acuity and patients' comfort were assessed. Representative OCT images from both wavelengths were compared by 5 independent graders using a subjective grading scheme.

RESULTS

A total of 30 eyes of 30 participants (8 females and 22 males) with a mean age of 26.5 years (range from 19 to 55 years) were included. Dual-wavelength image acquisition was made possible in each subject. The participant's effort and comfort assessment using the Hydra-OCT imaging revealed an equivalent value as compared to the commercially available OCT machine. No adverse events were reported, and visual acuity was not altered by the Hydra-OCT. Imaging between the systems was comparable.

CONCLUSIONS

This study provides evidence for the feasibility and safety of a coaxial dual-wavelength OCT imaging method under real-life conditions. The novel Hydra-OCT imaging device may offer additional insights into the pathology of retinal and choroidal diseases.