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Enhanced Visualization of Hematoxylin and Eosin Stained Pathological Characteristics by Phasor Approach Teng Luo, Yuan Lu, Shaoxiong Liu, Danying Lin, and Junle Qu Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.7b01999 • Publication Date (Web): 01 Aug 2017 Downloaded from http://pubs.acs.org on August 2, 2017

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Analytical Chemistry

Enhanced Visualization of Hematoxylin and Eosin Stained Pathological Characteristics by Phasor Approach Teng Luo†, Yuan Lu‡, Shaoxiong Liu§, Danying Lin†,*, Junle Qu†,* †

Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, College of Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China

‡ §

Department of Dermatology, The Sixth People's Hospital of Shenzhen, Shenzhen 518052, China Department of Pathology, The Sixth People's Hospital of Shenzhen, Shenzhen 518052, China

ABSTRACT: The phasor approach to fluorescence lifetime imaging microscopy (FLIM) is used to identify different types of tissues from hematoxylin and eosin (H&E) stained basal cell carcinoma (BCC) sections. The results suggest that working directly on the phasor space with the clustering assignment achieves immunofluorescence like simultaneous five or six-color imaging by using multiplexed fluorescence lifetimes of H&E. The phase approach is of particular effectiveness for enhanced visualization of the abnormal morphology of a suspected nidus. Moreover, the phasor approach to H&E FLIM data can determine the actual paths or the infiltrating trajectories of basophils and immune cells associated with the pre-neoplastic or neoplastic skin lesions. The integration of the phasor approach with routine histology proved its available value for skin cancer prevention and early detection. We therefore believe that the phasor analysis of H&E tissue sections is an enhanced visualization tool with the potential to simplify the preparation process of special staining, and serve as a color contrast aided imaging in clinical pathological examination.

Tissue sections, which are normally colorless, are commonly stained to enhance contrast. For light microscopic examinations, colored agents (chromophores) are used. The normal stain in dermatopathology is hematoxylin and eosin (H&E), which can disclose abundant structural information, with specific functional implications such as inflammation.1, 2 However, hematoxylin colors cells nuclei deep blue-purple. The changes observed in H&E stained sections are insufficient for diagnosis. Especially, the suspected nidus and the infiltrating path of basophils and immune cells associated with the preneoplastic or neoplastic skin lesions are often missed or misdiagnosed due to the lack of specificity and preparation of sequential tissue sections for H&E staining. Therefore, additional specific stains or other advanced tests are needed. Multicolor immunostaining is often desirable or even necessary to identify discrete tissue components following H&E biopsy,3 but it is limited by the spectra of the fluorophore mixture, the low number of fluorochromes that can be conjugated to one staining, and the number of commercially available antibodies.4,5 Moreover, H&E staining and immunofluorescence are hard to match because they are performed in different sequential tissue sections, which would lead to the change or disappearance of morphology in irregular regions of interest. Multiple slices would lead to the change or disappearance of morphology in irregular regions of interest, and consequently the missing of some diagnostic information.6 Therefore, there is a real need to develop an easy method for combining H&E staining with immunofluorescence in situ for convenient and precise diagnosis. Adjusting the colors of histology slides is not an easy task as there is great variation not only in staining quality, but also in heterogeneous staining of different tissues. Multicolor im-

