The diagnosis of acute kidney disease (AKI) has been examined mainly by histology, immunohistochemistry and western blot. Though these approaches are widely accepted in the field, it has an inherent limitation due to the lack of high-throughput and quantitative information. For a better understanding of prognosis in AKI, we present a new approach using quantitative phase imaging combined with a wide-field scanning platform. Through the phase-delay information from the tissue, we were able to predict a stage of AKI based on various optical properties such as light scattering coefficient and anisotropy. These optical parameters quantify the deterioration process of the AKI model of tissue. Our device would be a very useful tool when it is required to deliver fast feedback of tissue pathology or when diseases are related to mechanical properties such as fibrosis.
© 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
Acute kidney injury (AKI) is characterized by sudden loss of renal ability of wasting materials from the blood. In order to verify the abnormalities caused by AKI, the renal histopathological study has been investigated based on standard hematoxylin and eosin (H&E) staining or selectively labeled-tagging molecules with specific immuno-histochemical stains. Failure of accurate prediction of kidney damage and alterations associated with AKI represents a major clinical problem. Thus, it is very important to quantitatively track the tissue deterioration during disease progression. Existing imaging methods for the kidney study include magnetic resonance imaging (MRI) and positron emission tomography (PET), which have a limited low spatial resolution of around 100 µm . Micro computed tomography (µCT) can achieve higher spatial resolution up to 1 µm, and is currently being used in order to quantify blood vessel architecture in kidney ex vivo. However, it requires adequate amount of contrast agent . Histological imaging technique for sliced thin tissue in 4 – 5 µm has been the gold standard for diagnosis of renal failure ranging from the subcellular scale to several millimeter scale. However, this approach requires manual investigation by a pathologist, and the result brings about only qualitative analysis. Furthermore, high contrast fluorescence imaging of endogenous/exogenous fluorophores has been used in addressing progressive renal tubule-interstitial fibrosis, but this type of imaging also requires many steps of sample preparation . Complementary label-free imaging techniques, such as optical coherence tomography (OCT) were employed in renal studies due to its relatively high penetration depth [4, 5]. However, they only provide a limited information of sample characteristic such as morphology and anatomical feature. Recently, quantitative phase imaging (QPI) has emerged as a new tool for measuring refractive index distribution in various types of cell membrane including, i.e., neurons, HeLa, bovine/human sperm, red blood cell (RBC), etc [6–14]. QPI has also demonstrated its great potential to be used in turbid media combined with microfluidic channel [15–21], and in tissue level with nanoscale sensitivity [22–24]. Complex optical fields measured by interferometry can be employed in many biological applications by calculating optical parameter including dry mass density and refractive index (RI) of tissues . Using RI values from different types of tissue, optical parameter of scattering coefficient and anisotropy highlight unique tissue characteristics [26, 27]. Not only to normal tissues, QPI has also showed great possibility for uncovering tissue properties in disease models such as prostate and breast cancer [28, 29].
Here, we present a label-free approach to quantitatively measure optical properties of acute kidney disease. Diffraction phase microscopy (DPM)  equipped with XY motorized stages is a wide-field QPI technique which allows for the label-free visualization of the kidney anatomy over broad spatial scales. It demonstrates that our method shed light on previously unknown tissue properties affected by renal disease. In particular, AKI, one of the typical renal diseases, was investigated in terms of phase delay, retrieved scattering coefficient (µs) and anisotropy (g). Compared to healthy kidney tissue, we observed altered anatomical structure and optical parameter distribution in the disease model. Our results show that the label-free DPM technique provides great capability as a valuable tool complement to existing gold standard in pathophysiology of AKI and nephrology.
2. Materials and method
2.1 Sample preparation
All animal procedures were carried out in accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. The animal protocol was approved by Animal Care and Use Committee in Ulsan National Institute of Science and Technology (UNIST IACUC-15-27). All experiments were conducted using 8 weeks old male C57BL/6 mice. The mice were sacrificed after deep anesthetization by intraperitoneal injection of Zoletil (30 mg/kg) and Rompun (10 mg/kg) mixture. Then, the kidney sample that was transcardially perfusion-fixed were incubated in 10% neutral buffered formalin for 24 hours at 4°C, and dehydrated through graded ethanol and xylene, and infiltrated with paraffin wax. The paraffin embedded kidney sample was dissected out along the coronal plane with thickness of 5 μm by microtome (catalog no. RM2255. Leica). Every histological sections of the mouse kidney were prepared according to the standard procedures. Prior to imaging, the paraffin was completely removed by washes with xylene and gradedethanol. After DPM analysis, the samples were stained with hematoxylin and eosin dye according to standard procedure. The corresponding sections were imaged by virtual microscope slide scanning system (.slide, OLYMPUS) for comparison.
