Abstract

Tissue fibrosis is a progressive and destructive disease process that can occur in many different organs including the liver, kidney, skin, and lungs. Fibrosis is typically initiated by inflammation as a result of chronic insults such as infection, chemicals and autoimmune diseases. Current approaches to examine organ fibrosis are limited to radiological and histological analyses. Infrared spectroscopic imaging offers a potential alternative approach to gain insight into biochemical changes associated with fibrosis progression. In this study, we demonstrate that IR imaging of a mouse model of pulmonary fibrosis can identify biochemical changes observed with fibrosis progression and the beginning of resolution using K-means analysis, spectral ratios and multivariate data analysis. This study demonstrates that IR imaging may be a useful approach to understand the biochemical events associated with fibrosis initiation, progression and resolution for both the clinical setting and for assessing novel anti-fibrotic drugs in a model system.

© 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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2020 (2)

R. Tikhomirov, B. R. Donnell, F. Catapano, G. Faggian, J. Gorelik, F. Martelli, and C. Emanueli, “Exosomes: From Potential Culprits to New Therapeutic Promise in the Setting of Cardiac Fibrosis,” Cells 9(3), 592 (2020).
[Crossref]

A. Sala, D. J. Anderson, P. M. Brennan, H. J. Butler, J. M. Cameron, M. D. Jenkinson, C. Rinaldi, A. G. Theakstone, and M. J. Baker, “Biofluid Diagnostics by FTIR Spectroscopy: A Platform Technology for Cancer Detection,” Cancer Lett. 477, 122–130 (2020).
[Crossref]

2019 (1)

V. Suryadevara, L. Huang, S. J. Kim, P. Cheresh, M. Shaaya, M. Bandela, P. Fu, C. Feghali-Bostwick, G. Di Paolo, D. W. Kamp, and V. Natarajan, “Role of phospholipase D in bleomycin-induced mitochondrial reactive oxygen species generation, mitochondrial DNA damage, and pulmonary fibrosis,” Am. J. Physiol. Cell Physiol. 317(2), L175–L187 (2019).
[Crossref]

2018 (3)

S. Pahlow, K. Weber, J. Popp, B. R. Wood, K. Kochan, A. Ruther, D. Perez-Guaita, P. Heraud, N. Stone, A. Dudgeon, B. Gardner, R. Reddy, D. Mayerich, and R. Bhargava, “Application of Vibrational Spectroscopy and Imaging to Point-of-Care Medicine: A Review,” Appl Spectrosc 72, 52–84 (2018).
[Crossref]

E. Kaznowska, J. Depciuch, K. Łach, M. Kołodziej, A. Koziorowska, J. Vongsvivut, I. Zawlik, M. Cholewa, and J. Cebulski, “The classification of lung cancers and their degree of malignancy by FTIR, PCA-LDA analysis, and a physics-based computational model,” Talanta 186, 337–345 (2018).
[Crossref]

V. K. Varma, A. Kajdacsy-Balla, S. Akkina, S. Setty, and M. J. Walsh, “Predicting Fibrosis Progression in Renal Transplant Recipients Using Laser-Based Infrared Spectroscopic Imaging,” Sci. Rep. 8(1), 686 (2018).
[Crossref]

2017 (5)

W. Querido, J. M. Falcon, S. Kandel, and N. Pleshko, “Vibrational spectroscopy and imaging: applications for tissue engineering,” Analyst 142(21), 4005–4017 (2017).
[Crossref]

L. Berchtold, I. Friedli, J. P. Vallee, S. Moll, P. Y. Martin, and S. de Seigneux, “Diagnosis and assessment of renal fibrosis: the state of the art,” Swiss Med. Wkly. 147(1920), w14442 (2017).
[Crossref]

B. M. Elicker, K. G. Kallianos, and T. S. Henry, “The role of high-resolution computed tomography in the follow-up of diffuse lung disease: Number 2 in the Series “Radiology” Edited by Nicola Sverzellati and Sujal Desai,” Eur Respir Rev 26(144), 170008 (2017).
[Crossref]

S. S. Nazeer, H. Sreedhar, V. K. Varma, D. Martinez-Marin, C. Massie, and M. J. Walsh, “Infrared spectroscopic imaging: Label-free biochemical analysis of stroma and tissue fibrosis,” Int. J. Biochem. Cell Biol. 92, 14–17 (2017).
[Crossref]

B. Bird and J. Rowlette, “A protocol for rapid, label-free histochemical imaging of fibrotic liver,” Analyst 142(8), 1179–1184 (2017).
[Crossref]

2016 (2)

V. K. Varma, A. Kajdacsy-Balla, S. K. Akkina, S. Setty, and M. J. Walsh, “A label-free approach by infrared spectroscopic imaging for interrogating the biochemistry of diabetic nephropathy progression,” Kidney Int. 89(5), 1153–1159 (2016).
[Crossref]

S. Tomassetti, A. U. Wells, U. Costabel, A. Cavazza, T. V. Colby, G. Rossi, N. Sverzellati, A. Carloni, E. Carretta, M. Buccioli, P. Tantalocco, C. Ravaglia, C. Gurioli, A. Dubini, S. Piciucchi, J. H. Ryu, and V. Poletti, “Bronchoscopic Lung Cryobiopsy Increases Diagnostic Confidence in the Multidisciplinary Diagnosis of Idiopathic Pulmonary Fibrosis,” Am. J. Respir. Crit. Care Med. 193(7), 745–752 (2016).
[Crossref]

