Numerical and length densities of microvessels in the human brain: Correlation with preferential orientation of microvessels in the cerebral cortex, subcortical grey matter and white matter, pons and cerebellum.

To provide basic data on the local differences in density of microvessels between various parts of the human brain, including representative grey and white matter structures of the cerebral hemispheres, the brain stem and the cerebellum, we quantified the numerical density NV and the length density LV of microvessels in two human brains. We aimed to correlate the density of microvessels with previously published data on their preferential orientation (anisotropy). Microvessels were identified using immunohistochemistry for laminin in 32 samples harvested from the following brain regions of two adult individuals: the cortex of the telencephalon supplied by the anterior, middle, and posterior cerebral artery; the basal ganglia (putamen and globus pallidus); the thalamus; the subcortical white matter of the telencephalon; the internal capsule; the pons; the cerebellar cortex; and the cerebellar white matter. NV was calculated from the number of vascular branching points and their valence, which were assessed using the optical disector in 20-μm-thick sections. LV was estimated using counting frames applied to routine sections with randomized cutting planes. After correction for shrinkage, NV in the cerebral cortex was 1311±326mm-3 (mean±SD) and LV was 255±119mm-2 . Similarly, in subcortical grey matter (which included the basal ganglia and thalamus), NV was 1350±445mm-3 and LV was 328±117mm-2 . The vascular networks of cortical and subcortical grey matter were comparable. Their densities were greater than in the white matter, with NV =222±147mm-3 and LV =160±96mm-2 . NV was moderately correlated with LV. In parts of brain with greater NV , blood vessels lacked a preferential orientation. Our data were in agreement with other studies on microvessel density focused on specific brain regions, but showed a greater variability, thus mapping the basic differences among various parts of brain. To facilitate the planning of other studies on brain vascularity and to support the development of computational models of human brain circulation based on real microvascular morphology; stereological data in form of continuous variables are made available as supplements.