2.2 Acute kidney injury model
The mice were anesthetized with Zoletil (30 mg/kg) and Rompun (10 mg/kg) mixture. After haircut, right kidney was exposed through the site of the right flank incision. Ischemia/reperfusion injury was induced for 30 min by clamping renal pedicle with nontraumatic micro-aneurysm clamp (Roboz Surgical Instruments, Washington, DC). When clamp were removed, reperfusion was confirmed completely. Then, sham-operated mice underwent the same surgical procedure except for the renal pedicle clamping. And, the mice were sacrificed at 0, 3, 5, 7 days after procedure for a dynamic monitoring of disease progression of I/R injury.
As shown in Fig. 1(a), DPM set up was built based on common-path and off-axis interferometry . With motorized long-range enabled stages for XY scanning, it enabled imaging entire coronal section of the mouse kidney. For the illumination source, broadband white light laser (Fianium, WhiteLase SC-400) was used. Optical filters (Delta optical thin film, LVNIRBP) were placed for the purpose of specific wavelength selection in this case of 550 nm. After passing through by two lens (L1/L2) and pinhole (P1), beam is spatially filtered to produce a clean Gaussian beam. To acquire high resolution image in wide field and in multi-scale, we used a 40 × objective lens (OL, Olympus, UMPlanFl NA 0.8) and a 200 mm tube lens (Thorlabs, ITL200). The diffraction grating (G) (Edmond, 92 grooves/mm) was placed at the image plane, and the light field is divided by diffraction orders. The 0th and 1st order were used as reference and sample beam, respectively. The two beams pass through the lens (L5) and only the 0th beam is spatially filtered at the Fourier plane (FP) by the pinhole (P2), of 50 µm radius. The reference and sample beams are collected by the next lens (L6) such that they make interference at the EMCCD (Andor, iXon3). Each recorded individual interferogram was used to extract the phase information. Using field-retrieval algorithm , we took the Fourier transform of raw interferogram, and a simple bandpass filter was used to select spatially modulated first-order and shifted back to baseband (Fig. 1(b) and 1(c)). For the background subtraction, image complex field was divided by its calibration image complex field [31, 32], which was acquired in the no-sample region. The field of view (FOV) for single tile image is 150 x 150 µm2 which overlaps 25% with adjacent images. Automatic plugin stitching function in ImageJ tool was used to reconstruct a wide-field phase image having the total FOV of 7.9 x 5.8 mm from 7,416 mosaic tiles (72 x 103) for Fig. 2(a), with total imaging time of ~30 minutes. Acquisition rate of DPM system was measured to be 5 frame/sec. In order to prevent any unnecessary motion artifact, motorized linear stages was set to wait 200 ms till a single image acquisition of EMCCD is completed. By measuring the phase differences from the specimen and surrounding mounting agent over whole area of sectioned kidney, the entire phase delay images were achieved. The reconstructed image represent the phase delay due to its spatial alteration and difference of refractive index of tissue (Fig. 1(d)). The more detailed phase image reconstruction method using interference pattern was described in , Bhaduri et al. The spatial and temporal phase stability of the system was measured to be 40 and 50 mrad. The transverse resolution was 1.2 μm at the wavelength of 550 nm.
