Abstract

Thin tissue slice based histology has been used as a gold standard for disease diagnosis since over a hundred years ago. However, histopathological evaluation on two-dimensional slides suffers from large variations due to limited sampling. To improve the diagnostic accuracy, three-dimensional (3D) histology is performed through serial sectioning, staining, imaging and reconstruction of individual slices, which is highly time-consuming and labor intensive. We developed a volumetric stimulated Raman scattering (SRS) imaging method, which provides histology-like information in 3D context without the need for staining with dyes. Using a small molecule clearing agent, formamide, we performed tissue clearing within 30 min and achieved an imaging depth up to 500 µm in highly scattered tissues, including brain, kidney, liver and lung. Through a two-color SRS imaging scheme, we obtained histology-like images in cleared brain tissue slices. Our method has the potential for 3D tissue histopathology to improve the accuracy of histopathological examination.

© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

Full Article  |  PDF Article
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References

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2019 (1)

M. Wei, L. Shi, Y. Shen, Z. Zhao, A. Guzman, L. J. Kaufman, L. Wei, and W. Min, “Volumetric chemical imaging by clearing-enhanced stimulated Raman scattering microscopy,” Proc. Natl. Acad. Sci. U. S. A. 116(14), 6608–6617 (2019).
[Crossref]

2018 (3)

Y. Sun, S. You, H. Tu, D. R. Spillman, E. J. Chaney, M. Marjanovic, J. Li, R. Barkalifa, J. Wang, A. M. Higham, N. N. Luckey, K. A. Cradock, Z. George Liu, and S. A. Boppart, “Intraoperative visualization of the tumor microenvironment and quantification of extracellular vesicles by label-free nonlinear imaging,” Sci. Adv. 4(12), eaau5603 (2018).
[Crossref]

D. A. Lawson, K. Kessenbrock, R. T. Davis, N. Pervolarakis, and Z. Werb, “Tumour heterogeneity and metastasis at single-cell resolution,” Nat. Cell Biol. 20(12), 1349–1360 (2018).
[Crossref]

I. Dagogo-Jack and A. T. Shaw, “Tumour heterogeneity and resistance to cancer therapies,” Nat. Rev. Clin. Oncol. 15(2), 81–94 (2018).
[Crossref]

2017 (6)

D. A. Orringer, B. Pandian, Y. S. Niknafs, T. C. Hollon, J. Boyle, S. Lewis, M. Garrard, S. L. Hervey-Jumper, H. J. L. Garton, C. O. Maher, J. A. Heth, O. Sagher, D. A. Wilkinson, M. Snuderl, S. Venneti, S. H. Ramkissoon, K. A. McFadden, A. Fisher-Hubbard, A. P. Lieberman, T. D. Johnson, X. S. Xie, J. K. Trautman, C. W. Freudiger, and S. Camelo-Piragua, “Rapid intraoperative histology of unprocessed surgical specimens via fibre-laser-based stimulated Raman scattering microscopy,” Nat. Biomed. Eng. 1(2), 0027 (2017).
[Crossref]

X. Chen, C. Zhang, P. Lin, K.-C. Huang, J. Liang, J. Tian, and J.-X. Cheng, “Volumetric chemical imaging by stimulated Raman projection microscopy and tomography,” Nat. Commun. 8(1), 15117 (2017).
[Crossref]

T. T. W. Wong, R. Zhang, P. Hai, C. Zhang, M. A. Pleitez, R. L. Aft, D. V. Novack, and L. V. Wang, “Fast label-free multilayered histology-like imaging of human breast cancer by photoacoustic microscopy,” Sci. Adv. 3(5), e1602168 (2017).
[Crossref]

F. Fereidouni, Z. T. Harmany, M. Tian, A. Todd, J. A. Kintner, J. D. McPherson, A. D. Borowsky, J. Bishop, M. Lechpammer, S. G. Demos, and R. Levenson, “Microscopy with ultraviolet surface excitation for rapid slide-free histology,” Nat. Biomed. Eng. 1(12), 957–966 (2017).
[Crossref]

