Ultraviolet Hyperspectral Interferometric Microscopy

Detecting and differentiating neurotransmitters using ultraviolet plasmonic engineered native fluorescence

Detecting neurotransmitters with high sensitivity and selectivity is important to understand their roles in biological functions. Current detection methods for neurotransmitters suffer from poor sensitivity or selectivity. In this article, we propose ultraviolet (UV) plasmonic engineered native fluorescence as a new sensing mechanism to detect neurotransmitters with high sensitivity and selectivity. We measured the native fluorescence of three monoamine neurotransmitters, dopamine (DA), norepinephrine (NE), and 3,4-dihydroxyphenylacetic acid (DOPAC). The average net enhancement and total photon yield enhancement on an aluminum hole array with 300 nm hole spacing substrate were found to be 50× and 60×, for the three molecules. We also observed a 1.5-1.7× reduction in the dominant photon bleaching rate on an aluminum hole array compared to an aluminum-thin film substrate. The photobleaching rates of the native fluorescence of DA, NE and DOPAC were found to be highly sensitive to their molecular structures and can be further engineered by UV plasmonic substrates. The differences in the photobleaching rates for DA and NE were 2× and 1.6× larger on an aluminum thin film and an aluminum hole array than on a silicon substrate. As a proof-of-concept experiment, we mixed DA with NE at different concentration ratios and measured the average photobleaching rates of the mixture. We found that the average photobleaching rate is proportional to the concentration of NE in the mixture. Our findings demonstrate the potential of UV plasmonic engineered native fluorescence to achieve sensitive and selective detection of neurotransmitters.

Deep ultraviolet high-resolution microscopic hyperspectral imager and its biological tissue detection

Ultraviolet (UV) hyperspectral imaging technology is commonly used in the field of atmospheric remote sensing. In recent years, some in-laboratory research has been carried out for substance detection and identification. In this paper, UV hyperspectral imaging technology is introduced into microscopy to better utilize the obvious absorption characteristics of components, such as proteins and nucleic acids in biological tissues in the ultraviolet band. A deep UV microscopic hyperspectral imager based on the Offner structure with F # 2.5, low spectral keystone and smile is designed and developed. A 0.68 numerical aperture microscope objective is designed. The spectral range of the system is from 200 nm to 430 nm; the spectral resolution is better than 0.5 nm; and the spatial resolution is better than 1.3 µm. The K562 cells can be distinguished by transmission spectrum of nucleus. The UV microscopic hyperspectral image of the unstained mouse liver slices showed similar results to the microscopic image after hematoxylin and eosin staining, which could help to simplify the pathological examination process. Both results show a great performance in spatial and spectral detecting capabilities of our instrument, which has the potential for biomedical research and diagnosis.

Compact and low-cost deep-ultraviolet microscope system for label-free molecular imaging and point-of-care hematological analysis

Deep-ultraviolet (UV) microscopy enables label-free, high-resolution, quantitative molecular imaging and enables unique applications in biomedicine, including the potential for fast hematological analysis at the point-of-care. UV microscopy has been shown to quantify hemoglobin content and white blood cells (five-part differential), providing a simple alternative to the current gold standard, the hematological analyzer. Previously, however, the UV system comprised a bulky broadband laser-driven plasma light source along with a large and expensive camera and 3D translation stage. Here, we present a modified deep-UV microscope system with a compact footprint and low-cost components. We detail the novel design with simple, inexpensive optics and hardware to enable fast and accurate automated imaging. We characterize the system, including a modified low-cost web-camera and custom automated 3D translation stage, and demonstrate its ability to scan and capture large area images. We further demonstrate the capability of the system by imaging and analyzing blood smears, using previously trained networks for automatic segmentation, classification (including 5-part white blood cell differential), and colorization. The developed system is approximately 10 times less expensive than previous configurations and can serve as a point-of-care hematology analyzer, as well as be applied broadly in biomedicine as a simple compact, low-cost, quantitative molecular imaging system.

Rapid and label-free histological imaging of unprocessed surgical tissues via dark-field reflectance ultraviolet microscopy

Routine examination for intraoperative histopathologic assessment is lengthy and laborious. Here, we present the dark-field reflectance ultraviolet microscopy (DRUM) that enables label-free imaging of unprocessed and thick tissues with subcellular resolution and a high signal-to-background ratio. To the best of our knowledge, DRUM provides image results for pathological assessment with the shortest turnaround time (2-3 min in total from sample preparation to tissue imaging). We also proposed a virtual staining process to convert DRUM images into pseudo-colorized images and enhance the image familiarity of pathologists. By imaging various tissues, we found DRUM can resolve cell nuclei and some extranuclear features, which are comparable to standard H&E images. Furthermore, the essential diagnostic features of intraoperatively excised tumor tissues also can be revealed by DRUM, demonstrating its potential as an additional aid for intraoperative histopathology.