2015 (8)

D. Mayerich, M. J. Walsh, A. Kadjacsy-Balla, P. S. Ray, S. M. Hewitt, and R. Bhargava, “Stain-less staining for computed histopathology,” Technology 03(01), 27–31 (2015).
[Crossref]

B. Bird and M. J. Baker, “Quantum cascade lasers in biomedical infrared imaging,” Trends Biotechnol. 33(10), 557–558 (2015).
[Crossref]

K. Yeh, S. Kenkel, J.-N. Liu, and R. Bhargava, “Fast infrared chemical imaging with a quantum cascade laser,” Anal. Chem. 87(1), 485–493 (2015).
[Crossref]

R. J. Perea, J. T. Ortiz-Perez, M. Sole, M. T. Cibeira, T. M. de Caralt, S. Prat-Gonzalez, X. Bosch, A. Berruezo, M. Sanchez, and J. Blade, “T1 mapping: characterisation of myocardial interstitial space,” Insights Imaging 6(2), 189–202 (2015).
[Crossref]

C. B. Nanthakumar, R. J. Hatley, S. Lemma, J. Gauldie, R. P. Marshall, and S. J. Macdonald, “Dissecting fibrosis: therapeutic insights from the small-molecule toolbox,” Nat. Rev. Drug Discovery 14(10), 693–720 (2015).
[Crossref]

S. Tomassetti, S. Piciucchi, P. Tantalocco, A. Dubini, and V. Poletti, “The multidisciplinary approach in the diagnosis of idiopathic pulmonary fibrosis: a patient case-based review,” Eur Respir Rev. 24(135), 69–77 (2015).
[Crossref]

J. T. Kwak, A. Kajdacsy-Balla, V. Macias, M. Walsh, S. Sinha, and R. Bhargava, “Improving prediction of prostate cancer recurrence using chemical imaging,” Sci. Rep. 5(1), 8758 (2015).
[Crossref]

F. Großerueschkamp, A. Kallenbach-Thieltges, T. Behrens, T. Brüning, M. Altmayer, G. Stamatis, D. Theegarten, and K. Gerwert, “Marker-free automated histopathological annotation of lung tumour subtypes by FTIR imaging,” Analyst 140(7), 2114–2120 (2015).
[Crossref]

2014 (4)

M. J. Baker, J. Trevisan, P. Bassan, R. Bhargava, H. J. Butler, K. M. Dorling, P. R. Fielden, S. W. Fogarty, N. J. Fullwood, and K. A. Heys, “Using Fourier transform IR spectroscopy to analyze biological materials,” Nat. Protoc. 9(8), 1771–1791 (2014).
[Crossref]

J. Wilder and K. Patel, “The clinical utility of FibroScan((R)) as a noninvasive diagnostic test for liver disease,” Med. Devices: Evidence Res. 7, 107–114 (2014).
[Crossref]

Y. Sumida, A. Nakajima, and Y. Itoh, “Limitations of liver biopsy and non-invasive diagnostic tests for the diagnosis of nonalcoholic fatty liver disease/nonalcoholic steatohepatitis,” World J. Gastroenterol. 20(2), 475–485 (2014).
[Crossref]

S. E. Holton, A. Bergamaschi, B. S. Katzenellenbogen, and R. Bhargava, “Integration of molecular profiling and chemical imaging to elucidate fibroblast-microenvironment impact on cancer cell phenotype and endocrine resistance in breast cancer,” PLoS One 9(5), e96878 (2014).
[Crossref]

2013 (4)

N. Krishnakumar, N. Sulfikkarali, S. Manoharan, and R. M. Nirmal, “Screening of chemopreventive effect of naringenin-loaded nanoparticles in DMBA-induced hamster buccal pouch carcinogenesis by FT-IR spectroscopy,” Mol. Cell. Biochem. 382(1-2), 27–36 (2013).
[Crossref]

R. Kaarteenaho, “The current position of surgical lung biopsy in the diagnosis of idiopathic pulmonary fibrosis,” Respir Res 14(1), 43 (2013).
[Crossref]

M. Zeisberg and R. Kalluri, “Cellular mechanisms of tissue fibrosis. 1. Common and organ-specific mechanisms associated with tissue fibrosis,” Am. J. Physiol. Cell Physiol. 304(3), C216–C225 (2013).
[Crossref]

X. Sun, Y. Xu, J. Wu, Y. Zhang, and K. Sun, “Detection of lung cancer tissue by attenuated total reflection–Fourier transform infrared spectroscopy—a pilot study of 60 samples,” J. Surg. Res. 179(1), 33–38 (2013).
[Crossref]

2012 (1)

M. J. Walsh, R. K. Reddy, and R. Bhargava, “Label-free biomedical imaging with mid-IR spectroscopy,” IEEE J. Sel. Top. Quantum Electron. 18(4), 1502–1513 (2012).
[Crossref]

2011 (4)

S. E. Holton, M. J. Walsh, and R. Bhargava, “Subcellular localization of early biochemical transformations in cancer-activated fibroblasts using infrared spectroscopic imaging,” Analyst 136(14), 2953–2958 (2011).
[Crossref]

S. Holton, M. Walsh, A. Kajdacsy-Balla, and R. Bhargava, “Label-free characterization of cancer-activated fibroblasts using infrared spectroscopic imaging,” Biophys. J. 101(6), 1513–1521 (2011).
[Crossref]

