High-definition fourier transform infrared (FT-IR) spectroscopic imaging of human tissue sections towards improving pathology

Journal of Visualized Experiments

Volumn , Issue 95, 2015, Pages

  Sreedhar, Hari ^a   Varma, Vishal K ^a   Nguyen, Peter L ^b   Davidson, Bennett ^b   Akkina, Sanjeev ^b   Guzman, Grace ^b   Setty, Suman ^b   Kajdacsy Balla, Andre ^b   Walsh, Michael J ^b  

^a University of Illinois at Chicago   (United States)

^b UNIVERSITY OF ILLINOIS AT CHICAGO   (United States)

Author keywords

Biopsy; Cancer; Fourier transform; Hyperspectral; Imaging; Infrared; Issue 95; Kidney; Liver; Medicine; Optics; Pathology; Spectroscopy; Tissue

Indexed keywords

DIAGNOSTIC IMAGING; FOURIER ANALYSIS; HUMAN; INFRARED SPECTROSCOPY; KIDNEY; LIVER; PATHOLOGY; PROCEDURES;

DIAGNOSTIC IMAGING; FOURIER ANALYSIS; HUMANS; KIDNEY; LIVER; PATHOLOGY; SPECTROSCOPY, FOURIER TRANSFORM INFRARED;

EID: 84923605832     PISSN: 1940087X     EISSN: None     Source Type: Journal    
DOI: 10.3791/52332     Document Type: Article

References (60)

