Abstract
BackgroundAn increase in blood brain barrier permeability commonly precedes neuro-inflammation and cognitive impairment in models of dementia. Common methods to estimate capillary permeability have potential confounders, or require laborious and subjective semi-manual analysis.New methodHere we used snap frozen mouse and rat brain sections that were double-immunofluorescent labeled for immunoglobulin G (IgG; plasma protein) and laminin-α4 (capillary basement membrane). A Machine Learning Image Analysis program (Zeiss ZEN Intellisis) was trained to recognize and segment laminin-α4 to equivocally identify blood vessels in large sets of images. An IgG subclass based on a threshold intensity was segmented and quantitated only in extravascular regions. The residual parenchymal IgG fluorescence is indicative of blood-to-brain extravasation of IgG and was accurately quantitated.ResultsAutomated machine-learning and threshold based segmentation of only parenchymal IgG extravasation accentuates otherwise indistinct capillary permeability, particularly frequent in minor BBB leakage. Comparison with Existing Methods: Large datasets can be processed and analyzed quickly and robustly to provide an overview of vascular permeability throughout the brain. All human bias or ambiguity involved in classifying and measuring leakage is removed.ConclusionHere we describe a fast and precise method of visualizing and quantitating BBB permeability in mouse and rat brain tissue, while avoiding the confounding influence of unphysiological conditions such as perfusion and eliminating any human related bias from analysis.
Highlights
Alterations in cerebral capillary blood-brain barrier (BBB) are increasingly recognized as central in maintaining optimal brain and cognitive functioning (Zlokovic, 2008)
BBB disruptions observed in neurodegenerative disorders are often subtle, resulting in a modest amount of protein leakage (Takechi et al, 2010), as opposed to more severe cerebrovascular damages seen in stroke and traumatic brain injury causing microhemorrhage (Mao et al, 2018; O’Keeffe et al, 2020)
Acknowledging the importance to remove blood from the vasculature to measure the cerebral extravasation of dye, perfusion of animals introduces another layer of unphysiological conditions, which may confound the detection of subtle BBB alterations
Summary
Alterations in cerebral capillary blood-brain barrier (BBB) are increasingly recognized as central in maintaining optimal brain and cognitive functioning (Zlokovic, 2008). Utilized methods to determine permeability of the BBB in animal models include the ex vivo measurement of cerebral extravasation of exogenous dyes such as fluorescein and Evans Blue that are injected intravenously. Acknowledging the importance to remove blood from the vasculature to measure the cerebral extravasation of dye, perfusion of animals introduces another layer of unphysiological conditions, which may confound the detection of subtle BBB alterations. These include the use of non-physiological perfusing solution (e.g., chilled PBS and fixative), artificial intravascular flow and pressure, and prolonged application of anesthesia (Thal et al, 2012). The residual parenchymal IgG fluorescence is indicative of blood-to-brain extravasation of IgG and was accurately quantitated
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