aging is often engaged to improve visualization of histology slides, and multimodal nonlinear optical imaging plays an important role in multicolor imaging.7, 8 However, the types of fluorophores, tunable laser source, and multichannel detector need to be selected according to specific customer requirements, thus making it difficult for multimodal nonlinear optical imaging to be used in pathology department.9,10 Fortunately, fluorescence signals contain more parameters than just intensity and spectrum. Another parameter of fluorescence signal, the fluorescence lifetime, is defined as the time it takes for the intensity to decay to 1/e of its initial value. Compared to fluorescence intensity imaging, fluorescence lifetime imaging (FLIM) is independent of the excitation power, fluorophore concentration, and photo-bleaching.11 Moreover, lifetime measurements are sensitive to changes in local conditions of the micro-environment such as pH, ion concentration, and the binding of protein.12 Therefore, FLIM can potentially be correlated to cell and tissue state during physiological and/or pathological processes.13 Advances in digital histopathology and new tools for image analysis reflect a growing interest in designing efficient automated tools for extracting features for cancer diagnosis.14–16 Recently, hyperspectral phasor software has been used for denoising and unmixing multiple spectrally overlapping fluorophores in a low signal-to-noise level with fast analysis speed.17 The phasor approach to fluorescence lifetime imaging analysis has also been applied to study the extent of fibrosis of the kidney in a unilateral ureter obstruction.18 This approach is well established for mapping lifetime to a pseudo-color image and separating areas of image having distinctively different lifetimes. The analysis of the decay at each pixel using exponentials is a formidable computational problem. The ad-

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vantage of the phasor approach compared to multi-exponential decay fitting is that it provides a graphical global view of the fluorescence decay occurring at each pixel.19 Moreover, populations having similar lifetimes can be selected in the phasor plot and the fluorescence image is painted accordingly. Thus, the phasor analysis is a fit-free way of analyzing FLIM data in the Fourier space and increases the speed of analysis since there is no need to perform exponential fittings. The phasor approach to lifetime has the potential to simplify the analysis of FLIM data, and can automatically distinguish pixels having different fluorescence lifetimes.20, 21 In this study, we have used time domain FLIM technique to directly measure fluorescence lifetimes from H&E stained basal cell carcinoma (BCC) slides and applied the phasor approach to fluorescence lifetime analysis to enhance the visualization of pathological characteristics. The phasor approach to fluorescence lifetime can be used to study differential types of tissues in H&E stained BCC sections and obtain immunostaining like multicolor images, thus provide a simple method for histopathology examination in situ.

EXPERIMENT SECTION Sample preparation. Three fresh human skin specimens were obtained from three patients undergoing skin biopsies for routine diagnostic procedures in the Department of Dermatology at the Sixth People's Hospital of Shenzhen. The samples were placed in a standard pathologic transport container covered with ice and then sent to the Department of Pathology. Three consecutive sections were cut from paraffin blocks by cryostat microtome with standard histology procedures. A total of 9 H&E stained skin tissue sections from 3 patients were collected. The histopathological examination of the H&E stained skin sections was performed by a senior pathologist, and the corresponding tissues were identified as BCC. For each patient, one H&E stained section was selected for the following imaging. This study was performed according to a protocol approved by the Shenzhen Sixth People's Hospital research ethics committee. All patients gave their informed consent for the use of their tissues for medical research. Two-photon excited FLIM system. A time-resolved fluorescence measurement system incorporating a confocal laser scanning microscope (TCS SP2, Leica) and a time-correlated single photon counting (TCSPC) system was used to image the H&E stained sections of BCC. The mode-locked Titanium (Ti): Sapphire laser (Coherent Mira 900, 76 MHz, 120 fs) was used for excitation. The laser was tuned to a wavelength of 785 nm for two-photon excitation. The excitation beam was diverted by a dichroic beam splitter to the galvanometer mirrors before being focused on the sample via a scan lens and an objective (63× PL APO CS Leica, NA = 1.4). The fluorescence emission (520–580 nm) was collected using the same objective lens, and detected with a photomultiplier tube (Hamamatsu). For the time resolved setup, a cutting short-pass filter (700 nm, Chroma) was used to block the reflected laser, and the fluorescence signal passed through a band-pass filter (550±30 nm, Chroma) and detected with a micro-channel plate photomultiplier tube (MCP-PMT, Hamamatsu) that was mounted to the optional port of the confocal microscope and connected with TCSPC module (SPC150, Becker & Hickl GmbH) to measure fluorescence lifetime. The fluorescence

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lifetime at each pixel of a 256×256 image was calculated for all stained tissue sections, with bi-exponential fitting expressed as:

I(t)/I(0) = a1 exp( -t/τ1 ) + a2 exp( -t/τ2 )

(1)

where τ1, τ2 and a1, a2 denote the lifetimes and proportions of the two different components, respectively. For each pixel, the average lifetime (τm) was determined according to the following equation:

τm= (a1 τ1 +a2 τ2 )/(a1 +a2 ) (2) A pseudo-colored lifetime image was generated by assigning a specific color to the value of τm at each pixel. The minimum time channel of the TCSPC module was 813 fs, and the response time of the system was less than 30 ps. The lifetime fittings and calculations were performed using the SPCImage software (Becker & Hickl GmbH, Germany). In addition, bright field images were obtained with a digital camera (Leica DFC310 FX CCD). The phasor approach to FLIM data analysis. The signals collected from each pixel were transformed to the Fourier space. The phasor plot, a graphical representation of intensity decays for a FLIM image was constructed. Points in the twodimensional phasor plot are defined by the values of sine (S) and cosine (G) transforms derived by the following equations: ∞

si,j (ω)=

0 I(t) sin(nωt) dt ∞

(3)

0 I(t) dt ∞

gi,j (ω)=

0 I(t) cos(nωt) dt ∞

(4)

0 I(t) dt

where the indices i and j identify a pixel of the image and si, j (ω) and gi, j (ω) are the y and x coordinates of the phasor plot, respectively; ω = 2πf, where f is the laser repetition frequency (i.e., 76 MHz in our experiment); and n is the harmonic order (n=1 in our experiment) The analysis of the phasor distribution was performed by cluster identification. There is a direct relationship between a phasor location and lifetime. Every possible lifetime can be mapped into this universal representation of the decay (phasor plot) (Supplementary Fig. 1d). All possible single exponential lifetimes lie on the “universal circle”, defined as the semicircle going from point (0, 0) to point (1, 0), with radius 1/2. Point (1, 0) corresponds to τ=0, and point (0, 0) to τ=∞. In the phasor space, two single lifetime components add directly because the phasor follows the vector algebra. Therefore, a mixture of two distinct single lifetime components, each of which lies separately on the single lifetime semicircle, lies on the chord instead, and pixels with the same fluorescence lifetime constituents consequently locate at the same position in the phasor plot. On this basis, clustering assignment can be performed by selecting different clusters from the phasor plot, each of which corresponds to a collection of pixels with similar fluorescence lifetime properties in the image. Considering of the spatial distribution and morphological features of different cellular substructures or tissues, the separation of different clusters was carefully adjusted.

RESULTS AND DISCUSSION

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In light of the low cost, ease of use, and high popularity of H&E staining, as well as the two photon excited fluorescence properties of hematein and eosin, two photon fluorescence intensity images (Figure 1c1 and e1) and their corresponding pseudo-color fluorescence lifetime images (Figure 1c2 and e2) can be directly obtained from H&E stained BCC sections (Figure 1a and b). Figure 1d and f show the histograms of average fluorescence lifetime (τm) corresponding to Figure 1c2 and e2, respectively. The histogram shows the distribution of lifetimes found in the image and a scale that associates the color of a pixel with τm. In Figure 1c2 and e2, due to the low fluorescence quantum yield of hematein, many morphological alterations of the nuclei are not as easily distinguishable as in the bright field micrographs of H&E-stained sections (Figure 1a and b). Interestingly, the τm distribution in Figure 1d shows two distinct peaks: the shorter τm peak (191.83±7 ps) originating from epidermis and the longer one (363.63±4 ps) from

dermis (Figure 1c2, continuous measurement of four times). Although τm in H&E stained sections can distinguish between the epidermis and the dermis, the local region in Figure 1e2 (white dashed rectangle) cannot be further distinguished based on the unimodal τm histogram (Figure 1g). Nest-like tumor cell lumps in Supplementary Fig. 1b is selected to compare with those in Figure 1e2. Supplementary Fig. 1b and Figure 1e2 can be distinguished by their corresponding histograms in Supplementary Fig. 1c, since there are more fibrous connective tissues in Figure 1e2, and the cancer cells lumps in Supplementary Fig.1b include abundant stroma, basaloid cells, or dead cells. However, such a tumor cell lump is not always found in sequential sections, especially in early stage diagnosis. Therefore, it is still necessary to improve the visualization of pathological characteristics from the images with information other than just τm histogram.

