Abstract

In the clinical practice of pathology, trichrome stains are commonly used to highlight collagen and to help evaluate fibrosis. Such stains do delineate collagen deposits but are not molecularly specific and can suffer from staining inconsistencies. Moreover, performing histochemical stain evaluation requires the preparation of additional sections beyond the original hematoxylin- and eosin-stained slides, as well as additional staining steps, which together add cost, time, and workflow complications. We have developed a new microscopy approach, termed DUET (DUal-mode Emission and Transmission) that can be used to extract signals that would typically require special stains or advanced optical methods. Our preliminary analysis demonstrates the potential of using the resulting signals to generate virtual histochemical images that resemble trichrome-stained slides and can support clinical evaluation. We demonstrate advantages of this approach over images acquired from conventional trichrome-stained slides and compare them with images created using second harmonic generation microscopy.

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

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    [Crossref]
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    [Crossref]
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    [Crossref]
  27. P.A. Bautista, T. Abe, M. Yamaguchi, N. Ohyama, and Y. Yagi, Multispectral image enhancement for H&E stained pathological tissue specimens, Medical Imaging 2008: Visualization, Image-Guided Procedures, and Modeling, International Society for Optics and Photonics, 2008, pp. 691836.
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  31. J. T. McMahon, J. L. Myles, and R. R. Tubbs, “Demonstration of Immune Complex Deposits Using Fluorescence Microscopy of Hematoxylin and Eosin–Stained Sections of Hollande's Fixed Renal Biopsies,” Mod. Pathol. 15(9), 988–997 (2002).
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    [Crossref]
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    [Crossref]
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    [Crossref]
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    [Crossref]
  40. F. J. Vergeldt, A. Prusova, F. Fereidouni, H. Van Amerongen, H. Van As, T. W. Scheenen, and A. N. Bader, “Multi-component quantitative magnetic resonance imaging by phasor representation,” Sci. Rep. 7(1), 861 (2017).
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    [Crossref]
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  44. A. L. Fidler, C. E. Darris, S. V. Chetyrkin, V. K. Pedchenko, S. P. Boudko, K. L. Brown, W. G. Jerome, J. K. Hudson, A. Rokas, and B. G. Hudson, “Collagen IV and basement membrane at the evolutionary dawn of metazoan tissues,” elife 6, e24176 (2017).
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  45. A. Likas, N. Vlassis, and J. J. Verbeek, “The global k-means clustering algorithm,” Pattern Recognition 36(2), 451–461 (2003).
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  46. S.-O. Deininger, M. P. Ebert, A. Futterer, M. Gerhard, and C. Rocken, “MALDI imaging combined with hierarchical clustering as a new tool for the interpretation of complex human cancers,” J. Proteome Res. 7(12), 5230–5236 (2008).
    [Crossref]

2019 (2)

D. Tokarz, R. Cisek, A. Joseph, A. Golaraei, K. Mirsanaye, S. Krouglov, S.L. Asa, B.C. Wilson, and V. Barzda, “Characterization of Pancreatic Cancer Tissue using Multiphoton Excitation Fluorescence and Polarization-Sensitive Harmonic Generation Microscopy,” Front. Oncol. 9, 272 (2019).
[Crossref]

Y. Rivenson, H. Wang, Z. Wei, K. de Haan, Y. Zhang, Y. Wu, H. Günaydın, J. E. Zuckerman, T. Chong, and A. E. Sisk, “Virtual histological staining of unlabelled tissue-autofluorescence images via deep learning,” Nat. Biomed. Eng. 3(6), 466–477 (2019).
[Crossref]

2018 (5)

F. Fereidouni, C. Griffin, A. Todd, and R. Levenson, “Multispectral analysis tools can increase utility of RGB color images in histology,” J. Opt. 20(4), 044007 (2018).
[Crossref]

A. L. Fidler, S. P. Boudko, A. Rokas, and B. G. Hudson, “The triple helix of collagens–an ancient protein structure that enabled animal multicellularity and tissue evolution,” J. Cell. Sci. 131(7), jcs203950 (2018).
[Crossref]

M. Yamauchi, T. H. Barker, D. L. Gibbons, and J. M. Kurie, “The fibrotic tumor stroma,” J. Clin. Invest. 128(1), 16–25 (2018).
[Crossref]

R. A. Natal, J. Vassallo, G. R. Paiva, V. B. Pelegati, G. O. Barbosa, G. R. Mendonça, C. Bondarik, S. F. Derchain, H. F. Carvalho, and C. S. Lima, “Collagen analysis by second-harmonic generation microscopy predicts outcome of luminal breast cancer,” Tumor Biol. 40(4), 1010428318770953 (2018).
[Crossref]

E. Rodner, T. Bocklitz, F. von Eggeling, G. Ernst, O. Chernavskaia, J. Popp, J. Denzler, and O. Guntinas-Lichius, “Fully convolutional networks in multimodal nonlinear microscopy images for automated detection of head and neck carcinoma: Pilot study,” Head & Neck 41(1), hed.25489 (2018).
[Crossref]

2017 (3)

T. Luo, Y. Lu, S. Liu, D. Lin, and J. Qu, “Enhanced Visualization of Hematoxylin and Eosin Stained Pathological Characteristics by Phasor Approach,” Anal. Chem. 89(17), 9224–9231 (2017).
[Crossref]