1. Lewis, E N. et al. Fourier transform spectroscopic imaging using an infrared focal-plane array detector.Anal Chem. 67(19), 3377-3381 doi:10.1021/ac00115a003, (1995).
2. Dorling, K. M., & Baker, M. J. Rapid FTIR chemical imaging: highlighting FPA detectors. Trends Biotechnol. 31(8), 437-438, doi:10.1016/j.tibtech.2013.05.008, (2013).
3. Fernandez, D. C., Bhargava, R., Hewitt, S. M., & Levin, I. W. Infrared spectroscopic imaging for histopathologic recognition. Nat Biotechnol. 23(4), 469-474, doi:10.1038/nbt1080, (2005).
4. Nasse, M J, et al. High-resolution Fourier-transform infrared chemical imaging with multiple synchrotron beams. Nat Methods. 8(5), 413-416, doi:10.1038/nmeth.1585 (2011).
5. Reddy, R. K., Walsh, M. J., Schulmerich, M. V., Carney, P. S., & Bhargava, R. High-definition infrared spectroscopic imaging. Appl Spectrosc. 67(1), 93-105, doi:10.1366/11-06568, (2013).
6. Walsh, M. J., Bhargava, R. Chapter 10; Infrared spectroscopic imaging: an integrative approach to pathology. Nanobiophotonics. McGraw Hill, (2010).
7. Walsh, M. J., Reddy, R. K., & Bhargava, R. Label-Free Biomedical Imaging With Mid-IR Spectroscopy.Ieee J Sel Top Quant. 18(4), 1502-1513, doi:10.1109/Jstqe.2011.2182635 (2012).
8. Matthaus C, et al Chapter 10: Infrared and Raman microscopy in cell biology. Methods Cell Biol. 89, 275-308, doi:10.1016/s0091-679x(08)00610-9, (2008).
9. Walsh, M J. et al. IR microspectroscopy: potential applications in cervical cancer screening. Cancer Lett.246(1-2), 1-11, doi:10.1016/j.canlet.2006.03.019, (2007).
10. Kazarian, S. G., & Chan, K. L. ATR-FTIR spectroscopic imaging: recent advances and applications to biological systems. Analyst. 138(7), 1940-1951, doi:10.1039/c3an36865c, (2013).
11. Sahu, R. K., & Mordechai, S. Spectral signatures of colonic malignancies in the mid-infrared region: from basic research to clinical applicability. Future Oncol. 6(10), 1653-1667, doi:10.2217/fon.10.120, (2010).
12. Kendall C, et al.Vibrational spectroscopy: a clinical tool for cancer diagnostics. Analyst. 134(6), 1029-1045, doi:10.1039/b822130h, (2009).
13. Steiner, G., & Koch, E. Trends in Fourier transform infrared spectroscopic imaging. Anal Bioanal Chem.394(3), 671-678, doi:10.1007/s00216-009-2737-5, (2009).
14. Biswas, S., Walsh, M. J., & Bhargava, R. in Optical Spectroscopy and Computational Methods in Biology and Medicine. Vol. 14 Challenges and Advances in Computational Chemistry and Physics Ch. 16, 475-504, (2014).
15. Bhargava, R. Infrared Spectroscopic Imaging: The Next Generation. Appl Spectrosc. 66(10), 1091-1120 doi:10.1366/12-06801, (2012).
16. Malek, K., Wood, B. R., & Bambery, K. R. in Optical Spectroscopy and Computational Methods in Biology and Medicine. Vol. 14 Challenges and Advances in Computational Chemistry and Physics Ch. 15, 419-473, (2014).
17. Martin, F L, et al. Distinguishing cell types or populations based on the computational analysis of their infrared spectra. Nat Protoc. 5(11), 1748-1760, doi:10.1038/nprot.2010.133, (2010).
18. Sommer, A. J., Tisinger, L. G., Marcott, C., & Story, G. M. Attenuated Total Internal Reflection Infrared Mapping Microspectroscopy Using an Imaging Microscope. Appl Spectrosc. 55(3), 252-256, doi:10.1366/0003702011951803, (2001).
19. Glassford, S. E., Byrne, B., & Kazarian, S. G. Recent applications of ATR FTIR spectroscopy and imaging to proteins. Biochim Biophys Acta. 1834(12), 2849-2858, doi:10.1016/j.bbapap.2013.07.015, (2013).
20. Andanson, J. M., Chan, K. L., & Kazarian, S. G. High-throughput spectroscopic imaging applied to permeation through the skin. Appl Spectrosc. 63(5), 512-517, doi:10.1366/000370209788347011, (2009).
21. Kuimova, M. K., Chan, K. L., & Kazarian, S. G. Chemical imaging of live cancer cells in the natural aqueous environment. Appl Spectrosc. 63(2), 164-171, doi:10.1366/000370209787391969, (2009).
22. Chan, K. L., & Kazarian, S. G. Attenuated total reflection-Fourier transform infrared imaging of large areas using inverted prism crystals and combining imaging and mapping. Appl Spectrosc. 62(10), 1095-1101, doi:10.1366/000370208786049042, (2008).