Label-free deep-UV microscopy detection and grading of neutropenia using a passive microfluidic device

Neutropenia is a condition comprising an abnormally low number of neutrophils, a type of white blood cell, which puts patients at an increased risk of severe infections. Neutropenia is especially common among cancer patients and can disrupt their treatment or even be life-threatening in severe cases. Therefore, routine monitoring of neutrophil counts is crucial. However, the current standard of care to assess neutropenia, the complete blood count (CBC), is resource-intensive, time-consuming, and expensive, thereby limiting easy or timely access to critical hematological information such as neutrophil counts. Here, we present a simple technique for fast, label-free neutropenia detection and grading via deep-ultraviolet (deep-UV) microscopy of blood cells in polydimethylsiloxane (PDMS)-based passive microfluidic devices. The devices can potentially be manufactured in large quantities at a low cost, requiring only 1 μL of whole blood for operation. We show that the absolute neutrophil counts (ANC) obtained from our proposed microfluidic device-enabled deep-UV microscopy system are highly correlated with those from CBCs using commercial hematology analyzers in patients with moderate and severe neutropenia, as well as healthy donors. This work lays the foundation for the development of a compact, easy-to-use UV microscope system to track neutrophil counts that is suitable for low-resource, at-home, or point-of-care settings.

Specific refraction-index increments of oxygenated hemoglobin from thalassemia-minor patients are not significantly different than those from healthy individuals

The mass and concentration of hemoglobin per erythrocyte are important hematological parameters. Measuring these parameters from intact erythrocytes requires the value of specific refraction-index increment (RII) of oxygenated hemoglobin, which diverges in the literature. Refractive indices of hemoglobin solutions are measured directly by digital holographic microscopy on a microfluidic channel filled with hemoglobin solutions prepared by hemolysis of fresh human erythrocytes and refractive-index standards sequentially. Hemoglobin extracted from thalassemic patients shows 3-4% higher RII than that from healthy volunteers, but the difference is not significant in comparison to inter-subject variations within each group. The quantified RIIs are applied to quantify mean corpuscular hemoglobin mass of blood from 37 human subjects, and results are in accord with standard clinical test results.

Virtual Staining, Segmentation, and Classification of Blood Smears for Label-Free Hematology Analysis

Objective and Impact Statement. We present a fully automated hematological analysis framework based on single-channel (single-wavelength), label-free deep-ultraviolet (UV) microscopy that serves as a fast, cost-effective alternative to conventional hematology analyzers. Introduction. Hematological analysis is essential for the diagnosis and monitoring of several diseases but requires complex systems operated by trained personnel, costly chemical reagents, and lengthy protocols. Label-free techniques eliminate the need for staining or additional preprocessing and can lead to faster analysis and a simpler workflow. In this work, we leverage the unique capabilities of deep-UV microscopy as a label-free, molecular imaging technique to develop a deep learning-based pipeline that enables virtual staining, segmentation, classification, and counting of white blood cells (WBCs) in single-channel images of peripheral blood smears. Methods. We train independent deep networks to virtually stain and segment grayscale images of smears. The segmented images are then used to train a classifier to yield a quantitative five-part WBC differential. Results. Our virtual staining scheme accurately recapitulates the appearance of cells under conventional Giemsa staining, the gold standard in hematology. The trained cellular and nuclear segmentation networks achieve high accuracy, and the classifier can achieve a quantitative five-part differential on unseen test data. Conclusion. This proposed automated hematology analysis framework could greatly simplify and improve current complete blood count and blood smear analysis and lead to the development of a simple, fast, and low-cost, point-of-care hematology analyzer.

Prostate cancer histopathology using label-free multispectral deep-UV microscopy quantifies phenotypes of tumor aggressiveness and enables multiple diagnostic virtual stains

Identifying prostate cancer patients that are harboring aggressive forms of prostate cancer remains a significant clinical challenge. Here we develop an approach based on multispectral deep-ultraviolet (UV) microscopy that provides novel quantitative insight into the aggressiveness and grade of this disease, thus providing a new tool to help address this important challenge. We find that UV spectral signatures from endogenous molecules give rise to a phenotypical continuum that provides unique structural insight (i.e., molecular maps or “optical stains") of thin tissue sections with subcellular (nanoscale) resolution. We show that this phenotypical continuum can also be applied as a surrogate biomarker of prostate cancer malignancy, where patients with the most aggressive tumors show a ubiquitous glandular phenotypical shift. In addition to providing several novel “optical stains” with contrast for disease, we also adapt a two-part Cycle-consistent Generative Adversarial Network to translate the label-free deep-UV images into virtual hematoxylin and eosin (H&E) stained images, thus providing multiple stains (including the gold-standard H&E) from the same unlabeled specimen. Agreement between the virtual H&E images and the H&E-stained tissue sections is evaluated by a panel of pathologists who find that the two modalities are in excellent agreement. This work has significant implications towards improving our ability to objectively quantify prostate cancer grade and aggressiveness, thus improving the management and clinical outcomes of prostate cancer patients. This same approach can also be applied broadly in other tumor types to achieve low-cost, stain-free, quantitative histopathological analysis.