A. L. Fidler, C. E. Darris, S. V. Chetyrkin, V. K. Pedchenko, S. P. Boudko, K. L. Brown, W. G. Jerome, J. K. Hudson, A. Rokas, and B. G. Hudson, “Collagen IV and basement membrane at the evolutionary dawn of metazoan tissues,” elife 6, e24176 (2017).
[Crossref]

F. J. Vergeldt, A. Prusova, F. Fereidouni, H. Van Amerongen, H. Van As, T. W. Scheenen, and A. N. Bader, “Multi-component quantitative magnetic resonance imaging by phasor representation,” Sci. Rep. 7(1), 861 (2017).
[Crossref]

2016 (3)

S. Awasthi, L. T. Izu, Z. Mao, Z. Jian, T. Landas, A. Lerner, R. Shimkunas, R. Woldeyesus, J. Bossuyt, and B. M. Wood, “Multimodal SHG-2PF imaging of microdomain Ca2+-contraction coupling in live cardiac myocytes,” Circ. Res. 118(2), e19–e28 (2016).
[Crossref]

C. R. Drifka, A. G. Loeffler, K. Mathewson, G. Mehta, A. Keikhosravi, Y. Liu, S. Lemancik, W. A. Ricke, S. M. Weber, and W. J. Kao, “Comparison of picrosirius red staining with second harmonic generation imaging for the quantification of clinically relevant collagen fiber features in histopathology samples,” J. Histochem. Cytochem. 64(9), 519–529 (2016).
[Crossref]

C. R. Drifka, A. G. Loeffler, K. Mathewson, A. Keikhosravi, J. C. Eickhoff, Y. Liu, S. M. Weber, W. J. Kao, and K. W. Eliceiri, “Highly aligned stromal collagen is a negative prognostic factor following pancreatic ductal adenocarcinoma resection,” Oncotarget 7, 76197 (2016).
[Crossref]

2015 (2)

M. Shribak, “Polychromatic polarization microscope: bringing colors to a colorless world,” Sci. Rep. 5(1), 17340 (2015).
[Crossref]

L. Andronia, V. Mireșan, A. Coroian, I. Pop, C. Răducu, A. Rotaru, D. Cocan, S.C. Pânzaru, I. Domșa, and C.O. Coroian, “Raman Spectroscopy of the Hematoxylin-Eosin Stained Tissue,” ProEnvironment/ProMediu 8(24), 590–600 (2015).

2014 (4)

E. Leoncini, W. Ricciardi, G. Cadoni, D. Arzani, L. Petrelli, G. Paludetti, P. Brennan, D. Luce, I. Stucker, and K. Matsuo, “Adult height and head and neck cancer: a pooled analysis within the INHANCE Consortium,” Eur. J. Epidemiol. 29(1), 35–48 (2014).
[Crossref]

J. Gu, C. Y. Fu, B. K. Ng, S. Gulam Razul, and S. K. Lim, “Quantitative diagnosis of cervical neoplasia using fluorescence lifetime imaging on haematoxylin and eosin stained tissue sections,” J. Biophotonics 7(7), 483–491 (2014).
[Crossref]

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]

F. Fereidouni, A. N. Bader, A. Colonna, and H. C. Gerritsen, “Phasor analysis of multiphoton spectral images distinguishes autofluorescence components of in vivo human skin,” J. Biophotonics 7, 589–596 (2014).
[Crossref]

2013 (1)

2012 (3)

F. Fereidouni, A. N. Bader, and H. C. Gerritsen, “Spectral phasor analysis allows rapid and reliable unmixing of fluorescence microscopy spectral images,” Opt. Express 20(12), 12729–12741 (2012).
[Crossref]

P. A. Bautista and Y. Yagi, “Digital simulation of staining in histopathology multispectral images: enhancement and linear transformation of spectral transmittance,” J. Biomed. Opt. 17(5), 056013 (2012).
[Crossref]

X. Chen, O. Nadiarynkh, S. Plotnikov, and P. J. Campagnola, “Second harmonic generation microscopy for quantitative analysis of collagen fibrillar structure,” Nat. Protoc. 7(4), 654–669 (2012).
[Crossref]

2011 (4)

P.A. Bautista and Y. Yagi, “Localization of Eosinophilic Esophagitis from H&E stained images using multispectral imaging,” Diagn. Pathol. 6(S1), S2 (2011).
[Crossref]

P.A. Bautista and Y. Yagi, “Localization of eosinophilic esophagitis from H&E stained images using multispectral imaging,” Diagn. Pathol. 6(S1), S2 (2011).
[Crossref]

A. B. Farris, C. D. Adams, N. Brousaides, P. A. Della Pelle, A. B. Collins, E. Moradi, R. N. Smith, P. C. Grimm, and R. B. Colvin, “Morphometric and visual evaluation of fibrosis in renal biopsies,” J. Am. Soc. Nephrol. 22(1), 176–186 (2011).
[Crossref]

N. Hashimoto, Y. Murakami, P. A. Bautista, M. Yamaguchi, T. Obi, N. Ohyama, K. Uto, and Y. Kosugi, “Multispectral image enhancement for effective visualization,” Opt. Express 19(10), 9315–9329 (2011).
[Crossref]

2010 (1)