23. Gajjar K et al. Diagnostic segregation of human brain tumours using Fourier-transform infrared and/or Raman spectroscopy coupled with discriminant analysis. Anal Methods. 5, 89-102, doi:10.1039/c2ay25544h, (2012).
24. Holton, S. E., Walsh, M. J., & Bhargava, R. Subcellular localization of early biochemical transformations in cancer-activated fibroblasts using infrared spectroscopic imaging. Analyst. 136(14), 2953-2958, doi:10.1039/c1an15112f, (2011).
25. Gulley-Stahl, H. J., Bledsoe, S. B., Evan, A. P., & Sommer, A. J. The advantages of an attenuated total internal reflection infrared microspectroscopic imaging approach for kidney biopsy analysis. Appl Spectrosc. 64(1), 15-22 doi:10.1366/000370210792966161, (2010).
26. Walsh, M. J., Kajdacsy-Balla, A., Holton, S. E., & Bhargava, R. Attenuated total reflectance Fourier-transform infrared spectroscopic imaging for breast histopathology. Vib Spectrosc. 60, 23-28, doi:10.1016/j.vibspec.2012.01.010, (2012).
27. Sreedhar H, et al.Investigating the Biochemical Progression of Liver Disease Through Fibrosis, Cirrhosis, Dysplasia and Hepatocellular Carcinoma using Fourier Transform Infrared Spectroscopic Imaging. Proc. SPIE 8939, Biomedical Vibrational Spectroscopy VI: Advances in Research and Industry 89390J.doi:10.1117/12.2040408, (2014).
28. Reddy, R. K., & Bhargava, R. Accurate histopathology from low signal-to-noise ratio spectroscopic imaging data. Analyst. 135(11), 2818-2825, doi:10.1039/c0an00350f, (2010).
29. Bassan P, et al.The inherent problem of transflection-mode infrared spectroscopic microscopy and the ramifications for biomedical single point and imaging applications. Analyst. 138(1), 144-157, doi:10.1039/c2an36090j, (2013).
30. Bassan P, et al. FTIR microscopy of biological cells and tissue: data analysis using resonant Mie scattering (RMieS) EMSC algorithm. Analyst. 137(6), 1370-1377, doi:10.1039/c2an16088a, (2012).
31. Bassan P, et al. Resonant Mie scattering in infrared spectroscopy of biological materials--understanding the 'dispersion artefact'. Analyst. 134(8), 1586-1593, doi:10.1039/b904808a, (2009).
32. Bassan P, et al. RMieS-EMSC correction for infrared spectra of biological cells: extension using full Mie theory and GPU computing. J Biophotonics. 3(8-9), 609-620, doi:10.1002/jbio.201000036, (2010).
33. Bassan P, et al. Resonant Mie scattering (RMieS) correction of infrared spectra from highly scattering biological samples. Analyst. 135(2), 268-277, doi:10.1039/b921056c, (2010).
34. Bassan P, et al. Reflection contributions to the dispersion artefact in FTIR spectra of single biological cells. Analyst. 134(6), 1171-1175, doi:10.1039/b821349f, (2009).
35. Davis, B. J., Carney, P. S., & Bhargava, R. Theory of mid-infrared absorption microspectroscopy: II. Heterogeneous samples. Anal Chem. 82(9), 3487-3499, doi:10.1021/ac902068e, (2010).
36. Davis, B. J., Carney, P. S., & Bhargava, R. Theory of midinfrared absorption microspectroscopy: I. Homogeneous samples. Anal Chem. 82(9), 3474-3486, doi:10.1021/ac902067p, (2010).
37. Kohlet A, et al. Estimating and correcting mie scattering in synchrotron-based microscopic fourier transform infrared spectra by extended multiplicative signal correction. Appl Spectrosc. 62(3), 259-266, doi:10.1366/000370208783759669, (2008).
38. Miljkovic, M., Bird, B., Lenau, K., Mazur, A. I., & Diem, M. Spectral cytopathology: new aspects of data collection, manipulation and confounding effects. Analyst. 138(14), 3975-3982, doi:10.1039/c3an00185g, (2013).
39. Miljkovic, M., Bird, B., & Diem, M. Line shape distortion effects in infrared spectroscopy. Analyst. 137(17), 3954-3964, doi:10.1039/c2an35582e, (2012).
40. Bird, B., Miljkovic, M., & Diem, M. Two step resonant Mie scattering correction of infrared micro-spectral data: human lymph node tissue. J Biophotonics. 3(8-9), 597-608, doi:10.1002/jbio.201000024, (2010).
41. Mohlenhoff, B., Romeo, M., Diem, M., & Wood, B. R. Mie-type scattering and non-Beer-Lambert absorption behavior of human cells in infrared microspectroscopy. Biophys J. 88(5), 3635-3640, doi:10.1529/biophysj.104.057950, (2005).