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Figure 1. Fluorescence lifetime imaging of an H&E stained basal cell carcinoma (BCC) section. a and b: Bright field images. Specifically, b1– b4 correspond to the marked regions in a. c1 and e1: the fluorescence intensity images. c2 and e2: Corresponding fluorescence lifetime images (e represents the region of interest in c, zoom=2). d and f: Lifetime histograms for c2 and e2, respectively. The lifetime histogram for the white dashed rectangle in e2 is shown as g. Lifetime pseudo color bar: 100 to 600ps.

There is a direct relationship between a phasor location and fluorescence lifetime. Every possible fluorescence lifetime can be mapped into this universal representation of the decay (phasor plot). To improve FLIM results, the phasor approach to the lifetime data was subsequently applied, and the clustering assignment was performed to achieve the discrimination of different tissue components in H&E stained BCC sections. Figure 2c and e are the phasor plots corresponding to Figure 1c2 and e2, and the lifetime phasor distributions both show clusters with similar lifetimes. By selecting different clusters from the phasor plot, a collection of pixels with similar fluorescence lifetime properties in the image can be highlighted and mapped accordingly. Taking into account the spatial distribution and morphologic features of cellular substructures or tissues, five segments based on similar phasor clustering and hence similar tissue were separated from the phasor plot, each of which was assigned a corresponding pseudo color (Figure 2a and b). We infer that the red regions in Figure 2a1 and b1 mainly represent nuclei, and the yellow areas in Figure 2a2 and b2 represent relatively poorly defined cytoplasm and cellular stroma without clefting artifact. As shown by the white arrows in Figure 2a1, atypical cells arrange in the peripheral region along one side, and the lobulated, round, or elongated nuclei are densely stacked, making their borders unclear. In Figure 2d1 (a composite image from three images, Figure 2a1, a2 and a4), the sizes of the cytoplasm distribute unevenly and the nuclei seem to be embedded in the slurry nodules. These characteristics coincide to the histopathological manifestations of basophils in BCC (Figure 1b). Thus, the white arrows in Figure 2a1 indicate irregular masses of basophils extending from the epidermis to the dermis. The two cells within the white dashed rectangle in Figure 2b1 and b2 have small and round nuclei, and their nucleoplasm is larger than that of basophils. We believe that these cells correspond to lymphocytes within the dotted circle in Figure 1b4 (marked by white arrows in Figure 1c2 and e2), where the nuclei are densely stained deep blue-purple. Moreover, the C-shaped nucleus of a monocyte is easy to find in Figure 2b1 and b2 (white arrow), which agrees with previous studies indicating that switching the differentiation of monocytes to macrophages in BCC.22, 23 In Figure 2d1 and f1, the cells within the white dotted circle, where the nuclei are round or located in one side of the cell, are smaller than lymphocytes, and thus are considered as plasmocytes. It is not unusual to encounter heterogeneous morphologic features within the same tumor. The pre-neoplastic or neoplastic cells appear simultaneously on the BCC, but some suspected niduses are often missed because the consecutive series of sections were cut from paraffin embedded tissues. Figure 2d1 shows a lucky example of a suspected nidus in the regions of interest selected in Figure 1a. Hence, the infiltrating trajectories of basophils (white dotted arrows in Figure 2d1) and immune cells (dotted circles in Figure 2d1) associated with the pre-neoplastic or neoplastic skin lesions can be obtained using the phase approach to analyze the fluorescence lifetimes of H&E.