3.1 Quantitative phase imaging of renal cortex, medulla, and pelvis
We obtained DPM images of kidney in a coronal section as shown in Fig. 2. The corresponding H&E stained image are also presented for a side by side comparison. DPM reveals detailed information about the architecture of renal tissue. In order to delineate internal region of kidney slice at macro-scale, we applied the background thresholding only in wide-field imaging as shown in Fig. 2(a), whereas rest of other magnified structures of Fig. 2(b)-2(e) were visualized in raw data without any thresholding process. This bean-shaped organ is divided into three main internal regions: outer renal cortex, medulla in middle, and pelvis in inner area (Fig. 2(a)). The renal cortex coats the outside of kidney where groups of nephrons are distributed. The nephron is the basic structural and functional unit being composed of different types of tubules, including the proximal convoluted tubule (PCT) (Fig. 2(c3)), distal convoluted tubule (DCT) (Fig. 2(c4)) and renal corpuscle (Fig. 2(c1)). As shown in Fig. 2, PCT has higher phase variance value than the other types of tubule. This is because PCT has brush border, which is densely packed with microvilli. While PCT looks occluded, DCT has relatively clean border inside, resulting in less phase variance value. Another component of the nephron is the renal corpuscle, which consists of two structures like a glomerulus and a Bowman’s capsule. The main role of the renal corpuscle is to make blood filtration and regulate blood flow. The renal corpuscle retains a tuft of micro-capillaries, endothelial cells, and mesangial cells. Since renal corpuscles need to play the role of filtration, the endothelial cell in glomerulus has large fenestrae, a number of small pore-like structures in the cell. These porous structures can be easily attacked and damaged depending on renal dysfunction and a variety of genetic and environmental causes, which affect the higher phase variance in glomerulus.
Underneath the cortex, the renal medulla is found at the center of the kidney. This part of the kidney also consists of different types of vessels and tubules, including vasa recta, interstitium, loop of Henle, and medullary collecting ducts. Nephrons are not only located in the cortex, but also extend to medulla. The unique spatial arrangement of the nephron component makes medulla more crucial for urine concentration and other specialized kidney functions. As shown in Fig. 2(d), the medullary region is clearly visualized, corresponding closely to the H&E stained image. The thick and thin limb of loop of Henle was shown in detailed (Fig. 2(d1) and 2(d2)). As indicted from the name of each tubule, thick limb of loopof Henle shows higher phase variance due to its spatial thickness. And medullary collecting duct in medulla concentrates and transports urine from the nephrons and moves it into the renal pelvis and ureters. This structure is relatively easier to distinguish from the other tubules since it has a long and narrow appearance. Since it also shows low value of phase variance, this type of tubule can be readily delineated among other types of tubules.
Renal pelvis is area that collects urine from the end part of nephron and narrows into the upper end of the ureter. Most region of pelvis comprised of collecting tubules and papillary ducts. As shown in Fig. 2(e), the boundary between inner part of the medulla and pelvis is clearly visualized. A group of collecting ducts exist in elongated way shown in Fig. 2(e1) with relatively low phase value.
3.2 Fluctuations of phase values and glomerular size in renal cortex during AKI development
In Fig. 3, we analyzed and tracked how this disease makes morphological and functional alterations to the renal cortex. Previously, it was known that the cortex region is the first area that is severely deteriorated due to renal tubule-interstitial fibrosis . Renal fibrosis is a progressive process that leads to tissue scarring and architectural change. Thus, we obtained phase maps from the renal cortex region and glomerular to make graph of Fig. 3(a) and 3(b). Specifically, we obtained 40 for phase delay and 20 for glomerulus from each AKI stage and averaged for each map. Then, we draw a box plot about randomly selected average phase values for each stage. The inset figures of Fig. 3(a) and 3(b) represents phase map of each stage we randomly picked in renal cortex and glomerular, respectively. The raw data besides to box plot represents an averaged value of each phase map. It is found that the phase variance in the renal cortex is decreased from normal to DAY 7 (Fig. 3(a)). The altered geometrical shapes and spatial inhomogeneity induced by ischemic stress makes lower phase variance value in day 7. We confirmed that the phase variance of the glomeruli in renal cortex decreased due to relatively increased Bowman’s space surrounding the Glomeruli capillaries (Fig. 3(b)). Glomerular capsule consists of two sub components, glomerular capillary and Bowman’s space, respectively. As AKI develops, blood flow into glomerular is decreasedresulting to glomerular capillary congestion and acute tubular necrosis . Not only phase value of glomeruli, but also the size of glomerular capillary was evaluated because it is important risk factor in renal fibrosis diagnosis (Fig. 3(c)). It demonstrates that the size of glomerular capillary was decreased while Bowman’s space is increased. For the correlation study between three factors of phase delay in the cortex, phase delay in glomerular, and glomerular capillary size, respectively, we plotted their correlative linear relationship as shown in Fig. 3(d). Phase information in the cortex and glomerular show significant correlation with high value of Pearson’s r value (red dot line). Similarly, correlation linear fit study between glomerular phase delay and size is analyzed with blue line. Through correlation analysis, it reflects that renal damage in cortex region is related to the phase fluctuation and the size of glomerular capillaries.
