Spectral Unmixing Methods and Tools for the Detection and Quantitation of Collagen and Other Macromolecules in Tissue Specimens.

Collagen and other components in the extracellular matrix are proving of increasing importance for the understanding of complex cell and tissue interactions in a variety of settings. Detection and quantitation of these components can still prove challenging, and a number of techniques have been developed. We focus here on methods in fluorescence-based assessments, including multiplexed immunodetection and the use of simpler histochemical stains, both complemented by linear unmixing techniques. Typically, differentiating these components requires the use of a set of optical filters to isolate each fluorescent compound from each other and from often bright background autofluorescence signals. However, standard fluorescent microscopes are usually only able to separate a limited number of components. If the emission spectra of the fluorophores are spectrally distinct, but overlapping, sophisticated spectral imaging or computational methods can be used to optimize separation and quantitation. This chapter describes spectral unmixing methodology and associated open-source software tools available to analyze multispectral as well as simple color (RGB) images.

[1]  P J Tadrous Digital stain separation for histological images , 2010, Journal of microscopy.

[2]  R. Oldenbourg A new view on polarization microscopy , 1996, Nature.

[3]  Chichung Wang,et al.  Multiplexed immunohistochemistry, imaging, and quantitation: a review, with an assessment of Tyramide signal amplification, multispectral imaging and multiplex analysis. , 2014, Methods.

[4]  L. Vaughan,et al.  Cartilage contains mixed fibrils of collagen types II, IX, and XI , 1989, The Journal of cell biology.

[5]  R. Timpl,et al.  Immunofluorescent localization of collagen types I, II, and III in the embryonic chick eye. , 1977, Developmental biology.

[6]  Antonio J. Plaza,et al.  Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches , 2012, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[7]  Abdul Kader Sagar,et al.  Second-harmonic generation imaging of cancer. , 2014, Methods in cell biology.

[8]  Michael Shribak,et al.  Polychromatic polarization microscope: bringing colors to a colorless world , 2015, Scientific Reports.

[9]  Lanlan Zhou,et al.  Multispectral Fluorescence Imaging , 2009, Journal of Nuclear Medicine.

[10]  A. Ruifrok,et al.  Quantification of histochemical staining by color deconvolution. , 2001, Analytical and quantitative cytology and histology.

[11]  Hisataka Kobayashi,et al.  Multiplexing with multispectral imaging: from mice to microscopy. , 2008, ILAR journal.

[12]  K. Bloom,et al.  Determining absolute protein numbers by quantitative fluorescence microscopy. , 2014, Methods in cell biology.

[13]  M. Herlyn,et al.  CCN3 controls 3D spatial localization of melanocytes in the human skin through DDR1 , 2006, The Journal of cell biology.

[14]  F. B. Mallory The Anilin Blue Collagen Stain , 1936 .

[15]  Katie O Fuchs,et al.  The effects of an estrogen and glycolic acid cream on the facial skin of postmenopausal women: a randomized histologic study. , 2003, Cutis.

[16]  Clive R. Taylor,et al.  Antigen Retrieval in Immunohistochemistry , 2014 .

[17]  Richard M Levenson,et al.  Autofluorescence removal, multiplexing, and automated analysis methods for in-vivo fluorescence imaging. , 2005, Journal of biomedical optics.

[18]  B. Kowalski,et al.  Selectivity, local rank, three‐way data analysis and ambiguity in multivariate curve resolution , 1995 .

[19]  E. Hay,et al.  Immunohistochemical localization of collagen types I and II in the developing chick cornea and tibia by electron microscopy. , 1982, Investigative ophthalmology & visual science.

[20]  Yukako Yagi,et al.  Multispectral Enhancement towards Digital Staining , 2012, Analytical cellular pathology.

[21]  J. Mansfield,et al.  Multispectral imaging in biology and medicine: Slices of life , 2006, Cytometry. Part A : the journal of the International Society for Analytical Cytology.

[22]  Bayrammurad Saparov,et al.  Corrigendum: Complex structures of different CaFe2As2 samples , 2015, Scientific Reports.

[23]  Stavros G. Demos,et al.  Slide-free histology via MUSE: UV surface excitation microscopy for imaging unsectioned tissue (Conference Presentation) , 2016, SPIE BiOS.

[24]  Jennifer C. Waters,et al.  Accuracy and precision in quantitative fluorescence microscopy , 2009, The Journal of cell biology.

[25]  J. Mansfield,et al.  Multispectral Imaging , 2014, Veterinary pathology.

[26]  B. Brown,et al.  Quantitative multispectral imaging of Herovici's polychrome for the assessment of collagen content and tissue remodelling , 2013, Journal of tissue engineering and regenerative medicine.

[27]  Juan Liu,et al.  Application of multispectral imaging in quantitative immunohistochemistry study of breast cancer: a comparative study , 2015, Tumor Biology.

[28]  Denny A. Jones,et al.  A simple and effective heat induced antigen retrieval method , 2016, MethodsX.

[29]  J. Boardman,et al.  Geometric mixture analysis of imaging spectrometry data , 1994, Proceedings of IGARSS '94 - 1994 IEEE International Geoscience and Remote Sensing Symposium.