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Visualization of Microscopy‐Based Spectral Imaging Data from Multi‐Label Tissue Sections

James R. Mansfield1,  Clifford Hoyt1,  Richard M. Levenson1

1Cambridge Research & Instrumentation (CRi), Woburn, Massachusetts

Publication Name: 
Current Protocols in Molecular Biology
Unit Number: 
UNIT 14.19
DOI: 
10.1002/0471142727.mb1419s84
Print Publication Date: 
October, 2008
Online Posting Date: 
October, 2008
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Abstract

Combining images taken with light of specific wavelengths can dramatically enhance light-microscopic images. This technology is enabled by the availability of programmable filters that can be set to transmit light only of particular wavelengths. Spectral imaging technologies have become an important part of microscopy, and are particularly useful for analyzing samples that have been labeled with multiple (two or more) molecular markers. The most commonly used methodology for separating the markers from each other is linear unmixing, which results in a quantitative image of the location and amount of each marker present in the sample. The very complexity of these multilabel samples requires a high degree of sophistication in methods to visualize the results of unmixing. This article describes a wide range of useful visualization tools designed to better enable discrimination of different features in multilabeled tissue or cell samples. These commercially available tools can be attached to the standard laboratory light microscope to significantly enhance the power of light microscopy. Curr. Protoc. Mol. Biol. 84:14.19.1-14.19.15. © 2008 by John Wiley & Sons, Inc.

Keywords: spectral imaging; unmixing; data visualization

     
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Table of Contents

  • Introduction
  • Instrumentation
  • Labeling
  • Spectral Imaging Methods
  • Summary
  • Acknowledgments
  • Literature Cited
  • Figures
  • Tables
     
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Figures

  • Figure 14.19.1
    Liver section imaged at 10x using an FITC long-pass emission filter cube from 500 to 720 nm in 10-nm steps. (A) RGB representation of the spectral imaging dataset; (B-D) unmixed images of the tissue autofluorescence, Alexa Fluor 488 and Cy3, respectively; (E) pseudo-color composite image of the combined unmixing results, with autofluorescence in gray, Alexa Fluor 488 in green, and Cy3 in red.

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  • Figure 14.19.2
    Zoomed images from liver section in Figure 14.19.1. (A) RGB representation; (B) composite image; (C) unmixed Alexa Fluor 488 image; (D) monochrome image captured at peak of Alexa Fluor 488 emission (530 nm).

    View Image
  • Figure 14.19.3
    Invasive ductal carcinoma section stained for estrogen receptor (ER, DAB) and progesterone receptor (PR, Fast Red), and counterstained with hematoxylin. (A) RGB representation of data set; (B-D) unmixed images corresponding to hematoxylin, ER, and PR, respectively; (E) simulated fluorescence composite with hematoxylin in blue, ER in red, and PR in green; (F) simulated fluorescence composite showing only ER (red) and PR (green).

    View Image
  • Figure 14.19.4
    Intraductal carcinoma sample stained for CD44v6 (QDot 655) and CD24 (QDot 605). (A) RGB representation of spectral data; (B-C) unmixed images of CD44v6 and CD24, respectively; (D) pseudo-color composite with DAPI in blue, CD44v6 in red and CD24 in green; (E) simulated bright-field composite with DAPI in blue, CD44v6 in red, and CD24 in green.

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  • Figure 14.19.5
    Three nuclear immunohistochemical markers (Ki67, pHH3, CC3) and a nuclear counterstain (hematoxylin) distinguished using chromogens in bright-field in the germinal center of a tonsil. (A) Shows the RGB representation of the dataset; (B) simulated fluorescence display of Ki-67 (red); (C) simulated fluorescence display of Ki-67 (red) and pHH3 (green); (D) simulated fluorescence display of Ki-67 (red), pHH3 (green), and CC3 (blue).

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  • Figure 14.19.6
    Co-localization analysis of Ki-67 and pHH3 in tonsil sample from Fig. 14.19.5. (A) unmixed hematoxylin image (blue on white); (B) thresholded hematoxylin image with positive hematoxylin pixels in dark blue superimposed on RGB representation (Fig. 14.19.5A); (C) thresholded Ki-67 (red) and pHH3 (green) images superimposed on RGB representation; (D) the same image as 6C but with co-localized pixels (those containing both Ki-67 and pHH3) shown in yellow.

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  • Figure 14.19.7
    Tonsil germinal center stained with 5 quantum dots and DAPI. (A) unmixed DAPI image (purple); (B) DAPI plus Ki-67 (blue); (C) Ki-67 (blue) plus CD3 (yellow) (DAPI not shown); (D) Ki-67 and CD3 plus CD20 (red); (E) Ki-67, CD3 and CD20 plus IgD (green); (F) Ki-67, CD3, CD20, and IgD plus CD68 (cyan).

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  • Figure 14.19.8
    Simulated bright-field “DAB on hematoxylin” composite images showing individual markers from 5-quantum-dot tonsil sample in Fig. 14.19.7. (A) Ki-67; (B) CD20; (C) CD3; and (D) CD68.

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  • Figure 14.19.9
    Breast cancer sections stained with ER, PR and hematoxylin showing “flow-on-a-slide” analysis of ER- and PR-positivity and co-localization. (A) Sample showing mainly double-negative nuclei; (B) sample showing a mixture of double-negative and single ER-positive nuclei; (C) Sample showing mixture of double-negative and double-positive nuclei.

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Literature Cited

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