An automated approach to improve the speed and accuracy of pericyte and microglia quantification in whole mouse brain sections

Courtney, J.-M.; Morris, G. P.; Cleary, E. M.; Howells, D. W.; Sutherland, B. A.

doi:10.1101/2021.04.29.442048

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bioRxiv · 10.1101/2021.04.29.442048

An automated approach to improve the speed and accuracy of pericyte and microglia quantification in whole mouse brain sections

Courtney, J.-M.·Morris, G. P.·Cleary, E. M.·Howells, D. W.·Sutherland, B. A.

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Abstract

Whole slide scanning technology has enabled the generation of high-resolution images of complete tissue sections. However, commonly used analysis software is often unable to handle the large data files produced. Here we present a method using the open-source software QuPath to detect, classify and quantify fluorescently-labelled cells (microglia and pericytes) in whole coronal brain tissue sections. Whole brain sections from both male and female NG2DsRed x CX3CR1+/GFP mice were analysed. Small regions of interest were selected and manual counts were compared to counts generated from an automated approach, across a range of detection parameters. The optimal parameters for detecting cells and classifying them as microglia or pericytes in each brain region were determined and applied to annotations corresponding to the entire cortex, hippocampus, thalamus and hypothalamus in each section. 3.71% of all detected cells were classified as pericytes, however this proportion was significantly higher in the thalamus (6.39%) than in other regions. In contrast, microglia (4.45% of total cells) were more abundant in the cortex (5.54%). No differences were detected between male and female mice. In conclusion, QuPath offers a user-friendly, rapid and accurate solution to whole-slide image analysis which could lead to important new discoveries in both health and disease. Significance StatementRapid and accurate quantification of cell numbers and distributions from whole tissue sections represents a difficult challenge in biomedical research. Slide scanning microscopes generate high-resolution images of complete tissue sections but most common image analysis software packages struggle to cope with the large data files they produce. We provide a method for rapidly and accurately quantifying pericyte and microglia cell numbers in whole brain tissue sections using QuPath, a new open-source software designed specifically to overcome this challenging roadblock.

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Courtney, J.-M., Morris, G. P., Cleary, E. M., Howells, D. W., Sutherland, B. A.. 2021-04-30. An automated approach to improve the speed and accuracy of pericyte and microglia quantification in whole mouse brain sections. https://doi.org/10.1101/2021.04.29.442048

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