Figure 2b4 and b5 represent keratinized pre-neoplastic or neoplastic cell matrix (green) and nuclei (blue), respectively. In Supplementary Fig. 1e3, numerous nuclear fragments are present in the cancer cell lumps, and basaloid cells with large pleomorphic nuclei and scant cytoplasm are obvious. Figure 2f1 and f2 indicate that Figure 2b4 and b5 accord with the pathological features of the cracks between basal cell nodules and stroma. In addition, except for the cancer cell stroma in Figure 2b4, the destruction of basement membranes (within white dashed line) can also be found in Figure 2a4. As shown in Figure 2a5, suspected epidermal cells, as well as abnormal nodules of accumulated keratin (within the white dashed oval) locate in dermis and connect to epidermis. In contrast, there is no obvious change within the bright field microscopy images (Figure 1b4). It is possible that negligent diagnosis seems to mistakenly believe that these regions (Figure 1b4) are hair cell bundles or bundles in a group of hair cells due to thin sections becoming folded as they are being cut. However, the occurrence of tissue-fold artifacts cannot be easily prevented during slide preparation. The phase approach can improve visualization and analysis ability to help identify the suspected tumor lesions at first glance. These preliminary results on the test set also suggest a lack of specificity as there is a mixing between keratinization and epidermal cells, and the basaloid tumor cells resemble cells from the basal epidermal layer, which is in agreement with the clinical manifestations of BCC. As shown in the white dotted oval in Figure 2d2 and f2, the nuclei of tumor cells are large, ovoid, or elongated with less cytoplasm, and there are no cytoplasmic bridges between cells. The trend of cellular infiltration of pre-neoplastic or neoplastic basaloid cells (white dotted arrows) is visible in Figure 2d2, and the white arrows in Figure 2f2 refer to fibroblasts with oval nuclei in connective tissues. Collagen in tissues has been traditionally regarded as merely a physical barrier against cancer invasion and tumor cells migration.24 In normal stroma, collagen fibers typically appear “curly” and anisotropic. During early cancer progression, the amount of collagen in the stroma increases, and collagen fibers appear straighter and are aligned parallel to the tumor border.25 Figure 2a3 and b3 show dense fibrous tissues (cyan) with assembly in parallel bundles around the nodule (Figure 2a4 and a5). The aforementioned results also verify the presence of lymphocytes and plasma cells infiltrate in dermis (Figure 2d3 and f3). In addition, the connective tissue in Figure 2b3 is different from the stroma shown in Supplementary Fig. 1b, which is consistent with those presented in Supplementary Fig. 1c. However, some discrepancies are noticeable between the H&E stained sections and the pseudo-color phasor maps. For example, different pseudo-colors for the stratum corneum (SC) are shown in Figure 2a1–a4, which is mainly due to the fact that the SC or epidermis is made primarily of keratinocytes but also has several other minor cell populations; keratinocytes synthesize the tonofibril, which is composed of intermediate keratin filaments responsible for structures such as the SC, and the bottom layer is composed of basal keratinocytes abutting the basement membrane.26 To some extent, BCC and basal cell

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keratinocytes share many histologic similarities, as is reflected in their names. On the other hand, improvements of the phasor approach could involve the development of clustering assignment on the pseudo-color maps to remove small areas that are not representative of any histological structures and help understand the complexities of the SC in BCC. A portion of the lamina, the basal lamina (white dotted line) with an associated collagen mesh built on a lamina network, is depicted in Figure 2a3 and a4; there is a separation between epidermis and dermis and the boundary is clearly visible. In the bright field H&E image, the contrast is present due to different physical and chemical properties of stained tissue. H&E can generally distinguish basic cell types, such as macrophages, neutrophils, lymphocytes and epithelial cells. However, hemalum colors almost all type of cellular nuclei deep blue-purple, and the color differences between nuclei of different types of cells are not obvious. In particular, the good histopathological interpretation must meet at least two factors: observation of relevant morphologic features and observer experience. The discrimination of immune cell-rich areas such as B and T cells cannot be easily identified from their histo-

