Optical properties of acute kidney injury measured by quantitative phase imaging

Pre-transplant kidney quality evaluation using photoacoustic imaging during normothermic machine perfusion

Due to the shortage of kidneys donated for transplantation, surgeons are forced to use the organs with an elevated risk of poor function or even failure. Although the existing methods for pre-transplant quality evaluation have been validated over decades in population cohort studies across the world, new methods are needed as long as delayed graft function or failure in a kidney transplant occurs. In this study, we explored the potential of utilizing photoacoustic (PA) imaging during normothermic machine perfusion (NMP) as a means of evaluating kidney quality. We closely monitored twenty-two porcine kidneys using 3D PA imaging during a two-hour NMP session. Based on biochemical analyses of perfusate and produced urine, the kidneys were categorized into 'non-functional' and 'functional' groups. Our primary focus was to quantify oxygenation (sO2) within the kidney cortical layer of depths 2 mm, 4 mm, and 6 mm using two-wavelength PA imaging. Next, receiver operating characteristic (ROC) analysis was performed to determine an optimal cortical layer depth and time point for the quantification of sO2 to discriminate between functional and non-functional organs. Finally, for each depth, we assessed the correlation between sO2 and creatinine clearance (CrCl), oxygen consumption (VO2), and renal blood flow (RBF). We found that hypoxia of the renal cortex is associated with poor renal function. In addition, the determination of sO2 within the 2 mm depth of the renal cortex after 30 min of NMP effectively distinguishes between functional and non-functional kidneys. The non-functional kidneys can be detected with the sensitivity and specificity of 80% and 85% respectively, using the cut-off point of sO2 < 39%. Oxygenation significantly correlates with RBF and VO2 in all kidneys. In functional kidneys, sO2 correlated with CrCl, which is not the case for non-functional kidneys. We conclude that the presented technique has a high potential for supporting organ selection for kidney transplantation.

Implementation of a portable diffraction phase microscope for digital histopathology

Quantitative phase imaging (QPI) has a significant advantage in histopathology as it helps in differentiating biological tissue structures and cells without the need for staining. To make this capability more accessible, it is crucial to develop compact and portable systems. In this study, we introduce a portable diffraction phase microscopy (DPM) system that allows the acquisition of phase map images from various organs in mice using a low-NA objective lens. Our findings indicate that the cell and tissue structures observed in portable DPM images are similar to those seen in conventional histology microscope images. We confirmed that the developed system's performance is comparable to the benchtop DPM system. Additionally, we investigate the potential utility of digital histopathology by applying deep learning technology to create virtual staining of DPM images.

Multi-contrast digital histopathology of mouse organs using quantitative phase imaging and virtual staining

Quantitative phase imaging (QPI) has emerged as a new digital histopathologic tool as it provides structural information of conventional slide without staining process. It is also capable of imaging biological tissue sections with sub-nanometer sensitivity and classifying them using light scattering properties. Here we extend its capability further by using optical scattering properties as imaging contrast in a wide-field QPI. In our first step towards validation, QPI images of 10 major organs of a wild-type mouse have been obtained followed by H&E-stained images of the corresponding tissue sections. Furthermore, we utilized deep learning model based on generative adversarial network (GAN) architecture for virtual staining of phase delay images to a H&E-equivalent brightfield (BF) image analogues. Using the structural similarity index, we demonstrate similarities between virtually stained and H&E histology images. Whereas the scattering-based maps look rather similar to QPI phase maps in the kidney, the brain images show significant improvement over QPI with clear demarcation of features across all regions. Since our technology provides not only structural information but also unique optical property maps, it could potentially become a fast and contrast-enriched histopathology technique.