Label-free automated neutropenia detection and grading using deep-ultraviolet microscopy

Neutropenia is a condition identified by an abnormally low number of neutrophils in the bloodstream and signifies an increased risk of severe infection. Cancer patients are particularly susceptible to this condition, which can be disruptive to their treatment and even life-threatening in severe cases. Thus, it is critical to routinely monitor neutrophil counts in cancer patients. However, the standard of care to assess neutropenia, the complete blood count (CBC), requires expensive and complex equipment, as well as cumbersome procedures, which precludes easy or timely access to critical hematological information, namely neutrophil counts. Here we present a simple, low-cost, fast, and robust technique to detect and grade neutropenia based on label-free multi-spectral deep-UV microscopy. Results show that the developed framework for automated segmentation and classification of live, unstained blood cells in a smear accurately differentiates patients with moderate and severe neutropenia from healthy samples in minutes. This work has significant implications towards the development of a low-cost and easy-to-use point-of-care device for tracking neutrophil counts, which can not only improve the quality of life and treatment-outcomes of many patients but can also be lifesaving.

Label-free imaging and classification of live P. falciparum enables high performance parasitemia quantification without fixation or staining

Manual microscopic inspection of fixed and stained blood smears has remained the gold standard for Plasmodium parasitemia analysis for over a century. Unfortunately, smear preparation consumes time and reagents, while manual microscopy is skill-dependent and labor-intensive. Here, we demonstrate that deep learning enables both life stage classification and accurate parasitemia quantification of ordinary brightfield microscopy images of live, unstained red blood cells. We tested our method using both a standard light microscope equipped with visible and near-ultraviolet (UV) illumination, and a custom-built microscope employing deep-UV illumination. While using deep-UV light achieved an overall four-category classification of Plasmodium falciparum blood stages of greater than 99% and a recall of 89.8% for ring-stage parasites, imaging with near-UV light on a standard microscope resulted in 96.8% overall accuracy and over 90% recall for ring-stage parasites. Both imaging systems were tested extrinsically by parasitemia titration, revealing superior performance over manually-scored Giemsa-stained smears, and a limit of detection below 0.1%. Our results establish that label-free parasitemia analysis of live cells is possible in a biomedical laboratory setting without the need for complex optical instrumentation. We anticipate future extensions of this work could enable label-free clinical diagnostic measurements, one day eliminating the need for conventional blood smear analysis.

Hemoglobin quantification in red blood cells via dry mass mapping based on UV absorption

SIGNIFICANCE

The morphological properties and hemoglobin (Hb) content of red blood cells (RBCs) are essential biomarkers to diagnose or monitor various types of hematological disorders. Label-free mass mapping approaches enable accurate Hb quantification from individual cells, serving as promising alternatives to conventional hematology analyzers. Deep ultraviolet (UV) microscopy is one such technique that allows high-resolution, molecular imaging, and absorption-based mass mapping.

AIM

To compare UV absorption-based mass mapping at four UV wavelengths and understand variations across wavelengths and any assumptions necessary for accurate Hb quantification.

APPROACH

Whole blood smears are imaged with a multispectral UV microscopy system, and the RBCs' dry masses are computed. This approach is compared to quantitative phase imaging-based mass mapping using data from an interferometric UV imaging system.

RESULTS

Consistent Hb mass and mean corpuscular Hb values are obtained at all wavelengths, with the precision of the single-cell mass measurements being nearly identical at 220, 260, and 280 nm but slightly lower at 300 nm.

CONCLUSIONS

A full hematological analysis (including white blood cell identification and characterization, and Hb quantification) may be achieved using a single UV illumination wavelength, thereby improving the speed and cost-effectiveness.