M. J. Nasse, M. J. Walsh, E. C. Mattson, R. Reininger, A. Kajdacsy-Balla, V. Macias, R. Bhargava, and C. J. Hirschmugl, “High-resolution Fourier-transform infrared chemical imaging with multiple synchrotron beams,” Nat. Methods 8(5), 413–416 (2011).
[Crossref]

D. Hanahan and R. A. Weinberg, “Hallmarks of cancer: the next generation,” Cell 144(5), 646–674 (2011).
[Crossref]

2010 (3)

F. L. Martin, J. G. Kelly, V. Llabjani, P. L. Martin-Hirsch, I. I. Patel, J. Trevisan, N. J. Fullwood, and M. J. Walsh, “Distinguishing cell types or populations based on the computational analysis of their infrared spectra,” Nat. Protoc. 5(11), 1748–1760 (2010).
[Crossref]

J. Pijanka, G. D. Sockalingum, A. Kohler, Y. Yang, F. Draux, G. Parkes, K.-P. Lam, D. Collins, P. Dumas, and C. Sandt, “Synchrotron-based FTIR spectra of stained single cells. Towards a clinical application in pathology,” Lab. Invest. 90(5), 797–807 (2010).
[Crossref]

P. D. Lewis, K. E. Lewis, R. Ghosal, S. Bayliss, A. J. Lloyd, J. Wills, R. Godfrey, P. Kloer, and L. A. Mur, “Evaluation of FTIR spectroscopy as a diagnostic tool for lung cancer using sputum,” BMC Cancer 10(1), 640 (2010).
[Crossref]

2008 (2)

C. Krafft, D. Codrich, G. Pelizzo, and V. Sergo, “Raman and FTIR imaging of lung tissue: methodology for control samples,” Vib. Spectrosc. 46(2), 141–149 (2008).
[Crossref]

T. A. Wynn, “Cellular and molecular mechanisms of fibrosis,” J. Pathol. 214(2), 199–210 (2008).
[Crossref]

2007 (1)

Y. P. Huang, Y. P. Zheng, S. F. Leung, and A. P. Choi, “High frequency ultrasound assessment of skin fibrosis: clinical results,” Ultrasound Med. Biol. 33(8), 1191–1198 (2007).
[Crossref]

2005 (2)

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]

Y. Yang, J. Sulé-Suso, G. D. Sockalingum, G. Kegelaer, M. Manfait, and A. J. El Haj, “Study of tumor cell invasion by Fourier transform infrared microspectroscopy,” Biopolymers 78, 311–317 (2005).
[Crossref]

2004 (2)

S. Koljenovic, T. C. B. Schut, J. P. van Meerbeeck, A. P. Maat, S. A. Burgers, P. E. Zondervan, J. M. Kros, and G. J. Puppels, “Raman microspectroscopic mapping studies of human bronchial tissue,” J. Biomed. Opt. 9(6), 1187–1198 (2004).
[Crossref]

P. Lasch, W. Haensch, D. Naumann, and M. Diem, “Imaging of colorectal adenocarcinoma using FT-IR microspectroscopy and cluster analysis,” Biochim. Biophys. Acta, Mol. Basis Dis. 1688, 176–186 (2004).
[Crossref]

2003 (1)

Z. Huang, A. McWilliams, H. Lui, D. I. McLean, S. Lam, and H. Zeng, “Near-infrared Raman spectroscopy for optical diagnosis of lung cancer,” Int. J. Cancer 107(6), 1047–1052 (2003).
[Crossref]

2002 (2)

G. Izbicki, M. J. Segel, T. G. Christensen, M. W. Conner, and R. Breuer, “Time course of bleomycin-induced lung fibrosis,” Int. J. Exp. Pathol. 83(3), 111–119 (2002).
[Crossref]

S. Kaminaka, T. Ito, H. Yamazaki, E. Kohda, and H. O. Hamaguchi, “Near-infrared multichannel Raman spectroscopy toward real-time in vivo cancer diagnosis,” J. Raman Spectrosc. 33(7), 498–502 (2002).
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E. Kaznowska, J. Depciuch, K. Łach, M. Kołodziej, A. Koziorowska, J. Vongsvivut, I. Zawlik, M. Cholewa, and J. Cebulski, “The classification of lung cancers and their degree of malignancy by FTIR, PCA-LDA analysis, and a physics-based computational model,” Talanta 186, 337–345 (2018).
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J. Pijanka, G. D. Sockalingum, A. Kohler, Y. Yang, F. Draux, G. Parkes, K.-P. Lam, D. Collins, P. Dumas, and C. Sandt, “Synchrotron-based FTIR spectra of stained single cells. Towards a clinical application in pathology,” Lab. Invest. 90(5), 797–807 (2010).
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Z. Huang, A. McWilliams, H. Lui, D. I. McLean, S. Lam, and H. Zeng, “Near-infrared Raman spectroscopy for optical diagnosis of lung cancer,” Int. J. Cancer 107(6), 1047–1052 (2003).
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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).
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K. Yeh, S. Kenkel, J.-N. Liu, and R. Bhargava, “Fast infrared chemical imaging with a quantum cascade laser,” Anal. Chem. 87(1), 485–493 (2015).
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C. B. Nanthakumar, R. J. Hatley, S. Lemma, J. Gauldie, R. P. Marshall, and S. J. Macdonald, “Dissecting fibrosis: therapeutic insights from the small-molecule toolbox,” Nat. Rev. Drug Discovery 14(10), 693–720 (2015).
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J. T. Kwak, A. Kajdacsy-Balla, V. Macias, M. Walsh, S. Sinha, and R. Bhargava, “Improving prediction of prostate cancer recurrence using chemical imaging,” Sci. Rep. 5(1), 8758 (2015).
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Y. Yang, J. Sulé-Suso, G. D. Sockalingum, G. Kegelaer, M. Manfait, and A. J. El Haj, “Study of tumor cell invasion by Fourier transform infrared microspectroscopy,” Biopolymers 78, 311–317 (2005).
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N. Krishnakumar, N. Sulfikkarali, S. Manoharan, and R. M. Nirmal, “Screening of chemopreventive effect of naringenin-loaded nanoparticles in DMBA-induced hamster buccal pouch carcinogenesis by FT-IR spectroscopy,” Mol. Cell. Biochem. 382(1-2), 27–36 (2013).
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C. B. Nanthakumar, R. J. Hatley, S. Lemma, J. Gauldie, R. P. Marshall, and S. J. Macdonald, “Dissecting fibrosis: therapeutic insights from the small-molecule toolbox,” Nat. Rev. Drug Discovery 14(10), 693–720 (2015).
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Martin, P. Y.