A. K. Glaser, N. P. Reder, Y. Chen, E. F. McCarty, C. Yin, L. Wei, Y. Wang, L. D. True, and J. T. C. Liu, “Light-sheet microscopy for slide-free non-destructive pathology of large clinical specimens,” Nat. Biomed. Eng. 1(7), 0084 (2017).
[Crossref]

M. Balu, G. Lentsch, D. Z. Korta, K. König, K. M. Kelly, B. J. Tromberg, and C. B. Zachary, “In vivo multiphoton-microscopy of picosecond-laser-induced optical breakdown in human skin,” Lasers Surg. Med. 49(6), 555–562 (2017).
[Crossref]

2016 (7)

M. Balu, H. Mikami, J. Hou, E. O. Potma, and B. J. Tromberg, “Rapid mesoscale multiphoton microscopy of human skin,” Biomed. Opt. Express 7(11), 4375–4387 (2016).
[Crossref]

T. W. Bocklitz, F. S. Salah, N. Vogler, S. Heuke, O. Chernavskaia, C. Schmidt, M. J. Waldner, F. R. Greten, R. Bräuer, M. Schmitt, A. Stallmach, I. Petersen, and J. Popp, “Pseudo-HE images derived from CARS/TPEF/SHG multimodal imaging in combination with Raman-spectroscopy as a pathological screening tool,” BMC Cancer 16(1), 534 (2016).
[Crossref]

F.-K. Lu, D. Calligaris, O. I. Olubiyi, I. Norton, W. Yang, S. Santagata, X. S. Xie, A. J. Golby, and N. Y. R. Agar, “Label-Free Neurosurgical Pathology with Stimulated Raman Imaging,” Cancer Res. 76(12), 3451–3462 (2016).
[Crossref]

R. M. Nolan, S. G. Adie, M. Marjanovic, E. J. Chaney, F. A. South, G. L. Monroy, N. D. Shemonski, S. J. Erickson-Bhatt, R. L. Shelton, A. J. Bower, D. G. Simpson, K. A. Cradock, Z. G. Liu, P. S. Ray, and S. A. Boppart, “Intraoperative optical coherence tomography for assessing human lymph nodes for metastatic cancer,” BMC Cancer 16(1), 144 (2016).
[Crossref]

M. Pilling and P. Gardner, “Fundamental developments in infrared spectroscopic imaging for biomedical applications,” Chem. Soc. Rev. 45(7), 1935–1957 (2016).
[Crossref]

S. Tiwari, J. Raman, V. Reddy, A. Ghetler, R. P. Tella, Y. Han, C. R. Moon, C. D. Hoke, and R. Bhargava, “Towards Translation of Discrete Frequency Infrared Spectroscopic Imaging for Digital Histopathology of Clinical Biopsy Samples,” Anal. Chem. 88(20), 10183–10190 (2016).
[Crossref]

K. L. Andrew Chan and S. G. Kazarian, “Attenuated total reflection Fourier-transform infrared (ATR-FTIR) imaging of tissues and live cells,” Chem. Soc. Rev. 45(7), 1850–1864 (2016).
[Crossref]

2015 (5)

E. Provenzano, V. Bossuyt, G. Viale, D. Cameron, S. Badve, C. Denkert, G. MacGrogan, F. Penault-Llorca, J. Boughey, G. Curigliano, J. M. Dixon, L. Esserman, G. Fastner, T. Kuehn, F. Peintinger, G. von Minckwitz, J. White, W. Yang, and W. F. Symmans, “Standardization of pathologic evaluation and reporting of postneoadjuvant specimens in clinical trials of breast cancer: recommendations from an international working group,” Mod. Pathol. 28(9), 1185–1201 (2015).
[Crossref]

M. Ji, S. Lewis, S. Camelo-Piragua, S. H. Ramkissoon, M. Snuderl, S. Venneti, A. Fisher-Hubbard, M. Garrard, D. Fu, A. C. Wang, J. A. Heth, C. O. Maher, N. Sanai, T. D. Johnson, C. W. Freudiger, O. Sagher, X. S. Xie, and D. A. Orringer, “Detection of human brain tumor infiltration with quantitative stimulated Raman scattering microscopy,” Sci. Transl. Med. 7(309), 309ra163 (2015).
[Crossref]