C. Frantz, K. M. Stewart, and V. M. Weaver, “The extracellular matrix at a glance,” J. Cell Sci. 123(24), 4195–4200 (2010).
[Crossref]

2009 (1)

M. D. Shoulders and R. T. Raines, “Collagen structure and stability,” Annu. Rev. Biochem. 78(1), 929–958 (2009).
[Crossref]

2008 (4)

D. Tretheway, A. Jain, R. LaPoint, R. Sharma, M. Orloff, P. Milot, A. Bozorgzadeh, and C. Ryan, “Should trichrome stain be used on all post–liver transplant biopsies with hepatitis C virus infection to estimate the fibrosis score?” Liver Transpl. 14, 695–700 (2008).
[Crossref]

R. M. Levenson, A. Fornari, and M. Loda, “Multispectral imaging and pathology: seeing and doing more,” Expert Opin. Med. Diagn. 2(9), 1067–1081 (2008).
[Crossref]

S.-O. Deininger, M. P. Ebert, A. Futterer, M. Gerhard, and C. Rocken, “MALDI imaging combined with hierarchical clustering as a new tool for the interpretation of complex human cancers,” J. Proteome Res. 7(12), 5230–5236 (2008).
[Crossref]

M. A. Digman, V. R. Caiolfa, M. Zamai, and E. Gratton, “The phasor approach to fluorescence lifetime imaging analysis,” Biophys. J. 94(2), L14–L16 (2008).
[Crossref]

2005 (1)

P. A. Bautista, T. Abe, M. Yamaguchi, Y. Yagi, and N. Ohyama, “Digital staining for multispectral images of pathological tissue specimens based on combined classification of spectral transmittance,” Computerized Medical Imaging and Graphics 29(8), 649–657 (2005).
[Crossref]

2003 (1)

A. Likas, N. Vlassis, and J. J. Verbeek, “The global k-means clustering algorithm,” Pattern Recognition 36(2), 451–461 (2003).
[Crossref]

2002 (2)

J. T. McMahon, J. L. Myles, and R. R. Tubbs, “Demonstration of Immune Complex Deposits Using Fluorescence Microscopy of Hematoxylin and Eosin–Stained Sections of Hollande's Fixed Renal Biopsies,” Mod. Pathol. 15(9), 988–997 (2002).
[Crossref]

J. Jakubovský, L. Guller, M. Černá, K. Balážová, Š Polák, V. Jakubovská, and P. Babál, “Fluorescence of hematoxylin and eosin-stained histological sections of the human spleen,” Acta Histochem. 104(4), 353–356 (2002).
[Crossref]

1996 (1)

H. F. de Carvalho and S. R. Taboga, “Fluorescence and confocal laser scanning microscopy imaging of elastic fibers in hematoxylin-eosin stained sections,” Histochem. Cell Biol. 106(6), 587–592 (1996).
[Crossref]

1994 (1)

P. Whittaker, R. Kloner, D. Boughner, and J. Pickering, “Quantitative assessment of myocardial collagen with picrosirius red staining and circularly polarized light,” Basic Res. Cardiol. 89(5), 397–410 (1994).
[Crossref]

1969 (2)

D. Goldstein, “The fluorescence of elastic fibres stained with eosin and excited by visible light,” Histochem. J. 1(3), 187–198 (1969).
[Crossref]

R. Lev and P. J. Stoward, “On the use of eosin as a fluorescent dye to demonstrate mucous cells and other structures in tissue sections,” Histochemie 20(4), 363–377 (1969).
[Crossref]

1964 (1)

R. Lillie and G. Miller, “Histochemical acylation of hydroxyl and amino groups. Effect on the periodic acid Schiff reaction, anionic and cationic dye and Van Gieson collagen stains,” J. Histochem. Cytochem. 12(11), 821–841 (1964).
[Crossref]

1950 (1)

J. E. Cason, “A rapid one-step Mallory-Heidenhain stain for connective tissue,” Stain Technol. 25(4), 225–226 (1950).
[Crossref]

Abe, T.

P. A. Bautista, T. Abe, M. Yamaguchi, Y. Yagi, and N. Ohyama, “Digital staining for multispectral images of pathological tissue specimens based on combined classification of spectral transmittance,” Computerized Medical Imaging and Graphics 29(8), 649–657 (2005).
[Crossref]

P.A. Bautista, T. Abe, M. Yamaguchi, N. Ohyama, and Y. Yagi, Multispectral image enhancement for H&E stained pathological tissue specimens, Medical Imaging 2008: Visualization, Image-Guided Procedures, and Modeling, International Society for Optics and Photonics, 2008, pp. 691836.

Abeysekera, S.

S. Abeysekera, M.P.-L. Ooi, Y.C. Kuang, C.P. Tan, and S.S. Hassan, Detecting spongiosis in stained histopathological specimen using multispectral imaging and machine learning, 2014 IEEE Sensors Applications Symposium (SAS), IEEE, 2014, pp. 195–200.

Adams, C. D.

A. B. Farris, C. D. Adams, N. Brousaides, P. A. Della Pelle, A. B. Collins, E. Moradi, R. N. Smith, P. C. Grimm, and R. B. Colvin, “Morphometric and visual evaluation of fibrosis in renal biopsies,” J. Am. Soc. Nephrol. 22(1), 176–186 (2011).
[Crossref]

Andronia, L.