L. Berchtold, I. Friedli, J. P. Vallee, S. Moll, P. Y. Martin, and S. de Seigneux, “Diagnosis and assessment of renal fibrosis: the state of the art,” Swiss Med. Wkly. 147(1920), w14442 (2017).
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S. Tomassetti, S. Piciucchi, P. Tantalocco, A. Dubini, and V. Poletti, “The multidisciplinary approach in the diagnosis of idiopathic pulmonary fibrosis: a patient case-based review,” Eur Respir Rev. 24(135), 69–77 (2015).
[Crossref]

Trevisan, J.

M. J. Baker, J. Trevisan, P. Bassan, R. Bhargava, H. J. Butler, K. M. Dorling, P. R. Fielden, S. W. Fogarty, N. J. Fullwood, and K. A. Heys, “Using Fourier transform IR spectroscopy to analyze biological materials,” Nat. Protoc. 9(8), 1771–1791 (2014).
[Crossref]

F. L. Martin, J. G. Kelly, V. Llabjani, P. L. Martin-Hirsch, I. I. Patel, J. Trevisan, N. J. Fullwood, and M. J. Walsh, “Distinguishing cell types or populations based on the computational analysis of their infrared spectra,” Nat. Protoc. 5(11), 1748–1760 (2010).
[Crossref]

Vallee, J. P.

L. Berchtold, I. Friedli, J. P. Vallee, S. Moll, P. Y. Martin, and S. de Seigneux, “Diagnosis and assessment of renal fibrosis: the state of the art,” Swiss Med. Wkly. 147(1920), w14442 (2017).
[Crossref]

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S. Koljenovic, T. C. B. Schut, J. P. van Meerbeeck, A. P. Maat, S. A. Burgers, P. E. Zondervan, J. M. Kros, and G. J. Puppels, “Raman microspectroscopic mapping studies of human bronchial tissue,” J. Biomed. Opt. 9(6), 1187–1198 (2004).
[Crossref]

Varma, V. K.

V. K. Varma, A. Kajdacsy-Balla, S. Akkina, S. Setty, and M. J. Walsh, “Predicting Fibrosis Progression in Renal Transplant Recipients Using Laser-Based Infrared Spectroscopic Imaging,” Sci. Rep. 8(1), 686 (2018).
[Crossref]

S. S. Nazeer, H. Sreedhar, V. K. Varma, D. Martinez-Marin, C. Massie, and M. J. Walsh, “Infrared spectroscopic imaging: Label-free biochemical analysis of stroma and tissue fibrosis,” Int. J. Biochem. Cell Biol. 92, 14–17 (2017).
[Crossref]

V. K. Varma, A. Kajdacsy-Balla, S. K. Akkina, S. Setty, and M. J. Walsh, “A label-free approach by infrared spectroscopic imaging for interrogating the biochemistry of diabetic nephropathy progression,” Kidney Int. 89(5), 1153–1159 (2016).
[Crossref]

Vongsvivut, J.

E. Kaznowska, J. Depciuch, K. Łach, M. Kołodziej, A. Koziorowska, J. Vongsvivut, I. Zawlik, M. Cholewa, and J. Cebulski, “The classification of lung cancers and their degree of malignancy by FTIR, PCA-LDA analysis, and a physics-based computational model,” Talanta 186, 337–345 (2018).
[Crossref]

Walsh, M.

J. T. Kwak, A. Kajdacsy-Balla, V. Macias, M. Walsh, S. Sinha, and R. Bhargava, “Improving prediction of prostate cancer recurrence using chemical imaging,” Sci. Rep. 5(1), 8758 (2015).
[Crossref]

S. Holton, M. Walsh, A. Kajdacsy-Balla, and R. Bhargava, “Label-free characterization of cancer-activated fibroblasts using infrared spectroscopic imaging,” Biophys. J. 101(6), 1513–1521 (2011).
[Crossref]

Walsh, M. J.