J.-X. Cheng and X. S. Xie, “Vibrational spectroscopic imaging of living systems: An emerging platform for biology and medicine,” Science 350(6264), aaa8870 (2015).
[Crossref]

B. Liu, H. J. Lee, D. Zhang, C.-S. Liao, N. Ji, Y. Xia, and J.-X. Cheng, “Label-free spectroscopic detection of membrane potential using stimulated Raman scattering,” Appl. Phys. Lett. 106(17), 173704 (2015).
[Crossref]

D. S. Richardson and J. W. Lichtman, “Clarifying Tissue Clearing,” Cell 162(2), 246–257 (2015).
[Crossref]

2014 (1)

D. Fu and X. S. Xie, “Reliable Cell Segmentation Based on Spectral Phasor Analysis of Hyperspectral Stimulated Raman Scattering Imaging Data,” Anal. Chem. 86(9), 4115–4119 (2014).
[Crossref]

2013 (4)

D. Zhu, K. V. Larin, Q. Luo, and V. V. Tuchin, “Recent progress in tissue optical clearing,” Laser Photonics Rev. 7(5), 732–757 (2013).
[Crossref]

T. Kuwajima, A. A. Sitko, P. Bhansali, C. Jurgens, W. Guido, and C. Mason, “ClearT: a detergent- and solvent-free clearing method for neuronal and non-neuronal tissue,” Development 140(6), 1364–1368 (2013).
[Crossref]

R. Mittal, M. Balu, T. Krasieva, E. O. Potma, L. Elkeeb, C. B. Zachary, and P. Wilder-Smith, “Evaluation of stimulated raman scattering microscopy for identifying squamous cell carcinoma in human skin,” Lasers Surg. Med. 45(8), 496–502 (2013).
[Crossref]

M. Ji, D. A. Orringer, C. W. Freudiger, S. Ramkissoon, X. Liu, D. Lau, A. J. Golby, I. Norton, M. Hayashi, N. Y. R. Agar, G. S. Young, C. Spino, S. Santagata, S. Camelo-Piragua, K. L. Ligon, O. Sagher, and X. S. Xie, “Rapid, Label-Free Detection of Brain Tumors with Stimulated Raman Scattering Microscopy,” Sci. Transl. Med. 5(201), 201ra119 (2013).
[Crossref]

2012 (2)

C. W. Freudiger, R. Pfannl, D. A. Orringer, B. G. Saar, M. Ji, Q. Zeng, L. Ottoboni, W. Ying, C. Waeber, J. R. Sims, P. L. De Jager, O. Sagher, M. A. Philbert, X. Xu, S. Kesari, X. S. Xie, and G. S. Young, “Multicolored stain-free histopathology with coherent Raman imaging,” Lab. Invest. 92(10), 1492–1502 (2012).
[Crossref]

N. Roberts, D. Magee, Y. Song, K. Brabazon, M. Shires, D. Crellin, N. M. Orsi, R. Quirke, P. Quirke, and D. Treanor, “Toward Routine Use of 3D Histopathology as a Research Tool,” Am. J. Pathol. 180(5), 1835–1842 (2012).
[Crossref]

2011 (1)

H. Hama, H. Kurokawa, H. Kawano, R. Ando, T. Shimogori, H. Noda, K. Fukami, A. Sakaue-Sawano, and A. Miyawaki, “Scale: a chemical approach for fluorescence imaging and reconstruction of transparent mouse brain,” Nat. Neurosci. 14(11), 1481–1488 (2011).
[Crossref]

2010 (1)

F. T. Nguyen, A. M. Zysk, E. J. Chaney, S. G. Adie, J. G. Kotynek, U. J. Oliphant, F. J. Bellafiore, K. M. Rowland, P. A. Johnson, and S. A. Boppart, “Optical Coherence Tomography: The Intraoperative Assessment of Lymph Nodes in Breast Cancer,” IEEE Eng. Med. Biol. Mag. 29(2), 63–70 (2010).
[Crossref]