L. Andronia, V. Mireșan, A. Coroian, I. Pop, C. Răducu, A. Rotaru, D. Cocan, S.C. Pânzaru, I. Domșa, and C.O. Coroian, “Raman Spectroscopy of the Hematoxylin-Eosin Stained Tissue,” ProEnvironment/ProMediu 8(24), 590–600 (2015).

Arzani, D.

E. Leoncini, W. Ricciardi, G. Cadoni, D. Arzani, L. Petrelli, G. Paludetti, P. Brennan, D. Luce, I. Stucker, and K. Matsuo, “Adult height and head and neck cancer: a pooled analysis within the INHANCE Consortium,” Eur. J. Epidemiol. 29(1), 35–48 (2014).
[Crossref]

Asa, S.L.

D. Tokarz, R. Cisek, A. Joseph, A. Golaraei, K. Mirsanaye, S. Krouglov, S.L. Asa, B.C. Wilson, and V. Barzda, “Characterization of Pancreatic Cancer Tissue using Multiphoton Excitation Fluorescence and Polarization-Sensitive Harmonic Generation Microscopy,” Front. Oncol. 9, 272 (2019).
[Crossref]

Awasthi, S.

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D. Tretheway, A. Jain, R. LaPoint, R. Sharma, M. Orloff, P. Milot, A. Bozorgzadeh, and C. Ryan, “Should trichrome stain be used on all post–liver transplant biopsies with hepatitis C virus infection to estimate the fibrosis score?” Liver Transpl. 14, 695–700 (2008).
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D. Tretheway, A. Jain, R. LaPoint, R. Sharma, M. Orloff, P. Milot, A. Bozorgzadeh, and C. Ryan, “Should trichrome stain be used on all post–liver transplant biopsies with hepatitis C virus infection to estimate the fibrosis score?” Liver Transpl. 14, 695–700 (2008).
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F. J. Vergeldt, A. Prusova, F. Fereidouni, H. Van Amerongen, H. Van As, T. W. Scheenen, and A. N. Bader, “Multi-component quantitative magnetic resonance imaging by phasor representation,” Sci. Rep. 7(1), 861 (2017).
[Crossref]

Sharma, R.

D. Tretheway, A. Jain, R. LaPoint, R. Sharma, M. Orloff, P. Milot, A. Bozorgzadeh, and C. Ryan, “Should trichrome stain be used on all post–liver transplant biopsies with hepatitis C virus infection to estimate the fibrosis score?” Liver Transpl. 14, 695–700 (2008).
[Crossref]

Shimkunas, R.

S. Awasthi, L. T. Izu, Z. Mao, Z. Jian, T. Landas, A. Lerner, R. Shimkunas, R. Woldeyesus, J. Bossuyt, and B. M. Wood, “Multimodal SHG-2PF imaging of microdomain Ca2+-contraction coupling in live cardiac myocytes,” Circ. Res. 118(2), e19–e28 (2016).
[Crossref]

Shoulders, M. D.

M. D. Shoulders and R. T. Raines, “Collagen structure and stability,” Annu. Rev. Biochem. 78(1), 929–958 (2009).
[Crossref]

Shribak, M.

M. Shribak, “Polychromatic polarization microscope: bringing colors to a colorless world,” Sci. Rep. 5(1), 17340 (2015).
[Crossref]

Sisk, A. E.

Y. Rivenson, H. Wang, Z. Wei, K. de Haan, Y. Zhang, Y. Wu, H. Günaydın, J. E. Zuckerman, T. Chong, and A. E. Sisk, “Virtual histological staining of unlabelled tissue-autofluorescence images via deep learning,” Nat. Biomed. Eng. 3(6), 466–477 (2019).
[Crossref]

Smith, R. N.

A. B. Farris, C. D. Adams, N. Brousaides, P. A. Della Pelle, A. B. Collins, E. Moradi, R. N. Smith, P. C. Grimm, and R. B. Colvin, “Morphometric and visual evaluation of fibrosis in renal biopsies,” J. Am. Soc. Nephrol. 22(1), 176–186 (2011).
[Crossref]

Stewart, K. M.

C. Frantz, K. M. Stewart, and V. M. Weaver, “The extracellular matrix at a glance,” J. Cell Sci. 123(24), 4195–4200 (2010).
[Crossref]

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R. Lev and P. J. Stoward, “On the use of eosin as a fluorescent dye to demonstrate mucous cells and other structures in tissue sections,” Histochemie 20(4), 363–377 (1969).
[Crossref]

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E. Leoncini, W. Ricciardi, G. Cadoni, D. Arzani, L. Petrelli, G. Paludetti, P. Brennan, D. Luce, I. Stucker, and K. Matsuo, “Adult height and head and neck cancer: a pooled analysis within the INHANCE Consortium,” Eur. J. Epidemiol. 29(1), 35–48 (2014).
[Crossref]

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H. F. de Carvalho and S. R. Taboga, “Fluorescence and confocal laser scanning microscopy imaging of elastic fibers in hematoxylin-eosin stained sections,” Histochem. Cell Biol. 106(6), 587–592 (1996).
[Crossref]

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S. Abeysekera, M.P.-L. Ooi, Y.C. Kuang, C.P. Tan, and S.S. Hassan, Detecting spongiosis in stained histopathological specimen using multispectral imaging and machine learning, 2014 IEEE Sensors Applications Symposium (SAS), IEEE, 2014, pp. 195–200.