Label-free SARS-CoV-2 detection and classification using phase imaging with computational specificity

Efforts to mitigate the COVID-19 crisis revealed that fast, accurate, and scalable testing is crucial for curbing the current impact and that of future pandemics. We propose an optical method for directly imaging unlabeled viral particles and using deep learning for detection and classification. An ultrasensitive interferometric method was used to image four virus types with nanoscale optical path-length sensitivity. Pairing these data with fluorescence images for ground truth, we trained semantic segmentation models based on U-Net, a particular type of convolutional neural network. The trained network was applied to classify the viruses from the interferometric images only, containing simultaneously SARS-CoV-2, H1N1 (influenza-A virus), HAdV (adenovirus), and ZIKV (Zika virus). Remarkably, due to the nanoscale sensitivity in the input data, the neural network was able to identify SARS-CoV-2 vs. the other viruses with 96% accuracy. The inference time for each image is 60 ms, on a common graphic-processing unit. This approach of directly imaging unlabeled viral particles may provide an extremely fast test, of less than a minute per patient. As the imaging instrument operates on regular glass slides, we envision this method as potentially testing on patient breath condensates. The necessary high throughput can be achieved by translating concepts from digital pathology, where a microscope can scan hundreds of slides automatically.

Monitoring reactivation of latent HIV by label-free gradient light interference microscopy

Human immunodeficiency virus (HIV) can infect cells and take a quiescent and nonexpressive state called latency. In this study, we report insights provided by label-free, gradient light interference microscopy (GLIM) about the changes in dry mass, diameter, and dry mass density associated with infected cells that occur upon reactivation. We discovered that the mean cell dry mass and mean diameter of latently infected cells treated with reactivating drug, TNF-α, are higher for latent cells that reactivate than those of the cells that did not reactivate. Cells with mean dry mass and diameter less than approximately 10 pg and 8 μm, respectively, remain exclusively in the latent state. Also, cells with mean dry mass greater than approximately 28-30 pg and mean diameter greater than 11–12 μm have a higher probability of reactivating. This study is significant as it presents a new label-free approach to quantify latent reactivation of a virus in single cells.

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GLIM imaging reveals differences between latent and reactivated HIV in JLat cells

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Cells with reactivated HIV have higher dry mass and diameter

Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Spatial transcriptomic and proteomic technologies have provided new opportunities to investigate cells in their native microenvironment. Here we present Giotto, a comprehensive and open-source toolbox for spatial data analysis and visualization. The analysis module provides end-to-end analysis by implementing a wide range of algorithms for characterizing tissue composition, spatial expression patterns, and cellular interactions. Furthermore, single-cell RNAseq data can be integrated for spatial cell-type enrichment analysis. The visualization module allows users to interactively visualize analysis outputs and imaging features. To demonstrate its general applicability, we apply Giotto to a wide range of datasets encompassing diverse technologies and platforms.

Toward image quality assessment in optical coherence tomography (OCT) of rat kidney

BACKGROUND

Optical coherence tomography (OCT) is a useful tool for the evaluation of structure and function of the kidney, but the image quality can be effected by many factors.

OBJECTIVE

The objective of this study was to assess the image quality of different OCT systems in OCT imaging of the living kidney.

METHODS

One swept-source OCT (SSOCT) of 1300 nm, one spectral domain OCT (SDOCT) of 1300 nm and another of 900 nm were used. A FeO phantom was used to establish the point spread function (PSF). Rat kidneys were imaged for image quality assessment. Light penetration in the kidney and the optical attenuation coefficient were also evaluated. The quantification of uriniferous tubules was carried out via the threshold segmentation of 3D OCT images.

RESULTS

The quality of kidney images was resolution dependent. SDOCT of 900 nm showed higher peak signal-to noise ratio and dynamic range. The spatial resolution in the light field could be derived from the PSF distribution along three mutually orthogonal axes. In conjunction with the PSF, the Lucy-Richardson algorithm could improve image quality but could not reveal more microstructural information. The penetration depth of 1300 nm was deeper than that of 900 nm. The attenuation coefficient of the kidney was 29 cm^-1 at 1300 nm and 50 cm^-1 at 900 nm (P < 0.001). More accurate measurement of uriniferous tubules was achieved with the SDOCT-900 due to its higher resolution.

CONCLUSIONS

Both SSOCT and SDOCT systems could be useful for imaging uriniferous tubules in the superficial layers of the cortex. The OCT image quality was highly correlated with the spatial resolution of OCT system.