3.3 AKI scattering coefficient and anisotropy
DPM delineates morphological information with nanometer sensitivity, but the phase value does not provide sufficient macroscopic contrast which determines the progress of interstitial fibrosis. Thus, we quantitatively calculated its optical scattering parameters, namely the scattering coefficient (µs) and anisotropy (g) using the complex field information . µs can be described by light intensityattenuation per unit distance. From the phase delay, the scattering coefficient (µs) (Fig. 5(a)) can be retrieved based on the scattering-phase theorem.36], which result in the low scattering value as shown in Fig. 4. As shown in Fig. 5(a), the corresponding µs value is decreased, and this result reflects significant effect of interstitial fibrosis on spatial alteration in cortex region.
The other critical optical parameter is anisotropy (g). g can be retrieved by the average of the cosine of the scattering angle, and has the single directionality of forward scattering. Anisotropy can be calculated through the following equation using scattering phase theorem .Fig. 4, mapped distribution of g exhibits a value ranging from 0.9 to 1, which is analogous to other types of tissues . In healthy mice, high g is found in renal cortex mainly due to the large size of scattering particles. Though the g value is high in normal with median value of 0.994, it gradually decreases as kidney get injured by ischemic stress as shown in Fig. 5(b). In order to check the correlation between two different optical properties and geometrical information of glomerular capillaries, linear fitting was computed and plotted as shown in Fig. 5(c). These analysis exhibit adequate correlation of µs and g in renal cortex about the gradual renal fibrosis of AKI with Pearson’s r value of 0.77 and 0.63, respectively. Eventually, low µs and g value in day 7 of AKI represent high tissue homogeneity and small scattering particles mostly induced by tubuolo-interstitial fibrosis in renal cortex. And, density contour plot of scattering and anisotropy clearly distinguished their distinct distribution showing better discrimination from normal to day 7 (Fig. 5(d)).
3.4 Renal fibrosis is closely associated with optical characteristics of µs and g
Renal fibrosis in AKI can be confirmed through immunohistochemical (IHC) study. For comparison, we used a tissue slice adjacent to the DPM image slice for IHC. A continuous increase of positive fibroblast from α-smooth muscle actin (αSMA) and collagen I confirmed the development of progressive fibrosis (Fig. 6(a)). Positively stained area fractions for αSMA and collagen I represent the reconstructed neo-vascular area, which is one of the major renal fibrosis indicator (Fig. 6(b) and 6(c)). In addition, significant correlations were found between the computationally filled area fractions for αSMA and collagen I, illustrating a close association between renal fibrosis and optical properties of µs and g. (Fig. 6(d) and 6(e)). High Pearson’s r value between fibrosis and µs, and between fibrosis and g explains the potential of QPI as a reliable tool for kidney pathophysiology
4. Discussion and conclusion
Ischemic stress damage to the cortex and causes a decreased renal blood flow from major renal artery, which eventually brings about renal dysfunction, and a series of inflammatory process in extra cellular matrix, ending up with developing chronic kidney disease (CKD) . There has been no label free technique for detecting the tubule-interstitial fibrogenetic injury quantitatively in large-scale. Using DPM, we developed a new approach for generating high resolution images of ex-vivo mouse kidney in multi-scale with high phase stability and sensitivity. We demonstrated wide-field label free analysis for detecting the progressive renal disease for the first time. Using a mosaic platform equipped with XY motorized linear stages, wide field quantitative phase image with an image-mosaicking technique were acquired. In order to delineate macroscopic contrast on renal fibrosis, we retrieved light scattering parameters, i.e., scattering coefficient (µs) and anisotropy (g). The results suggest that this approach can be applied to systematically quantify the structural alteration of AKI pathophysiology by measuring quantitative phase delay of kidney slices. The µs and g retrieved by 2D phase image showed a great potential on detecting interstitial fibrosis, which H&E staining, gold standard of kidney pathology, cannot offer. The contrast generated from optical properties showed a good agreement with previously reported result of IHC study addressed by αSMA and collagen I. The correlative result between optical parameters and fibrogenetic marker supports the efficacy of DPM as a versatile tool for describing the prognosis of AKI.
National Research Foundation of Korea (NRF) grant from Korea government (MSIP) (No. 2017009566); and 2017 Research Fund (1.170009) of UNIST (Ulsan National Institute of Science & Technology).
We would like to thank Sung Chul Bae and Sung Ho Lee for technical assistance.
The authors declare that there are no conflicts of interest related to this article.
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