Todd, A.

F. Fereidouni, C. Griffin, A. Todd, and R. Levenson, “Multispectral analysis tools can increase utility of RGB color images in histology,” J. Opt. 20(4), 044007 (2018).
[Crossref]

Tokarz, D.

D. Tokarz, R. Cisek, A. Joseph, A. Golaraei, K. Mirsanaye, S. Krouglov, S.L. Asa, B.C. Wilson, and V. Barzda, “Characterization of Pancreatic Cancer Tissue using Multiphoton Excitation Fluorescence and Polarization-Sensitive Harmonic Generation Microscopy,” Front. Oncol. 9, 272 (2019).
[Crossref]

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D. Tretheway, A. Jain, R. LaPoint, R. Sharma, M. Orloff, P. Milot, A. Bozorgzadeh, and C. Ryan, “Should trichrome stain be used on all post–liver transplant biopsies with hepatitis C virus infection to estimate the fibrosis score?” Liver Transpl. 14, 695–700 (2008).
[Crossref]

Tubbs, R. R.

J. T. McMahon, J. L. Myles, and R. R. Tubbs, “Demonstration of Immune Complex Deposits Using Fluorescence Microscopy of Hematoxylin and Eosin–Stained Sections of Hollande's Fixed Renal Biopsies,” Mod. Pathol. 15(9), 988–997 (2002).
[Crossref]

Uto, K.

Van Amerongen, H.

F. J. Vergeldt, A. Prusova, F. Fereidouni, H. Van Amerongen, H. Van As, T. W. Scheenen, and A. N. Bader, “Multi-component quantitative magnetic resonance imaging by phasor representation,” Sci. Rep. 7(1), 861 (2017).
[Crossref]

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F. J. Vergeldt, A. Prusova, F. Fereidouni, H. Van Amerongen, H. Van As, T. W. Scheenen, and A. N. Bader, “Multi-component quantitative magnetic resonance imaging by phasor representation,” Sci. Rep. 7(1), 861 (2017).
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R. A. Natal, J. Vassallo, G. R. Paiva, V. B. Pelegati, G. O. Barbosa, G. R. Mendonça, C. Bondarik, S. F. Derchain, H. F. Carvalho, and C. S. Lima, “Collagen analysis by second-harmonic generation microscopy predicts outcome of luminal breast cancer,” Tumor Biol. 40(4), 1010428318770953 (2018).
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A. Likas, N. Vlassis, and J. J. Verbeek, “The global k-means clustering algorithm,” Pattern Recognition 36(2), 451–461 (2003).
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F. J. Vergeldt, A. Prusova, F. Fereidouni, H. Van Amerongen, H. Van As, T. W. Scheenen, and A. N. Bader, “Multi-component quantitative magnetic resonance imaging by phasor representation,” Sci. Rep. 7(1), 861 (2017).
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E. Rodner, T. Bocklitz, F. von Eggeling, G. Ernst, O. Chernavskaia, J. Popp, J. Denzler, and O. Guntinas-Lichius, “Fully convolutional networks in multimodal nonlinear microscopy images for automated detection of head and neck carcinoma: Pilot study,” Head & Neck 41(1), hed.25489 (2018).
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Y. Rivenson, H. Wang, Z. Wei, K. de Haan, Y. Zhang, Y. Wu, H. Günaydın, J. E. Zuckerman, T. Chong, and A. E. Sisk, “Virtual histological staining of unlabelled tissue-autofluorescence images via deep learning,” Nat. Biomed. Eng. 3(6), 466–477 (2019).
[Crossref]

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C. Frantz, K. M. Stewart, and V. M. Weaver, “The extracellular matrix at a glance,” J. Cell Sci. 123(24), 4195–4200 (2010).
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C. R. Drifka, A. G. Loeffler, K. Mathewson, A. Keikhosravi, J. C. Eickhoff, Y. Liu, S. M. Weber, W. J. Kao, and K. W. Eliceiri, “Highly aligned stromal collagen is a negative prognostic factor following pancreatic ductal adenocarcinoma resection,” Oncotarget 7, 76197 (2016).
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C. R. Drifka, A. G. Loeffler, K. Mathewson, G. Mehta, A. Keikhosravi, Y. Liu, S. Lemancik, W. A. Ricke, S. M. Weber, and W. J. Kao, “Comparison of picrosirius red staining with second harmonic generation imaging for the quantification of clinically relevant collagen fiber features in histopathology samples,” J. Histochem. Cytochem. 64(9), 519–529 (2016).
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S. Awasthi, L. T. Izu, Z. Mao, Z. Jian, T. Landas, A. Lerner, R. Shimkunas, R. Woldeyesus, J. Bossuyt, and B. M. Wood, “Multimodal SHG-2PF imaging of microdomain Ca2+-contraction coupling in live cardiac myocytes,” Circ. Res. 118(2), e19–e28 (2016).
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S. Awasthi, L. T. Izu, Z. Mao, Z. Jian, T. Landas, A. Lerner, R. Shimkunas, R. Woldeyesus, J. Bossuyt, and B. M. Wood, “Multimodal SHG-2PF imaging of microdomain Ca2+-contraction coupling in live cardiac myocytes,” Circ. Res. 118(2), e19–e28 (2016).
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P.A. Bautista and Y. Yagi, “Localization of Eosinophilic Esophagitis from H&E stained images using multispectral imaging,” Diagn. Pathol. 6(S1), S2 (2011).
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N. Hashimoto, Y. Murakami, P. A. Bautista, M. Yamaguchi, T. Obi, N. Ohyama, K. Uto, and Y. Kosugi, “Multispectral image enhancement for effective visualization,” Opt. Express 19(10), 9315–9329 (2011).
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M. Yamauchi, T. H. Barker, D. L. Gibbons, and J. M. Kurie, “The fibrotic tumor stroma,” J. Clin. Invest. 128(1), 16–25 (2018).
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Yang, D.-H.