morphology by H&E staining (bright field views). Thus, high resolution microscopy (400×) is needed to identify the cellular morphologies. The phase approach is to achieve a contrast among lymphocyte, monocyte, cytoplasm, connective tissue, stroma, and pre-neoplastic and neoplastic epithelium. This contrast improves the visualization of the bright field H&E images and the morphologies of certain tissues can be obtained under low magnification objective (63×), yet cannot be identified accurately through a fluorescence lifetime histogram. RGB–based histogram was also used to try to extract the features from Figure 1c2 (Supplementary Fig. 2). However, the RGB histogram analysis cannot achieve a contrast among lymphocyte, monocyte and cytoplasm. As shown in Supplementary Fig. 3a, the emission spectrum of the different skin layers in Figure 1c2 has severe peak overlap, which means that the spectrum is mainly from the strong signal of eosin, and thus we cannot distinguish connective tissue, stroma, and pre-neoplastic and neoplastic epithelium by spectral separation. Moreover, spectral phasor plot based on the fluorescence intensity of eosin (Supplementary Fig. 3b) also cannot improve the visualization of the morphologies of tissues.

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Figure 2. Enhanced visualization of H&E stained BCC section based on fluorescence lifetime and clustering assignment in the phasor plot. c and e: Phase plots corresponding to Figure 1c and e, respectively. a and b: Fluorescence images corresponding to selected clusters from the phasor plots in c and e, respectively. Specifically, a1 and b1 represent basophilic nuclei, a2 and b2 represent cytoplasm, a3 and b3 represent fibrous connective tissue and collagen matrix, a4 and b4 represent basement membranes, stroma of keratinized pre-neoplastic and neoplastic cells, and a5 and b5 represent epithelial cells and keratinized pre-neoplastic and neoplastic cells in dermis. b and f: Regions of interest in a and d, respectively, zoom=2. d1: Overlapped image of a1, a2 and a4. d2: Overlapped image of a1, a2, a4 and a5. d3: Overlapped image of a1–a5. f1: Overlapped image of b1, b2 and b4. f2: Overlapped image of b1, b2, b4 and b5. f3: Overlapped image of b1– b5.

More samples are required to determine whether the phasor approach can contribute to the differential diagnosis of skin carcinomas in clinics by enhancing visualization of H&E stained tissue sections. As shown in Supplementary Fig. 4, BCC samples from two other patients with different morphology were also imaged by FLIM. In Supplementary Fig. 4a1, the pseudo-color fluorescence lifetime images cannot be used to distinguish different types of tissues through the corresponding τm histogram. However, it seems that working on the phasor analysis for the clustering assignment can achieve immunofluorescence like simultaneous five-color imaging by multiplexed fluorescence lifetimes of H&E. Although there are few lymphocytes in Supplementary Fig. 4b1 (white arrow), the phase analysis method can still distinguish them from other tissues. Nuclei of basophils, cytoplasm of basophils, subcutaneous matrix, basement membranes and stroma, and epithelial cells can be selected easily via clustering assignment in the phasor map, and then the multicolor localization images of the above separating tissues can be painted corresponding to red, yellow, cyan, green and blue, respectively. Interestingly, the residual erythrocytes remained on the BCC tissue slice (white arrow in Supplementary Fig. 4a2) can be identified using the phasor approach. Similarly, the clustering assignment on the other BCC section can achieve simultaneous six-color imaging (Supplementary Fig. 4c). Specially, erythrocyte can be distinguished from others according to its phasor map (Supplementary Fig. 4c6 and c8, colored with orange). The absorption and emission maxima of eosin in alcoholic solution are 527 and 550 nm, respectively.27 In case of Forster energy transfer, there is spectral overlap between hemoglobin and red blood cells (RBCs) stained eosin.28 Compared to the eosin lifetimes from other tissues, the fluorescence lifetime of eosin stained RBCs is the shortest. In Supplementary Fig. 5, statistical analysis of the areas of phase distribution (G×S) corresponding to the nuclei of basophils, cytoplasm of basophils, subcutaneous matrix, basement membranes and stroma, and epithelial cells (n=3, samples from three BCC patients) derived from the clustering assignment was performed using GraphPad software (San Diego, California, USA). The blue color represents epithelial cells, and part of the green color represents extracellular stroma. As is well known, maintenance of epithelial tissues needs the stroma. In BCC, changes in the stroma drive invasion and metastasis, the stroma becomes sparse, and the epithelium predominates over the stroma. Thus, epithelium and its stroma share many histologic similarities. In this case, the phasor approach could benefit from the combination of morphological analyses. We separated the epithelium from its stroma mainly through their morphological characteristics, the areas of the phase distributions where epithelium and its stroma located were not statistically significant (P=0.54), which is in agreement with the clinical manifestations of BCC. Although the areas of the epithelium and the cytoplasm of basophils are

