QuPath Automated Analysis of Optic Nerve Degeneration in Brown Norway Rats.

Clicks: 271
ID: 109330
2020
A novel application of QuPath open-source digital analysis software is used to provide in-depth morphological analysis of progressive optic nerve (ON) degeneration in rats.QuPath software was adapted to assess axon and gliotic morphology in toluidine blue-stained, Brown Norway rat ON light micrographs. QuPath axon numbers, density, size distributions, and gliotic areas were obtained from test images and ON cross-sections separated by damage grade. QuPath results were compared with manual counting, AxonJ, and electron microscopy axon estimates.QuPath-derived axon number, density, and diameter decreased with increasing ON damage. Axon density negatively correlated with gliotic areas in test images ( = 0.759; < 0.0001; = 40) and in ON cross-sections ( = 0.803; < 0.0004; = 10). Although axon losses occurred across most axon diameters, large axons were more susceptible to degeneration. The exception was swollen axons > 2 µm, which increased in moderately but not severely damaged images. QuPath axon counts correlated strongly with manual counts of test images ( = 0.956; < 0.0001). QuPath outperformed AxonJ on test images and total ON axon counts. Compared to electron microscopy analysis, QuPath undercounted ON axons; however, correlation between the methods was robust ( = 0.797; < 0.001; = 10).QuPath analysis reliably identified axon loss, axon morphology changes, and gliotic expansion that occurred in degenerating ONs.QuPath is a valuable tool for rapid, automated, analysis of healthy and degenerating ONs. Reproducible preclinical studies for new glaucoma treatments depend on unbiased in-depth analysis of ON pathology. This was provided by the QuPath approach.
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mysona2020qupathtranslational Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Mysona, Barbara A;Segar, Sharmila;Hernandez, Cecilia;Kim, Christian;Zhao, Jing;Mysona, David;Bollinger, Kathryn E;
Journal Translational vision science & technology
Year 2020
DOI 10.1167/tvst.9.3.22
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