2009 (1)

P. S. Tsai, J. P. Kaufhold, P. Blinder, B. Friedman, P. J. Drew, H. J. Karten, P. D. Lyden, and D. Kleinfeld, “Correlations of Neuronal and Microvascular Densities in Murine Cortex Revealed by Direct Counting and Colocalization of Nuclei and Vessels,” J. Neurosci. 29(46), 14553–14570 (2009).
[Crossref]

2006 (1)

C. Petibois and G. Déléris, “Chemical mapping of tumor progression by FT-IR imaging: towards molecular histopathology,” Trends Biotechnol. 24(10), 455–462 (2006).
[Crossref]

2005 (1)

D. C. Fernandez, R. Bhargava, S. M. Hewitt, and I. W. Levin, “Infrared spectroscopic imaging for histopathologic recognition,” Nat. Biotechnol. 23(4), 469–474 (2005).
[Crossref]

Adie, S. G.

R. M. Nolan, S. G. Adie, M. Marjanovic, E. J. Chaney, F. A. South, G. L. Monroy, N. D. Shemonski, S. J. Erickson-Bhatt, R. L. Shelton, A. J. Bower, D. G. Simpson, K. A. Cradock, Z. G. Liu, P. S. Ray, and S. A. Boppart, “Intraoperative optical coherence tomography for assessing human lymph nodes for metastatic cancer,” BMC Cancer 16(1), 144 (2016).
[Crossref]

F. T. Nguyen, A. M. Zysk, E. J. Chaney, S. G. Adie, J. G. Kotynek, U. J. Oliphant, F. J. Bellafiore, K. M. Rowland, P. A. Johnson, and S. A. Boppart, “Optical Coherence Tomography: The Intraoperative Assessment of Lymph Nodes in Breast Cancer,” IEEE Eng. Med. Biol. Mag. 29(2), 63–70 (2010).
[Crossref]

Aft, R. L.

T. T. W. Wong, R. Zhang, P. Hai, C. Zhang, M. A. Pleitez, R. L. Aft, D. V. Novack, and L. V. Wang, “Fast label-free multilayered histology-like imaging of human breast cancer by photoacoustic microscopy,” Sci. Adv. 3(5), e1602168 (2017).
[Crossref]

Agar, N. Y. R.

F.-K. Lu, D. Calligaris, O. I. Olubiyi, I. Norton, W. Yang, S. Santagata, X. S. Xie, A. J. Golby, and N. Y. R. Agar, “Label-Free Neurosurgical Pathology with Stimulated Raman Imaging,” Cancer Res. 76(12), 3451–3462 (2016).
[Crossref]

M. Ji, D. A. Orringer, C. W. Freudiger, S. Ramkissoon, X. Liu, D. Lau, A. J. Golby, I. Norton, M. Hayashi, N. Y. R. Agar, G. S. Young, C. Spino, S. Santagata, S. Camelo-Piragua, K. L. Ligon, O. Sagher, and X. S. Xie, “Rapid, Label-Free Detection of Brain Tumors with Stimulated Raman Scattering Microscopy,” Sci. Transl. Med. 5(201), 201ra119 (2013).
[Crossref]

Ando, R.

H. Hama, H. Kurokawa, H. Kawano, R. Ando, T. Shimogori, H. Noda, K. Fukami, A. Sakaue-Sawano, and A. Miyawaki, “Scale: a chemical approach for fluorescence imaging and reconstruction of transparent mouse brain,” Nat. Neurosci. 14(11), 1481–1488 (2011).
[Crossref]

Andrew Chan, K. L.

K. L. Andrew Chan and S. G. Kazarian, “Attenuated total reflection Fourier-transform infrared (ATR-FTIR) imaging of tissues and live cells,” Chem. Soc. Rev. 45(7), 1850–1864 (2016).
[Crossref]

Badve, S.

