Digital pathology image quantification and statistical analysis

Digital pathology image analysis is a powerful approach to accurately assess a range of cellular and tissue-based features – from counting of positively stained cells to more complex measures of staining intensity and cellular spatial analysis. 

Propath offers a full range of services for digital quantification and analysis of H&E, IHC and IF markers – cell by cell and across whole tissue sections.    

Using market leading software platforms, including Indica Labs Halo and Definiens, our service includes development of custom algorithms to accurately assess positive nuclear, cytoplasmic and membranous staining, morphological features and staining marker intensity. Morphological and multiplexed expression data can be gained on a cell by cell basis, across entire tissue sections. Sorting and filtering capabilities allow mining of millions of cells while visually assessing corresponding cell populations.  

We provide a detailed image analysis report, including all parameters of the image analysis algorithm, representative images and statistical analysis.

 

Selected applications of digital image analysis

IHC
Quantify single or double stain IHC positivity in the nucleus, cytoplasm and/or membrane on a cell by cell basis
Multiplex IHC
Measure cytoplasmic, nuclear, and/or membrane positivity on a cell by cell basis for up to 4 stains
Immunofluorescence
Measure single, double or triple stain immunofluorescence positivity
Spatial analysis
Quantify nearest neighbour proximity and infiltration analysis of specified cell populations
Tissue classification
Advanced pattern recognition for automatic tissue classification and region of interest selection 
Immune cell proximity
Quantify IHC-labelled immune cells and measure their proximity to other IHC labelled structures – e.g. tumours
Chromogenic RNA ISH
Quantify RNA probe signals on a per cell basis with histogram capability
 

Please feel free to contact us for more detailed information about your specific study.

 
 

We believe the key to reliable image analysis is in first developing a specific and reproducible IHC staining protocol that provides the best possible signal-to-noise ratio. This ensures that subsequent application of any image analysis algorithm accurately distinguishes between positive and negative cells and background staining.  

Through our scientists and our partners we offer many decades of collective experience of digital image analysis. Please feel free to contact us for more detailed information about your specific study. 

Click here to see an example of a recent image analysis study involving dual stained GCP clinical samples, distinguishing macrophage sub populations and providing M1 and M2 positive index read outs.