also not statistically significant (P=0.13), they have different locations in the phase map and thus are easy to separate. The phase areas of the remaining pairs of clusters are statistically significant, indicating the clustering assignment to be reasonable. However, even in these situations, we also took into account the locations and morphological features of each segment during clustering assignment. Eosin is a well characterized anionic dye, belongs to the hydroxy-xanthene group. Arginine, histidine, lysine and tryptophan residues of a protein bind electrostatically to carboxylic and phenolic groups of eosin to produce a stable water-soluble protein–dye complex.29 The absorbance and bathochromatic shift in absorption maximum of the protein–dye complex are proportional to the concentration of protein, and the binding constant varies with the solution pH.29 Time-resolved fluorescence studies have been carried out to measure the emission decay parameters for eosin Y in different solvents and surfactants.30 In previous experiments, it was found that 10 µM eosin Y exhibited a lifetime of 2.50 ns.30,31 The lifetime did not change significantly with the variation of solvent polarity and surfactant concentration, the fluorescence decay curve of eosin Y was found to be single exponential in water and surfactants.30 However, the fluorescence lifetime of H&E stained sections in this study is found to be less than 1 ns, and double exponential decay function rather than single exponential fitting was found to provide a better fit with a chi-squared (χ2) close to one. In complex samples such as tissue sections, endogenous fluorophores also contribute to the detected fluorescence, but the lifetimes of endogenous fluorophores in skin range from ~1 ns up to ~2 ns as reported. Meanwhile, the band pass filter (550±30 nm, Chroma) used in this study selectively detected the fluorescence of H&E, whereas most of the endogenous autofluorescence were blocked. Therefore, the short fluorescence lifetimes in the range of 100–600 ps (Figure 1c2) obtained from the H&E stained sections should attribute to the interaction of eosin and its complex micro-environment. In more viscous solvents, such as propylene glycol/water mixtures the apparent Debye rotational relaxation times of eosin differ upon excitation in the regions of positive and negative anisotropy.32 In aqueous glycerol solutions, the rotational correlation time is proportional to viscosity/temperature in the microsecond time range.33 As shown in Supplementary Fig. 6, we confirmed the fluorescence emission level of eosin changes with the pH and the solvent's viscosity. Supplementary Fig. 6a reveals that with the increasing pH, the fluorescence intensity was reduced and the λmax em was shifted to longer wavelengths up to ~554.5 nm. However, in case of fluorescence spectra of eosin dissolved in 1, 4-dioxane/water mixtures of varying viscosity (Supplementary Fig. 6b), the fluorescence intensity was reduced with the increasing viscosity and the λmax em was progressively shifted to shorter wavelengths up to ~552 nm. As shown in Supplementary Fig. 6c and d, eosin (100µg/ml) at