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M. Ji, S. Lewis, S. Camelo-Piragua, S. H. Ramkissoon, M. Snuderl, S. Venneti, A. Fisher-Hubbard, M. Garrard, D. Fu, A. C. Wang, J. A. Heth, C. O. Maher, N. Sanai, T. D. Johnson, C. W. Freudiger, O. Sagher, X. S. Xie, and D. A. Orringer, “Detection of human brain tumor infiltration with quantitative stimulated Raman scattering microscopy,” Sci. Transl. Med. 7(309), 309ra163 (2015).
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Y. Sun, S. You, H. Tu, D. R. Spillman, E. J. Chaney, M. Marjanovic, J. Li, R. Barkalifa, J. Wang, A. M. Higham, N. N. Luckey, K. A. Cradock, Z. George Liu, and S. A. Boppart, “Intraoperative visualization of the tumor microenvironment and quantification of extracellular vesicles by label-free nonlinear imaging,” Sci. Adv. 4(12), eaau5603 (2018).
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M. Wei, L. Shi, Y. Shen, Z. Zhao, A. Guzman, L. J. Kaufman, L. Wei, and W. Min, “Volumetric chemical imaging by clearing-enhanced stimulated Raman scattering microscopy,” Proc. Natl. Acad. Sci. U. S. A. 116(14), 6608–6617 (2019).
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R. Mittal, M. Balu, T. Krasieva, E. O. Potma, L. Elkeeb, C. B. Zachary, and P. Wilder-Smith, “Evaluation of stimulated raman scattering microscopy for identifying squamous cell carcinoma in human skin,” Lasers Surg. Med. 45(8), 496–502 (2013).
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D. A. Orringer, B. Pandian, Y. S. Niknafs, T. C. Hollon, J. Boyle, S. Lewis, M. Garrard, S. L. Hervey-Jumper, H. J. L. Garton, C. O. Maher, J. A. Heth, O. Sagher, D. A. Wilkinson, M. Snuderl, S. Venneti, S. H. Ramkissoon, K. A. McFadden, A. Fisher-Hubbard, A. P. Lieberman, T. D. Johnson, X. S. Xie, J. K. Trautman, C. W. Freudiger, and S. Camelo-Piragua, “Rapid intraoperative histology of unprocessed surgical specimens via fibre-laser-based stimulated Raman scattering microscopy,” Nat. Biomed. Eng. 1(2), 0027 (2017).
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T. T. W. Wong, R. Zhang, P. Hai, C. Zhang, M. A. Pleitez, R. L. Aft, D. V. Novack, and L. V. Wang, “Fast label-free multilayered histology-like imaging of human breast cancer by photoacoustic microscopy,” Sci. Adv. 3(5), e1602168 (2017).
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B. Liu, H. J. Lee, D. Zhang, C.-S. Liao, N. Ji, Y. Xia, and J.-X. Cheng, “Label-free spectroscopic detection of membrane potential using stimulated Raman scattering,” Appl. Phys. Lett. 106(17), 173704 (2015).
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D. Fu and X. S. Xie, “Reliable Cell Segmentation Based on Spectral Phasor Analysis of Hyperspectral Stimulated Raman Scattering Imaging Data,” Anal. Chem. 86(9), 4115–4119 (2014).
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M. Ji, D. A. Orringer, C. W. Freudiger, S. Ramkissoon, X. Liu, D. Lau, A. J. Golby, I. Norton, M. Hayashi, N. Y. R. Agar, G. S. Young, C. Spino, S. Santagata, S. Camelo-Piragua, K. L. Ligon, O. Sagher, and X. S. Xie, “Rapid, Label-Free Detection of Brain Tumors with Stimulated Raman Scattering Microscopy,” Sci. Transl. Med. 5(201), 201ra119 (2013).
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Supplementary Material (12)