Z.-S.J. Chen and D.-H. Yang, Protein Kinase Inhibitors as Sensitizing Agents for Chemotherapy (Academic Press, 2018).

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Y. Rivenson, H. Wang, Z. Wei, K. de Haan, Y. Zhang, Y. Wu, H. Günaydın, J. E. Zuckerman, T. Chong, and A. E. Sisk, “Virtual histological staining of unlabelled tissue-autofluorescence images via deep learning,” Nat. Biomed. Eng. 3(6), 466–477 (2019).
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Y. Rivenson, H. Wang, Z. Wei, K. de Haan, Y. Zhang, Y. Wu, H. Günaydın, J. E. Zuckerman, T. Chong, and A. E. Sisk, “Virtual histological staining of unlabelled tissue-autofluorescence images via deep learning,” Nat. Biomed. Eng. 3(6), 466–477 (2019).
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Annu. Rev. Biochem. (1)

M. D. Shoulders and R. T. Raines, “Collagen structure and stability,” Annu. Rev. Biochem. 78(1), 929–958 (2009).
[Crossref]

Basic Res. Cardiol. (1)

P. Whittaker, R. Kloner, D. Boughner, and J. Pickering, “Quantitative assessment of myocardial collagen with picrosirius red staining and circularly polarized light,” Basic Res. Cardiol. 89(5), 397–410 (1994).
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M. A. Digman, V. R. Caiolfa, M. Zamai, and E. Gratton, “The phasor approach to fluorescence lifetime imaging analysis,” Biophys. J. 94(2), L14–L16 (2008).
[Crossref]

Circ. Res. (1)

S. Awasthi, L. T. Izu, Z. Mao, Z. Jian, T. Landas, A. Lerner, R. Shimkunas, R. Woldeyesus, J. Bossuyt, and B. M. Wood, “Multimodal SHG-2PF imaging of microdomain Ca2+-contraction coupling in live cardiac myocytes,” Circ. Res. 118(2), e19–e28 (2016).
[Crossref]

Computerized Medical Imaging and Graphics (1)

P. A. Bautista, T. Abe, M. Yamaguchi, Y. Yagi, and N. Ohyama, “Digital staining for multispectral images of pathological tissue specimens based on combined classification of spectral transmittance,” Computerized Medical Imaging and Graphics 29(8), 649–657 (2005).
[Crossref]

Diagn. Pathol. (2)

P.A. Bautista and Y. Yagi, “Localization of eosinophilic esophagitis from H&E stained images using multispectral imaging,” Diagn. Pathol. 6(S1), S2 (2011).
[Crossref]

P.A. Bautista and Y. Yagi, “Localization of Eosinophilic Esophagitis from H&E stained images using multispectral imaging,” Diagn. Pathol. 6(S1), S2 (2011).
[Crossref]

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A. L. Fidler, C. E. Darris, S. V. Chetyrkin, V. K. Pedchenko, S. P. Boudko, K. L. Brown, W. G. Jerome, J. K. Hudson, A. Rokas, and B. G. Hudson, “Collagen IV and basement membrane at the evolutionary dawn of metazoan tissues,” elife 6, e24176 (2017).
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E. Leoncini, W. Ricciardi, G. Cadoni, D. Arzani, L. Petrelli, G. Paludetti, P. Brennan, D. Luce, I. Stucker, and K. Matsuo, “Adult height and head and neck cancer: a pooled analysis within the INHANCE Consortium,” Eur. J. Epidemiol. 29(1), 35–48 (2014).
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R. M. Levenson, A. Fornari, and M. Loda, “Multispectral imaging and pathology: seeing and doing more,” Expert Opin. Med. Diagn. 2(9), 1067–1081 (2008).
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Front. Oncol. (1)

D. Tokarz, R. Cisek, A. Joseph, A. Golaraei, K. Mirsanaye, S. Krouglov, S.L. Asa, B.C. Wilson, and V. Barzda, “Characterization of Pancreatic Cancer Tissue using Multiphoton Excitation Fluorescence and Polarization-Sensitive Harmonic Generation Microscopy,” Front. Oncol. 9, 272 (2019).
[Crossref]

Head & Neck (1)

E. Rodner, T. Bocklitz, F. von Eggeling, G. Ernst, O. Chernavskaia, J. Popp, J. Denzler, and O. Guntinas-Lichius, “Fully convolutional networks in multimodal nonlinear microscopy images for automated detection of head and neck carcinoma: Pilot study,” Head & Neck 41(1), hed.25489 (2018).
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H. F. de Carvalho and S. R. Taboga, “Fluorescence and confocal laser scanning microscopy imaging of elastic fibers in hematoxylin-eosin stained sections,” Histochem. Cell Biol. 106(6), 587–592 (1996).
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A. B. Farris, C. D. Adams, N. Brousaides, P. A. Della Pelle, A. B. Collins, E. Moradi, R. N. Smith, P. C. Grimm, and R. B. Colvin, “Morphometric and visual evaluation of fibrosis in renal biopsies,” J. Am. Soc. Nephrol. 22(1), 176–186 (2011).
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J. Biomed. Opt. (1)