V. K. Varma, A. Kajdacsy-Balla, S. Akkina, S. Setty, and M. J. Walsh, “Predicting Fibrosis Progression in Renal Transplant Recipients Using Laser-Based Infrared Spectroscopic Imaging,” Sci. Rep. 8(1), 686 (2018).
[Crossref]

S. S. Nazeer, H. Sreedhar, V. K. Varma, D. Martinez-Marin, C. Massie, and M. J. Walsh, “Infrared spectroscopic imaging: Label-free biochemical analysis of stroma and tissue fibrosis,” Int. J. Biochem. Cell Biol. 92, 14–17 (2017).
[Crossref]

V. K. Varma, A. Kajdacsy-Balla, S. K. Akkina, S. Setty, and M. J. Walsh, “A label-free approach by infrared spectroscopic imaging for interrogating the biochemistry of diabetic nephropathy progression,” Kidney Int. 89(5), 1153–1159 (2016).
[Crossref]

D. Mayerich, M. J. Walsh, A. Kadjacsy-Balla, P. S. Ray, S. M. Hewitt, and R. Bhargava, “Stain-less staining for computed histopathology,” Technology 03(01), 27–31 (2015).
[Crossref]

M. J. Walsh, R. K. Reddy, and R. Bhargava, “Label-free biomedical imaging with mid-IR spectroscopy,” IEEE J. Sel. Top. Quantum Electron. 18(4), 1502–1513 (2012).
[Crossref]

S. E. Holton, M. J. Walsh, and R. Bhargava, “Subcellular localization of early biochemical transformations in cancer-activated fibroblasts using infrared spectroscopic imaging,” Analyst 136(14), 2953–2958 (2011).
[Crossref]

M. J. Nasse, M. J. Walsh, E. C. Mattson, R. Reininger, A. Kajdacsy-Balla, V. Macias, R. Bhargava, and C. J. Hirschmugl, “High-resolution Fourier-transform infrared chemical imaging with multiple synchrotron beams,” Nat. Methods 8(5), 413–416 (2011).
[Crossref]

F. L. Martin, J. G. Kelly, V. Llabjani, P. L. Martin-Hirsch, I. I. Patel, J. Trevisan, N. J. Fullwood, and M. J. Walsh, “Distinguishing cell types or populations based on the computational analysis of their infrared spectra,” Nat. Protoc. 5(11), 1748–1760 (2010).
[Crossref]

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[Crossref]

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D. Hanahan and R. A. Weinberg, “Hallmarks of cancer: the next generation,” Cell 144(5), 646–674 (2011).
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S. Tomassetti, A. U. Wells, U. Costabel, A. Cavazza, T. V. Colby, G. Rossi, N. Sverzellati, A. Carloni, E. Carretta, M. Buccioli, P. Tantalocco, C. Ravaglia, C. Gurioli, A. Dubini, S. Piciucchi, J. H. Ryu, and V. Poletti, “Bronchoscopic Lung Cryobiopsy Increases Diagnostic Confidence in the Multidisciplinary Diagnosis of Idiopathic Pulmonary Fibrosis,” Am. J. Respir. Crit. Care Med. 193(7), 745–752 (2016).
[Crossref]

Wilder, J.

J. Wilder and K. Patel, “The clinical utility of FibroScan((R)) as a noninvasive diagnostic test for liver disease,” Med. Devices: Evidence Res. 7, 107–114 (2014).
[Crossref]

Wills, J.

P. D. Lewis, K. E. Lewis, R. Ghosal, S. Bayliss, A. J. Lloyd, J. Wills, R. Godfrey, P. Kloer, and L. A. Mur, “Evaluation of FTIR spectroscopy as a diagnostic tool for lung cancer using sputum,” BMC Cancer 10(1), 640 (2010).
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S. Pahlow, K. Weber, J. Popp, B. R. Wood, K. Kochan, A. Ruther, D. Perez-Guaita, P. Heraud, N. Stone, A. Dudgeon, B. Gardner, R. Reddy, D. Mayerich, and R. Bhargava, “Application of Vibrational Spectroscopy and Imaging to Point-of-Care Medicine: A Review,” Appl Spectrosc 72, 52–84 (2018).
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X. Sun, Y. Xu, J. Wu, Y. Zhang, and K. Sun, “Detection of lung cancer tissue by attenuated total reflection–Fourier transform infrared spectroscopy—a pilot study of 60 samples,” J. Surg. Res. 179(1), 33–38 (2013).
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T. A. Wynn, “Cellular and molecular mechanisms of fibrosis,” J. Pathol. 214(2), 199–210 (2008).
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J. Pijanka, G. D. Sockalingum, A. Kohler, Y. Yang, F. Draux, G. Parkes, K.-P. Lam, D. Collins, P. Dumas, and C. Sandt, “Synchrotron-based FTIR spectra of stained single cells. Towards a clinical application in pathology,” Lab. Invest. 90(5), 797–807 (2010).
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Y. Yang, J. Sulé-Suso, G. D. Sockalingum, G. Kegelaer, M. Manfait, and A. J. El Haj, “Study of tumor cell invasion by Fourier transform infrared microspectroscopy,” Biopolymers 78, 311–317 (2005).
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K. Yeh, S. Kenkel, J.-N. Liu, and R. Bhargava, “Fast infrared chemical imaging with a quantum cascade laser,” Anal. Chem. 87(1), 485–493 (2015).
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E. Kaznowska, J. Depciuch, K. Łach, M. Kołodziej, A. Koziorowska, J. Vongsvivut, I. Zawlik, M. Cholewa, and J. Cebulski, “The classification of lung cancers and their degree of malignancy by FTIR, PCA-LDA analysis, and a physics-based computational model,” Talanta 186, 337–345 (2018).
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Zhang, Y.

