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9EARLY DIAGNOSIS OF DISEASES BY LABEL-FREE, HIGH-RESOLUTION, MULTIPARAMETRIC IMAGING
ZHIYI LIU1, JIA MENG1, SHUHAO QIAN1, SHENYI JIANG1, AND ZHIHUA DING1
1State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, International Research Center
for Advanced Photonics, Zhejiang University, China
Abstract
Disease progression is associated with subtle changes in both cellular metabolism and extracellular matrix organization, especially at early stages [1, 2]. Therefore, detecting early changes of these components in a sensitive and accurate manner can serve as a powerful tool for prediction of diseases and better treatments. However, there are limited techniques that work well for this goal. Two-photon excited fluorescence (TPEF) has emerged as a powerful modality for high-resolution, label-free, quantitative assessments of metabolic activity[3, 4].Two key coenzymes actively involved in several important metabolic pathways, NAD(P)H and FAD, can provide endogenous fluorescence for these metabolic assessments[5]. Second harmonic generation (SHG) microscopy, another multi-photon modality, is an effective method for direct non-invasive, label-free imaging of collagen fibers (main components in extracellular matrix) in biological tissues at sub-micrometer resolution [6, 7].
Inthis work, we use TPEF and SHG to acquire images from cells and collagen fibers, respectively, without the need for any exogenous labels. Based on these images, we have developed quantitative, multi-parametric measures, including optical redox ratio and mitochondrial clustering corresponding to cellular metabolic activity, as well as directional variance and fiberconcentration representative of collagen spatial organization. A combination of these quantitative metrics can provide systematic investigations of correlation between cells and matrix during progression of diseases.
Figure 1 shows the TPEF images of coenzymes NAD(P)H and FAD within cardiomyocyte spheroids, and optical measures generated to quantify cellular metabolism. The merged image contains three different contrasts, including NADH, FAD and collagen fibers (Fig. 1a). Throughout this study, two optical measures are developed for characterization of cell metabolic activity. The first one is optical redox ratio defined as FAD/ (NADH + FAD) (Fig. 1d), which is generated on a per pixel basis relying on raw NADH (Fig. 1b) and FAD (Fig. 1c) images. Optical redox ratio reflects the reduction-oxidation events based on which cells optimize energy production to maintain cellular homeostasis through various metabolic pathways [8]. Meanwhile, mitochondria dynamically fuse and fissionto manage energy distributionor to protect the cell from insult[9]. To account for this, we develop the other optical metric which is corresponding to the spatial organization of mitochondria, named mitochondrial clustering, generated from the clone-stamped map (Fig. 1e) of raw NADH image. Briefly, we acquire the power spectral density (PSD) curve (Fig. 1f) of the 2D Fourier transformation of the clone-stamped image, and fit the curve to obtain the exponential power which is an indicator of the mitochondrial clustering level.
Figure 1. Imaging and quantification of cellular metabolism. (a) Merged image of cardiomyocyte spheroids containing TPEF images of NADH (blue) and FAD (red), and SHG image of collagen fibers (green). (b) Raw NADH image. (c) Raw FAD image. (d) Redox ratio map defined as: FAD/ (NADH + FAD) on a per pixel basis. (e) The clone-stamping of raw NADH intensity image used for assessment of mitochondrial clustering. (f) The power spectral density (PSD) curve generated from the clone-stamped NADH image for acquisition of the exponential power, which is used as a quantitative measure of mitochondrial clustering level. Scale bar: 100 ¡um.
Besides quantitative characterizations of cellular metabolism from TPEF images of coenzymes, we acquire SHG images of collagen fibers from mouse breast tissue (Fig. 2a), and quantify their spatial randomness and density. Directional variance, ranging between 0 and 1, is a measure of spatial alignment, with 0 corresponding to perfect parallel alignment, and 1 corresponding to complete randomness (Fig. 2b) [10, 11]. Fiber concentration, slightly different from fiber density, focuses more on the relationship among collagen fibers in localized regions. It is generated on a per pixel basis and ranges between 0 and 1, with 0 indicating no fibers in neighbouring regions of the assessed pixel, while 1 corresponding to full occupying by collagen fibers in neighbouring regions (Fig. 2c).
a b c
Figure 2. Imaging and quantification of collagen fiber spatial organization. (a) Raw SHG intensity image of mouse breast tissue. (b) The pixel-wise directional variance map of the same field which reflects the fiber alignment. (c) The pixel-wise fiber concentration
map. Scale bar: 50 ¡um.
Overall, in this study we acquire TPEF and SHG images from both cells and extracellular matrix, relying on completely endogenous contrast. Especially, these label-free, high-resolution imaging modalities, along with highly-quantitative characterizations, enable a better understanding of cellular metabolic activity and collagen fiber organization. These optical biomarkers provide complementary insights into the functional and structural alterations at early stages of diseases, and offer opportunities to study interactions between cells and matrix as disease progresses. Thus, a combination of them might serve as a sensitive approach to early diagnosis of diseases.
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