Journal
ENEURO
Volume 8, Issue 6, Pages -Publisher
SOC NEUROSCIENCE
DOI: 10.1523/ENEURO.0177-21.2021
Keywords
brain; cell counting; image analysis; microglia; pericytes; QuPath
Categories
Funding
- National Health and Medical Research Council for Australia [APP1137776, APP1163384]
- University of Tasmania
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Whole slide scanning technology allows high-resolution imaging of tissue sections, but commonly used analysis software may struggle with large data files. This study demonstrates the use of QuPath software for detecting and classifying fluorescently-labeled cells in whole brain tissue sections, revealing varying proportions of microglia and pericytes across different brain regions, with no gender differences observed. QuPath could provide a user-friendly solution for important discoveries in research on both health and disease.
Whole slide scanning technology has enabled the generation of high-resolution images from 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 fluores-cently-labeled cells (microglia and pericytes) in whole coronal brain tissue sections. Whole-brain sections from both male and female NG2DsRed x CX(3)CR1(+/GFP) mice were analyzed. Small regions of interest were selected and manual counts were compared with 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 somatosensory and motor cortices, hippocampus, thalamus, and hypothalamus in each section. 3.74% of all detected cells were classified as pericytes; however, this proportion was significantly higher in the thalamus (6.20%) than in other regions. In contrast, microglia (4.51% 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 solution to whole-slide image analysis which could lead to important new discoveries in both health and disease.
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