X. Sun, Y. Xu, J. Wu, Y. Zhang, and K. Sun, “Detection of lung cancer tissue by attenuated total reflection–Fourier transform infrared spectroscopy—a pilot study of 60 samples,” J. Surg. Res. 179(1), 33–38 (2013).
[Crossref]

Zheng, Y. P.

Y. P. Huang, Y. P. Zheng, S. F. Leung, and A. P. Choi, “High frequency ultrasound assessment of skin fibrosis: clinical results,” Ultrasound Med. Biol. 33(8), 1191–1198 (2007).
[Crossref]

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S. Koljenovic, T. C. B. Schut, J. P. van Meerbeeck, A. P. Maat, S. A. Burgers, P. E. Zondervan, J. M. Kros, and G. J. Puppels, “Raman microspectroscopic mapping studies of human bronchial tissue,” J. Biomed. Opt. 9(6), 1187–1198 (2004).
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M. Zeisberg and R. Kalluri, “Cellular mechanisms of tissue fibrosis. 1. Common and organ-specific mechanisms associated with tissue fibrosis,” Am. J. Physiol. Cell Physiol. 304(3), C216–C225 (2013).
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Am. J. Respir. Crit. Care Med. (1)

S. Tomassetti, A. U. Wells, U. Costabel, A. Cavazza, T. V. Colby, G. Rossi, N. Sverzellati, A. Carloni, E. Carretta, M. Buccioli, P. Tantalocco, C. Ravaglia, C. Gurioli, A. Dubini, S. Piciucchi, J. H. Ryu, and V. Poletti, “Bronchoscopic Lung Cryobiopsy Increases Diagnostic Confidence in the Multidisciplinary Diagnosis of Idiopathic Pulmonary Fibrosis,” Am. J. Respir. Crit. Care Med. 193(7), 745–752 (2016).
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Anal. Chem. (1)

K. Yeh, S. Kenkel, J.-N. Liu, and R. Bhargava, “Fast infrared chemical imaging with a quantum cascade laser,” Anal. Chem. 87(1), 485–493 (2015).
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W. Querido, J. M. Falcon, S. Kandel, and N. Pleshko, “Vibrational spectroscopy and imaging: applications for tissue engineering,” Analyst 142(21), 4005–4017 (2017).
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F. Großerueschkamp, A. Kallenbach-Thieltges, T. Behrens, T. Brüning, M. Altmayer, G. Stamatis, D. Theegarten, and K. Gerwert, “Marker-free automated histopathological annotation of lung tumour subtypes by FTIR imaging,” Analyst 140(7), 2114–2120 (2015).
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B. Bird and J. Rowlette, “A protocol for rapid, label-free histochemical imaging of fibrotic liver,” Analyst 142(8), 1179–1184 (2017).
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S. E. Holton, M. J. Walsh, and R. Bhargava, “Subcellular localization of early biochemical transformations in cancer-activated fibroblasts using infrared spectroscopic imaging,” Analyst 136(14), 2953–2958 (2011).
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Appl Spectrosc (1)

S. Pahlow, K. Weber, J. Popp, B. R. Wood, K. Kochan, A. Ruther, D. Perez-Guaita, P. Heraud, N. Stone, A. Dudgeon, B. Gardner, R. Reddy, D. Mayerich, and R. Bhargava, “Application of Vibrational Spectroscopy and Imaging to Point-of-Care Medicine: A Review,” Appl Spectrosc 72, 52–84 (2018).
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Biochim. Biophys. Acta, Mol. Basis Dis. (1)

P. Lasch, W. Haensch, D. Naumann, and M. Diem, “Imaging of colorectal adenocarcinoma using FT-IR microspectroscopy and cluster analysis,” Biochim. Biophys. Acta, Mol. Basis Dis. 1688, 176–186 (2004).
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Biophys. J. (1)

S. Holton, M. Walsh, A. Kajdacsy-Balla, and R. Bhargava, “Label-free characterization of cancer-activated fibroblasts using infrared spectroscopic imaging,” Biophys. J. 101(6), 1513–1521 (2011).
[Crossref]

Biopolymers (1)

Y. Yang, J. Sulé-Suso, G. D. Sockalingum, G. Kegelaer, M. Manfait, and A. J. El Haj, “Study of tumor cell invasion by Fourier transform infrared microspectroscopy,” Biopolymers 78, 311–317 (2005).
[Crossref]

BMC Cancer (1)

P. D. Lewis, K. E. Lewis, R. Ghosal, S. Bayliss, A. J. Lloyd, J. Wills, R. Godfrey, P. Kloer, and L. A. Mur, “Evaluation of FTIR spectroscopy as a diagnostic tool for lung cancer using sputum,” BMC Cancer 10(1), 640 (2010).
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Cancer Lett. (1)

A. Sala, D. J. Anderson, P. M. Brennan, H. J. Butler, J. M. Cameron, M. D. Jenkinson, C. Rinaldi, A. G. Theakstone, and M. J. Baker, “Biofluid Diagnostics by FTIR Spectroscopy: A Platform Technology for Cancer Detection,” Cancer Lett. 477, 122–130 (2020).
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Cell (1)

D. Hanahan and R. A. Weinberg, “Hallmarks of cancer: the next generation,” Cell 144(5), 646–674 (2011).
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Cells (1)

R. Tikhomirov, B. R. Donnell, F. Catapano, G. Faggian, J. Gorelik, F. Martelli, and C. Emanueli, “Exosomes: From Potential Culprits to New Therapeutic Promise in the Setting of Cardiac Fibrosis,” Cells 9(3), 592 (2020).
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Eur Respir Rev (1)

