A Novel Three‐Dimensional Computer‐Assisted Method for a Quantitative Study of Microvascular Networks of the Human Cerebral Cortex

Abstract

Among the many parameters that can be analyzed by this method, the capillary size, the frequency distributions of diameters and lengths, the fractal nature of these networks, and the depth-related density of vessels are all vital features for an adequate model of cerebral microcirculation.

Vascular remodelling of an arterio-venous blood vessel network during solid tumour growth

“…Their lengths and locations are sampled from uniform distributions. The approach was motivated by the observation that vasculatures exhibit relatively thick straight vessels down to a certain level in the hierarchy as can be seen in photos from the CAM (Mironov et al, 1998), or in recent 3d vascular imaging (Cassot et al, 2006) experiments. Starting with these different initial networks the final tumour vasculature predicted by our model is depicted in the bottom row of Fig.5.…”

Model of the Transient Neurovascular Response Based on Prompt Arterial Dilation

“…Therefore, instead of using total CBV for gray matter, we use an effective cerebral blood volume (eCBV) that includes only the fraction of the blood volume that participates in oxygen transport. We quantify the volume fraction for each longitudinal blood-vessel compartment based on the results of Cassot et al 34 We then weighted each branch's volume by its fraction of oxygen transport as measured by Vovenko et al where n is the number of longitudinal blood-vessel compartment. The eCBV in cortex is V c ¼ 0.017 (B29% of total CBV).…”

“…Because oxygen transport mainly occurs in capillaries (B52% of total oxygen transport), 8,18 we chose to use the predicted extravascular oxygen concentration over a 60-mm region at the distal end of the model blood vessel, which corresponds to the mean length of a capillary segment. 34 However, we also tested two other sampling approaches: permitting the sampling to vary along the length of the cylinder as an optimization parameter, and averaging over the entire blood-vessel length. These approaches also provide good fits to the measurements that were qualitatively identical to those presented in the Results.…”

Simulation study of brain blood flow regulation by intra-cortical arterioles in an anatomically accurate large human vascular network. Part II: Flow variations induced by global or localized modifications of arteriolar diameters

“…Further work on various cortical areas and various conditions is necessary in order to perform parametric studies of the effect of vascular architecture (in particular vascular density) on the flow reorganizations induced by arteriolar vasodilations in the context of functional neuroimaging. In this context, it may also prove useful to perform numerical studies on structures generated in silico to reproduce the main known morphometric and topological characteristics of the human intra-cortical networks (Cassot et al, 2006;Lauwers et al, 2008;Cassot et al, 2010;Lorthois and Cassot, 2010). Such studies could either use ad hoc algorithms to reproduce the fractal properties of arteriolar and venular trees (Schreiner et al, 2005;Bui et al, 2009) or be based on morphogenesis models (Nguyen et al, 2006;Lorthois and Cassot, 2010).…”

“…In particular, the smooth muscle cells surrounding the arterioles, and possibly pericytes (Peppiatt et al, 2006;Fernández-Klett, 2008), at capillary level, convert the bio-chemical signals that originate from this integrated unit into changes in vascular diameter, thus regulating blood flow by modulating their vascular resistance. As argued in a companion paper (Lorthois et al, Neuroimage, in press), fluid dynamic modeling can be used to gain insight into brain blood flow regulation by intra-cortical arterioles, based on quantitative morphometric and topological data previously acquired on a large volume of the healthy human vasculature (Cassot et al, 2006).…”