Label-free hematology analysis using deep-ultraviolet microscopy

Hematological analysis, via a complete blood count (CBC) and microscopy, is critical for screening, diagnosing, and monitoring blood conditions and diseases but requires complex equipment, multiple chemical reagents, laborious system calibration and procedures, and highly trained personnel for operation. Here we introduce a hematological assay based on label-free molecular imaging with deep-ultraviolet microscopy that can provide fast quantitative information of key hematological parameters to facilitate and improve hematological analysis. We demonstrate that this label-free approach yields 1) a quantitative five-part white blood cell differential, 2) quantitative red blood cell and hemoglobin characterization, 3) clear identification of platelets, and 4) detailed subcellular morphology. Analysis of tens of thousands of live cells is achieved in minutes without any sample preparation. Finally, we introduce a pseudocolorization scheme that accurately recapitulates the appearance of cells under conventional staining protocols for microscopic analysis of blood smears and bone marrow aspirates. Diagnostic efficacy is evaluated by a panel of hematologists performing a blind analysis of blood smears from healthy donors and thrombocytopenic and sickle cell disease patients. This work has significant implications toward simplifying and improving CBC and blood smear analysis, which is currently performed manually via bright-field microscopy, and toward the development of a low-cost, easy-to-use, and fast hematological analyzer as a point-of-care device and for low-resource settings.

Ultraviolet hyperspectral microscopy using chromatic-aberration-based iterative phase recovery

Ultraviolet (UV) microscopy has recently re-emerged as an important label-free, molecular imaging technique. This stems from the unique UV absorption properties of many endogenous biomolecules that play a critical role in cell structure and function. However, broadband hyperspectral imaging in this spectral region is challenging due to strong chromatic aberrations inherent in UV systems. Here we apply an intensity-based, two-stage, iterative phase-recovery algorithm that leverages the same chromatic aberrations to overcome this challenge. Importantly, knowledge of samples' dispersion or absorption properties is not required. We demonstrate that the computationally retrieved phase can be applied to digitally refocus images across a large bandwidth. This enables hyperspectral UV imaging with a simple microscope for quantitative molecular analysis. We validate this method through simulations and through experiments with red blood cells.

Low-coherent optical diffraction tomography by angle-scanning illumination

Temporally low-coherent optical diffraction tomography (ODT) is proposed and demonstrated based on angle-scanning Mach-Zehnder interferometry. Using a digital micromirror device based on diffractive tilting, the full-field interference of incoherent light is successfully maintained during every angle-scanning sequences. Further, current ODT reconstruction principles for temporally incoherent illuminations are thoroughly reviewed and developed. Several limitations of incoherent illumination are also discussed, such as the nondispersive assumption, optical sectioning capacity and illumination angle limitation. Using the proposed setup and reconstruction algorithms, low-coherent ODT imaging of plastic microspheres, human red blood cells and rat pheochromocytoma cells is experimentally demonstrated.

Refractive index of human red blood cells between 290 nm and 1100 nm determined by optical extinction measurements

The knowledge of optical properties of biological cells is essential to interpret their interaction with light and to derive morphological information and parameters associated with cell function like the oxygen transport capacity of human red blood cells (RBCs). We present a method to determine the dependence between the refractive index (RI) of human RBCs and their intracellular hemoglobin (Hb) concentration from spectral extinction measurements of a cell suspension. The procedure is based on the analysis of the corresponding ensemble averaged extinction cross section \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\bar{{\boldsymbol{C}}}}_{{\bf{e}}{\bf{x}}{\bf{t}}}(\lambda )$$\end{document}C¯ext(λ). Thus far two complementary approaches have been taken to derive RIs of RBCs. The first one uses homogeneous macroscopic samples prepared by hemolysis for the destruction of the RBCs’ membranes and subsequent centrifugation. A second approach is the determination of RIs of single intact cells by microscopic investigation. These techniques are limited to a few discrete wavelengths or a rather narrow wavelength range. In addition most of these techniques require additional information about the concentration dependence. In contrast, our approach yields the RI increment with Hb concentration of intact, reversibly isovolumetrically sphered, oxygenated RBCs over a wide wavelength range from 290 nm to 1100 nm from macroscopic measurements.

Deep UV dispersion and absorption spectroscopy of biomolecules

Owing to the high precision and sensitivity of optical systems, there is an increasing demand for optical methods that quantitatively characterize the physical and chemical properties of biological samples. Information extracted from such quantitative methods, through phase and/or amplitude variations of light, can be crucial in the diagnosis, treatment and study of disease. In this work we apply a recently developed quantitative method, called ultraviolet hyperspectral interferometry (UHI), to characterize the dispersion and absorbing properties of various important biomolecules. Our system consists of (1) a broadband light source that spans from the deep-UV to the visible region of the spectrum, and (2) a Mach-Zehnder interferometer to gain access to complex optical properties. We apply this method to characterize (and tabulate) the dispersive and absorptive properties of hemoglobin, beta nicotinamide adenine dinucleotide (NAD), flavin adenine dinucleotide (FAD), elastin, collagen, cytochrome c, tryptophan and DNA. Our results shed new light on the complex properties of important biomolecules.