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different pH (3–10), viscosity (0%–100%) can be distinguished by fluorescence lifetime images, τm histograms, fluorescence attenuations and the corresponding phase distributions, respectively. These results show that eosin is a fluorescent pH and viscosity indicator. We therefore infer that pH and viscosity of the solution will affect the fluorescence lifetime of eosin. Moreover, increased micro-environmental pH has effects on cancer cell functions such as increased proliferation, highly viscous nucleus and cytoplasm, but tumors also can influence the micro-environment by releasing extracellular signals, promoting tumor angiogenesis.34 Therefore, the cancer cells and their surrounding micro-environment are closely related and interact constantly. Supplementary Fig. 6 shows that eosin is able to serve as a probe for the micro-environment in the tissue section. However, eosin staining lacks specificity, the H&E lifetimes (Figure 1c2) were continuously distributed within the whole image. Thus, continuous lifetime distributions of eosin present the continuous phase distributions. Until now, the phasor approach to FLIM is used to separate the discrete fluorescence lifetimes of different fluorophores20, 21. Because the micro-environment (viscosity, pH, hydrophobicity and binding protein) of nuclei, cytoplasm, epithelial cell, subcutaneous matrix and erythrocyte are different, the fluorescence lifetimes of eosin can be used to reveal the spatial distribution of eosin and information about their local microenvironments. Moreover, differences in the H&E fluorescence lifetimes for different tissues suggest different pathological states and correlate with heterogeneous morphologic features within the same tumor. Herein, we use phase analysis for segmentation of the continuous lifetime changes of eosin (tissue non-specific dye), and continuous lifetime distributions were painted using several discrete colors. The clustering assignment is performed by taking into account not only the similar fluorescence properties in the phasor map but also exploiting the spatial distribution and localization in cellular substructures or tissues. In conclusion, H&E staining provides a pink color contrast to the blue color of the nuclei. This contrast improves the visualization of the cellular morphology, but is insufficient to identify certain types of tissues and cells due to lack of specificity. Pseudo-color FLIM images of H&E stained slices exhibited more contrast. However, analyzing FLIM data by fitting the fluorescence decay at each pixel using multiexponential model still cannot separate different types of tissues from the slice. From the H&E stained sections, counterstaining like images can be obtained by the phasor approach to FLIM data. This procedure helps to ease the diagnosis by enhancing contrast through phasor clustering assignment of the similar phase distributions. The combination of phasor plot to FLIM and H&E staining has promoted the visualization of H&E pathological diagnosis significantly, and make it possible for simplified traditional pathological counterstain and shortened diagnostic period. Moreover, multiplexed fluorescence lifetimes of nonspecific binding of single fluorescent dyes (especially eosin) and simple multicolor colocalization will help to bridge immunofluorescence and H&E staining for routine diagnostic assessment.

ASSOCIATED CONTENT

Supporting Information Details of the phasor analysis of the H&E stained BCC slides, fluorescence spectra and lifetimes of eosin at different pH and dissolved in 1, 4-dioxane /water mixtures of varying viscosity.

AUTHOR INFORMATION Corresponding Author E-mail: [email protected] or [email protected]

Notes The authors declare no conflict of interest.

Author Contributions All authors have given approval to the final version of the manuscript.

ACKNOWLEDGMENT Parts of this work were supported by the National Basic Research Program of China (2015CB352005); the National Natural Science F o u n d at io n o f Ch in a (6 1 5 0 5 1 2 1 /6 1 5 2 5 5 0 3 /6 1 3 7 8 0 9 1 /61620106016); Guangdong Natural Science Foundation Innovation Team (2014A030312008); Hong Kong, Macao and Taiwan cooperation innovation platform & major projects of international cooperation in Colleges and Universities in Guangdong Province (2015KGJHZ002) and Shenzhen Basic Research Program (No. J C Y J2 0 1 4 0 4 1 1 0 9 4 3 5 3 7 1 3 , J C Y J2 0 1 5 0 9 3 0 1 0 4 9 4 8 1 6 9 , JCYJ20160328144746940, GJHZ20160226202139185).

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