Authors: Peter Miller, Yi Zheng, Darryn Unfricht, Wenliang Zhang, Kent Johnson, Carla Coltharp

Issue:  Digital Pathology Association: Visions 2018 Tradeshow Poster


Digital pathology methods are of growing value for studying fluorescently-labeled samples, to obtain quantitative expression measures and to take advantage of multiple markers. At the same time, multiplexed immunofluorescence (mIF) labeling techniques and multispectral imaging systems have made it practical to measure up to 7 colors per specimen, enabling insight into complex samples such as are present in immunooncology studies. We report on a new platform that brings these together. It includes optimized dyes, software, and a scanner that performs rapid whole-slide multispectral imaging of FFPE samples (6 minutes for an entire section). This enables studying cell-to-cell interactions over multiple spatial scales; and measuring heterogeneity in immune response across the tumor microenvironment.

Methods: Staining & Scanning

Formalin-fixed paraffin-embedded samples of primary lung cancer tumors were immunostained using an Opal™ Polaris 7 detection kit, with primary antibodies targeting PDL1, PD1, CD8, CD68, FoxP3, and cytokeratin. Staining was done on a Leica BOND RXTM.

A novel, high-throughput whole-slide multispectral scanning workflow was used to digitize the samples:

  • Scanning with Vectra Polaris using agile LED illumination and multiband filters to produce the required spectral bands. Scan time is 6 minutes for a 1 x 1.5 cm sample at 20x
  • The raw multispectral imagery was stored as a pyramidal tiff (QPTIFF) with no compression; it was 2.6 GB in size.

Fig. 1. Multispectral imaging on the Vectra Polaris is built upon an epifluorescence light path (above, left). Different combinations of agile LED bands, bandpass excitation filters, bandpass emission filters, and a liquid crystal tunable filter (LCTF) are used to select narrow spectral bands that reach the imaging sensor.

Methods: Image Viewing & Analysis

Multispectral software was used to view and analyze the samples. 

  • Analysis regions were selected by drawing annotations using a special version of the Phenochart viewer. When desired, the entire sample could be selected and analyzed.  
  • The viewer used unmixing-on-demand to obtain pure components, with autofluorescence isolation and this guided the operator during region selection. 
  • A one-time measurement of an autofluorescence witness slide was used for all subsequent slides.

Fig. 2:  Viewing and annotation of the multispectral scan. The Phenochart viewer provides a composite view of the sample at all zoom levels using an unmix-on-demand scheme. This enables the usual digital pathology interactions with a multispectral dataset.

Selected regions were analyzed using a special version of inForm software, which processed the regions directly from the raw multispectral scan and the annotations. Spectra were measured from control samples. 

  • It, too, used unmix-on-demand to process the large dataset efficiently, without intermediate steps or files 
  • Cells were then segmented and phenotyped for positivity in each marker based on operator-trained classifiers
Phenotyping and segmentation obtained this way were compared with results from field-based MSI methods

  • Non-adjacent sections were prepared from the same block, using the Opal™ Polaris 7 detection kit, and the standard Opal™ detection kit, using the same Abs
  • The standard Opal™ kit sample was imaged using fieldbased MSI on a Vectra Polaris and analyzed in inForm
  • The Opal™ Polaris 7 detection kit sample was imaged using the whole-slide workflow tools described above
  • While this work is preliminary, results appear consistent across the two methods.

Example: Heterogeneity Of A Lung Cancer Sample

Fig 3. Cell density and interaction density. Lung cancer section, shown as composite image with marker colors indicated in key. Cells were phenotyped in inForm, and interactions assessed with R and Phenoptr. Heatmaps on the top row show cellular density for tumor cells, CD8+, and CD8+ within 30 µm of a tumor cell. Bottom row shows density contours of CK+; contours of CK+ within 30 µm of a CD8+ cell; and a satellite view showing CD8+ as red dots if within 30 µm of a tumor cell and white dots otherwise, with tumor cells shown in gradient colors as shown in the key

Fig. 4. Comparison with field-based results. This shows results from field-based acquisition and analysis on the left, with the corresponding portion of another section from the same block processed with whole-slide multispectral methods on the right.

The entire section was selected, and we analyzed cell populations and cell-interactions at a variety of spatial scales across the entire section

  • Tables of cell data, containing location, expression of each marker, phenotype assignment, and other data were subjected to spatial analysis
  • R and the Phenoptr package were used to identify cells with a given phenotype; or cells of given phenotype for which a neighboring cell of a specified type is adjacent, as a measure of cellular interaction
  • The results were visualized using heatmap, contour, and satellite views to show the density and distribution of cells and their interactions across the sample


Whole slide multispectral workflows have been demonstrated that greatly simplify multiplexed tissue studies through the following innovations:

  • Rapid whole-slide scanning for 6-plex (7-color) samples with only a single operator touch-point
  • Viewer and analysis software with unmix-on demand to enable the usual digital pathology workflows for these complex image sets
  • The datasets are ripe for studying cells and their interactions at all spatial scales either within a region or across the entire sample
The resulting scan time and file size – 6 minutes, and 2.5 GB per slide – make this technique practical even for large studies. In turn, the information content of these spatially complete, rich datasets recommends them for biomarker hunting and translational use.

a. BOND RX is for Research Use Only. Not For Use In Diagnostic Procedures.
b. LEICA and the Leica Logo are registered trademarks of Leica Microsystems IR GmbH.
c. BOND is a trademark of Leica Biosystems Melbourne Pty Ltd.