Tissue spatial correlation as cancer marker

We propose an intrinsic cancer marker in fixed tissue biopsy slides, which is based on the local spatial autocorrelation length obtained from quantitative phase images. The spatial autocorrelation length in a small region of the tissue phase image is sensitive to the nanoscale cellular morphological alterations and can hence inform on carcinogenesis. Therefore, this metric can potentially be used as an intrinsic cancer marker in histopathology. Typically, these correlation length maps are calculated by computing two-dimensional Fourier transforms over image subregions-requiring long computational times. We propose a more time-efficient method of computing the correlation map and demonstrate its value for diagnosis of benign and malignant breast tissues. Our methodology is based on highly sensitive quantitative phase imaging data obtained by spatial light interference microscopy.

A Wearable Fiberless Optical Sensor for Continuous Monitoring of Cerebral Blood Flow in Mice

Continuous and longitudinal monitoring of cerebral blood flow (CBF) in animal models provides information for studying the mechanisms and interventions of various cerebral diseases. Since anesthesia may affect brain hemodynamics, researchers have been seeking wearable devices for use in conscious animals. We present a wearable diffuse speckle contrast flowmeter (DSCF) probe for monitoring CBF variations in mice. The DSCF probe consists of a small low-power near-infrared laser diode as a point source and an ultra-small low-power CMOS camera as a 2D detector array, which can be affixed on a mouse head. The movement of red blood cells in brain cortex (i.e., CBF) produces spatial fluctuations of laser speckles, which are captured by the camera. The DSCF system was calibrated using tissue phantoms and validated in a human forearm and mouse brains for continuous monitoring of blood flow increases and decreases against the established technologies. Significant correlations were observed among these measurements (R² ≥ 0.80, p < 10^-5). This small fiberless probe has the potential to be worn by a freely moving conscious mouse. Moreover, the flexible source-detector configuration allows for varied probing depths up to ~8 mm, which is sufficient for transcranially detecting CBF in the cortices of rodents and newborn infants.

Morphological changes in the ovarian carcinoma cells of Wistar rats induced by chemotherapy with cisplatin and dioxadet

The development of new express methods for the analysis of the efficacy of anti-cancer therapy on the cellular level is highly desirable for the analysis of chemotherapeutic agent performance. In this paper we suggest the use of parameters of cell morphology determined by holographic microscopy and tomography for the effective label free quantitative analysis of cell viability under antitumor chemotherapy and thus of cytostatic agent efficacy. As shown, measured phase shifts and cell morphology change dramatically as a result of chemotherapy and depend strongly on the cell type and agent applied. Experimentally, a comparative analysis of the antitumor efficacy of the two cytostatics, cisplatin and dioxadet, that are commonly used for chemotherapy of disseminated ovarian carcinoma has been performed. The experiments were carried out on the Wistar rat model. An essential difference in the morphology of cells, both normal (erythrocytes) and cancerous, present in ascitic fluid taken from the non-treated group of rats and the groups treated with either dioxadet or cisplatin, has been observed. The results obtained can be interpreted as an indication of the antitumor performance of both cytostatics at the cellular level and as a demonstration of the higher efficacy of therapy with dioxadet as compared to that with cisplatin. Differences in cell morphology are suggested to be applied as quantitative markers of cell viability and cytostatic agent efficacy. The conclusions made are supported by a comparison with the results of recent experiments based on survival rates of laboratory animals treated with these agents..

Effect of tissue staining in quantitative phase imaging

Quantitative phase imaging (QPI) is an emerging modality, which enables the identification of abnormalities in tissue based on optical properties. QPI can be applied to any biological specimen due to its label-free imaging capability, but its use in stained tissue is unclear. Here, we study the variability of QPI with the staining dye. Several tissues such as brain, heart and lung were stained with hematoxylin and eosin, and their optical properties compared at 550 and 730 nm. Our results showed that phase and scattering coefficients varied when QPI was used at the absorption wavelength of the staining dye. We also found that the variation of optical properties was dependent on tissue morphology.