The cerebral vasculature facilitates blood flow to maintain normal function in the brain. Vascular injury can impair the ability of the cerebral vasculature to regulate blood flow and preserve the integrity of the blood-brain barrier. Cerebral microhemorrhages (CMH) are an indicator of structural damage in the brain vasculature. Aging and hypertension are the most common risk factors for CMH. In this study, we analyzed the effect of hypertension on resting-state cerebral blood flow and the development of CMH in a mouse model of aging. A reduction in resting-state cerebral blood flow was observed in hypertension mice. CMH were found to appear nearest to capillary-sized vessels. Together, these findings demonstrate hypertension can impair the function (via reduced resting-state cerebral blood flow) and structure (via formation of CMH) of the brain vasculature.
Cerebral microhemorrhages (CMH) are the accumulation of hemosiderin-iron deposits which are associated with cognitive impairments. CMH are suspected to be the result of the deterioration of cerebral microvessels. Despite the clinical significance of CMH, our understanding of CMH formation remains limited. Standard histology for CMH visualization is constrained by thin planar views obtained sparsely throughout brain tissue. This limitation can misrepresent the true size and extent of CMH. Here we incorporate tissue clearing to capture a complete view of CMH and compare it to that of a two-dimensional approach.
Cerebral microhemorrhages (CMHs) occur due to ruptures in cerebral microvessels that cause deposits of blood in the brain. Hypertension (HTN) is a major risk factor for CMHs, which have been associated with cognitive decline and ischemic strokes. Despite the clinical significance of CMHs, our understanding of CMH formation remains limited. To address this gap, our group has employed a perfusion-based vascular label with tissue clearing to enable three-dimensional visualization of CMHs with the surrounding microvasculature in HTN mice. Vessel diameters surrounding a CMH were approximately 4.22±0.81 µm. Vessel density in CMH positive tissue regions was approximately 0.083±0.017 µm-1.
Significance: To explore brain architecture and pathology, a consistent and reliable methodology to visualize the three-dimensional cerebral microvasculature is beneficial. Perfusion-based vascular labeling is quick and easily deliverable. However, the quality of vascular labeling can vary with perfusion-based labels due to aggregate formation, leakage, rapid photobleaching, and incomplete perfusion.
Aim: We describe a simple, two-day protocol combining perfusion-based labeling with a two-day clearing step that facilitates whole-brain, three-dimensional microvascular imaging and characterization.
Approach: The combination of retro-orbital injection of Lectin-Dylight-649 to label the vasculature, the clearing process of a modified iDISCO+ protocol, and light-sheet imaging collectively enables a comprehensive view of the cerebrovasculature.
Results: We observed ∼threefold increase in contrast-to-background ratio of Lectin-Dylight-649 vascular labeling over endogenous green fluorescent protein fluorescence from a transgenic mouse model. With light-sheet microscopy, we demonstrate sharp visualization of cerebral microvasculature throughout the intact mouse brain.
Conclusions: Our tissue preparation protocol requires fairly routine processing steps and is compatible with multiple types of optical microscopy.
Cerebral microbleeds (CMB) are deposits of blood that accumulate within the brain. An increase in CMBs is associated with an increased risk of cognitive impairment and stroke. The types of vessels associated with CMB formation remains unclear. We recently demonstrated the combined use of exogenous labels, vessel painting, and optical clearing to achieve three-dimensional views of blood vessels and CMBs. Here, we aimed to characterize brain vasculature by quantifying key vasculature-related metrics. An automated algorithm was developed to segment blood vessels within fluorescence images. An open-source neuron tracing software, neuTube, was then used to quantify blood vessel diameters.
Cerebral microhemorrhages (CMHs) are associated with cognitive impairment and several conditions, diseases, and normal aging processes. Current histological methods manually identify and quantify Prussian blue-stained CMHs, which can take months to complete. To speed up this labor-intensive process, we developed a spectroscopic, semi-automated approach. We used the ratio of the red and green intensities relative to the blue intensity squared to discriminate CMH-pixels from background pixels. We calculated a sensitivity and specificity of 83.75% and 99.74%, respectively. The intraclass correlation coefficient was 0.992 (95% confidence interval: 0.989-0.995). Future studies are needed to test if this approach works in other CMH models.
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