P. A. Bautista and Y. Yagi, “Digital simulation of staining in histopathology multispectral images: enhancement and linear transformation of spectral transmittance,” J. Biomed. Opt. 17(5), 056013 (2012).
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F. Fereidouni, A. N. Bader, A. Colonna, and H. C. Gerritsen, “Phasor analysis of multiphoton spectral images distinguishes autofluorescence components of in vivo human skin,” J. Biophotonics 7, 589–596 (2014).
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J. Gu, C. Y. Fu, B. K. Ng, S. Gulam Razul, and S. K. Lim, “Quantitative diagnosis of cervical neoplasia using fluorescence lifetime imaging on haematoxylin and eosin stained tissue sections,” J. Biophotonics 7(7), 483–491 (2014).
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A. L. Fidler, S. P. Boudko, A. Rokas, and B. G. Hudson, “The triple helix of collagens–an ancient protein structure that enabled animal multicellularity and tissue evolution,” J. Cell. Sci. 131(7), jcs203950 (2018).
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M. Yamauchi, T. H. Barker, D. L. Gibbons, and J. M. Kurie, “The fibrotic tumor stroma,” J. Clin. Invest. 128(1), 16–25 (2018).
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C. R. Drifka, A. G. Loeffler, K. Mathewson, G. Mehta, A. Keikhosravi, Y. Liu, S. Lemancik, W. A. Ricke, S. M. Weber, and W. J. Kao, “Comparison of picrosirius red staining with second harmonic generation imaging for the quantification of clinically relevant collagen fiber features in histopathology samples,” J. Histochem. Cytochem. 64(9), 519–529 (2016).
[Crossref]

J. Opt. (1)

F. Fereidouni, C. Griffin, A. Todd, and R. Levenson, “Multispectral analysis tools can increase utility of RGB color images in histology,” J. Opt. 20(4), 044007 (2018).
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D. Tretheway, A. Jain, R. LaPoint, R. Sharma, M. Orloff, P. Milot, A. Bozorgzadeh, and C. Ryan, “Should trichrome stain be used on all post–liver transplant biopsies with hepatitis C virus infection to estimate the fibrosis score?” Liver Transpl. 14, 695–700 (2008).
[Crossref]

Mod. Pathol. (1)

J. T. McMahon, J. L. Myles, and R. R. Tubbs, “Demonstration of Immune Complex Deposits Using Fluorescence Microscopy of Hematoxylin and Eosin–Stained Sections of Hollande's Fixed Renal Biopsies,” Mod. Pathol. 15(9), 988–997 (2002).
[Crossref]

Nat. Biomed. Eng. (1)

Y. Rivenson, H. Wang, Z. Wei, K. de Haan, Y. Zhang, Y. Wu, H. Günaydın, J. E. Zuckerman, T. Chong, and A. E. Sisk, “Virtual histological staining of unlabelled tissue-autofluorescence images via deep learning,” Nat. Biomed. Eng. 3(6), 466–477 (2019).
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C. R. Drifka, A. G. Loeffler, K. Mathewson, A. Keikhosravi, J. C. Eickhoff, Y. Liu, S. M. Weber, W. J. Kao, and K. W. Eliceiri, “Highly aligned stromal collagen is a negative prognostic factor following pancreatic ductal adenocarcinoma resection,” Oncotarget 7, 76197 (2016).
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Opt. Express (3)

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A. Likas, N. Vlassis, and J. J. Verbeek, “The global k-means clustering algorithm,” Pattern Recognition 36(2), 451–461 (2003).
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M. Shribak, “Polychromatic polarization microscope: bringing colors to a colorless world,” Sci. Rep. 5(1), 17340 (2015).
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F. J. Vergeldt, A. Prusova, F. Fereidouni, H. Van Amerongen, H. Van As, T. W. Scheenen, and A. N. Bader, “Multi-component quantitative magnetic resonance imaging by phasor representation,” Sci. Rep. 7(1), 861 (2017).
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R. A. Natal, J. Vassallo, G. R. Paiva, V. B. Pelegati, G. O. Barbosa, G. R. Mendonça, C. Bondarik, S. F. Derchain, H. F. Carvalho, and C. S. Lima, “Collagen analysis by second-harmonic generation microscopy predicts outcome of luminal breast cancer,” Tumor Biol. 40(4), 1010428318770953 (2018).
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Other (3)

Z.-S.J. Chen and D.-H. Yang, Protein Kinase Inhibitors as Sensitizing Agents for Chemotherapy (Academic Press, 2018).

S. Abeysekera, M.P.-L. Ooi, Y.C. Kuang, C.P. Tan, and S.S. Hassan, Detecting spongiosis in stained histopathological specimen using multispectral imaging and machine learning, 2014 IEEE Sensors Applications Symposium (SAS), IEEE, 2014, pp. 195–200.