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Eur Respir Rev. (1)

S. Tomassetti, S. Piciucchi, P. Tantalocco, A. Dubini, and V. Poletti, “The multidisciplinary approach in the diagnosis of idiopathic pulmonary fibrosis: a patient case-based review,” Eur Respir Rev. 24(135), 69–77 (2015).
[Crossref]

IEEE J. Sel. Top. Quantum Electron. (1)

M. J. Walsh, R. K. Reddy, and R. Bhargava, “Label-free biomedical imaging with mid-IR spectroscopy,” IEEE J. Sel. Top. Quantum Electron. 18(4), 1502–1513 (2012).
[Crossref]

Insights Imaging (1)

R. J. Perea, J. T. Ortiz-Perez, M. Sole, M. T. Cibeira, T. M. de Caralt, S. Prat-Gonzalez, X. Bosch, A. Berruezo, M. Sanchez, and J. Blade, “T1 mapping: characterisation of myocardial interstitial space,” Insights Imaging 6(2), 189–202 (2015).
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Int. J. Biochem. Cell Biol. (1)

S. S. Nazeer, H. Sreedhar, V. K. Varma, D. Martinez-Marin, C. Massie, and M. J. Walsh, “Infrared spectroscopic imaging: Label-free biochemical analysis of stroma and tissue fibrosis,” Int. J. Biochem. Cell Biol. 92, 14–17 (2017).
[Crossref]

Int. J. Cancer (1)

Z. Huang, A. McWilliams, H. Lui, D. I. McLean, S. Lam, and H. Zeng, “Near-infrared Raman spectroscopy for optical diagnosis of lung cancer,” Int. J. Cancer 107(6), 1047–1052 (2003).
[Crossref]

Int. J. Exp. Pathol. (1)

G. Izbicki, M. J. Segel, T. G. Christensen, M. W. Conner, and R. Breuer, “Time course of bleomycin-induced lung fibrosis,” Int. J. Exp. Pathol. 83(3), 111–119 (2002).
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J. Biomed. Opt. (1)

S. Koljenovic, T. C. B. Schut, J. P. van Meerbeeck, A. P. Maat, S. A. Burgers, P. E. Zondervan, J. M. Kros, and G. J. Puppels, “Raman microspectroscopic mapping studies of human bronchial tissue,” J. Biomed. Opt. 9(6), 1187–1198 (2004).
[Crossref]

J. Pathol. (2)

T. A. Wynn, “Cellular and molecular mechanisms of fibrosis,” J. Pathol. 214(2), 199–210 (2008).
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A. W. Jones and N. L. Reeve, “Ultrastructural study of bleomycin-induced pulmonary changes in mice,” J. Pathol. 124(4), 227–233 (1978).
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J. Raman Spectrosc. (1)

S. Kaminaka, T. Ito, H. Yamazaki, E. Kohda, and H. O. Hamaguchi, “Near-infrared multichannel Raman spectroscopy toward real-time in vivo cancer diagnosis,” J. Raman Spectrosc. 33(7), 498–502 (2002).
[Crossref]

J. Surg. Res. (1)

X. Sun, Y. Xu, J. Wu, Y. Zhang, and K. Sun, “Detection of lung cancer tissue by attenuated total reflection–Fourier transform infrared spectroscopy—a pilot study of 60 samples,” J. Surg. Res. 179(1), 33–38 (2013).
[Crossref]

Kidney Int. (1)

V. K. Varma, A. Kajdacsy-Balla, S. K. Akkina, S. Setty, and M. J. Walsh, “A label-free approach by infrared spectroscopic imaging for interrogating the biochemistry of diabetic nephropathy progression,” Kidney Int. 89(5), 1153–1159 (2016).
[Crossref]

Lab. Invest. (1)

J. Pijanka, G. D. Sockalingum, A. Kohler, Y. Yang, F. Draux, G. Parkes, K.-P. Lam, D. Collins, P. Dumas, and C. Sandt, “Synchrotron-based FTIR spectra of stained single cells. Towards a clinical application in pathology,” Lab. Invest. 90(5), 797–807 (2010).
[Crossref]

Med. Devices: Evidence Res. (1)

J. Wilder and K. Patel, “The clinical utility of FibroScan((R)) as a noninvasive diagnostic test for liver disease,” Med. Devices: Evidence Res. 7, 107–114 (2014).
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Mol. Cell. Biochem. (1)

N. Krishnakumar, N. Sulfikkarali, S. Manoharan, and R. M. Nirmal, “Screening of chemopreventive effect of naringenin-loaded nanoparticles in DMBA-induced hamster buccal pouch carcinogenesis by FT-IR spectroscopy,” Mol. Cell. Biochem. 382(1-2), 27–36 (2013).
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Nat. Biotechnol. (1)

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Nat. Methods (1)

M. J. Nasse, M. J. Walsh, E. C. Mattson, R. Reininger, A. Kajdacsy-Balla, V. Macias, R. Bhargava, and C. J. Hirschmugl, “High-resolution Fourier-transform infrared chemical imaging with multiple synchrotron beams,” Nat. Methods 8(5), 413–416 (2011).
[Crossref]

Nat. Protoc. (2)

M. J. Baker, J. Trevisan, P. Bassan, R. Bhargava, H. J. Butler, K. M. Dorling, P. R. Fielden, S. W. Fogarty, N. J. Fullwood, and K. A. Heys, “Using Fourier transform IR spectroscopy to analyze biological materials,” Nat. Protoc. 9(8), 1771–1791 (2014).
[Crossref]