42. Bambery, K. R., Wood, B. R., & McNaughton, D. Resonant Mie scattering (RMieS) correction applied to FTIR images of biological tissue samples. Analyst. 137(1), 126-132, doi:10.1039/c1an15628d, (2012).
43. Kwak, J. T., Reddy, R., Sinha, S., & Bhargava, R. Analysis of variance in spectroscopic imaging data from human tissues. Anal Chem. 84(2), 1063-1069, doi:10.1021/ac2026496, (2012).
44. Trevisan, J., Angelov, P. P., Carmichael, P. L., Scott, A. D., & Martin, F. L. Extracting biological information with computational analysis of Fourier-transform infrared (FTIR) biospectroscopy datasets: current practices to future perspectives. Analyst. 137(14), 3202-3215, doi:10.1039/c2an16300d, (2012).
45. Trevisan J, et al. Measuring similarity and improving stability in biomarker identification methods applied to Fourier-transform infrared (FTIR) spectroscopy. J Biophotonics. 7(3-4), 254-265, doi:10.1002/jbio.201300190, (2014).
46. Bhargava, R., Fernandez, D. C., Hewitt, S. M., & Levin, I. W. High throughput assessment of cells and tissues: Bayesian classification of spectral metrics from infrared vibrational spectroscopic imaging data.Biochim Biophys Acta. 1758(7), 830-845, doi:10.1016/j.bbamem.2006.05.007, (2006).
47. Menze, B H, et al. A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of spectral data. BMC bioinformatics. 10, 213, doi:10.1186/1471-2105-10-213, (2009).
48. Kelly, J G, et al. Biospectroscopy to metabolically profile biomolecular structure: a multistage approach linking computational analysis with biomarkers. J Proteome Res. 10(4), 1437-1448, doi:10.1021/pr101067u, (2011).
49. Bird B, et al. Infrared micro-spectral imaging: distinction of tissue types in axillary lymph node histology.BMC Clin Pathol. 8, 8, doi:10.1186/1472-6890-8-8, (2008).
50. Baker M J, et al. Investigating FTIR based histopathology for the diagnosis of prostate cancer. J Biophotonics. 2(1-2), 104-113, doi:10.1002/jbio.200810062, (2009).
51. Baker M J, et al. Using Fourier transform IR spectroscopy to analyze biological materials. Nat Protoc.9(8), 1771-1791, doi:10.1038/nprot.2014.110, (2014).
52. Katzenmeyer, A. M., Aksyuk, V., & Centrone, A. Nanoscale Infrared Spectroscopy: Improving the Spectral Range of the Photothermal Induced Resonance Technique. Anal Chem. 85(4), 1972-1979, doi:10.1021/ac303620y, (2013).
53. Dazzi A, et al. AFM-IR: combining atomic force microscopy and infrared spectroscopy for nanoscale chemical characterization. Appl Spectrosc. 66(12), 1365-1384, doi:10.1366/12-06804, (2012).
54. Kole, M. R., Reddy, R. K., Schulmerich, M. V., Gelber, M. K., & Bhargava, R. Discrete frequency infrared microspectroscopy and imaging with a tunable quantum cascade laser. Anal Chem. 84(23), 10366-10372, doi:10.1021/ac302513f, (2012).
55. Vrancic C, et al. Continuous glucose monitoring by means of mid-infrared transmission laser spectroscopy in vitro. Analyst. 136(6), 1192-1198, doi:10.1039/c0an00537a, (2011).
56. Yeh, K., Schulmerich, M., & Bhargava, R. Mid-infrared microspectroscopic imaging with a quantum cascade laser. Proc. SPIE. 8726, Next-Generation Spectroscopic Technologies VI, 87260E, doi:10.1117/12.2015984, (2013).
57. Brandstetter, M., Volgger, L., Genner, A., Jungbauer, C., & Lendl, B. Direct determination of glucose, lactate and triglycerides in blood serum by a tunable quantum cascade laser-based mid-IR sensor. Appl. Phys. B. 110(2), 233-239, doi:10.1007/s00340-012-5080-z, (2013).
58. Martin M C, et al. 3D spectral imaging with synchrotron Fourier transform infrared spectro-microtomography. Nat Meth. 10(9), 861-864, doi:10.1038/nmeth.2596, (2013).
59. Kwon B, et al.Infrared microspectroscopy combined with conventional atomic force microscopy.Ultramicroscopy. 116, 56-61, doi:10.1016/j.ultramic.2012.03.007, (2012).
60. Marcott C, et al. Nanoscale infrared (IR) spectroscopy and imaging of structural lipids in human stratum corneum using an atomic force microscope to directly detect absorbed light from a tunable IR laser source. Exp Dermatol. 22(6), 419-421, doi:10.1111/exd.12144, (2013).