NameDescription
» Visualization 1       SRS image stack of brain slice (~500 µm) incubated in PBS solution.
» Visualization 2       SRS image stack of brain slice (~500 µm) cleared by ScaleA2 solution.
» Visualization 3       SRS image stack of brain slice (~500 µm) cleared by sucrose solution.
» Visualization 4       SRS image stack of brain slice (~500 µm) cleared by ClearT solution.
» Visualization 5       SRS image stack of kidney slice (~1 mm) cleared by ClearT solution.
» Visualization 6       SRS image stack of liver slice (~1 mm) cleared by ClearT solution.
» Visualization 7       SRS image stack of lung slice (~1 mm) cleared by ClearT solution.
» Visualization 8       SRS image stack of brain slice (~1 mm) cleared by ClearT solution.
» Visualization 9       SRS image stack of brain slice (~1 mm) cleared by ClearT solution with 5% Triton X-100.
» Visualization 10       Reconstructed 3D SRS image of brain slice (~1 mm) cleared by ClearT solution with 5% Triton X-100.
» Visualization 11       Hyperspectral SRS image stack of brain slice cleared by ClearT with 5% Triton X-100.
» Visualization 12       Composite SRS image stack of brain slice at different depth.

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Figures (5)

Fig. 1.
Fig. 1. Comparison of different clearing methods. (a) Pictures of brains slices (∼500 µm thick) cleared with different methods. (b) SRS images taken at 2930 cm−1 from brain slices cleared by different methods at indicated depth (see Visualization 1Visualization 4). Nerve fibers and individual cell bodies can be clearly resolved. Image display ranges were adjusted individually to show the contrast clearly. Scale bars: 20 µm. (c) Intensity profile over depth from the images shown in (b).
Fig. 2.
Fig. 2. Demonstration of tissue clearance in various organs. (a) SRS images taken at 2930 cm−1 from ClearT cleared kidney, liver and lung tissue slices (∼ 1 mm thick) at indicated depth (see Visualization 5Visualization 7). Tissue organization and characteristic structures like renal tubules (kidney), lobules and veins (liver), and alveoli (lung) can be identified. Image display ranges were adjusted individually to better show the contrast. Scale bars: 20 µm. (b) Intensity profile over depth from the images in (a).
Fig. 3.
Fig. 3. Spectroscopic analysis of different clearing solutions. (a) SRS images of different clearing solutions at 2930 cm−1 and 2850 cm−1. Scale bars: 20 µm. (b) SRS spectra of clearing solutions in the region from 2800 cm−1 to 3050 cm−1. (c) Raman spectra taken by spontaneous Raman spectroscopy with 532 nm as excitation light.
Fig. 4.
Fig. 4. Improvement of imaging depth with detergent. (a) SRS images taken at 2930 cm−1 from brain slices (∼1 mm thick) cleared by ClearT solution with or without 5% Triton X-100 at indicated depth (see Visualization 8Visualization 10). Individual neural cell bodies and nerve fiber can be resolved at indicated depths of brain slices. Two cortex layers (stronger signal) are reveled in the ClearT + 5% Triton X-100 cleared brain slice. Image display ranges were adjusted individually to better show the contrast. Scale bars: 20 µm. (b) Intensity profile over depth from the images shown in (a). (c) Raman spectra of ClearT solution with or without 5% Triton X-100.
Fig. 5.
Fig. 5. Two-color SRS imaging of cleared tissue toward 3D histopathology. (a) Left: maximum intensity projection image projected from a hyperspectral SRS image stack of a brain tissue slice cleared with ClearT method with 5% Triton X-100 (see Visualization 11). Right: single frame SRS images at 2930 cm−1 (CH3), 2850 cm−1 (CH2), subtracted image (CH3 ‒ CH2), and composite image of (CH3 ‒ CH2) and (CH2). Individual neural cell bodies are clearly resolved. (b) CH3, CH2, CH3 ‒ CH2, and composite images of cleared brain slice at different depth (see Visualization 12). Neural cell bodies and nerve fibers are resolved at different layers of brain cortex. Image display ranges were adjusted individually to better show the contrast. Scale bars: 20 µm.

Tables (1)

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Table 1. Comparison of different clearing methods in composition and clearance time.

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