F. L. Martin, J. G. Kelly, V. Llabjani, P. L. Martin-Hirsch, I. I. Patel, J. Trevisan, N. J. Fullwood, and M. J. Walsh, “Distinguishing cell types or populations based on the computational analysis of their infrared spectra,” Nat. Protoc. 5(11), 1748–1760 (2010).
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Nat. Rev. Drug Discovery (1)

C. B. Nanthakumar, R. J. Hatley, S. Lemma, J. Gauldie, R. P. Marshall, and S. J. Macdonald, “Dissecting fibrosis: therapeutic insights from the small-molecule toolbox,” Nat. Rev. Drug Discovery 14(10), 693–720 (2015).
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PLoS One (1)

S. E. Holton, A. Bergamaschi, B. S. Katzenellenbogen, and R. Bhargava, “Integration of molecular profiling and chemical imaging to elucidate fibroblast-microenvironment impact on cancer cell phenotype and endocrine resistance in breast cancer,” PLoS One 9(5), e96878 (2014).
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Respir Res (1)

R. Kaarteenaho, “The current position of surgical lung biopsy in the diagnosis of idiopathic pulmonary fibrosis,” Respir Res 14(1), 43 (2013).
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Sci. Rep. (2)

V. K. Varma, A. Kajdacsy-Balla, S. Akkina, S. Setty, and M. J. Walsh, “Predicting Fibrosis Progression in Renal Transplant Recipients Using Laser-Based Infrared Spectroscopic Imaging,” Sci. Rep. 8(1), 686 (2018).
[Crossref]

J. T. Kwak, A. Kajdacsy-Balla, V. Macias, M. Walsh, S. Sinha, and R. Bhargava, “Improving prediction of prostate cancer recurrence using chemical imaging,” Sci. Rep. 5(1), 8758 (2015).
[Crossref]

Swiss Med. Wkly. (1)

L. Berchtold, I. Friedli, J. P. Vallee, S. Moll, P. Y. Martin, and S. de Seigneux, “Diagnosis and assessment of renal fibrosis: the state of the art,” Swiss Med. Wkly. 147(1920), w14442 (2017).
[Crossref]

Talanta (1)

E. Kaznowska, J. Depciuch, K. Łach, M. Kołodziej, A. Koziorowska, J. Vongsvivut, I. Zawlik, M. Cholewa, and J. Cebulski, “The classification of lung cancers and their degree of malignancy by FTIR, PCA-LDA analysis, and a physics-based computational model,” Talanta 186, 337–345 (2018).
[Crossref]

Technology (1)

D. Mayerich, M. J. Walsh, A. Kadjacsy-Balla, P. S. Ray, S. M. Hewitt, and R. Bhargava, “Stain-less staining for computed histopathology,” Technology 03(01), 27–31 (2015).
[Crossref]

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B. Bird and M. J. Baker, “Quantum cascade lasers in biomedical infrared imaging,” Trends Biotechnol. 33(10), 557–558 (2015).
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Ultrasound Med. Biol. (1)

Y. P. Huang, Y. P. Zheng, S. F. Leung, and A. P. Choi, “High frequency ultrasound assessment of skin fibrosis: clinical results,” Ultrasound Med. Biol. 33(8), 1191–1198 (2007).
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G. Theophilou, M. Paraskevaidi, K. M. Lima, M. Kyrgiou, P. L. Martin-Hirsch, and F. L. Martin, “Expert review of molecular diagnostics,” 15, 693–713 (2015).

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Figures (5)

Fig. 1.
Fig. 1. Array of representative tissue sections examined by infrared microscopy (a)-(e) Brightfield images of the parallel sections stained with H&E (f)-(j) Brightfield images of parallel tissue sections stained using Masson’s trichrome. (k)-(o) Infrared observation of the parallel section from the tissue based on K-means clustering image (6 clusters) calculated from a full band (900–1800cm−1) infrared absorbance dataset.).
Fig. 2.
Fig. 2. K-means cluster analysis depicting the histopathological regions of each lung section across different groups (a) K-means clustering image (6 clusters) of the lung tissues from each group calculated from a full band (900–1800cm−1) infrared absorbance dataset. Each image is from a different mouse (c) Mean absorption spectra calculated from each cluster, which is quantified as seen in (b).
Fig. 3.
Fig. 3. Spectral data were extracted from the fibrotic regions of the IR image scans. The average spectra for different stages of fibrosis in the fibrotic regions of the lung tissue showing a significant variation in certain points of the IR spectra.
Fig. 4.
Fig. 4. Ratiometric analysis of the IR spectra by time point. The ratio of intensities at (a) 1232/1336 gives the collagen map in the tissue for the fibrotic regions. (b) Glycosylation patterns across the lung tissue are interpreted using the 1080/1030 spectral ratio in the fibrotic regions. (c) The spectral ratio of 1654/1554 in fibrotic areas indicates not only any changes in the structural rearrangements of the existing proteins, but also the expression of a new proteins with varied structural characteristics.
Fig. 5.
Fig. 5. PCA-LDA analysis could classify the different groups with varying stages of fibrosis based on the time points from bleomycin treatment with control (black), day 7 (red), day 14 (green), day 21 (blue), and day 28 (magenta). Different symbols are used to identify the three mice per time-point and each ROI is an individual symbol.