P.A. Bautista, T. Abe, M. Yamaguchi, N. Ohyama, and Y. Yagi, Multispectral image enhancement for H&E stained pathological tissue specimens, Medical Imaging 2008: Visualization, Image-Guided Procedures, and Modeling, International Society for Optics and Photonics, 2008, pp. 691836.

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Figures (10)

Fig. 1.
Fig. 1. (Visual abstract) DUET imaging can identify collagen faithfully on H&E-stained slides and generate images that can improve upon conventional histochemical stains for better diagnostics and patient care.

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Fig. 2.
Fig. 2. Concept of the spectral phasor approach. A) Transformation of three example spectra into phasor points within the unit circle. B) Synthetic image composed of three (noisy) components. C) The phasor transformation of the image in panel B. D) Fitting a rotating two-dimensional Gaussian function to a phasor plot lobe and the fit parameters.

Download Full Size | PPT Slide | PDF

Fig. 3.
Fig. 3. DUET dual-mode imaging. An H&E slide is illuminated from below using a high color rendering index white LED and a color image is acquired; the white LEDs are turned off, and a 405-nm LED then is used in standard epifluorescence mode to excite fluorescence signals that are then collected using the same light path and camera. The two image modes are naturally pixel-registered. The process is repeated at each position of a whole-slide scanning procedure, using an XY stage and 10X lens. Brightfield image of human (B) kidney (C) liver and (D) breast from H&E slide. E-F: fluorescence images of human kidney, liver and breast from the same regions shown on B, C and D.

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Fig. 4.
Fig. 4. Multispectral fluorescence imaging and phasor plot analysis of an H&E-stained slide of human kidney. A) Brightfield image; B) fluorescence color image synthesized from a 420-720-nm spectral data stack; C) spectra from representative regions containing collagen, basement membrane, tubules, and red blood cells; D) same spectra plotted in log scale for better visibility. E) Phasor plot of spectral data from the complete image with phasor clusters representing specific components identified as follows: Col (collagen); AF (autofluorescence); BM (basement membrane); PT (proximal tubules); and RBC (red blood cells). F-I) phasor-segmented images corresponding to the outlined clusters.

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Fig. 5.
Fig. 5. RGB images of H&E-stained slide fluorescence. Top row: kidney; middle row: ovarian cancer; bottom row: breast cancer. Phasor plots are shown in the middle column, with unmixed collagen signals shown as monochrome images and as blue overlays on top of the original brightfield images. Compared to the multispectral phasor plot shown in Fig. 4, these plots have fewer clusters, and it is not possible to separate collagen from basement membrane signals. The shapes of the phasor clusters differ from each other, reflecting the fact the slides were stained in different laboratories, and that 3 different color cameras (CCD, CMOS and 3-band filter-wheel-equipped monochrome) were used to capture these images.

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Fig. 6.
Fig. 6. Brightfield and fluorescence images from the slides processed at UC Davis and Johns Hopkins University. Phasor plots demonstrate extractable components in spite of large color discrepancy between the fluorescence images from two institutions.

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Fig. 7.
Fig. 7. A) Brightfield and B) fluorescence image of human liver biopsy from H&E slide. C) Serial section from the same region stained with trichrome. D) SHG signal and E) collagen image from DUET imaged from H&E slide. F) Overlaid image of collagen distribution from DUET on brightfield image. Zoomed in version of G) brightfield, H) overlaid, I) SHG and J) collagen extracted from DUET setup.

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Fig. 8.
Fig. 8. A) Brightfield and B) fluorescence image of kidney biopsy from an H&E slide. C) Image of a serial section stained with trichrome. D) SHG image of the same region. Unlike DUET, SHG is does not highlight collagen structures (mostly collagen IV) within the glomerulus. E) Collagen distribution from the DUET-analyzed fluorescence image. F) Overlaid image of collagen distribution from DUET onto the corresponding brightfield image.

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Fig. 9.
Fig. 9. Serial section images of kidney stained with H&E (A), DUET overlaid (B), IHC staining for collagen type III (C). The blue pseudocolor in panel B correlates well with COLIII IHC.

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Fig. 10.
Fig. 10. A) Brightfield and B) DUET overlay image. C) Image of a serial section stained with trichrome. The yellow arrow points to the location of a nerve and the green arrow indicates the smooth muscle of arterial wall. These structures do not contain collagen, and do not show as positive in the DUET overlay image; however, they do appear blue (positive for collagen) in the trichrome-stained slide.

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Equations (6)

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G = ∑ l = 1 L a l cos ⁡ ( 2 π L l ) / ∑ l = 1 L a l  and  S = ∑ l = 1 L a l sin ⁡ ( 2 π L l ) / ∑ l = 1 L a l
f ( x , y ) = A exp ⁡ ( − a ( x − x 0 ) 2 − 2 b ( x − x 0 ) ( y − y 0 ) − c ( y − y 0 ) 2 )
a = cos 2 θ 2 σ x 2 + sin 2 θ 2 σ y 2 b = − sin ⁡ 2 θ 4 σ x 2 + sin ⁡ 2 θ 4 σ y 2 c = sin 2 θ 2 σ x 2 + cos 2 θ 2 σ y 2
B i = I 0 e − O D i
O D i = ln ⁡ ( I 0 B i )
O i = I 0 e − ( O D i + c i F i ) = I 0 e − ln ⁡ ( I 0 / B i ) − c i F i = B i e − c i F i